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Genome-wide association studies (GWAS) of human complex traits or diseases often implicate genetic loci that span hundreds or thousands of genetic variants, many of which have similar statistical significance. While statistical fine-mapping in individuals of European ancestry has made important discoveries, cross-population fine-mapping has the potential to improve power and resolution by capitalizing on the genomic diversity across ancestries. Here we present SuSiEx, an accurate and computationally efficient method for cross-population fine-mapping. SuSiEx integrates data from an arbitrary number of ancestries, explicitly models population-specific allele frequencies and linkage disequilibrium patterns, accounts for multiple causal variants in a genomic region and can be applied to GWAS summary statistics. We comprehensively assessed the performance of SuSiEx using simulations. We further showed that SuSiEx improves the fine-mapping of a range of quantitative traits available in both the UK Biobank and Taiwan Biobank, and improves the fine-mapping of schizophrenia-associated loci by integrating GWAS across East Asian and European ancestries.
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Educational attainment (EduYears), a heritable trait often used as a proxy for cognitive ability, is associated with various health and social outcomes. Previous genome-wide association studies (GWASs) on EduYears have been focused on samples of European (EUR) genetic ancestries. Here we present the first large-scale GWAS of EduYears in people of East Asian (EAS) ancestry (n = 176,400) and conduct a cross-ancestry meta-analysis with EduYears GWAS in people of EUR ancestry (n = 766,345). EduYears showed a high genetic correlation and power-adjusted transferability ratio between EAS and EUR. We also found similar functional enrichment, gene expression enrichment and cross-trait genetic correlations between two populations. Cross-ancestry fine-mapping identified refined credible sets with a higher posterior inclusion probability than single population fine-mapping. Polygenic prediction analysis in four independent EAS and EUR cohorts demonstrated transferability between populations. Our study supports the need for further research on diverse ancestries to increase our understanding of the genetic basis of educational attainment.
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Éxito Académico , Pueblos del Este de Asia , Humanos , Escolaridad , Estudio de Asociación del Genoma Completo , Herencia Multifactorial/genética , Población BlancaRESUMEN
Genome-wide association studies (GWASs) have identified tens of thousands of genetic loci associated with human complex traits. However, the majority of GWASs were conducted in individuals of European ancestries. Failure to capture global genetic diversity has limited genomic discovery and has impeded equitable delivery of genomic knowledge to diverse populations. Here we report findings from 102,900 individuals across 36 human quantitative traits in the Taiwan Biobank (TWB), a major biobank effort that broadens the population diversity of genetic studies in East Asia. We identified 968 novel genetic loci, pinpointed novel causal variants through statistical fine-mapping, compared the genetic architecture across TWB, Biobank Japan, and UK Biobank, and evaluated the utility of cross-phenotype, cross-population polygenic risk scores in disease risk prediction. These results demonstrated the potential to advance discovery through diversifying GWAS populations and provided insights into the common genetic basis of human complex traits in East Asia.
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Genome-wide association studies (GWASs) have been mostly conducted in populations of European ancestry, which currently limits the transferability of their findings to other populations. Here, we show, through theory, simulations and applications to real data, that adjustment of GWAS analyses for polygenic scores (PGSs) increases the statistical power for discovery across all ancestries. We applied this method to analyze seven traits available in three large biobanks with participants of East Asian ancestry (n = 340,000 in total) and report 139 additional associations across traits. We also present a two-stage meta-analysis strategy whereby, in contributing cohorts, a PGS-adjusted GWAS is rerun using PGSs derived from a first round of a standard meta-analysis. On average, across traits, this approach yields a 1.26-fold increase in the number of detected associations (range 1.07- to 1.76-fold increase). Altogether, our study demonstrates the value of using PGSs to increase the power of GWASs in underrepresented populations and promotes such an analytical strategy for future GWAS meta-analyses.
