Retraction and Correction

RETRACTION

GENETICS, SOCIAL SCIENCES Retraction for ‘‘PKNOX2 is significantly associated with substance dependence in European-origin women,’’ by Xiang Chen, Kelly Cho, Burton H. Singer, and Heping Zhang, which published online August 31, 2009, in Proc Natl Acad Sci USA (10.1073/pnas.0908521106). The authors wish to retract this paper because its publication violates the Gene Environment Association Studies and Environment Initiative Study of Addiction: Genetics and Envi- ronment (SAGE) dataset’s embargo policy. The SAGE data access agreement states that investigators agree not to submit findings of the SAGE dataset(s) for publication until September 23, 2009. The authors sincerely apologize for this violation of SAGE policy. Xiang Chen Kelly Cho Burton H. Singer Heping Zhang

www.pnas.org/cgi/doi/10.1073/pnas.0910252106

CORRECTION RETRACTION

NEUROSCIENCE AND CORRECTION Correction for ‘‘Stomach ghrelin-secreting cells as food- entrainable circadian clocks,’’ by Joseph LeSauter, Nawshin Hoque, Michael Weintraub, Donald W. Pfaff, and Rae Silver, which appeared in issue 32, August 11, 2009, of Proc Natl Acad Sci USA (106:13582–13587; first published July 24, 2009; 10.1073/ Ϫ Ϫ pnas.0906426106). Fig. 2. Running wheel behavior of wild-type and GHSR / mice during ad The authors note that on page 13583, in the legend for Fig. 2, libitum feeding, food restriction, and food deprivation conditions. (A) The bar above the actograms shows the light–dark cycle; time of food availability is an equation appeared incorrectly. The figure and its corrected shown in gray. Actograms depict activity of representative GHSRϩ/ϩ and legend appear below. Additionally, in Fig. 3A on page 13584, the GHSRϪ/Ϫ mice during ad libitum feeding (days 1–4), food restriction ZT6–ZT14 panels labeled ‘‘Ghrelin’’ and ‘‘PER1’’ appeared incorrectly. The (days 4–15), ad libitum food availability (days 15–18), and food deprivation corrected figure and its legend appear below. These errors do not (day 19). (B) Group activity profiles show the amount of wheel running during affect the conclusions of the article. the last 7 days of restricted feeding in GHSRϩ/ϩ (black) and GHSRϪ/Ϫ (gray) mice. The data are plotted in 10-min bins (mean Ϯ SEM). **, P ϭ 0.002, difference between GHSRϩ/ϩ and GHSRϪ/Ϫ in onset time of activity. (C) Line graph of cumulative wheel-running activity (mean Ϯ SEM) from lights on (ZT0) to time of food presentation (ZT6) shows that GHSRϪ/Ϫ mice (solid gray line) ran 42.4% less than GHSRϩ/ϩ (solid black line) mice. Superimposed are the curves derived from the Gaussian function f(x) ϭ eϪx2/2/͌2␲ (dashed lines). (D) The anticipation ratios during 7 days of restricted feeding (Top) and the persistence ratio (Middle) on the day of food deprivation are shown for GHSRϪ/Ϫ (gray bars) and control GHSRϩ/ϩ (black bars) mice, with significant differences between groups. (Bottom) Daily activity during the period of food restriction. *, P ϭ 0.02; **, P ϭ 0.01.

www.pnas.org PNAS ͉ October 6, 2009 ͉ vol. 106 ͉ no. 40 ͉ 17241–17242 Downloaded by guest on September 25, 2021 See Retraction Published September 9, 2009 PKNOX2 gene is significantly associated with substance dependence in European-origin women

Xiang Chena,1, Kelly Choa,1, Burton H. Singerb,2, and Heping Zhanga,2 aDepartment of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520-8034; and bOffice of Population Research, Princeton University, Princeton, NJ 08544

