Meta-analysis in psychiatric genetics

Familial risk for depressive and anxiety disorders: associations with genetic, clinical, and psychosocial vulnerabilities

BACKGROUND

In research and clinical practice, familial risk for depression and anxiety is often constructed as a simple Yes/No dichotomous family history (FH) indicator. However, this measure may not fully capture the liability to these conditions. This study investigated whether a continuous familial loading score (FLS), incorporating family- and disorder-specific characteristics (e.g. family size, prevalence of depression/anxiety), (i) is associated with a polygenic risk score (PRS) for major depression and with clinical/psychosocial vulnerabilities and (ii) still captures variation in clinical/psychosocial vulnerabilities after information on FH has been taken into account.

METHODS

Data came from 1425 participants with lifetime depression and/or anxiety from the Netherlands Study of Depression and Anxiety. The Family Tree Inventory was used to determine FLS/FH indicators for depression and/or anxiety.

RESULTS

Persons with higher FLS had higher PRS for major depression, more severe depression and anxiety symptoms, higher disease burden, younger age of onset, and more neuroticism, rumination, and childhood trauma. Among these variables, FH was not associated with PRS, severity of symptoms, and neuroticism. After regression out the effect of FH from the FLS, the resulting residualized measure of FLS was still associated with severity of symptoms of depression and anxiety, rumination, and childhood trauma.

CONCLUSIONS

Familial risk for depression and anxiety deserves clinical attention due to its associated genetic vulnerability and more unfavorable disease profile, and seems to be better captured by a continuous score that incorporates family- and disorder-specific characteristics than by a dichotomous FH measure.

MicroRNA biomarkers of type 2 diabetes: A protocol for corroborating evidence by computational genomics and meta-analyses

BACKGROUND

Few microRNAs were found consistently dysregulated in type 2 diabetes (T2D) that would gain confidence from Big Pharma to develop diagnostic or therapeutic biomarkers. This study aimed to corroborate evidence from eligible microRNAs-T2D association studies according to stringent quality criteria covering both biological and statistical significance in T2D for biomarker development.

METHODS AND ANALYSES

Controlled microRNA expression profiling studies on human with T2D will be retrieved from PubMed, ScienceDirect, and Embase for selecting the statistically significant microRNAs according to pre-specified search strategies and inclusion criteria. Multiple meta-analyses with restricted maximum-likelihood estimation and empirical Bayes estimation under the random-effects model will be conducted by metafor package in R. Subgroup and sensitivity analyses further examine the microRNA candidates for their disease specificity, tissue specificity, blood fraction specificity, and statistical robustness of evidence. Biologically relevant microRNAs will then be selected through genomic database corroboration. Their association with T2D is further measured by area under the curve (AUC) of receive operating characteristic (ROC). Meta-analysis of AUC of potential biomarkers will also be conducted. Enrichment analysis on potential microRNA biomarkers and their target genes will be performed by iPathwayGuide and clusterProfiler, respectively. The corresponding reporting guidelines will be used to assess the quality of included studies according to their profiling methods (microarray, RT-PCR, and RNA-Seq).

ETHICS AND DISSEMINATION

No ethics approval is required since this study does not include identifiable personal patient data.

PROTOCOL REGISTRATION NUMBER

CRD42017081659.

Meta-analysis on the association between genetic polymorphisms and prepulse inhibition of the acoustic startle response

Sensorimotor gating measured by prepulse inhibition (PPI) of the acoustic startle response (ASR) has been proposed as one of the most promising electrophysiological endophenotypes of schizophrenia. During the past decade, a number of publications have reported significant associations between genetic polymorphisms and PPI in samples of schizophrenia patients and healthy volunteers. However, an overall evaluation of the robustness of these results has not been published so far. Therefore, we performed the first meta-analysis of published and unpublished associations between gene polymorphisms and PPI of ASR. Unpublished associations between genetic polymorphisms and PPI were derived from three independent samples. In total, 120 single observations from 16 independent samples with 2660 study participants and 43 polymorphisms were included. After correction for multiple testing based on false discovery rate and considering the number of analyzed polymorphisms, significant associations were shown for four variants, even though none of these associations survived a genome-wide correction (P<5∗10-8). These results imply that PPI might be modulated by four genotypes - COMT rs4680 (primarily in males), GRIK3 rs1027599, TCF4 rs9960767, and PRODH rs385440 - indicating a role of these gene variations in the development of early information processing deficits in schizophrenia. However, the overall impact of single genes on PPI is still rather small suggesting that PPI is - like the disease phenotype - highly polygenic. Future genome-wide analyses studies with large sample sizes will enhance our understanding on the genetic architecture of PPI.

