Original Article
Variant GADL1 and Response to Lithium Therapy in Bipolar I Disorder
N Engl J Med 2014; 370:119-128January 9, 2014DOI: 10.1056/NEJMoa1212444
- Abstract
Background
Lithium has been a first-line choice for maintenance treatment of bipolar disorders to prevent relapse of mania and depression, but many patients do not have a response to lithium treatment.
Methods
We selected subgroups from a sample of 1761 patients of Han Chinese descent with bipolar I disorder who were recruited by the Taiwan Bipolar Consortium. We assessed their response to lithium treatment using the Alda scale and performed a genomewide association study on samples from one subgroup of 294 patients with bipolar I disorder who were receiving lithium treatment. We then tested the single-nucleotide polymorphisms (SNPs) that showed the strongest association with a response to lithium for association in a replication sample of 100 patients and tested them further in a follow-up sample of 24 patients. We sequenced the exons, exon–intron boundaries, and part of the promoter of the gene encoding glutamate decarboxylase–like protein 1 (GADL1) in 94 patients who had a response to lithium and in 94 patients who did not have a response in the genomewide association sample.
Results
Two SNPs in high linkage disequilibrium, rs17026688 and rs17026651, that are located in the introns of GADL1 showed the strongest associations in the genomewide association study (P=5.50×10−37 and P=2.52×10−37, respectively) and in the replication sample of 100 patients (P=9.19×10−15 for each SNP). These two SNPs had a sensitivity of 93% for predicting a response to lithium and differentiated between patients with a good response and those with a poor response in the follow-up cohort. Resequencing of GADL1 revealed a novel variant, IVS8+48delG, which lies in intron 8 of the gene, is in complete linkage disequilibrium with rs17026688 and is predicted to affect splicing.
Conclusions
Genetic variations in GADL1 are associated with the response to lithium maintenance treatment for bipolar I disorder in patients of Han Chinese descent. (Funded by Academia Sinica and others.)
Media in This Article
Figure 1
Association between Single-Nucleotide Polymorphisms (SNPs) and a Response to Lithium Maintenance Treatment in the Discovery Cohort, According to Four Cutoff Points on the Alda Scale.Table 1
Demographic and Clinical Characteristics of 394 Patients.Article Activity
- Article
Bipolar disorder is a disabling mental illness that is characterized by episodes of both elevated or irritable mood and depression.1,2 Currently, lithium is the first-line choice for maintenance treatment of bipolar disorder and reduces the risks of relapse and suicide.3-5 Approximately 80% of patients with bipolar I disorder who are treated with lithium over the long term have at least a partial response,6 and 30% have an excellent response7,8 with complete remission of symptoms observed in populations of patients of European descent.
Clinical predictors of a good response to lithium treatment have been reported, such as age at the onset of symptoms, a family history of bipolar disorder, the occurrence of rapid cycling, and drug adherence.9,10 Patients who have a good response to lithium treatment seem to cluster in families, suggesting that familial clustering can be used as a predictor for a recurrence of symptoms.11,12 It has been suggested that lithium may exert its therapeutic effects through the inhibition of the G proteins and three other molecules: inositol monophosphatase, glycogen synthase kinase 3b, and adenylyl cyclase.13
The first genomewide association study of response to lithium for the prevention of the recurrence of symptoms of bipolar disorder in populations of European descent14 showed that a positive response might be associated with variation in a region on chromosome 4q32 spanning GRIA2, a gene encoding a glutamate receptor. However, a survey of genomewide association studies involving European populations that used an online repository of genetic data showed limited information about the response to lithium in bipolar disorder.15 No single-nucleotide polymorphisms (SNPs) that were associated with the response to lithium had sufficient sensitivity for clinical use. Here, we report the identification of genetic determinants of response to lithium maintenance treatment in patients with bipolar I disorder.
Methods
Study Patients
This study was conducted by the Taiwan Bipolar Consortium, which was established in 2003 with members from the Institute of Biomedical Sciences, Academia Sinica, and 25 psychiatric departments of general hospitals and psychiatric institutions in Taiwan.16 The consortium initially set out to understand genetic susceptibility to bipolar I disorder and broadened its scope to the pharmacogenetic study of mood stabilizers. The first part of the study has been described previously.16 In brief, unrelated patients, 20 to 65 years of age, who had bipolar I disorder were recruited from the psychiatric departments and institutions of the Taiwan Bipolar Consortium. Bipolar I disorder with recurrent episodes of mania with or without depressive episodes had been diagnosed in all the patients, according to criteria of the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV).17 We excluded patients with other psychotic and affective disorders.
