Jingchun Chen

Multiple Independent Loci at Chromosome 15q25.1 Affect Smoking Quantity: a Meta-Analysis and Comparison with Lung Cancer and COPD

Recently, genetic association findings for nicotine dependence, smoking behavior, and smoking-related diseases converged to implicate the chromosome 15q25.1 region, which includes the CHRNA5-CHRNA3-CHRNB4 cholinergic nicotinic receptor subunit genes. In particular, association with the nonsynonymous CHRNA5 SNP rs16969968 and correlates has been replicated in several independent studies. Extensive genotyping of this region has suggested additional statistically distinct signals for nicotine dependence, tagged by rs578776 and rs588765. One goal of the Consortium for the Genetic Analysis of Smoking Phenotypes (CGASP) is to elucidate the associations among these markers and dichotomous smoking quantity (heavy versus light smoking), lung cancer, and chronic obstructive pulmonary disease (COPD). We performed a meta-analysis across 34 datasets of European-ancestry subjects, including 38,617 smokers who were assessed for cigarettes-per-day, 7,700 lung cancer cases and 5,914 lung-cancer-free controls (all smokers), and 2,614 COPD cases and 3,568 COPD-free controls (all smokers). We demonstrate statistically independent associations of rs16969968 and rs588765 with smoking (mutually adjusted p-values<10−35 and <10−8 respectively). Because the risk alleles at these loci are negatively correlated, their association with smoking is stronger in the joint model than when each SNP is analyzed alone. Rs578776 also demonstrates association with smoking after adjustment for rs16969968 (p<10−6). In models adjusting for cigarettes-per-day, we confirm the association between rs16969968 and lung cancer (p<10−20) and observe a nominally significant association with COPD (p = 0.01); the other loci are not significantly associated with either lung cancer or COPD after adjusting for rs16969968. This study provides strong evidence that multiple statistically distinct loci in this region affect smoking behavior. This study is also the first report of association between rs588765 (and correlates) and smoking that achieves genome-wide significance; these SNPs have previously been associated with mRNA levels of CHRNA5 in brain and lung tissue.

Variants in nicotinic acetylcholine receptors α5 and α3 increase risks to nicotine dependence.

Nicotinic acetylcholine receptors bind to nicotine and initiate the physiological and pharmacological responses to tobacco smoking. In this report, we studied the association of α5 and α3 subunits with nicotine dependence and with the symptoms of alcohol and cannabis abuse and dependence in two independent epidemiological samples (n = 815 and 1,121, respectively). In this study, seven single nucleotide polymorphisms were genotyped in the CHRNA5 and CHRNA3 genes. In both samples, we found that the same alleles of rs16969968 (P = 0.0068 and 0.0028) and rs1051730 (P = 0.0237 and 0.0039) were significantly associated with the scores of Fagerström test for nicotine dependence (FTND). In the analyses of the symptoms of abuse/dependence of alcohol and cannabis, we found that rs16969968 and rs1051730 were significantly associated with the symptoms of alcohol abuse or dependence (P = 0.0072 and 0.0057) in the combined sample, but the associated alleles were the opposite of that of FTND. No association with cannabis abuse/dependence was found. These results suggested that the α5 and α3 subunits play a significant role in both nicotine dependence and alcohol abuse/dependence. However, the opposite effects with nicotine dependence and alcohol abuse/dependence were puzzling and future studies are necessary to resolve this issue.

Transcriptome Sequencing and Genome-wide Association Analyses Reveal Lysosomal Function and Actin Cytoskeleton Remodeling in Schizophrenia and Bipolar Disorder

Schizophrenia (SCZ) and bipolar disorder (BPD) are severe mental disorders with high heritability. Clinicians have long noticed the similarities of clinic symptoms between these disorders. In recent years, accumulating evidence indicates some shared genetic liabilities. However, what is shared remains elusive. In this study, we conducted whole transcriptome analysis of post-mortem brain tissues (cingulate cortex) from SCZ, BPD and control subjects, and identified differentially expressed genes in these disorders. We found 105 and 153 genes differentially expressed in SCZ and BPD, respectively. By comparing the t-test scores, we found that many of the genes differentially expressed in SCZ and BPD are concordant in their expression level (q⩽0.01, 53 genes; q⩽0.05, 213 genes; q⩽0.1, 885 genes). Using genome-wide association data from the Psychiatric Genomics Consortium, we found that these differentially and concordantly expressed genes were enriched in association signals for both SCZ (P<10−7) and BPD (P=0.029). To our knowledge, this is the first time that a substantially large number of genes show concordant expression and association for both SCZ and BPD. Pathway analyses of these genes indicated that they are involved in the lysosome, Fc gamma receptor-mediated phagocytosis, regulation of actin cytoskeleton pathways, along with several cancer pathways. Functional analyses of these genes revealed an interconnected pathway network centered on lysosomal function and the regulation of actin cytoskeleton. These pathways and their interacting network were principally confirmed by an independent transcriptome sequencing data set of the hippocampus. Dysregulation of lysosomal function and cytoskeleton remodeling has direct impacts on endocytosis, phagocytosis, exocytosis, vesicle trafficking, neuronal maturation and migration, neurite outgrowth and synaptic density and plasticity, and different aspects of these processes have been implicated in SCZ and BPD.