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Pueblos del Este de Asia , Estudio de Asociación del Genoma Completo , Herencia Multifactorial , Humanos , Estudio de Asociación del Genoma Completo/métodos , Fenotipo , Polimorfismo de Nucleótido Simple , Pueblos del Este de Asia/genéticaRESUMEN
OBJECTIVES: To assess the causal influence of sleep and circadian traits on coronary artery disease and sudden cardiac arrest with adjustment for obesity through a two-sample Mendelian randomization study. METHODS: We used summary statistics of 5 sleep and circadian traits for genome-wide association studies, including chronotype, sleep duration, long sleep (≥9 h a day), short sleep (<7 h a day), and insomnia (sample size range: 237,622-651,295). Coronary artery disease genome-wide association studies with 60,801 cases and 123,504 controls, sudden cardiac arrest genome-wide association studies with 3939 cases and 25,989 controls, and obesity genome-wide association studies with 806,834 individuals were also used. Multivariable Mendelian randomization was performed to estimate the causality. RESULTS: After adjusting for obesity, genetically predicted short sleep (odds ratio = 1.87 and p = .02), and genetically predicted insomnia (odds ratio = 1.17 and p = .001) were causally associated with increased odds of coronary artery disease. Genetically predicted long sleep (odds ratio = 0.06 and p = .02) and genetically predicted longer sleep duration (odds ratio = 0.36 for per-hour increase in sleep duration and p = .0006) were causally associated with decreased odds of sudden cardiac arrest. CONCLUSIONS: The findings of this Mendelian randomization study indicate that insomnia and short sleep contribute to the development of coronary artery disease, whereas a longer sleep duration protects from sudden cardiac arrest, independent of the influence of obesity. The mechanisms underlying these associations warrant further investigation.
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Antidepressant response, the effectiveness of antidepressants in relieving symptoms of depression, is a complex trait influenced by both genetic and environmental factors. However, despite decades of research, the specific genetic variations that contribute to antidepressant response and treatment-resistant depression (TRD) remain largely unknown. In this review, we summarize the current state of knowledge of the genetics of antidepressant response and TRD, including candidate gene association studies, genome-wide association studies (GWAS), polygenic risk score (PRS) analyses, whole genome sequencing studies, research on other genetic and epigenetic changes, and the potential for precision medicine in this field. Although some progress has been made in identifying genetic factors associated with antidepressant response and TRD, much work remains to be done, particularly in terms of larger sample sizes and standardization of outcome measures. Further research in this area has the potential to improve the treatment of depression and increase the chances of successful treatment for individuals with this common and debilitating mental illness.
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Depresión , Estudio de Asociación del Genoma Completo , Humanos , Depresión/tratamiento farmacológico , Depresión/genética , Antidepresivos/farmacología , Antidepresivos/uso terapéutico , Epigénesis GenéticaRESUMEN
Genome-wide association studies (GWAS) of human complex traits or diseases often implicate genetic loci that span hundreds or thousands of genetic variants, many of which have similar statistical significance. While statistical fine-mapping in individuals of European ancestries has made important discoveries, cross-population fine-mapping has the potential to improve power and resolution by capitalizing on the genomic diversity across ancestries. Here we present SuSiEx, an accurate and computationally efficient method for cross-population fine-mapping, which builds on the single-population fine-mapping framework, Sum of Single Effects (SuSiE). SuSiEx integrates data from an arbitrary number of ancestries, explicitly models population-specific allele frequencies and LD patterns, accounts for multiple causal variants in a genomic region, and can be applied to GWAS summary statistics. We comprehensively evaluated SuSiEx using simulations, a range of quantitative traits measured in both UK Biobank and Taiwan Biobank, and schizophrenia GWAS across East Asian and European ancestries. In all evaluations, SuSiEx fine-mapped more association signals, produced smaller credible sets and higher posterior inclusion probability (PIP) for putative causal variants, and captured population-specific causal variants.