Psychiatric nurses and psychiatrists evaluated the study patients using a cross-culturally validated Chinese version of the Schedules for Clinical Assessment in Neuropsychiatry (SCAN),18 supplemented by available medical records and reports from family members and treating psychiatrists. Only patients of Han Chinese descent were considered for the study, with ancestry determined on the basis of oral report by the patients to members of the research team. From March 2003 through May 2012, we recruited 1761 patients with bipolar I disorder.
Study Design and Oversight
We performed a discovery genomewide association study and two tests of replication. Using array methods, we genotyped 1647 patients with bipolar I disorder who were consecutively recruited from outpatient clinics and inpatient units of the 25 psychiatric departments and institutions in the Taiwan Bipolar Consortium. For the genomewide association study, we identified 294 (17.9%) of these patients (discovery cohort) who had received lithium treatment with good adherence for at least 2 years. The remainder of the patients in the series either did not receive such treatment or did not have good adherence for at least 2 years. We identified genetic regions associated with a response to lithium treatment and then performed a replication test using SNPs marking these loci in an independent group of 100 patients with bipolar I disorder (first replication cohort). These 100 patients were selected from 114 patients with bipolar I disorder (distinct from the discovery cohort) who were referred to us by staff psychiatrists who had treated them for more than 10 years with lithium and observed good adherence to the therapy. The remaining 14 patients were excluded because they did not fulfill the inclusion criteria.
In a second test of replication, we genotyped an independent series of 24 patients who had received lithium monotherapy for at least 2 years through May 2012 (second replication cohort). The inclusion criteria for these patients were based on a life chart that was constructed for all 1761 patients with bipolar I disorder. Each of these 24 patients had had a history of good adherence to mood stabilizers other than lithium before they initiated lithium monotherapy but had had an unsatisfactory response to such mood stabilizers.
The study was approved by the institutional review board at each participating hospital and at Academia Sinica, Taiwan. All the patients provided written informed consent.
Phenotype Definition and Assessment
To assess the response to long-term lithium treatment in bipolar I disorder, we prepared a life chart with a graphic depiction of a lifetime clinical course for each of the 1761 patients recruited before June 2012. This life chart included all manic, hypomanic, and depressive episodes with the date of onset (year and month), duration, and severity (including the extent of functional disability, hospitalization, and the presence of psychotic features); all doses of and duration of treatment with psychotropic drugs and mood stabilizers that were known have been prescribed; drug adherence, as recorded in medical charts for all visits at outpatient clinics; all recorded blood levels of mood stabilizers; and any adverse drug reactions. We presented this information graphically on the basis of integrated information gathered from direct interview with the patients and their family members, interviews with in-charge psychiatrists, and a thorough medical-chart review. On the basis of this life chart, we determined whether each patient had a history of good drug adherence.
We assessed the phenotype of lithium response on the basis of the life chart, using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder developed by Martin Alda and colleagues (Alda scale) (see the Methods section in the Supplementary Appendix, available with the full text of this article at NEJM.org).12 The Alda scale has two criteria. Criterion A measures the extent of clinical improvement (the reduction in illness activity) and takes into account the frequency, duration, and severity of episodes during periods of lithium treatment considered to be adequate in duration and dose, as compared with the frequency, duration, and severity of episodes during periods in which the patient was not receiving lithium treatment. Criterion A is scored on a scale from 0 (no change in disease severity or exacerbation) to 10 (complete remission). Criterion B (divided into B1 through B5, with each part scored as 0, 1, or 2 points) is used to determine whether there is a causal relationship between clinical improvement and treatment. B1 and B2 are measures of the number and frequency of episodes, respectively, while the patient is not receiving lithium treatment (with higher scores indicating lower number and frequency of episodes), B3 is a measure of the duration of lithium treatment (with higher scores indicating lower duration), B4 is a measure of adherence to lithium treatment (with higher scores indicating worse adherence), and B5 is a measure of concomitant use of psychotropic medications during periods of stability (with higher scores indicating higher dose and longer duration of use). The total score is obtained by subtracting the sum of the B scores from the A score.
