Association study between two variants in the DOPA decarboxylase gene in bipolar and unipolar affective disorder

Metabolomic analysis of the hippocampus in a rat model of chronic mild unpredictable stress-induced depression based on a pathway crosstalk and network module approach

BACKGROUND

The molecular alterations underlying the pathogenesis of depression have not been systematically defined. Increasing evidence suggests that hippocampus metabolism is strongly involved in the pathogenesis of chronic mild unpredictable stress (CUMS)-induced depression. The principal objective of this study was to reveal important information concerning the pathogenesis of depression through a comprehensive analysis of metabolites in the hippocampus in a CUMS rat model.

METHODS

Metabolites related to metabolic changes in the hippocampus in the CUMS model were collected from a depression-specific database and published literature. Potential metabolite pathways were identified by the Omicsolution tool. Then, crosstalk analysis was carried out to investigate the relationship between different important pathways. In addition, MetaboAnalyst was used to analyze potential metabolites for drug-related metabolite enrichment analysis, which was used to study hippocampus metabolite-related drug pathways in a CUMS model. Then, a metabolite-protein interaction (MPI) network was constructed and analyzed to identify important metabolites and proteins. The functional modules were extracted using the CNM network decomposition algorithm. Finally, neurotransmitters in the hippocampus of rats with CUMS depression were detected to verify the important pathways.

RESULTS

In the current study, 53 significantly enriched pathways related to the 107 identified metabolites were selected, and the top ranked enriched pathways included arginine and proline metabolism, neuroactive ligand-receptor interaction, phenylalanine metabolism, bile secretion, and glutathione metabolism. Pathway crosstalk analysis showed that the significantly enriched pathways were divided into two interrelated modules, which were mainly involved in metabolism, signal transduction, neurotransmitters, and the endocrine system. Enrichment analysis of drug-related metabolic KEGG pathways identified the antibiotic pathways as the most important pathways. In the MPI network, the hub metabolites were phosphate, arachidonic acid, oxoglutaric acid, l-glutamic acid, and glutathione, and the hub proteins were Got1, Got2, Tat, Ccbl1, Ccbl2, Il4i1. A total of 16 functional modules were extracted from the MPI network by using the CNM algorithm. Finally, metabolites related to serotonergic synapses, dopaminergic synapses, and glutamatergic synapses were found to be involved in the pathology of depression.

CONCLUSION

We found that neurotransmitter pathways (serotonergic synapses, dopaminergic synapses and glutamatergic synapses) in the hippocampus play a crucial role in the underlying molecular mechanism of depression, which provides useful clues for identifying the detailed depression-associated metabolic profiles.

Polymorphism of the Dopa-Decarboxylase Gene Modifies the Motor Response to Levodopa in Chinese Patients With Parkinson's Disease

Levodopa (L-DOPA) is the most effective drug for Parkinson's disease (PD). However, the response to L-DOPA remains individually variable, which hampers the practical value of L-DOPA in the clinic. Genetic factors play a role in L-DOPA efficacy. This study explored the associations between polymorphisms and motor response to L-DOPA in Chinese patients with PD. A total of 51 Chinese PD patients were enrolled in this study. Patients underwent an acute L-DOPA challenge and were evaluated by the Unified Parkinson Disease Rating Scale (UPDRS) part III at baseline and after L-DOPA administration. Subjects were genotyped for polymorphisms: rs921451 and rs3837091 in the DDC loci, rs3836790 in the SLC6A3 locus, rs4680 in the COMT locus, and rs1799836 in the MAOB locus. We found that patients carrying the DDC CT or TT genotype exhibited a better motor response to L-DOPA than patients with the DDC CC genotype, and there was still a significant difference after adjustment for the L-DOPA dose in the acute challenge. Improvement in the UPDRS III subscores, including bradykinesia and axial symptoms, was significantly lower in patients with the DDC CC genotype than in patients with the CT or TT genotype. There were no significant associations between the motor response to L-DOPA and the rs3837091, rs3836790, rs4680, and rs1799836 variants. The DDC single nucleotide polymorphism rs921451 modulated the motor response to L-DOPA in Chinese PD patients. Our results suggested that DDC may be a modifier gene for the L-DOPA treatment response in PD.