Contributed by Burton H. Singer, August 1, 2009 (sent for review March 18, 2009) Substance dependence is a complex environmental and genetic dis- dependence phenotype that may not be apparent when individ- order that results in serious health and socioeconomic consequences. ual addiction conditions are considered. A review of this topic is Many studies have reported and implicated genes associated with given by Li and Burmeister (21). The availability of the Gene various substance dependence outcomes, including addiction to nic- Environment Association Studies Genes and Environment Ini- otine and addiction to alcohol. Using data from several genome-wide tiative Study of Addiction: Genetics and Environment (SAGE) case-control studies, we conducted a genome-wide association study data provides an unprecedented opportunity to study the ge- of a composite substance dependence phenotype derived from six netics of a composite trait: namely, addiction to at least two of individual diagnoses: addiction to nicotine, alcohol, marijuana, co- the six substances under study (nicotine, alcohol, marijuana, caine, opiates, or other drugs as a whole. We identified a strong (odds cocaine, opiates, and other drugs). -7E-8) association signal with In this report, we present a significant association at the genome ؍ and significant (P value (1.77 ؍ ratio the PBX/knotted 1 2 (PKNOX2) gene on 11 in wide level (␣ ϭ 0.05) of the PKNOX2 gene on with European-origin women with the composite phenotype. Our findings substance dependence in European-origin women. PKNOX2 has also indicate that the associations are not as significant when indi- been previously identified as one of the cis-regulated genes for vidual outcomes for addiction are considered, underscoring the im- alcohol addiction in mice (22). However, to our knowledge, portance of considering multiple addiction types. PKNOX2 has not been reported to be associated with any sub-

stance addiction outcomes in human populations. We have iden- GENETICS comorbidity ͉ genetics of addiction ͉ genomewide association tified a cluster of markers in the region of the PKNOX2 gene that are strongly associated with a composite addiction at the genome- here is strong evidence that vulnerability to substance de- wide level. We also investigate potential sex-specificity and racial Tpendence or addiction (drugs, alcohol, or smoking) is a differences in the association. complex trait with both genetic and environmental components Results (1–3). Whether legal or illicit, substance abuse is one of the most sought-after phenomena in many populations because of its Table 1 summarizes the top eight significant SNPs which cluster serious health and socioeconomic consequences. In 2008, the in PKNOX2 on chromosome 11 (11q24). None of the eight SNPs Centers for Disease Control and Prevention estimated that violates the Hardy-Weinberg equilibrium assumption (minimum SOCIAL SCIENCES ϭ ϭ 443,000 deaths were caused by cigarette smoking and exposure P level 0.12). The most significant SNP (rs12284594; P to second-hand smoke (4). In addition, alcohol misuse has been 7.13E-08) is observed in white women with an odds ratio (OR) linked to attempted and successful suicide, particularly among of 1.77; thus, those who have the risk allele (G) for rs12284594 adolescents (5). Clearly, a better understanding of the genetics are at significantly increased risk of being diagnosed with at least behind vulnerability to addictions could tremendously improve two of the six categories of substance dependence. This P value overall health and quality of life in general. A useful start in this reaches the accepted genome-wide significance level (23). In direction is given by Kreek et al. (6) In the literature, candidate addition, there are seven other SNPs with P values less than genes for addiction to alcohol, nicotine, and other substances 3.8E-06 in white women, and the corresponding ORs are similar individually have been identified. For example, GABRA2, in magnitude (1.63–1.72). We also examined haplotypes in this CHRM2, and ADH4 are well studied for alcohol addiction and region, but they did not enhance the strength of the associations; have been replicated in many samples (7–10), while several hence, these results are not reported here. Similarly, when newer candidate genes, such as GABRG3, TAS2R16, SNCA, related individuals were included in the analysis, the strength of OPRK1, and PDYN, remain to be confirmed (11). Many variants association was not enhanced, whether the analysis was per- at the aldehyde dehydrogenase (ALDH) and alcohol dehydro- formed using PedGenie (24), or whether the correlation among genase (ADH) loci have also been well-documented, especially related individuals was ignored. Although we also observed that in East-Asian populations (12–15). Several studies also report a these eight SNPs confer increased risk in white men, black men, gene cluster of nicotinic acetylcholine receptors (CHRNA5, and black women, they fail to reach genome-wide significance. CHRNA3, and CHRNB4) and Neurexin1 show allelic differ- Hence, detailed results are not presented here for these groups. ences in heavy vs. light smokers (16–19). Li (20) reported 13 Additional analyses were performed to examine each sub- regions on 3–7, 9–11, 17, 20, and 22 to be stance dependence outcome separately for the top eight SNPs significantly associated with nicotine dependence in at least two presented above. The corresponding P values for the eight SNPs for each substance dependence outcome are presented in Table independent samples, although a significant number of reported ϭ genomic regions did not reach the level of ‘‘suggestive’’ or 2. shows the strongest association (P ‘‘significant’’ linkage and failed to be replicated in other inde- pendent studies. Author contributions: X.C., K.C., and H.Z. designed research; X.C., K.C., B.H.S., and H.Z. Although individually different substance dependence out- performed research; X.C., K.C., and H.Z. contributed new reagents/analytic tools; X.C., K.C., comes have been previously studied, substance dependence as a and H.Z. analyzed data; and X.C., K.C., B.H.S., and H.Z. wrote the paper. whole, combining addiction to nicotine, alcohol, marijuana, The authors declare no conflict of interest. cocaine, opiates, and other drugs, has not been thoroughly 1X.C. and K.C. contributed equally to this work. investigated in association studies. We hypothesize that there is 2To whom correspondence may be addressed. E-mail: [email protected] or a common genetic predisposition for the composite substance [email protected]. www.pnas.org͞cgi͞doi͞10.1073͞pnas.0908521106 PNAS Early Edition ͉ 1of4 See Retraction Published September 9, 2009