In investigating a causal relationship between lithium treatment and clinical improvement in individual patients, it is important to ensure the following three factors: the ability to compare the clinical course (number, frequency, and severity of episodes) between periods in which the patients were receiving lithium and those in which they were not, satisfactory drug adherence, and the minimization of influence from additional medications (hypnotics, antidepressants, antipsychotics, and other mood stabilizers). We determined inclusion criteria accordingly in order to minimize the misclassification of patients who had a response to lithium and those who did not have a response. For example, we included patients who had a poor response to lithium combined with prolonged use of antipsychotics or additional mood stabilizers and excluded those with a good response to lithium combined either with the use of an additional mood stabilizer throughout the course or with prolonged use of high-dose antipsychotic drugs (see the Methods section in the Supplementary Appendix).
For patients in the second replication cohort, we performed regular follow-up evaluations at outpatient clinics (usually monthly or at least once every 3 months) for at least 2 years. The evaluations included a lithium assay to assess drug adherence and a SCAN interview to assess the patient's clinical condition.
We tested the interrater reliability of the Alda scale by evaluating 18 randomly selected patients with bipolar I disorder from the discovery cohort. Three senior psychiatrists performed ratings that were based on the life chart. We observed an intraclass correlation among the three evaluators of 0.904 for the total score (0 to 10) (Table S1 in the Supplementary Appendix).
Outcomes
In previous studies that used the Alda scale, investigators adopted a total score of 6 to 7 as the best cutoff point between patients with no response to lithium treatment (0 to 6) and those with a response (7 to 10).12,19 For patients in the discovery cohort, we selected four potential cutoff points that were associated with a reduction in illness activity (4 to 5 points, >50% reduction; 5 to 6 points, >65% reduction; 6 to 7 points, >80% reduction; and 7 to 8 points, >90% reduction) for classifying patients according to their response to lithium treatment.
Genotyping, Imputation, and Sequencing
We genotyped samples obtained from the 1647 patients in the discovery cohort using the Illumina HumanHap550-Duo BeadChip and the HumanOmni1-Quad BeadChip and integrated the two data sets through imputation with HapMap phase 2 data. Quality-control procedures were applied to the genotype data and the imputed data (for details, see the Methods section in the Supplementary Appendix). We genotyped the top SNPs in the two replication cohorts using the Sequenom MassARRAY platform and then used the Applied Biosystems 3730 DNA Analyzer to sequence GADL1 in samples obtained from 94 patients with a response to lithium treatment and 94 patients without a response who were randomly selected from the discovery cohort (see the Methods section in the Supplementary Appendix).
Statistical Analysis
We compared the prevalence of alleles that were implicated by results of the genomewide association study in patients with a response to lithium treatment and those without a response using the Cochran–Armitage test for trend. The threshold P value was set at 6.9×10−9 after a Bonferroni correction for the number of SNPs (1,814,186) and for the four different cutoff points. We examined P-value distributions using quantile–quantile (Q-Q) plots (Fig. S2 in the Supplementary Appendix). We analyzed the data from the genomewide association study according to the four cutoff points used to classify patients with a response to lithium treatment and those without a response. We used PLINK software, version 1.07,20 to evaluate the top hits with adjustments for psychotic features (delusion and hallucination), a history of bipolar I disorder in at least one first-degree relative, rapid cycling, age at onset, sex, and history of alcoholism.
Results
Study Patients
Demographic and clinical characteristics of the 294 patients in the discovery cohort and the 100 patients in first replication cohort, including clinical phenotypes previously reported to be associated with lithium responses, are shown in Table 1Table 1
Demographic and Clinical Characteristics of 394 Patients.. The median age of the patients was 49 years, and there were similar proportions of men and women. A majority of patients (60%) were found to have a history of psychotic features. The percentages of rapid cycling and history of bipolar I disorder in at least one first-degree relative were 25% and 31%, respectively. Early-onset disease occurred in 15% of the patients, and 8% had a history of alcoholism.During periods in which the patients were not receiving lithium, the median number of episodes since disease onset was 6 (range, 4 to 144), and the median frequency of episodes was 1 per year (range, 0.4 to 15). The median duration of lithium therapy with good adherence was 7 years (range, 2 to 28). The reported lithium blood levels were equal to or exceeded 0.5 mmol per liter.21,22
We compared disease activity during periods with good adherence to lithium therapy with activity during periods in which the patients were not receiving lithium. During periods of good adherence, we observed that a large proportion of patients (88%) were taking other drugs, and a quarter of the patients had received a prolonged course of antidepressants, antipsychotics, or mood stabilizers in addition to lithium. (The distribution of scores on the Alda scale in the discovery and replication cohorts is provided in Table S2 in the Supplementary Appendix.).