GWA study data mining and independent replication identify cardiomyopathy-associated 5 (CMYA5) as a risk gene for schizophrenia

We conducted data-mining analyses using the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) and molecular genetics of schizophrenia genome-wide association study supported by the genetic association information network (MGS-GAIN) schizophrenia data sets and performed bioinformatic prioritization for all the markers with P-values ⩽0.05 in both data sets. In this process, we found that in the CMYA5 gene, there were two non-synonymous markers, rs3828611 and rs10043986, showing nominal significance in both the CATIE and MGS-GAIN samples. In a combined analysis of both the CATIE and MGS-GAIN samples, rs4704591 was identified as the most significant marker in the gene. Linkage disequilibrium analyses indicated that these markers were in low LD (3 828 611–rs10043986, r2=0.008; rs10043986–rs4704591, r2=0.204). In addition, CMYA5 was reported to be physically interacting with the DTNBP1 gene, a promising candidate for schizophrenia, suggesting that CMYA5 may be involved in the same biological pathway and process. On the basis of this information, we performed replication studies for these three single-nucleotide polymorphisms. The rs3828611 was found to have conflicting results in our Irish samples and was dropped out without further investigation. The other two markers were verified in 23 other independent data sets. In a meta-analysis of all 23 replication samples (family samples, 912 families with 4160 subjects; case–control samples, 11 380 cases and 15 021 controls), we found that both markers are significantly associated with schizophrenia (rs10043986, odds ratio (OR)=1.11, 95% confidence interval (CI)=1.04–1.18, P=8.2 × 10−4 and rs4704591, OR=1.07, 95% CI=1.03–1.11, P=3.0 × 10−4). The results were also significant for the 22 Caucasian replication samples (rs10043986, OR=1.11, 95% CI=1.03–1.17, P=0.0026 and rs4704591, OR=1.07, 95% CI=1.02–1.11, P=0.0015). Furthermore, haplotype conditioned analyses indicated that the association signals observed at these two markers are independent. On the basis of these results, we concluded that CMYA5 is associated with schizophrenia and further investigation of the gene is warranted.

RNA-Seq analysis implicates dysregulation of the immune system in schizophrenia

BackgroundWhile genome-wide association studies identified some promising candidates for schizophrenia, the majority of risk genes remained unknown. We were interested in testing whether integration gene expression and other functional information could facilitate the identification of susceptibility genes and related biological pathways.ResultsWe conducted high throughput sequencing analyses to evaluate mRNA expression in blood samples isolated from 3 schizophrenia patients and 3 healthy controls. We also conducted pooled sequencing of 10 schizophrenic patients and matched controls. Differentially expressed genes were identified by t-test. In the individually sequenced dataset, we identified 198 genes differentially expressed between cases and controls, of them 19 had been verified by the pooled sequencing dataset and 21 reached nominal significance in gene-based association analyses of a genome wide association dataset. Pathway analysis of these differentially expressed genes revealed that they were highly enriched in the immune related pathways. Two genes, S100A8 and TYROBP, had consistent changes in expression in both individual and pooled sequencing datasets and were nominally significant in gene-based association analysis.ConclusionsIntegration of gene expression and pathway analyses with genome-wide association may be an efficient approach to identify risk genes for schizophrenia.