A composite likelihood approach in testing for Hardy Weinberg Equilibrium using family-based genetic survey data

In population-based household surveys, for example, the National Health and Nutrition Examination Survey, households are often sampled by stratified multistage cluster sampling, and multiple individuals related by blood are often sampled within households. Therefore, genetic data collected from these population-based household surveys, called National Genetic Household Surveys, can be correlated because of two levels of correlation. One level of correlation is caused by the multistage geographical cluster sampling and the other is caused by biological inheritance among participants within the same sampled family. In this paper, we develop an efficient Hardy Weinberg Equilibrium (HWE) test utilizing pairwise composite likelihood methods that incorporate the sample weighting effect induced by the differential selection probabilities in complex sample designs, as well as the two-level clustering (correlation) effects described above. Monte Carlo simulation studies show that the proposed HWE test maintains the nominal levels, and is more powerful than existing methods (Li et al. 2011) under various (non)informative sample designs that depend on genotypes (explicitly or implicitly), family relationships or both, especially when within-household sampling depends on the genotypes. The developed tests are further evaluated using simulated genetic data based on the Hispanic Health and Nutrition Survey. Copyright © 2016 John Wiley & Sons, Ltd.

A comparison of tests for Hardy-Weinberg Equilibrium in national genetic household surveys

Background

This study is motivated by National Household Surveys that collect genetic data, in which complex samples (e.g. stratified multistage cluster sample), partially from the same family, are selected. In addition to the differential selection probabilities of selecting households and persons within the sampled households, there are two levels of correlations of the collected genetic data in National Genetic Household Surveys (NGHS). The first level of correlation is induced by the hierarchical geographic clustered sampling of households and the second level of correlation is induced by biological inheritances from individuals sampled in the same household.

Results

To test for Hardy-Weinberg Equilibrium (HWE) in NGHS, two test statistics, the CCS method [1] and the QS method [2], appear to be the only existing methods that take account of both correlations. In this paper, I evaluate both methods in terms of the test size and power under a variety of complex designs with different weighting schemes and varying magnitudes of the two correlation effects. Both methods are applied to a real data example from the Hispanic Health and Nutrition Examination Survey with simulated genotype data.

Conclusions

The QS method maintains the nominal size well and consistently achieves higher power than the CCS method in testing HWE under a variety of sample designs, and therefore is recommended for testing HWE of genetic survey data with complex designs.

Testing for Hardy Weinberg Equilibrium in national household surveys that collect family-based genetic data

In population-based household surveys, for example, the National Health and Nutrition Examination Survey (NHANES), blood-related individuals are often sampled from the same household. Therefore, genetic data collected from national household surveys are often correlated due to two levels of clustering (correlation) with one induced by the multistage geographical cluster sampling, and the other induced by biological inheritance among multiple participants within the same sampled household. In this paper, we develop efficient statistical methods that consider the weighting effect induced by the differential selection probabilities in complex sample designs, as well as the clustering (correlation) effects described above. We examine and compare the magnitude of each level of clustering effects under different scenarios and identify the scenario under which the clustering effect induced by one level dominates the other. The proposed method is evaluated via Monte Carlo simulation studies and illustrated using the Hispanic Health and Nutrition Survey (HHANES) with simulated genotype data.

The role of dopamine in bipolar disorder

OBJECTIVE

Despite effective pharmacological treatments for bipolar disorder, we still lack a comprehensive pathophysiological model of the illness. Recent neurobiological research has implicated a number of key brain regions and neuronal components in the behavioural and cognitive manifestations of bipolar disorder. Dopamine has previously been investigated in some depth in bipolar disorder, but of late has not been a primary focus of attention. This article examines the role of dopamine in bipolar disorder, incorporating recent advances into established models where possible.