Association Analysis
The 294 patients who provided samples for the genomewide association study shared a homogeneous genetic background and were unrelated to one another (Fig. S1 in the Supplementary Appendix). SNPs on chromosome 3p24.1 showed an association with a response to lithium at genomewide significance (P<6.9×10−9), with no other chromosome region showing a significant association (Figure 1Figure 1
Association between Single-Nucleotide Polymorphisms (SNPs) and a Response to Lithium Maintenance Treatment in the Discovery Cohort, According to Four Cutoff Points on the Alda Scale.). (Summary statistics from the genomewide association study can be found in the database of Genotypes and Phenotypes [dbGaP] of the National Center for Biotechnology Information, accession number phs000692.v1.p1.) Two SNPs in particular, rs17026688 and rs17026651, which are located approximately 7.2 kb apart in the introns of the gene encoding glutamate decarboxylase-like protein 1 (GADL1), showed the strongest associations, with a cutoff point of 5 to 6 (P=5.50×10−37 and P=2.52×10−37, respectively). The highest sensitivity and specificity for response to lithium were 93% and 85%, respectively, for rs17026688 and 93% and 86%, respectively, for rs17026651 at this cutoff point (Table S3 in the Supplementary Appendix).Subsequently, in the first replication cohort, we genotyped rs17026688 and rs17026651, together with flanking SNPs in GADL1 that showed genomewide significance in the discovery cohort. Both rs17026688 and rs17026651 showed the strongest associations in the test of replication (P=9.19×10−15 for both SNPs). The distributions of allele prevalence in the top SNPs did not differ significantly between the genomewide association study and replication samples. The P values for rs17026688 and rs17026651 in the combined series, comprising 394 study patients, were P=1.66×10−49 and P=7.07×10−50, respectively (Table S4 in the Supplementary Appendix). The association between allele status and response status in the combined series showed P values of 6.69×10−62 and 8.30×10−63, respectively, for the two SNPs with the use of Fisher's exact test (Table S5 in the Supplementary Appendix). We observed that the two SNPs were in high or absolute linkage disequilibrium (discovery cohort, r2=96.6%; first replication cohort, r2=100%).
Among the 24 patients in the second replication cohort (the follow-up study), the two top SNPs were also in complete linkage disequilibrium. All 16 carriers of the “response” alleles had a good response (total Alda score, 8 to 10), and all 8 noncarriers had a poor response (total Alda score, 0 to 3) (Table S6 in the Supplementary Appendix). The genomewide association study (with 394 patients) and the follow-up study (with 24 patients) reached acceptable statistical powers of 85% and 95%, respectively (see the Methods section in the Supplementary Appendix).
We carried out further analyses of rs17026688 to test the association between this SNP and the response to lithium treatment (Table 2Table 2
Allele Prevalence of rs17026688, According to the Response to Lithium Therapy.). To assess the influence of other factors that might contribute to a response to lithium, we performed logistic-regression analyses on data from all 394 patients (Table S7 in the Supplementary Appendix). We found that the “response” allele T at rs17026688 was associated with a much better response to lithium than was the alternative allele (P=3.39×10−32; odds ratio, 111.87; 95% confidence interval [CI], 51.14 to 244.73; positive predictive value, 83%; 95% CI, 76 to 88). In addition, patients with rapid cycling (regardless of genetic status) had a slightly better response to lithium than those without rapid cycling (P=8.47×10−4; odds ratio, 3.88; 95% CI, 1.75 to 8.59). Using the same logistic-regression model, we found that the other 21 flanking SNPs showed nominal significance or no significance when they were conditioned on rs17026688 (P>0.002 for all comparisons) (Table S8 in the Supplementary Appendix).Resequencing of GADL1
Because the SNPs that showed the strongest association were in the introns of GADL1, we next looked for local variants that were likely to affect the expression of GADL1. We randomly selected from the discovery cohort 94 patients with a response to lithium treatment and 94 patients without a response for sequence analysis of the exons, intron–exon boundaries, and a 2-kb region representing part of the promoter of GADL1. We found 32 genetic polymorphisms, including a 1-base deletion in intron 8 of GADL1 (IVS8+48delG) (Table S9 in the Supplementary Appendix). We genotyped this variant in samples from all 418 patients in the discovery and replication cohorts and found it to be in complete linkage disequilibrium with rs17026688.