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AIMS: Quetiapine is widely used to treat psychiatric disorders such as major depression, generalized anxiety disorder, dysthymic disorder, and insomnia other than schizophrenia and bipolar disorder. This study investigated the diagnostic distribution of quetiapine use in patients in a psychiatric hospital, the doses of quetiapine prescribed, and the plasma concentrations (Cps) of quetiapine and active metabolites. METHODS: We enrolled 107 patients who had been prescribed quetiapine for at least 4 weeks. Diagnoses, demographics, and concomitant medications were recorded. Blood sampling was performed in the morning, approximately 12 h after the before-bed dose of quetiapine. RESULTS: Diagnoses comprised schizophrenia (n = 25), bipolar disorder (n = 51), major depression (n = 15), dysthymic disorder (n = 9), and others (n = 7). The daily dose (DD) of quetiapine ranged from 25 to 800 (175.9 ± 184.4) mg, with the mean Cp being 105.6 ± 215.3 ng/ml, with a mean Cps/DD ratio of 0.58 ± 0.55 ng/ml/mg. There was a moderate positive linear correlation between the dose and Cps of quetiapine (r = 0.60), and the interpatient variation in Cps/DD ratio was up to 26-fold. CONCLUSION: Quetiapine is used in various doses to treat many psychiatric disorders other than psychosis, and it is usually prescribed as a secondary antipsychotic for symptoms such as insomnia or agitation. A wide interpatient variation of the Cps/DD ratio was noticed. Patients of East Asian descent may exhibit a 50% to 100% increase in the Cps/DD ratio for quetiapine compared with patients of Western descent.
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Antipsicóticos , Trastornos Psicóticos , Trastornos del Inicio y del Mantenimiento del Sueño , Humanos , Fumarato de Quetiapina/uso terapéutico , Trastornos del Inicio y del Mantenimiento del Sueño/tratamiento farmacológico , Dibenzotiazepinas/efectos adversos , Antipsicóticos/efectos adversos , Trastornos Psicóticos/tratamiento farmacológicoRESUMEN
BACKGROUND: The comorbidity of obesity and major depressive disorder (MDD) may be attributable to a bidirectional relationship and shared genetic influence. We aimed to examine the polygenic associations between obesity and MDD and to characterize their corresponding impacts on the obesity mechanism. METHODS: Genome-wide genotyping was available in 106,604 unrelated individuals from Taiwan Biobank. Polygenic risk score (PRS) for body mass index (BMI) and MDD was derived to evaluate their effects on obesity-related traits. Stratified analyses were performed for the modified effect of depression on the polygenic associations. RESULTS: The MDD PRS was positively associated with waistline (beta in per SD increase in PRS = 0.12), hipline (beta = 0.08), waist-hip ratio (WHR) (beta = 0.05), body fat rate (beta = 0.08), BMI (beta = 0.05), overweight (OR = 1.02 for BMI ≥ 25), and obesity (OR = 1.05 for BMI ≥ 30). For the synergism between depression and BMI PRS, the presence of active depression symptoms defined by the PHQ-4 (p for interaction < 0.05 for waistline, WHR, and BMI) was more salient than lifetime MDD. LIMITATIONS: Limitations include recall bias for MDD due to a retrospective self-reporting questionnaire, a low response rate of the PHQ-4 for evaluating active psychological symptoms, and limited generalizability to non-Taiwanese ancestries. CONCLUSIONS: The shared genetic etiology of obesity and depression was demonstrated. The amplified effect of BMI polygenic effect on obesity for individuals with active depressive symptoms was also characterized. The study may be helpful for designing public health interventions to reduce the disease burden caused by obesity and depression.
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Trastorno Depresivo Mayor , Humanos , Trastorno Depresivo Mayor/epidemiología , Trastorno Depresivo Mayor/genética , Trastorno Depresivo Mayor/diagnóstico , Bancos de Muestras Biológicas , Depresión/epidemiología , Depresión/genética , Estudios Retrospectivos , Predisposición Genética a la Enfermedad , Herencia Multifactorial , Obesidad/epidemiología , Obesidad/genética , Obesidad/diagnóstico , Estudio de Asociación del Genoma CompletoRESUMEN
Polygenic scores (PGS) are promising in stratifying individuals based on the genetic susceptibility to complex diseases or traits. However, the accuracy of PGS models, typically trained in European- or East Asian-ancestry populations, tend to perform poorly in other ethnic minority populations, and their accuracies have not been evaluated for Native Hawaiians. Using body mass index, height, and type-2 diabetes as examples of highly polygenic traits, we evaluated the prediction accuracies of PGS models in a large Native Hawaiian sample from the Multiethnic Cohort with up to 5,300 individuals. We evaluated both publicly available PGS models or genome-wide PGS models trained in this study using the largest available GWAS. We found evidence of lowered prediction accuracies for the PGS models in some cases, particularly for height. We also found that using the Native Hawaiian samples as an optimization cohort during training did not consistently improve PGS performance. Moreover, even the best performing PGS models among Native Hawaiians would have lowered prediction accuracy among the subset of individuals most enriched with Polynesian ancestry. Our findings indicate that factors such as admixture histories, sample size and diversity in GWAS can influence PGS performance for complex traits among Native Hawaiian samples. This study provides an initial survey of PGS performance among Native Hawaiians and exposes the current gaps and challenges associated with improving polygenic prediction models for underrepresented minority populations.