BDNF Val66Met polymorphism, life stress and depression: A meta-analysis of gene-environment interaction

BACKGROUND

Depression is thought to be multifactorial in etiology, including genetic and environmental components. While a number of gene-environment interaction studies have been carried out, meta-analyses are scarce. The present meta-analysis aimed to quantify evidence on the interaction between brain-derived neurotrophic factor (BDNF) Val66Met polymorphism and stress in depression.

METHODS

Included were 31 peer-reviewed with a pooled total of 21060 participants published before October 2016 and literature searches were conducted using PubMed, Wolters Kluwer, Web of Science, EBSCO, Elsevier Science Direct and Baidu Scholar databases.

RESULTS

The results indicated that the Met allele of BDNF Val66Met polymorphism significantly moderated the relationship between stress and depression (Z=2.666, p = 0.003). The results of subgroup analysis concluded that stressful life events and childhood adversity separately interacted with the Met allele of BDNF Val66Met polymorphism in depression (Z = 2.552, p = 0.005; Z = 1.775, p = 0.03).

LIMITATIONS

The results could be affected by errors or bias in primary studies which had small sample sizes with relatively lower statistic power. We could not estimate how strong the interaction effect between gene and environment was.

CONCLUSIONS

We found evidence that supported the hypothesis that BDNF Val66Met polymorphism moderated the relationship between stress and depression, despite the fact that many included individual studies did not show this effect.

Identification of Potential MicroRNA Biomarkers by Meta-analysis

Meta-analysis statistically assesses the results (e.g., effect sizes) across independent studies that are conducted in accordance with similar protocols and objectives. Current genomic meta-analysis studies do not perform extensive re-analysis on raw data because full data access would not be commonplace, although the best practice of open research for sharing well-formed data have been actively advocated. This chapter describes a simple and easy-to-follow method for conducting meta-analysis of multiple studies without using raw data. Examples for meta-analysis of microRNAs (miRNAs) are provided to illustrate the method. MiRNAs are potential biomarkers for early diagnosis and epigenetic monitoring of diseases. A number of miRNAs have been identified to be differentially expressed, i.e., overexpressed or underexpressed, under diseased states but only a small fraction would be highly effective biomarkers or therapeutic targets of diseases. The meta-analysis method as described in this chapter aims to identify the miRNAs that are consistently found dysregulated across independent studies as biomarkers.

The relationship of Chlamydophila pneumoniae with schizophrenia: The role of brain-derived neurotrophic factor (BDNF) and neurotrophin-3 (NT-3) in this relationship

Several pathogens have been suspected of playing a role in the pathogenesis of schizophrenia. Chronic inflammation has been proposed to occur as a result of persistent infection caused by Chlamydophila pneumoniae cells that reside in brain endothelial cells for many years. It was recently hypothesized that brain-derived neurotrophic factor (BDNF) and neurotrophin-3 (NT-3) may play prominent roles in the development of schizophrenia. NT-3 and BDNF levels have been suggested to change in response to various manifestations of infection. Therefore, we aimed to elucidate the roles of BDNF and NT3 in the schizophrenia-C. pneumoniae infection relationship. RT-PCR, immunofluorescence and ELISA methods were used. Fifty patients suffering from schizophrenia and 35 healthy individuals were included as the patient group (PG) and the healthy control group (HCG), respectively. We detected persistent infection in 14 of the 50 individuals in the PG and in 1 of the 35 individuals in the HCG. A significant difference was found between the two groups (p<0.05). Twenty-two individuals in the PG and 13 in the HCG showed seropositivity for past C. pneumoniae infection, and no difference was observed between the groups (p>0.05). C. pneumoniae DNA was not detected in any group. A significant difference in NT-3 levels was observed between the groups, with very low levels in the PG (p<0.001). A significant difference in BDNF levels was also found, with lower levels in the PG (p<0.05). The mean serum NT-3 level was higher in the PG cases with C. pneumoniae seropositivity than in seronegative cases; however, this difference was not statistically significant (p>0.05). In conclusion, we suggest that NT-3 levels during persistent C. pneumoniae infection may play a role in this relationship.

The new frontier in health services research: a behavioural paradigm guided by genetics

The incorporation of genetics into health services research has largely floundered, despite the rapidly accelerating availability of, and access to, such data. This is expected given the ethical questions involved. However, using these new resources robustly to examine population choices when it comes to health insurer selection, coverage therein and especially the subsequent use of health services is a necessary step forward, especially given the increasing prevalence of multimorbidity. Such a novel advancement in health services research may eventually propel public and private insurers to redesign their infrastructure to more accurately reflect the behavioural inclinations of their beneficiary populations. Using this resource will likely provide equally important insight for countries with extensive mixed insurer systems (like the United States) or nations with a greater emphasis on single-payer systems (such as various European models).