Table 1. Summary of the 8 most significant SNPs in PKNOX2 A Overall gene showing genomewide significant association with Alcohol (A) Nicotine (N) substance dependence in White women n=1693 n=1625 AN (546) SNP P-value OR N (393) rs1426153 (G) 1.84E-06 1.66 A (327) rs11220015(A) 1.97E-06 1.65 ANC rs11602925(G) 1.24E-06 1.67 (608) rs750338(C) 4.22E-07 1.63 rs12273605(T) 3.83E-06 1.71 NC(78) rs10893365(C) 2.27E-07 1.72 AC(212) rs10893366(T) 6.87E-07 1.70 C(39) rs12284594(G) 7.13E-08 1.77 Cocaine (C) n=937 The high-risk allele is in the parenthesis. B White women Alcohol (A) Nicotine (N) 1.97E-06 with rs12284594); however, none of these P values n=433 n=572 attains the genomewide significance level of 0.05.

Discussion AN (184) N (247) We have found a genome-wide significant association of a composite substance dependence phenotype with a SNP in the A (89) PKNOX2 gene in white women. PKNOX2, PBX/knotted 1 ANC homeobox 2, belongs to the three-amino acid loop extension (129) (TALE) homeobox family. Homeodomain are highly conserved regulators. PKNOX2 was identified as a NC (12) TALE homeodomain-encoding gene, located at 11q24 in hu- AC(31) mans by Imoto et al. (25). They reported that the structure and C(2) subcellular localization of PKNOX2 indicate that this Cocaine (C) functions as a nuclear . Several years later, n=174 PKNOX2 was identified as one of the cis-regulated genes for alcohol addiction in mice (22). However, PKNOX2 has not been Fig. 1. Number of substance dependent subjects, according to DSM-IV, for reported to be associated with any substance dependence phe- the top three addiction categories: alcohol (A), nicotine (N), and cocaine (C) for (A) the overall sample and (B) the white women subset. notype in humans to date. The composite dichotomous sub- stance dependence variable reflects cases with two or more addictions where the top three categories are alcohol, nicotine It may also mean that there is more power in detecting common and cocaine (Fig. 1). Among all subjects, 47% have been genes acting upon co-morbid addiction outcomes as a whole. diagnosed with alcohol dependence in combination with other Different ethnic groups have vastly different underlying ge- substance dependence outcomes. Our results, which show a netics for many complex diseases, and these differences may strong association of this composite substance dependence confound association results when they are pooled together as variable with PKNOX2 gene in a human sample, support the one in the analysis. Previously, racial differences in the preva- experimental findings in mice by Mulligan et al. (22). Thus our lence of substance abuse have been reported (26–28). More findings make an important contribution in reporting PKNOX2 recently, Luo et al. (29) have reported that genetic differences as a candidate gene for substance dependence in humans, between black smokers and white smokers influence the nature particularly for white women in the SAGE sample. of their nicotine dependence; they found that black smokers In addition, among our most significant SNPs, we do not become dependent at a lower threshold (number cigarettes per observe those genes previously reported for or day) than white smokers. In the presence of subjects in different nicotine. Rather we find a set of genes among the top SNPs. ethnic populations in the data, it is crucial to investigate and When each substance dependence outcome was individually control for potential confounding by stratification and admixture analyzed for association with the eight most significant SNPs, we due to disequilibrium between pairs of unlinked loci (30). We found no association that reached genomewide significance. This investigated these two major ethnic groups separately in our suggests that substance dependence or addiction as a whole has analysis. In addition, we stratified our analysis by gender; based different risk genes compared to any single addiction outcome. on the premise that gender may be a confounding factor for the