Effect of the IVS8+48delG Variant
To test the effect of the IVS8+48delG variant on splicing of GADL1 messenger RNA (mRNA), we determined the mRNA isoforms using a reverse-transcriptase–polymerase-chain-reaction assay in two glioma-derived neural cell lines.23,24 One line (GBMS1R1) carries a IVS8+48delG variant, and the other (GBM8401) carries two nonmutated alleles. We detected two GADL1 mRNA isoforms: GBM8401 expressed the major mRNA isoform (499 bp) containing exons 5 to 10 (Fig. S5 in the Supplementary Appendix). We also detected the minor splice variant (364 bp) containing exons 5, 6, 9, and 10; exons 7 and 8 were omitted, presumably by alternative splicing (Fig. S6 in the Supplementary Appendix). As compared with the cell line GBM8401, the cell line GBM S1R1 (which carried the IVS8+48delG variant) showed low levels of the major isoform and elevated levels of the smaller, alternatively spliced mRNA species.
Discussion
The wide variation in the clinical course of bipolar disorder, the lack of adherence of some patients to mood stabilizer therapy, and the difficulty in accurately recording adherence over the long term25 have probably resulted in the misclassification of the lithium response in a nontrivial proportion of patients in pharmacogenetic studies of the response to mood stabilizers. Since the Alda scale provides a means of addressing these problems, we used it in determining inclusion criteria for this study (see the Methods section in the Supplementary Appendix). We are confident that few if any of the patients who were evaluated in this study had affective or psychotic disorders other than bipolar I disorder, because previous studies have shown that interrater reliability is higher for bipolar I disorder than for any other affective spectrum disorder.26 In addition, there is evidence of substantive genetic heterogeneity underlying the various affective disorders.27 It is unlikely that we would have observed the strong associations that we did if there had been a substantial proportion of patients with disorders other than bipolar I disorder.
Using a stringent phenotype definition, we carried out a two-stage test of association and follow-up analyses and identified two SNPs and a single-base deletion associated with a response to lithium treatment. These three variants strongly predicted the outcome in a small follow-up cohort. It is likely that our attentive monitoring to ensure good drug adherence in the follow-up sample of 24 patients provided unusually accurate assessment of the response to lithium. This may explain the two-peak distribution of total Alda scores in patients with a good response (8 to 10) and those with a poor response (0 to 3), as compared with the distribution in the genomewide association study and replication groups (Table S2 in the Supplementary Appendix).
GADL1 protein belongs to the group II decarboxylase family. Although its physiologic function remains unknown, it may be similar to that of glutamate decarboxylase (GAD), because the two proteins have a pyridoxal-dependent decarboxylase catalytic domain, which is involved in the decarboxylation of glutamate, histidine, tyrosine, and aromatic l-amino acid (Fig. S3 in the Supplementary Appendix). GAD is also a key enzyme in the biosynthesis of γ-aminobutyric acid (GABA).28 Moreover, both GADL1 and GAD are expressed in the human brain, where glutamate acts as the primary excitatory neurotransmitter and GABA as the major inhibitory neurotransmitter (Fig. S4 in the Supplementary Appendix). Two isoforms of GAD (GAD65 and GAD67), which are encoded by two different genes, are underexpressed in patients with bipolar disorder.29 Long-term lithium treatment may alter not only the glutamate-receptor distribution but also synaptic morphologic features.13 Our results are consistent with those of the first genomewide association study of lithium treatment, which suggests the importance of the glutamate pathway in bipolar disorder and the mechanism by which lithium may affect glutamatergic neurotransmission.14 The deletion variant IVS8+48delG may affect the structure of the pyridoxal-dependent decarboxylase domain in GADL1 by altering splicing and thus decarboxylation activity, but this hypothesis remains to be resolved.
Our study suggests that rs17026651, GADL1 IVS8+48delG, and rs17026688 are useful biomarkers in predicting the response to lithium maintenance treatment in patients of Asian ancestry who have bipolar I disorder. These alleles are rare in persons of European and African ancestry (Table S10 in the Supplementary Appendix),30,31 but it is possible that other variants in GADL1 may influence the response to lithium therapy in these populations. The use of these markers in affective disorders other than bipolar disorder, such as refractory major depressive disorder (for which lithium is used to augment the effect of antidepressant drugs21), awaits investigation.
Nearly half of the 1761 patients with bipolar I disorder in this study (47.2%) carry the response allele T of rs17026688, a prevalence similar to that in the general Han Chinese population,30,31 suggesting that approximately half of the patients with bipolar I disorder in Taiwan may benefit from lithium therapy. The confirmation of our findings in larger case series is warranted.
