www.nature.com/scientificreports
OPEN
Received: 27 March 2017 Accepted: 16 June 2017 Published: xx xx xxxx
Genetic loci associated with an earlier age at onset in multiplex schizophrenia Annemarie L. Woolston 1, Po-Chang Hsiao2, Po-Hsiu Kuo1,2,3, Shi-Heng Wang1,4, Yin-Ju Lien5, Chih-Min Liu6,7, Hai-Gwo Hwu 1,6, Tzu-Pin Lu1,8, Eric Y. Chuang8,9, Li-Ching Chang10, Chien-Hsiun Chen10, Jer-Yuarn Wu10, Ming T. Tsuang11,12,13 & Wei J. Chen 1,2,6,7 An earlier age at onset (AAO) has been associated with greater genetic loadings in schizophrenia. This study aimed to identify modifier loci associated with an earlier AAO of schizophrenia. A genome-wide association analysis (GWAS) was conducted in 94 schizophrenia probands with the earliest AAO and 91 with the latest AAO. Candidate single nucleotide polymorphisms (SNPs) were then genotyped in the co-affected siblings and unrelated probands. Multi-SNP genetic risk scores (GRS) composed of the candidate loci were used to distinguish patients with an early or late AAO. The 14-SNP GRS could distinguish the co-affected siblings (n = 90) of the earliest probands from those (n = 91) of the latest probands. When 132 patients with an earlier AAO and 158 patients with a later AAO were included, a significant trend in the 14-SNP GRS was detected among those unrelated probands from 4 family groups with the earliest, earlier, later, and latest AAO. The overall effect of the 14 SNPs on an AAO in schizophrenia was verified using co-affected siblings of the GWAS probands and trend effect across unrelated patients. Preliminary network analysis of these loci revealed the involvement of PARK2, a gene intensively reported in Parkinson’s disease and schizophrenia research. Schizophrenia has long been described as a complex disorder and its aetiology remains elusive1–3. Family and twin studies have indicated that genetic factors contributed substantially to schizophrenia, with an estimated heritability of approximately 80%4. When hundreds of microsatellite markers were examined in genome-wide linkage studies (GWLS) to look for genetic variants that co-segregated with the illness within families, suggestive evidence for a dozen of linkage regions was found5. With the advent of genome-wide association studies (GWAS), in which hundreds of thousands of single nucleotide polymorphisms (SNPs) were examined, approximately 100 markers conferring small increments in risk have been found in schizophrenia6, 7. Nevertheless, the combined variance explained by the SNPs reaching genome-wide significance remained low6. Alternatively, an application of GWAS data, the polygenic risk score (PRS), has been discovered6. The PRS, consisting of SNPs with P-values less than certain thresholds in GWAS, has been demonstrated to provide clues to functional analysis6, 8. Examination of the PRS derived from the results of large-scale GWAS6, 7 has been used to predict individuals with first-episode psychosis from controls9 and those predisposed to schizophrenia 1 National Taiwan University, College of Public Health, Institute of Epidemiology and Preventive Medicine, Taipei, 100, Taiwan. 2National Taiwan University, Genetic Epidemiology Core, Center of Genomic Medicine, Taipei, 100, Taiwan. 3National Taiwan University, College of Public Health, Research Center of Genes, Environment, and Human Health, Taipei, 100, Taiwan. 4China Medical University, Graduate Institute of Biostatistics, Taichung, 404, Taiwan. 5 National Taiwan Normal University, College of Education, College of Education, Department of Health Promotion and Health Education, Taipei, 106, Taiwan. 6Department of Psychiatry, College of Medicine and National Taiwan University Hospital, National Taiwan University, Taipei, 100, Taiwan. 7National Taiwan University Hospital, College of Medicine, Graduate Institute of Brain and Mind Sciences, National Taiwan University, Taipei, 100, Taiwan. 8National Taiwan University, Center of Genomic Medicine, Bioinformatics and Biostatistics Core, Taipei, 100, Taiwan. 9National Taiwan University, College of Electrical Engineering and Computer Science, Graduate Institute of Biomedical Electronics and Bioinformatics, Taipei, 106, Taiwan. 10Academia Sinica, Institute of Biomedical Sciences, Taipei, 115, Taiwan. 11University of California, Center for Behavioral Genomics and Institute for Genomic Medicine, Department of Psychiatry, San Diego, 92093-0761, CA, USA. 12University of California, Department of Psychiatry, San Diego, 92093-0603, CA, USA. 13Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, 02115, MA, USA. Correspondence and requests for materials should be addressed to W.J.C. (email: [email protected])
SCIENTIfIC REPOrTS | 7:6486 | DOI:10.1038/s41598-017-06795-8
1