Table 2. Associations of the 8 most significant SNPs in PKNOX2 with six individual substance dependence outcomes (p-values) SNP Nicotine Alcohol Marijuana Cocaine Opiates Others

rs1426153 (G) 0.0159 5.75E-5 7E-4 3E-4 0.0113 1E-4 rs11220015(A) 0.0163 6.86E-5 0.0010 3E-4 0.0037 4.18E-5 rs11602925(G) 0.0136 4.24E-5 7E-4 3E-4 0.0059 5.29E-5 rs750338(C) 0.0491 4.26E-5 0.0013 2E-4 0.0112 2.22E-5 rs12273605(T) 0.0921 3E-4 3.53E-5 1E-4 0.0680 3.11E-5 rs10893365(C) 0.0411 1.72E-5 8.58E-6 2.91E-5 0.0699 2.58E-5 rs10893366(T) 0.0621 1.37E-5 8.80E-6 8.63E-5 0.0905 5.35E-5 rs12284594(G) 0.0239 1.97E-6 8.54E-6 4.39E-5 0.0533 2.45E-5

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Table 3. Descriptive statistics of the sample stratified by sex and race Black Men White Men Black Women White Women Overall

n 535 1131 568 1393 3627 Age (SD) yr. 40.9 (8.2) 38.7 (10.3) 39.7 (6.7) 38.2 (9.1) 39.0 (9.1) Height (SD) m 1.78 (0.08) 1.79 (0.07) 1.64 (0.08) 1.65 (0.07) 1.71 (0.10) Weight (SD) kg 89.7 (18.3) 88.7 (16.8) 85.0 (21.9) 72.4 (18.8) 81.1 (20.1) Alcohol (%) 62.1 62.3 39.4 31.1 46.7 Cocaine (%) 46.4 27.3 36.3 12.5 25.8 Marijuana (%) 25.4 25.2 13.7 8.7 17.1 Nicotine (%) 47.5 46.7 47.7 41.1 44.8 Opiates (%) 8.2 9.9 6.2 4.8 7.1 Other drugs (%) 11.4 18.0 6.5 9.4 11.9 No drug (%) 27.1 31.0 38.9 50.1 39.0 substance dependence outcome, men may be socially more excluded 60 duplicate genotype samples and removed nine subjects with prone to environmental influences promoting substance use, ethnic backgrounds other than African origin (black) or European origin and thus more vulnerable to addiction, compared to women (31). (white). Table 3 lists the descriptive statistics of the sample included in our Our results from the two ethnic groups do not corroborate each study. Almost all subjects were either black (30.3%) or white (69.4%). In our final analysis, a total of 3,627 unrelated subjects with 830,696 autosomal SNPs other, which underscores the underlying genetic differences in were included. The final subset considered in the analysis consisted of 45.9% white and black samples. In fact, strong association signals are men and 54.1% women with mean ages of 39.4 and 38.6 years old, respec- observed only in the white woman sample. With a heterogeneous tively. Because substance dependence is a complex disease with both genetic population like SAGE, one must be cautious in analyzing and and environmental components, we analyzed the male and female subsets interpreting the results. separately. In addition, we performed separate analysis for blacks and whites The identification of PKNOX2 as a candidate gene for sub- in light of the possibility that underlying genetic variants may be different in stance use disorders underscores two important issues: (a) this different ethnic groups. Thus our study included four subsamples: 1,393 white GENETICS has not been possible in the past due to limited sample size, and women, 1,131 white men, 568 black women, and 535 black men. For each (b) we have considered a composite trait of six substance subset, the proportions of subjects diagnosed with lifetime dependence on substances in each of the six categories—nicotine, alcohol, marijuana, cocaine, dependence outcomes as a whole. The association becomes less opiates or other drugs—are summarized in Table 3. significant if individual substance addictions are considered. Thus, this highlights the importance of studying highly comorbid Statistical Analysis. Because of the presence of different ethnic populations in disorders or those which might otherwise have a common our data, it was crucial for us to investigate and control for potential con- pathway. However, our study is limited to the information in the founding by stratification and admixture due to disequilibrium between pairs available data, and we acknowledge the difficulty in operation- of unlinked loci (30). To avoid potential population stratification, we first alizing substance dependence; whether our operationalization of stratified our analysis by race and sex. Then we performed formal population SOCIAL SCIENCES addiction to two or more substances, truly reflects the strength stratification analysis for each subset using PLINK software (version 1.04) (34). of the addiction phenotype is open to question. Indeed, it may The results confirmed that each subset comes from a homogenous population; thus no further adjustment was needed to control for potential confounding simply reflect the extent of access to drugs. We also recognize by stratification and admixture. Overall a total of 1,513 subjects were defined that dependence on one substance shows different characteris- as having two or more substance addictions according to DSM-IV. Of these, tics from dependence on another, and it is valuable and neces- there were 316, 585, 237, and 357 subjects in the black male, white male, black sary to study them as individual entities. However, our call for female, and white female subsets, respectively. The distribution of subjects more attention to comorbidity and the combinatorial study of diagnosed with each substance dependence is presented in Table 3. The top these disorders should be viewed as a valuable complementary three most widely used substances among the six were alcohol, nicotine and effort. cocaine, in that order (Fig. 1). We used allelic ␹2 tests with one degree of freedom in our analysis, Methods stratified by race and sex. Haploview (version 4.0) (35) was used to analyze the linkage disequilbrium in the PKNOX2 gene region and the association be- Study of Addiction: Genetics and Environment (SAGE) Data. We obtained the tween the haplotypes and the composite phenotype. We performed addi- genome-wide single nucleotide polymorphisms (SNP) data from the database tional analyses by examining and comparing the results of including and of Genotype and Phenotype (dbGaP). The data were from the Study of excluding 214 related subjects in the data. For mixtures of unrelated and Addiction: Genetics and Environment (SAGE), which originally included 4,121 related subjects, we used PedGenie (24) to perform association analyses. subjects for whom the addiction to the six categories of substances and PedGenie first performs the allelic ␹2 tests treating all individuals indepen- genome-wide SNP data (ILLUMINA Human 1M platform) were available. SAGE dently then takes the pedigree information into account to assess statistical is a case-controlled study of mostly unrelated individuals aimed at identifying significance through permutation analysis. genetic associations for addiction. Cases and controls were selected from three large, complementary cohorts: Collaborative Study on the Genetics of Determination of Significance Threshold for GWAS. Using genotypes from the Alcoholism (COGA), Family Study of Cocaine Dependence (FSCD), and Collab- Wellcome Trust Case-Control Consortium, Dudbridge and Gusnanto (23) stud- orative Genetic Study of Nicotine Dependence (COGEND). These three studies ied the genomewide significance threshold for the U.K. Caucasian population. have been previously described (8, 29, 32, 33). Lifetime dependence on nico- They subsampled the genotypes at different densities and estimated the tine, alcohol, marijuana, cocaine, opiates, or other dependence on other threshold for 5% family-wise error using permutations. They then extrapo- drugs was diagnosed in accordance with the Diagnostic and Statistical Manual lated to infinity density and estimated that the genomewide significance of Mental Disorders, Fourth Edition (DSM-IV). As stated above, we studied a threshold for this population is 7.2E-8. We used this genome-wide significance composite addiction phenotype according to whether a subject was addicted threshold (7.2E-8) for the Caucasian population (white men and white to substances in at least two of the aforementioned categories. women) in our analysis.