Supported by grants from Academia Sinica, Taiwan (AS 23-23, 52102310023C), and Academia Sinica Genomic Medicine Multicenter Study (AS 40-05); and the National Science Council, Taiwan (National Center for Genomic Medicine, NSC101-2319-B-001-001; Translational Resource Center for Genomic Medicine, NSC101-2325-B-001-035; and National Research Program for Biopharmaceuticals, NSC100-2325-B-001-026 and NSC101-2325-B-001-023).
Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.
Drs. C.-H. Chen, C.-S. Lee, and M.-T.M. Lee contributed equally to this article.
This article was published on December 25, 2013, and updated on May 8, 2014, at NEJM.org.
Source Information
The authors' affiliations are listed in the Appendix.
Address reprint requests to Dr. Cheng or Dr. Y.-T. Chen at the Institute of Biomedical Sciences, Academia Sinica, Taipei, 11529 Taiwan, or at bmandrew@gate.sinica.edu.tw or chen0010@ibms.sinica.edu.tw.
Members of the Taiwan Bipolar Consortium are listed in the Supplementary Appendix, available at NEJM.org.
Appendix
The authors' affiliations are as follows: the Institute of Biomedical Sciences, Academia Sinica (C.-H. Chen, M.-T.M.L., C.-F.L., K.H.-T.W., L.S.-H.W., Y.-C.L., H.-L.P., C.-P.C., L.-S.L., J.-Y.W., Y.-T.C., A.T.-A.C.), Department of Psychiatry, School of Medicine, Taipei Medical University (C.-H. Chiu, Chiao-Chicy Chen., J.-J.L.), Taipei City Psychiatric Center (F.-W.L., C.-H. Chiu, C.-C.F.), Department of Psychiatry, Mackay Medical College and Mackay Memorial Hospital (C.-S.L., Chiao-Chicy Chen), Department of Psychiatry, Taipei Veterans General Hospital (Y.-S.C., T.-P.S.), Department of Psychiatry, Far Eastern Memorial Hospital (J.F.), Department of Psychiatry, Cathay General Hospital (C.-J.C.), and Department of Psychiatry, Cardinal Tien Hospital School of Medicine, Fu Jen Catholic University (I-C.L.) — all in Taipei; Taoyuan Mental Hospital (H.K.-L.T., J.-J.C.), Department of Psychiatry, Chang-Gung University and Chang-Gung Medical Center at Linkou (C.-Y.L.), and Ju Shan Hospital (C.C.F.) — all in Taoyaun; Department of Psychiatry, Chang-Gung University and Chang-Gung Medical Center at Kaohsiung (M.-Y.C.), Kaohsiung Municipal Kai-Syuan Psychiatric Hospital (H.-Y.T., Cheng-Chung Chen), Department of Psychiatry, Kaohsiung Veterans General Hospital (C.-H.C., T.L.), Tsyr-Huey Mental Hospital (C.-K.W.), and Department of Psychiatry, Kaohsiung Medical University and National Defense Medical Center (F.-W.L.) — all in Kaohsiung; Department of Psychiatry, China Medical University Hospital (H.-Y.L.), Department of Psychiatry, Taichung Veterans General Hospital (L.-J.C.), Department of Psychiatry, Chung Shan Medical University Hospital (T.-J.L.), and Graduate Institute of Chinese Medical Science, China Medical University (C.-H.C., M.T.-M.L., J.-Y.W.) — all in Taichung; Department of Psychiatry, Changhua Christian Hospital (N.-Y.C.), and Department of Psychiatry, Show Chwan Memorial Hospital (P.-R.T.) — both in Changhua; Tsaotun Psychiatric Center, Nantou (T.-J.C., C.-Y.C.); Department of Psychiatry, Chia-Yi Christian Hospital (Y.-M.H.), and Department of Psychiatry, Buddhist Tzu Chi Da-Lin General Hospital (C.-L.T.) — both in Chiayi; Jianan Mental Hospital (W.-C.O.) and Department of Psychiatry, Chi Mei Medical Center — both in Tainan (J.-J.L.); Department of Psychiatry, Chang-Gung University and Chang-Gung Medical Center at Keelung, Keelung (C.-K.C.); Institute of Medical Sciences, Tzu Chi University, Hualien (L.S.-H.W.); and Institute of Molecular Medicine, National Tsing Hua University, Hsinchu (Y.-C.L.) — all in Taiwan; and Department of Pediatrics, Duke University Medical Center, Durham, NC (Y.-T.C.).
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