METHODS

A critical evaluation of the literature was undertaken, including a review of behavioural, neurochemical, receptor, and imaging studies, as well as genetic studies focusing on dopamine receptors and related metabolic pathways. In addition, pharmacologic manipulation of the central dopaminergic pathways and comparisons with other disease states such as schizophrenia were considered, principally as a means of exploring the hypothesised models.

RESULTS

Multiple lines of evidence, including data from pharmacological interventions and structural and functional magnetic resonance imaging studies, suggest that the dopaminergic system may play a central role in bipolar disorder.

CONCLUSION

Future research into the pathophysiological mechanisms of bipolar disorder and the development of new treatments for bipolar disorder should focus on the dopaminergic system.

The genetics of bipolar disorder: genome 'hot regions,' genes, new potential candidates and future directions

Bipolar disorder (BP) is a complex disorder caused by a number of liability genes interacting with the environment. In recent years, a large number of linkage and association studies have been conducted producing an extremely large number of findings often not replicated or partially replicated. Further, results from linkage and association studies are not always easily comparable. Unfortunately, at present a comprehensive coverage of available evidence is still lacking. In the present paper, we summarized results obtained from both linkage and association studies in BP. Further, we indicated new potential interesting genes, located in genome 'hot regions' for BP and being expressed in the brain. We reviewed published studies on the subject till December 2007. We precisely localized regions where positive linkage has been found, by the NCBI Map viewer (http://www.ncbi.nlm.nih.gov/mapview/); further, we identified genes located in interesting areas and expressed in the brain, by the Entrez gene, Unigene databases (http://www.ncbi.nlm.nih.gov/entrez/) and Human Protein Reference Database (http://www.hprd.org); these genes could be of interest in future investigations. The review of association studies gave interesting results, as a number of genes seem to be definitively involved in BP, such as SLC6A4, TPH2, DRD4, SLC6A3, DAOA, DTNBP1, NRG1, DISC1 and BDNF. A number of promising genes, which received independent confirmations, and genes that have to be further investigated in BP, have been also systematically listed. In conclusion, the combination of linkage and association approaches provided a number of liability genes. Nevertheless, other approaches are required to disentangle conflicting findings, such as gene interaction analyses, interaction with psychosocial and environmental factors and, finally, endophenotype investigations.

Meta-analyses of genetic studies on major depressive disorder

The genetic basis of major depressive disorder (MDD) has been investigated extensively, but the identification of MDD genes has been hampered by conflicting results from underpowered studies. We review all MDD case-control genetic association studies published before June 2007 and perform meta-analyses for polymorphisms that had been investigated in at least three studies. The study selection and data extraction were performed in duplicate by two independent investigators. The 183 papers that met our criteria studied 393 polymorphisms in 102 genes. Twenty-two polymorphisms (6%) were investigated in at least three studies. Seven polymorphisms had been evaluated in previous meta-analyses, 5 of these had new data available. Hence, we performed meta-analyses for 20 polymorphisms in 18 genes. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Statistically significant associations were found for the APOE varepsilon2 (OR, 0.51), GNB3 825T (OR, 1.38), MTHFR 677T (OR, 1.20), SLC6A4 44 bp Ins/Del S (OR, 1.11) alleles and the SLC6A3 40 bpVNTR 9/10 genotype (OR, 2.06). To date, there is statistically significant evidence for six MDD susceptibility genes (APOE, DRD4, GNB3, MTHFR, SLC6A3 and SLC6A4).

Genomic imprinting of Dopa decarboxylase in heart and reciprocal allelic expression with neighboring Grb10

By combining a tissue-specific microarray screen with mouse uniparental duplications, we have identified a novel imprinted gene, Dopa decarboxylase (Ddc), on chromosome 11. Ddc_exon1a is a 2-kb transcript variant that initiates from an alternative first exon in intron 1 of the canonical Ddc transcript and is paternally expressed in trabecular cardiomyocytes of the embryonic and neonatal heart. Ddc displays tight conserved linkage with the maternally expressed and methylated Grb10 gene, suggesting that these reciprocally imprinted genes may be coordinately regulated. In Dnmt3L mutant embryos that lack maternal germ line methylation imprints, we show that Ddc is overexpressed and Grb10 is silenced. Their imprinting is therefore dependent on maternal germ line methylation, but the mechanism at Ddc does not appear to involve differential methylation of the Ddc_exon1a promoter region and may instead be provided by the oocyte mark at Grb10. Our analysis of Ddc redefines the imprinted Grb10 domain on mouse proximal chromosome 11 and identifies Ddc_exon1a as the first example of a heart-specific imprinted gene.