www.nature.com/scientificreports/ in adolescence10. The associations between the PRS and some clinical dimensions of schizophrenia11 and first-episode psychosis12 have also been reported. In search of the genetic factors contributing to schizophrenia, another class of genes involved in the clinical manifestations of the illness, i.e., modifier genes, also needs to be considered13. Modifier loci associated with clinical features, such as the age at onset (AAO)14, 15 and positive and negative symptoms16 but not with schizophrenia susceptibility per se, have been identified using GWAS. Furthermore, our previous ordered subset linkage analysis identified a prominent linkage peak in a subset of schizophrenia patients characterized by earlier AAO17. In this study, we aimed to identify genetic loci associated with earlier AAO of schizophrenia in multiplex families from a single ethnicity. We performed a case-only GWAS for AAO of schizophrenia in a multiplex family sample of Han Chinese in Taiwan. Individual SNPs above certain significance thresholds were further tested in two subsamples, including co-affected siblings and other unrelated patients from the same recruitment scheme. Then, a multi-SNP genetic risk score (GRS) was applied to estimate an overall effect of the candidate genetic loci. The influence of the AAO-modifying genetic loci on the susceptibility of schizophrenia was also evaluated to clarify the potential effect using additional population-based case-control and family-based association tests. Finally, candidate SNPs were subjected to gene network analysis to explore their possible functions associated with the AAO of schizophrenia.
Materials and Methods
Participants. The multiplex family samples used in this study were selected from the Taiwan Schizophrenia Linkage Study (TSLS). First-degree relatives from Han Chinese families with more than two children affected by schizophrenia were recruited across Taiwan. Detailed methods of the fieldwork have been described elsewhere18. Briefly, interviews at recruitment were performed using the Diagnostic Interview for Genetic Studies (DIGS)19, accompanied with the Family Diagnostic Interview for Genetic Studies (FIGS)20. Research assistants carried out a Chinese version of the DIGS, following standard training as described by Chen and colleagues21. The diagnosis of schizophrenia was made independently by at least two research psychiatrists based on the criteria of the fourth edition of the Diagnostic and Statistical Manual (DSM-IV), joined with the record of DIGS, FIGS, interviewer notes, and hospital anamnesis. Information regarding an AAO of the first psychotic episode was extracted from the psychosis section of DIGS, or from the medical history where necessary. Whole blood samples were collected and sent to the National Institute of Mental Health (NIMH) Repository and Genomics Resource (RGR) to be transformed into lymphoblastoid cell lines and stored. DNA samples were extracted from the cell lines and then transported to Taiwan. The study design and selection of family samples are illustrated in Supplementary Figure S1. Among the 607 families recruited by the TSLS18, 2242 individuals from 557 multiplex families, including 1207 affected (1150 siblings, 57 parents) and 1035 unaffected (271 siblings and 764 parents) individuals, were successfully genotyped in a genome-wide linkage analysis22. Previous GWLS of these multiplex families indicated that a subset of families with early AAO led to a significant linkage signal17. Hence, we postulated that a GWAS screening based on a subsample with extreme contrast in AAO might maximize the power to identify candidate modifier genetic variants. Nevertheless, the chosen variants could then be genotyped in the remaining samples for the confirmation of the association with AAO. First, the 557 families were ranked according to the average AAO of the siblings affected by schizophrenia from each family. Second, a power evaluation of a two-group design (patients with extremely early AAO vs. patients with extremely late AAO) with 80 patients in each group reached 0.7–0.9 using Genetic Power Calculator23 under the following conditions: the minor allele frequencies of the SNPs are 0.2–0.45; the genotype relative risk for heterozygote and homozygote are 1.9–2.0 and 2.0–2.2, respectively; and the prevalence of early AAO among patients on average is 0.3–0.5, according to our empirical data. The final sample size increased from 80 to 95 per group since the microarray chips used in this study could hold 190 samples. Hence, the 95 families with the earliest average AAO and the 95 families with the latest average AAO were identified as the subsample with an extreme contrast in the AAO. One proband with an AAO conforming to the contrast from each family (i.e., earlier AAO in the extremely