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Cigarette smoking has been suggested to be associated with the risk of schizophrenia in observational studies. A significant causal effect of smoking on schizophrenia has been reported in European populations using the Mendelian randomization approach; however, no evidence of causality was found in participants from East Asia. Using Taiwan Biobank (TWBB), we conducted genome-wide association studies (GWAS) to identify susceptibility loci for smoking behaviors, including smoking initiation (N = 79,989) and the onset age (N = 15,582). We then meta-analyzed GWAS from TWBB and Biobank Japan (BBJ) with the total sample size of 245,425 for smoking initiation and 46,000 for onset age of smoking. The GWAS for schizophrenia was taken from the East Asia Psychiatric Genomics Consortium, which included 22,778 cases and 35,362 controls. We performed a two-sample Mendelian randomization to estimate the causality of smoking behaviors on schizophrenia in East Asia. In TWBB, we identified one locus that met genome-wide significance for onset age. In a meta-analysis of TWBB and BBJ, we identified two loci for smoking initiation. In Mendelian randomization, genetically predicted smoking initiation (odds ratio (OR) = 4.00, 95% confidence interval (CI) = 0.89-18.01, P = 0.071) and onset age (OR for a per-year increase = 0.96, 95% CI = 0.91-1.01, P = 0.098) were not significantly associated with schizophrenia; the direction of effect was consistent with European Ancestry samples, which had higher statistical power. These findings provide tentative evidence consistent with a causal role of smoking on the development of schizophrenia in East Asian populations.
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BACKGROUND: Extensive observational evidence links diet quality to the risk for major depressive disorder (MDD), while clinical trials show that dietary improvement can improve depressive symptoms. However, due to issues with blinding dietary trials, confirming a causal relationship for diet's influence on MDD requires further research. Thus, we systemically investigated the bi-directional causal relationships between dietary habits and MDD by using two-sample Mendelian randomization (MR). METHODS: We collected publicly available genome-wide association studies' summary statistics for dietary habits from UK Biobank (n = 449,210) and MDD from the Psychiatric Genomics Consortium (n = 142,646). We used a weighted median approach to synthesize MR estimates across genetic instruments. For the robustness of our results, we compared weighted median results with results from the inverse-variance weighted, the weighted mode, and MR-PRESSO. RESULTS: There was moderate evidence that beef intake has a protective effect on MDD. There was weak but detectable evidence that cereal intake has a protective effect on MDD, while non-oily fish intake might increase the risk of MDD. We did not observe any causal effect of MDD on dietary habits. LIMITATIONS: Our study may suffer from the violation of assumptions of MR due to horizontal pleiotropy; therefore, we did several sensitivity analyses to detect and minimize the bias. CONCLUSIONS: In this two-sample MR analysis, we observed that higher beef intake may be protective against MDD. However, MDD did not appear to affect dietary habits. Potential mechanisms need to be further investigated to support our novel findings.
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Trastorno Depresivo Mayor , Análisis de la Aleatorización Mendeliana , Humanos , Trastorno Depresivo Mayor/genética , Estudio de Asociación del Genoma Completo , Conducta Alimentaria , Dieta , Polimorfismo de Nucleótido SimpleRESUMEN
BACKGROUND: Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations. METHODS: We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts. RESULTS: The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance. CONCLUSIONS: By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.