Octopamine-mediated neuronal plasticity in honeybees: implications for olfactory dysfunction in humans

Biogenic amines, such as norepinephrine (in vertebrates) and octopamine (in invertebrates), have structural and functional similarities. These amines play crucial roles in animal behavior by modifying the synaptic output of relevant neurons. Increased levels of norepinephrine in the olfactory bulb preferentially increase mitral cell excitatory responses to olfactory nerve inputs, suggesting its critical role in modulating olfactory function including memory formation and/or recall of specific olfactory memories. Increased levels of octopamine in the antennal lobe play an important role in a reinforcement pathway involved in olfactory learning and memory in honeybees. Similar to adrenergic receptors in the human brain, activation of octopaminergic receptors in the honeybee brain induces specific second messenger pathways that change protein phosphorylation and/or gene expression, altering the activity and/or abundance of proteins responsible for neuronal signaling leading to changes in olfactory behavior. The author's studies in honeybees Apis mellifera indicate that oxidative stress plays a major role in olfactory dysfunction. A similar mechanism has been proposed for olfactory abnormalities in patients of Alzheimer disease and Parkinson disease. Due to similarities in cellular and molecular processes, which govern neuronal plasticity in humans and honeybees, the author proposes that the honeybee can be used as a potential and relatively simple model system for understanding human olfactory dysfunction during aging and in neurodegenerative diseases.

The merits of testing Hardy-Weinberg equilibrium in the analysis of unmatched case-control data: a cautionary note

Testing for departures from the assumption of Hardy-Weinberg equilibrium (HWE) has been widely recommended as a preliminary step in the analysis of genetic case-control studies. Some authors suggest using a two-stage procedure in which gene/disease associations are ultimately evaluated using either the Pearson chi-square procedure or the Cochran-Armitage test for trend. Other authors go further and encourage investigators to discard data that are in violation of HWE, essentially using the test as a tool for identifying genotyping errors. In this paper we show that 1) testing for HWE should not be used as a tool to identify genotyping errors; and 2) it is not necessary, and possibly even harmful, to test the HWE assumption before testing for association between alleles and disease. Instead one should inherently account for deviations from HWE with an adjusted chi-square test statistic, a procedure which in the present context is identical to the trend test. Examples from previous reports are used to illustrate the methodology.

Intronic variants in the dopa decarboxylase ( DDC ) gene are associated with smoking behavior in European-Americans and African-Americans

We report here a study considering association of alleles and haplotypes at the DOPA decarboxylase (DDC) locus with the DSM-IV diagnosis of nicotine dependence (ND) or a quantitative measure for ND using the Fagerstrom Test for Nicotine Dependence (FTND). We genotyped 18 single nucleotide polymorphisms (SNPs) spanning a region of approximately 210 kb that includes DDC and the genes immediately flanking DDC in 1,590 individuals from 621 families of African-American (AA) or European-American (EA) ancestry. Evidence of association (family-based tests) was observed with several SNPs for both traits (0.0002<or=P<or=0.04). The most significant result was obtained for the relationship of FTND score to SNP rs12718541 (AA families: P=0.002; EA families: P=0.03; all families: P=0.0002) which is in the same intron as the splice site for a neuronal isoform of human DDC lacking exons 10-15. Haplotype analysis did not reveal any SNP combination with stronger evidence for association than rs12718541 alone. Although sequence analysis suggests that rs12718541 may be an intronic splicing enhancer, further studies are needed to determine whether a direct link exists between an alternatively spliced form of DDC and predisposition to ND. These findings confirm a previous report of association of DDC with ND, localize the causative variants to the 3' end of the coding region and extend the association to multiple population groups.