The Interleukin 3 Gene (IL3) Contributes to Human Brain Volume Variation by Regulating Proliferation and Survival of Neural Progenitors

One of the most significant evolutionary changes underlying the highly developed cognitive abilities of humans is the greatly enlarged brain volume. In addition to being far greater than in most other species, the volume of the human brain exhibits extensive variation and distinct sexual dimorphism in the general population. However, little is known about the genetic mechanisms underlying normal variation as well as the observed sex difference in human brain volume. Here we show that interleukin-3 (IL3) is strongly associated with brain volume variation in four genetically divergent populations. We identified a sequence polymorphism (rs31480) in the IL3 promoter which alters the expression of IL3 by affecting the binding affinity of transcription factor SP1. Further analysis indicated that IL3 and its receptors are continuously expressed in the developing mouse brain, reaching highest levels at postnatal day 1–4. Furthermore, we found IL3 receptor alpha (IL3RA) was mainly expressed in neural progenitors and neurons, and IL3 could promote proliferation and survival of the neural progenitors. The expression level of IL3 thus played pivotal roles in the expansion and maintenance of the neural progenitor pool and the number of surviving neurons. Moreover, we found that IL3 activated both estrogen receptors, but estrogen didn’t directly regulate the expression of IL3. Our results demonstrate that genetic variation in the IL3 promoter regulates human brain volume and reveals novel roles of IL3 in regulating brain development.

Genetic Relationship between Schizophrenia and Nicotine Dependence

It is well known that most schizophrenia patients smoke cigarettes. There are different hypotheses postulating the underlying mechanisms of this comorbidity. We used summary statistics from large meta-analyses of plasma cotinine concentration (COT), Fagerström test for nicotine dependence (FTND) and schizophrenia to examine the genetic relationship between these traits. We found that schizophrenia risk scores calculated at P-value thresholds of 5 × 10−3 and larger predicted FTND and cigarettes smoked per day (CPD), suggesting that genes most significantly associated with schizophrenia were not associated with FTND/CPD, consistent with the self-medication hypothesis. The COT risk scores predicted schizophrenia diagnosis at P-values of 5 × 10−3 and smaller, implying that genes most significantly associated with COT were associated with schizophrenia. These results implicated that schizophrenia and FTND/CPD/COT shared some genetic liability. Based on this shared liability, we identified multiple long non-coding RNAs and RNA binding protein genes (DA376252, BX089737, LOC101927273, LINC01029, LOC101928622, HY157071, DA902558, RBFOX1 and TINCR), protein modification genes (MANBA, UBE2D3, and RANGAP1) and energy production genes (XYLB, MTRF1 and ENOX1) that were associated with both conditions. Further analyses revealed that these shared genes were enriched in calcium signaling, long-term potentiation and neuroactive ligand-receptor interaction pathways that played a critical role in cognitive functions and neuronal plasticity.

Variants in the 15q25 gene cluster are associated with risk for schizophrenia and bipolar disorder.

Background Rates of tobacco smoking are significantly higher in patients with schizophrenia compared with the general population. The underlying mechanism for this comorbidity is unclear. One hypothesis is that there are common genetic factors that predispose to both nicotine dependence (ND) and schizophrenia. To investigate this hypothesis, we examined the association of the 15q25 gene cluster, the most significant candidate region to date implicated in ND and smoking behavior, with schizophrenia and bipolar disorder. Methods Five variants in the 15q25 gene cluster (rs951266, rs16969968, rs1051730, rs8040868, and rs17477223) were selected to test for association with schizophrenia diagnosis, bipolar disorder diagnosis, and the presence of negative symptoms of schizophrenia. Effects of the variants on 15q25 gene expression were analyzed using publically available postmortem brain expression data. Results A meta-analysis revealed four markers associated with risk for schizophrenia and bipolar disorder (rs951266, rs16969968, rs8040868, and rs17477223), and with the presence of negative symptoms of schizophrenia (rs951266, rs1051730, rs8040868, and rs17477223). The associations were in the same direction as that found for ND. Gene expression analysis indicated an association between genotypes of the rs1051730 variant and CHRNA5 expression in brain and peripheral blood mononuclear cells, and with the rs16969968 and rs17477223 variants in brain. Conclusion Variants in the 15q25 gene cluster are associated with risk for schizophrenia/bipolar illness, negative symptoms of schizophrenia, and influence CHRNA5 expression in the brain and peripheral blood mononuclear cells. These results are consistent with the notion that there are genetic mechanisms common to schizophrenia, ND, and bipolar disorder.

Genome-Wide Meta-Analysis of Cotinine Levels in Cigarette Smokers Identifies Locus at 4q13.2.

Genome-wide association studies (GWAS) of complex behavioural phenotypes such as cigarette smoking typically employ self-report phenotypes. However, precise biomarker phenotypes may afford greater statistical power and identify novel variants. Here we report the results of a GWAS meta-analysis of levels of cotinine, the primary metabolite of nicotine, in 4,548 daily smokers of European ancestry. We identified a locus close to UGT2B10 at 4q13.2 (minimum p = 5.89 × 10−10 for rs114612145), which was consequently replicated. This variant is in high linkage disequilibrium with a known functional variant in the UGT2B10 gene which is associated with reduced nicotine and cotinine glucuronidation activity, but intriguingly is not associated with nicotine intake. Additionally, we observed association between multiple variants within the 15q25.1 region and cotinine levels, all located within the CHRNA5-A3-B4 gene cluster or adjacent genes, consistent with previous much larger GWAS using self-report measures of smoking quantity. These results clearly illustrate the increase in power afforded by using precise biomarker measures in GWAS. Perhaps more importantly however, they also highlight that biomarkers do not always mark the phenotype of interest. The use of metabolite data as a proxy for environmental exposures should be carefully considered in the context of individual differences in metabolic pathways.