early subgroup and later AAO in the extremely late subgroup) was selected for GWAS genotyping. After sample quality control (discussed later), 185 probands (94 of the earliest AAO subgroup and 91 of the latest AAO subgroup) remained. SNPs with the strongest association signals (P-value 98%). All genetic markers were checked for marker genotyping call rate (>98%), minor allele frequency (>0.05), and Hardy-Weinberg equilibrium (HWE) with a P-value of >0.001. For population stratification, or check for the homogeneity of the sample, we followed the procedures provided by PLINK. The whole-genome identical by state (IBS) distances were firstly calculated between all individuals. Four multidimensional scaling (MDS) components of each individual were then estimated using the Hamming distance. A MDS component with a significant difference in the comparison would be adjusted as a covariate in the GWAS analyses. Relatedness between probands was estimated based on pairwise kinship using the KING software28. Batch effects were also checked and adjusted. Finally, 185 probands with schizophrenia remained after the quality control measures, with 5 patients being deleted due to low call rates (n = 2), a high kinship with another proband (n = 1), or population stratification suggesting different ancestry (n = 2). A total of 564,836 SNPs remained after the quality control. The overall genotyping error was 0.42%. Afterwards, the genomic inflation factor was very small (λ = 1.0013). Genotyping for the candidate SNPs in available co-affected siblings and parents and an independent set of schizophrenia probands with less contrast in AAO was carried out using the Illumina GoldenGate Genotyping Assay, which allows for customising probes of the SNPs of interest. The SNP genotyping of the community controls was performed by the biobank using the same microarray chip (Affymetrix Axiom Genome-wide CHB 1 Array Plate) as used for the schizophrenia probands. Only the data of the candidate SNPs in the community controls are presented in this study. Data analyses. A two-tailed Fisher’s exact test for dichotomous variables and a two-tailed t-test for con-
tinuous variables were used for group comparisons. Multiple logistic regression with adjustment for one of the four MDS components was used for association analysis for individual SNPs between GWAS probands from families with extreme contrast in AAO. We did not include covariates such as age and gender in the regression models to increase the power when searching for new genetic loci in diseases with low prevalence like schizophrenia29. Because age and AAO of the patients in the TSLS sample (n = 1,285) were highly correlated, with a Pearson’s correlation coefficient (r) = 0.52, we did not adjust for age in subsequent association analyses in the data sets of individual genotyping. Furthermore, we did not adjust for gender in these analyses since only autosomal SNPs were included in our GWAS analysis. Multiple comparisons of the association tests on the candidate SNPs were adjusted using Bonferroni correction. A P-value lower than 7.2 × 10−8 was considered the threshold of genome-wide significance30, while a less stringent threshold of P-value
OPEN
Received: 27 March 2017 Accepted: 16 June 2017 Published: xx xx xxxx
Genetic loci associated with an earlier age at onset in multiplex schizophrenia Annemarie L. Woolston 1, Po-Chang Hsiao2, Po-Hsiu Kuo1,2,3, Shi-Heng Wang1,4, Yin-Ju Lien5, Chih-Min Liu6,7, Hai-Gwo Hwu 1,6, Tzu-Pin Lu1,8, Eric Y. Chuang8,9, Li-Ching Chang10, Chien-Hsiun Chen10, Jer-Yuarn Wu10, Ming T. Tsuang11,12,13 & Wei J. Chen 1,2,6,7 An earlier age at onset (AAO) has been associated with greater genetic loadings in schizophrenia. This study aimed to identify modifier loci associated with an earlier AAO of schizophrenia. A genome-wide association analysis (GWAS) was conducted in 94 schizophrenia probands with the earliest AAO and 91 with the latest AAO. Candidate single nucleotide polymorphisms (SNPs) were then genotyped in the co-affected siblings and unrelated probands. Multi-SNP genetic risk scores (GRS) composed of the candidate loci were used to distinguish patients with an early or late AAO. The 14-SNP GRS could distinguish the co-affected siblings (n = 90) of the earliest probands from those (n = 91) of the latest probands. When 132 patients with an earlier AAO and 158 patients with a later AAO were included, a significant trend in the 14-SNP GRS was detected among those unrelated probands from 4 family groups with the earliest, earlier, later, and latest AAO. The overall effect of the 14 SNPs on an AAO in schizophrenia was verified using co-affected siblings of the GWAS probands and trend effect across unrelated patients. Preliminary network analysis of these loci revealed