Subject Characteristics and Study Design. In our study, we filtered SNPs by ACKNOWLEDGMENTS. This work was supported in part by National Institutes setting thresholds for minor allele frequency (MAF) and call rate (i.e., MAF of Health Grants K02DA017713, R01DA016750, and T32 MH014235. Study of Ͼ5% and call rate Ͼ90%). The initial filtering was done to reduce the level of Addiction: Genetics and Environment (SAGE) was supported by National noise in genotypes and increase the efficiency of analysis. In addition, we Institutes of Health Genes, Environment, and Health Initiative Grant U01

Chen et al. PNAS Early Edition ͉ 3of4 See Retraction Published September 9, 2009

HG004422. Study of Addiction: Genetics and Environment is one of the Family Study of Cocaine Dependence which is supported by National Institutes genome-wide association studies funded as part of the Gene Environment of Health Grant R01 DA013423. Genotyping was performed at the Johns Association Studies under Genes, Environment, and Health Initiative. Assis- Hopkins University Center for Inherited Disease Research, and was supported tance with phenotype harmonization and genotype cleaning, as well as with by National Institutes of Health Genes, Environment, and Health Initiative general study coordination, was provided by the Gene Environment Associa- Grant U01HG004438, the National Institute on Alcohol Abuse and Alcoholism, tion Studies Coordinating Center, which is supported by National Institutes of the National Institute on Drug Abuse, and National Institutes of Health Health Grant U01 HG004446. Assistance with data cleaning was provided by the National Center for Biotechnology Information. Support for collection of contract HHSN268200782096C, ‘‘High throughput genotyping for studying datasets and samples was provided by the Collaborative Study on the Genetics the genetic contributions to human disease.’’ The datasets used for the of Alcoholism, which is supported by National Institutes of Health Grant U10 analyses described in this manuscript were obtained from dbGaP at http:// AA008401; the Collaborative Genetic Study of Nicotine Dependence, which is www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study࿝id ϭ supported by National Institutes of Health Grant P01 CA089392; and the phs000092.v1.p1 through dbGaP accession number phs000092.v1.p.

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