Functional SNPs are enriched for schizophrenia association signals

Recent results suggest that there are likely to be many true association signals in large psychiatric genome-wide association study (GWAS) data sets. The big challenge of the field is the identification of these risk genes of small effect. We attempt to address this issue by using Psychiatric Genetics Consortium (PGC) GWAS data sets to test whether functional variants from the GWAS are significantly enriched in low P-values when compared with the remainder of the GWAS data set. We hypothesized that as functional single-nucleotide polymorphisms (SNPs) can directly affect gene expression and function, they are likely to significantly have an impact on disease risk. Therefore, functional SNPs are more likely to have true association signals. To test this hypothesis, we used genomic controladjusted statistics from PGC schizophrenia, bipolar disorder and major depression disorder GWAS data sets to investigate SNPs that (i) affect transcription factor-binding sites in the promoter regions (promoter SNPs), (ii) change gene expression via microRNA binding (microRNA SNPs) and DNA methylation (methylation SNPs), and (iii) correlate with gene expression (eQTL (expression quantitative trait loci) SNPs) in different brain regions. The experimentally validated promoter SNPs were obtained from dbQSNP (http://qsnp.gen.kyushu-u.ac.jp/), whereas the microRNA, methylation and eQTL SNPs were obtained from the literature. We used all SNPs deemed statistically significant by the original studies (Supplementary Table S1). We extracted the association P-values for these functional SNPs from the PGC GWAS data sets, and tested if these SNPs were more enriched in association signals than the entire GWAS using the Simes and sum of squares tests (SST) (see Supplementary Methods). To account for the linkage disequilibrium amongst selected SNPs, the statistical significance of SST was assessed via 50 000 permutations based on the linkage disequilibrium patterns of the 288 European subjects sequenced by the 1000 Genomes Project. The results are summarized in Table 1. When applying SST, 6 of the 10 groups of SNPs (promoter SNPs, eQTL SNPs in the frontal cortex and cerebellum, methylation SNPs in the temporal cortex, pons and frontal cortex) showed significant enrichment above GWAS background for association signals for schizophrenia. Promoter SNPs were also significantly enriched in association with bipolar disorder, and showed a trend in major depression. No significant enrichments were detected by the Simes test (Supplementary Table S2). Intuitively, the Simes test is useful to detect SNP sets having few strong signals, and SST is valuable at detecting SNP sets having many signals of small effect. Thus, our results suggest that there are no SNPs showing stronger associations than that observed in the GWASs. In contrast, SST results indicate that many promoter, eQTL and methylation SNPs seem to have a modest association with both schizophrenia and bipolar disorder. As the tested functional groups overlap, we conducted post hoc analyses for the unique SNPs amongst the significant groups. There were 11 868 unique SNPs amongst the methylation SNP groups, and they were significantly enriched for schizophrenia signals (Po0.0001). The 4178 unique eQTL SNPs were enriched for similar signals as well (P1⁄4 0.0006). There were 127 and 49 shared SNPs between the promoter/methylation and between the promoter/eQTL groups (Supplementary Table S1), and both shared SNPs were enriched in schizophrenia association signals (P1⁄4 0.0014 and 0.07, respectively). A pathway analysis of these shared SNPs indicated that they are involved in DNA replication and repair, cell cycle, cellular development and proliferation, system development and function, neurological disease and immune response (Supplementary Tables S3 and S4). In this study, we found that functional SNPs are more enriched in association signals than the remainder of the PGC GWAS data. The most significant enrichment was found in promoters for schizophrenia and bipolar disorder, and eQTL and methylation SNPs for schizophrenia. We noticed a trend for a decrease of enrichment signals across the disorders, a reflection of the power (sample size) of original studies. We also observed that there are differences in association signals across brain regions, supporting the notion that brain dysfunction in schizophrenia may be regionspecific. Overall, our results suggested that for GWAS data sets with reasonable power, systematically selecting and testing functional SNPs may be an effective approach to identify risk genes with small but true effect. This conclusion may be extended to other complex diseases.