the involvement of PARK2, a gene intensively reported in Parkinson’s disease and schizophrenia research. Schizophrenia has long been described as a complex disorder and its aetiology remains elusive1–3. Family and twin studies have indicated that genetic factors contributed substantially to schizophrenia, with an estimated heritability of approximately 80%4. When hundreds of microsatellite markers were examined in genome-wide linkage studies (GWLS) to look for genetic variants that co-segregated with the illness within families, suggestive evidence for a dozen of linkage regions was found5. With the advent of genome-wide association studies (GWAS), in which hundreds of thousands of single nucleotide polymorphisms (SNPs) were examined, approximately 100 markers conferring small increments in risk have been found in schizophrenia6, 7. Nevertheless, the combined variance explained by the SNPs reaching genome-wide significance remained low6. Alternatively, an application of GWAS data, the polygenic risk score (PRS), has been discovered6. The PRS, consisting of SNPs with P-values less than certain thresholds in GWAS, has been demonstrated to provide clues to functional analysis6, 8. Examination of the PRS derived from the results of large-scale GWAS6, 7 has been used to predict individuals with first-episode psychosis from controls9 and those predisposed to schizophrenia 1 National Taiwan University, College of Public Health, Institute of Epidemiology and Preventive Medicine, Taipei, 100, Taiwan. 2National Taiwan University, Genetic Epidemiology Core, Center of Genomic Medicine, Taipei, 100, Taiwan. 3National Taiwan University, College of Public Health, Research Center of Genes, Environment, and Human Health, Taipei, 100, Taiwan. 4China Medical University, Graduate Institute of Biostatistics, Taichung, 404, Taiwan. 5 National Taiwan Normal University, College of Education, College of Education, Department of Health Promotion and Health Education, Taipei, 106, Taiwan. 6Department of Psychiatry, College of Medicine and National Taiwan University Hospital, National Taiwan University, Taipei, 100, Taiwan. 7National Taiwan University Hospital, College of Medicine, Graduate Institute of Brain and Mind Sciences, National Taiwan University, Taipei, 100, Taiwan. 8National Taiwan University, Center of Genomic Medicine, Bioinformatics and Biostatistics Core, Taipei, 100, Taiwan. 9National Taiwan University, College of Electrical Engineering and Computer Science, Graduate Institute of Biomedical Electronics and Bioinformatics, Taipei, 106, Taiwan. 10Academia Sinica, Institute of Biomedical Sciences, Taipei, 115, Taiwan. 11University of California, Center for Behavioral Genomics and Institute for Genomic Medicine, Department of Psychiatry, San Diego, 92093-0761, CA, USA. 12University of California, Department of Psychiatry, San Diego, 92093-0603, CA, USA. 13Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, 02115, MA, USA. Correspondence and requests for materials should be addressed to W.J.C. (email: [email protected])
SCIENTIfIC REPOrTS | 7:6486 | DOI:10.1038/s41598-017-06795-8
1
www.nature.com/scientificreports/ in adolescence10. The associations between the PRS and some clinical dimensions of schizophrenia11 and first-episode psychosis12 have also been reported. In search of the genetic factors contributing to schizophrenia, another class of genes involved in the clinical manifestations of the illness, i.e., modifier genes, also needs to be considered13. Modifier loci associated with clinical features, such as the age at onset (AAO)14, 15 and positive and negative symptoms16 but not with schizophrenia susceptibility per se, have been identified using GWAS. Furthermore, our previous ordered subset linkage analysis identified a prominent linkage peak in a subset of schizophrenia patients characterized by earlier AAO17. In this study, we aimed to identify genetic loci associated with earlier AAO of schizophrenia in multiplex families from a single ethnicity. We performed a case-only GWAS for AAO of schizophrenia in a multiplex family sample of Han Chinese in Taiwan. Individual SNPs above certain significance thresholds were further tested in two subsamples, including co-affected siblings and other unrelated patients from the same recruitment scheme. Then, a multi-SNP genetic risk score (GRS) was applied to estimate an overall effect of the candidate genetic loci. The influence of the AAO-modifying genetic loci on the susceptibility of schizophrenia was also evaluated to clarify the potential effect using additional population-based case-control and family-based association tests. Finally, candidate SNPs were subjected to gene network analysis to explore their possible functions associated with the AAO of schizophrenia.