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Diabetes Mellitus Tipo 2 , Estudio de Asociación del Genoma Completo , Teorema de Bayes , Diabetes Mellitus Tipo 2/genética , Predisposición Genética a la Enfermedad , Humanos , Estudios Prospectivos , Factores de RiesgoRESUMEN
BACKGROUND: Obesity has been associated with cognition in observational studies; however, whether its effect is confounding or a reverse causality remains inconclusive. This study aimed to investigate the causal relationships of overall obesity, measured by body mass index (BMI), and abdominal adiposity, measured by waist-hip ratio adjusted for BMI (WHRadjBMI), and cognition across European and Asian populations using Mendelian randomization (MR) analysis. METHODS: We used publicly available genome-wide association study (GWAS) summary data of European ancestry, including BMI (n = 322,154) and WHRadjBMI (n = 210,088) from the GIANT consortium, and cognition performance (n = 257,828) from the UK Biobank and COGENT consortium. Data for individuals of Asian ancestry were retrieved from Taiwan Biobank to perform GWAS for BMI (n = 65,689), WHRadjBMI (n = 65,683), and Mini-Mental State Examination (MMSE, n = 21,273). MR analysis was carried out using the inverse-variance weighted method for the main results. Further, we examined the overall pleiotropy by MR-Egger intercept, and detected and adjusted for possible outliers using MR PRESSO. RESULTS: No causal effect of BMI on cognition performance (beta [95% CI] = 0.00 [-0.07, 0.07], p value = 0.91) was found for Europeans; however, a 1-SD increase in WHRadjBMI was associated with a 0.07 standardized score decrease in cognition performance (beta [95% CI] = -0.07 [-0.12, -0.02], p value = 0.006). Further, no causal effect of BMI on MMSE (beta [95% CI] = 0.01 [-0.08, 0.10], p = 0.91) was found for Asians; however, a 1-SD increase in WHRadjBMI was associated with a 0.17 standardized score decrease in MMSE (beta [95% CI] = -0.17 [-0.30, -0.03], p = 0.02). In both populations, overall pleiotropy was not detected, and outliers did not affect the robustness of the main findings. CONCLUSIONS: This trans-ethnic MR study reveals that abdominal adiposity, as measured by WHR adjusted for BMI, impairs cognition, whereas weak evidence suggests that BMI impairs cognition.
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Análisis de la Aleatorización Mendeliana , Obesidad Abdominal , Índice de Masa Corporal , Cognición , Estudio de Asociación del Genoma Completo , Humanos , Obesidad/epidemiología , Obesidad/genética , Obesidad Abdominal/complicaciones , Obesidad Abdominal/epidemiología , Obesidad Abdominal/genética , Polimorfismo de Nucleótido Simple/genéticaRESUMEN
Polygenic risk scores (PRS) have attenuated cross-population predictive performance. As existing genome-wide association studies (GWAS) have been conducted predominantly in individuals of European descent, the limited transferability of PRS reduces their clinical value in non-European populations, and may exacerbate healthcare disparities. Recent efforts to level ancestry imbalance in genomic research have expanded the scale of non-European GWAS, although most remain underpowered. Here, we present a new PRS construction method, PRS-CSx, which improves cross-population polygenic prediction by integrating GWAS summary statistics from multiple populations. PRS-CSx couples genetic effects across populations via a shared continuous shrinkage (CS) prior, enabling more accurate effect size estimation by sharing information between summary statistics and leveraging linkage disequilibrium diversity across discovery samples, while inheriting computational efficiency and robustness from PRS-CS. We show that PRS-CSx outperforms alternative methods across traits with a wide range of genetic architectures, cross-population genetic overlaps and discovery GWAS sample sizes in simulations, and improves the prediction of quantitative traits and schizophrenia risk in non-European populations.