Genetic tests of biologic systems in affective disorders

To liberate candidate gene analyses from criticisms of inexhaustiveness of examination of specific candidate genes, or incompleteness in the choice of candidate genes to study for specific neurobiological pathways, study of sizeable sets of genes pertinent to each putative pathophysiological pathway is required. For many years, genes have been tested in a 'one by one' manner for association with major affective disorders, primarily bipolar illness. However, it is conceivable that not individual genes but abnormalities in several genes within a system or in several neuronal, neural, or hormonal systems are implicated in the functional hypotheses for etiology of affective disorders. Compilation of candidate genes for entire pathways is a challenge, but can reasonably be carried out for the major affective disorders as discussed here. We present here five groupings of genes implicated by neuropharmacological and other evidence, which suggest 252 candidate genes worth examining. Inexhaustiveness of gene interrogation would apply to many studies in which only one polymorphism per gene is analyzed. In contrast to whole-genome association studies, a study of a limited number of candidate genes can readily exploit information on genomic sequence variations obtained from databases and/or resequencing, and has an advantage of not having the complication of an extremely stringent statistical criterion for association.

Haplotype analysis indicates an association between the DOPA decarboxylase (DDC) gene and nicotine dependence

DOPA decarboxylase (DDC; also known as L-amino acid decarboxylase; AADC) is involved in the synthesis of dopamine, norepinephrine and serotonin. Because the mesolimbic dopaminergic system is implicated in the reinforcing effects of many drugs, including nicotine, the DDC gene is considered a plausible candidate for involvement in the development of vulnerability to nicotine dependence (ND). Further, this gene is located within the 7p11 region that showed a 'suggestive linkage' to ND in our previous genome-wide scan in the Framingham Heart Study population. In the present study, we tested eight single nucleotide polymorphisms (SNPs) within DDC for association with ND, which was assessed by smoking quantity (SQ), the heaviness of smoking index (HSI) and the Fagerstrom test for ND (FTND) score, in a total of 2037 smokers and non-smokers from 602 nuclear families of African- or European-American (AA or EA, respectively) ancestry. Association analysis for individual SNPs using the PBAT-GEE program indicated that SNP rs921451 was significantly associated with two of the three adjusted ND measures in the EA sample (P=0.01-0.04). Haplotype-based association analysis revealed a protective T-G-T-G haplotype for rs921451-rs3735273-rs1451371-rs2060762 in the AA sample, which was significantly associated with all three adjusted ND measures after correction for multiple testing (min Z=-2.78, P=0.006 for HSI). In contrast, we found a high-risk T-G-T-G haplotype for a different SNP combination in the EA sample, rs921451-rs3735273-rs1451371-rs3757472, which showed a significant association after Bonferroni correction with the SQ and FTND score (max Z=2.73, P=0.005 for FTND). In summary, our findings provide the first evidence for the involvement of DDC in the susceptibility to ND and, further, reveal the racial specificity of its impact.

No association between polymorphisms in the DDC gene and paranoid schizophrenia in a northern Chinese population

Several lines of evidence suggest that dysfunctions of neurotransmitters are associated with schizophrenia. DOPA decarboxylase (DDC) is an enzyme involved directly in the synthesis of dopamine and serotonin, and indirectly in the synthesis of noradrenaline. Therefore, the DDC gene can be considered a candidate gene for schizophrenia. We performed an association study between three single nucleotide polymorphisms in the DDC gene and paranoid schizophrenia. However, in our study no significant differences were found in the genotype distributions and allele frequencies between 80 paranoid schizophrenics and 108 controls for any of the polymorphisms. Neither did the haplotypes of the single nucleotide polymorphisms show any association with paranoid schizophrenia. Therefore, we conclude that the polymorphisms studied do not play a major role in paranoid schizophrenia pathogenesis in the population investigated.