Materials and Methods
Participants. The multiplex family samples used in this study were selected from the Taiwan Schizophrenia Linkage Study (TSLS). First-degree relatives from Han Chinese families with more than two children affected by schizophrenia were recruited across Taiwan. Detailed methods of the fieldwork have been described elsewhere18. Briefly, interviews at recruitment were performed using the Diagnostic Interview for Genetic Studies (DIGS)19, accompanied with the Family Diagnostic Interview for Genetic Studies (FIGS)20. Research assistants carried out a Chinese version of the DIGS, following standard training as described by Chen and colleagues21. The diagnosis of schizophrenia was made independently by at least two research psychiatrists based on the criteria of the fourth edition of the Diagnostic and Statistical Manual (DSM-IV), joined with the record of DIGS, FIGS, interviewer notes, and hospital anamnesis. Information regarding an AAO of the first psychotic episode was extracted from the psychosis section of DIGS, or from the medical history where necessary. Whole blood samples were collected and sent to the National Institute of Mental Health (NIMH) Repository and Genomics Resource (RGR) to be transformed into lymphoblastoid cell lines and stored. DNA samples were extracted from the cell lines and then transported to Taiwan. The study design and selection of family samples are illustrated in Supplementary Figure S1. Among the 607 families recruited by the TSLS18, 2242 individuals from 557 multiplex families, including 1207 affected (1150 siblings, 57 parents) and 1035 unaffected (271 siblings and 764 parents) individuals, were successfully genotyped in a genome-wide linkage analysis22. Previous GWLS of these multiplex families indicated that a subset of families with early AAO led to a significant linkage signal17. Hence, we postulated that a GWAS screening based on a subsample with extreme contrast in AAO might maximize the power to identify candidate modifier genetic variants. Nevertheless, the chosen variants could then be genotyped in the remaining samples for the confirmation of the association with AAO. First, the 557 families were ranked according to the average AAO of the siblings affected by schizophrenia from each family. Second, a power evaluation of a two-group design (patients with extremely early AAO vs. patients with extremely late AAO) with 80 patients in each group reached 0.7–0.9 using Genetic Power Calculator23 under the following conditions: the minor allele frequencies of the SNPs are 0.2–0.45; the genotype relative risk for heterozygote and homozygote are 1.9–2.0 and 2.0–2.2, respectively; and the prevalence of early AAO among patients on average is 0.3–0.5, according to our empirical data. The final sample size increased from 80 to 95 per group since the microarray chips used in this study could hold 190 samples. Hence, the 95 families with the earliest average AAO and the 95 families with the latest average AAO were identified as the subsample with an extreme contrast in the AAO. One proband with an AAO conforming to the contrast from each family (i.e., earlier AAO in the extremely early subgroup and later AAO in the extremely late subgroup) was selected for GWAS genotyping. After sample quality control (discussed later), 185 probands (94 of the earliest AAO subgroup and 91 of the latest AAO subgroup) remained. SNPs with the strongest association signals (P-value 98%). All genetic markers were checked for marker genotyping call rate (>98%), minor allele frequency (>0.05), and Hardy-Weinberg equilibrium (HWE) with a P-value of >0.001. For population stratification, or check for the homogeneity of the sample, we followed the procedures provided by PLINK. The whole-genome identical by state (IBS) distances were firstly calculated between all individuals. Four multidimensional scaling (MDS) components of each individual were then estimated using the Hamming distance. A MDS component with a significant difference in the comparison would be adjusted as a covariate in the GWAS analyses. Relatedness between probands was estimated based on pairwise kinship using the KING software28. Batch effects were also checked and adjusted. Finally, 185 probands with schizophrenia remained after the quality control measures, with 5 patients being deleted due to low call rates (n = 2), a high kinship with another proband (n = 1), or population stratification suggesting different ancestry (n = 2). A total of 564,836 SNPs remained after the quality control. The overall genotyping error was 0.42%. Afterwards, the genomic inflation factor was very small (λ = 1.0013). Genotyping for the candidate SNPs in available co-affected siblings and parents and an independent set of schizophrenia probands with less contrast in AAO was carried out using the Illumina GoldenGate Genotyping Assay, which allows for customising probes of the SNPs of interest. The SNP genotyping of the community controls was performed by the biobank using the same microarray chip (Affymetrix Axiom Genome-wide CHB 1 Array Plate) as used for the schizophrenia probands. Only the data of the candidate SNPs in the community controls are presented in this study. Data analyses. A two-tailed Fisher’s exact test for dichotomous variables and a two-tailed t-test for con-
tinuous variables were used for group comparisons. Multiple logistic regression with adjustment for one of the four MDS components was used for association analysis for individual SNPs between GWAS probands from families with extreme contrast in AAO. We did not include covariates such as age and gender in the regression models to increase the power when searching for new genetic loci in diseases with low prevalence like schizophrenia29. Because age and AAO of the patients in the TSLS sample (n = 1,285) were highly correlated, with a Pearson’s correlation coefficient (r) = 0.52, we did not adjust for age in subsequent association analyses in the data sets of individual genotyping. Furthermore, we did not adjust for gender in these analyses since only autosomal SNPs were included in our GWAS analysis. Multiple comparisons of the association tests on the candidate SNPs were adjusted using Bonferroni correction. A P-value lower than 7.2 × 10−8 was considered the threshold of genome-wide significance30, while a less stringent threshold of P-value