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Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo , Genética de Población , Estudio de Asociación del Genoma Completo/métodos , Humanos , Desequilibrio de Ligamiento , Herencia Multifactorial/genética , Factores de RiesgoRESUMEN
AIMS/HYPOTHESIS: Psychiatric disorders, such as schizophrenia (SCZ), major depressive disorder (MDD) and bipolar disorder (BPD), are highly comorbid with type 2 diabetes. However, the mechanisms underlying such comorbidity are understudied. This study explored the familial aggregation of common psychiatric disorders and type 2 diabetes by testing family history association, and investigated the shared genetic loading between them by testing the polygenic risk score (PRS) association. METHODS: A total of 105,184 participants were recruited from the Taiwan Biobank, and genome-wide genotyping data were available for 95,238 participants. The Psychiatric Genomics Consortium-derived PRS for SCZ, MDD and BPD was calculated. Logistic regression was used to estimate the OR with CIs between a family history of SCZ/MDD/BPD and a family history of type 2 diabetes, and between the PRS and the risk of type 2 diabetes. RESULTS: A family history of type 2 diabetes was associated with a family history of SCZ (OR 1.23, 95% CI 1.08, 1.40), MDD (OR 1.19, 95% CI 1.13, 1.26) and BPD (OR 1.26, 95% CI 1.15, 1.39). Compared with paternal type 2 diabetes, maternal type 2 diabetes was associated with a higher risk of a family history of SCZ. SCZ PRS was negatively associated with type 2 diabetes in women (OR 0.92, 95% CI 0.88, 0.97), but not in men; the effect of SCZ PRS reduced after adjusting for BMI. MDD PRS was positively associated with type 2 diabetes (OR 1.04, 95% CI 1.00, 1.07); the effect of MDD PRS reduced after adjusting for BMI or smoking. BPD PRS was not associated with type 2 diabetes. CONCLUSIONS/INTERPRETATION: The comorbidity of type 2 diabetes with psychiatric disorders may be explained by shared familial factors. The shared polygenic loading between MDD and type 2 diabetes implies not only pleiotropy but also a shared genetic aetiology for the mechanism behind the comorbidity. The negative correlation between polygenic loading for SCZ and type 2 diabetes implies the role of environmental factors.
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Trastorno Depresivo Mayor , Diabetes Mellitus Tipo 2 , Trastornos Mentales , Trastorno Depresivo Mayor/genética , Diabetes Mellitus Tipo 2/genética , Femenino , Predisposición Genética a la Enfermedad/genética , Estudio de Asociación del Genoma Completo , Humanos , MasculinoRESUMEN
The Taiwan Biobank (TWB) is an ongoing prospective study of >150,000 individuals aged 20-70 in Taiwan. A comprehensive list of phenotypes was collected for each consented participant at recruitment and follow-up visits through structured interviews and physical measurements. Biomarkers and genetic data were generated from blood and urine samples. We present here an overview of TWB's genetic data quality, population structure, and familial relationship, which consists of predominantly Han Chinese ancestry, and highlight its important attributes and genetic findings thus far. A linkage to Taiwan's National Health Insurance database of >25 years and other registries is underway to enrich the phenotypic spectrum and enable deep and longitudinal genetic investigations. TWB provides one of the largest biobank resources for biomedical and public health research in East Asia that will contribute to our understanding of the genetic basis of health and disease in global populations through collaborative studies with other biobanks.
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Chronic opioid use disorder patients often also use other substances such as amphetamines. The gene-based analysis method was applied in the genomic database obtained from our previous study with 343 methadone maintenance treatment (MMT) patients. We found that the gene encoding gamma-aminobutyric acid type A receptors (GABA-A receptor) delta subunit isoforms (GABRD) was associated with amphetamine use in heroin dependent patients under MMT in Taiwan. A total of 15% of the 343 MMT patients tested positive for amphetamine in the urine toxicology test. Two genetic variants in the GABRD, rs2889475 and rs2376805, were found to be associated with the positive urine amphetamine test. They are located in the exon 1 of the splice variant and altered amino acid compositions (T126I, C/T, for rs2889475, and R252Q, G/A, for rs2376805). The CC genotype carriers of rs2889475 showed a four times higher risk of amphetamine use than those with TT genotype. The GG genotype carriers of rs2376805 showed a three times higher risk of amphetamine use than the AA genotype carriers. To our knowledge, this is the first report that demonstrated an association of the delta splice variant isoform in the GABA-A receptor with an increased risk of amphetamine use in MMT patients. Our results suggest that rs2889475 and rs2376805 may be indicators for the functional role and risk of amphetamine use in MMT patients.