Specific and common genes implicated across major mental disorders: a review of meta-analysis studies

Major efforts have been directed at family-based association and case-control studies to identify the involvement of candidate genes in the major disorders of mental health. What remains unknown is whether candidate genes are associated with multiple disorders via pleiotropic mechanisms, and/or if other genes are specific to susceptibility for individual disorders. Here we undertook a review of genes that have been identified in prior meta-analyses examining specific genes and specific mental disorders that have core disruptions to emotional and cognitive function and contribute most to burden of illness- major depressive disorder (MDD), anxiety disorders (AD, including panic disorder and obsessive compulsive disorder), schizophrenia (SZ) and bipolar disorder (BD) and attention deficit hyperactivity disorder (ADHD). A literature review was conducted up to end-March 2013 which included a total of 1519 meta-analyses across 157 studies reporting multiple genes implicated in one or more of the five disorders studied. A total of 134 genes (206 variants) were identified as significantly associated risk variants for MDD, AD, ADHD, SZ or BD. Null genetic effects were also reported for 195 genes (426 variants). 13 genetic variants were shared in common between two or more disorders (APOE e4, ACE Ins/Del, BDNF Val66Met, COMT Val158Met, DAOA G72/G30 rs3918342, DAT1 40-bp, DRD4 48-bp, SLC6A4 5-HTTLPR, HTR1A C1019G, MTHR C677T, MTHR A1298C, SLC6A4 VNTR and TPH1 218A/C) demonstrating evidence for pleiotrophy. Another 12 meta-analyses of GWAS studies of the same disorders were identified, with no overlap in genetic variants reported. This review highlights the progress that is being made in identifying shared and unique genetic mechanisms that contribute to the risk of developing several major psychiatric disorders, and identifies further steps for progress.

The DRD2 rs1800497 polymorphism increase the risk of mood disorder: evidence from an update meta-analysis

BACKGROUND

Growing studies have revealed the association between rs1800497 polymorphism in the dopamine receptor D2 (DRD2) and susceptibility to mood disorder (MD). However, the results remained inconsistent.

METHODS

To assess the effect of DRD2 rs1800497 polymorphism on MD. We performed a meta-analysis based on eight case-control studies, including a total of 2097 MD cases and 1681 controls. Summary odds ratios (OR) and corresponding 95% confidence intervals (CIs) for DRD2 rs1800497 polymorphism and MD risk were estimated.

RESULTS

Our meta-analysis indicated that DRD2 rs1800497 was associated with an increased MD risk, especially in Asians. Moreover, in the subgroup analysis by the type of MD, DRD2 rs1800497 polymorphism was observed to increase risk in BP.

LIMITATIONS

The results should be treated with caution for lacking of data to perform gene-gene and gene-environment interaction.

CONCLUSIONS

Our results indicated that polymorphism in DRD2 rs1800497 may play a role in development of MD.

Impaired impulse control is associated with a 5-HT2A receptor polymorphism in schizophrenia

The impact of the serotonin2a (5-HT2A) receptor gene on the pathophysiology of schizophrenia is inconclusive despite accumulating evidence implicating the 5-HT2A receptor. To simplify the complexity of genetic analysis, we used an endophenotype approach. The relationship between Continuous Performance Test (CPT) performance and 5-HT2A receptor gene variance was examined. Both patients with schizophrenia (n=255) and healthy volunteers (n=380) were recruited. All were genotyped for the -1438A/G polymorphism and assessed with the CPT. The Positive and Negative Syndrome Scale and the Scale for the Assessment of Negative Symptoms were used to evaluate patients' clinical symptoms. The distribution of the 5-HT2A genotypes between patients and healthy controls was similar. Impulse control in schizophrenic patients, assessed with the false-alarm rate of the CPT, differed significantly between those with different 5-HT2A genotypes. We hypothesize that the 5-HT2A receptor gene is a modifier gene of schizophrenia and suggest that additional studies are warranted.

Personalized medicine in psychiatry: problems and promises

The central theme of personalized medicine is the premise that an individual's unique physiologic characteristics play a significant role in both disease vulnerability and in response to specific therapies. The major goals of personalized medicine are therefore to predict an individual's susceptibility to developing an illness, achieve accurate diagnosis, and optimize the most efficient and favorable response to treatment. The goal of achieving personalized medicine in psychiatry is a laudable one, because its attainment should be associated with a marked reduction in morbidity and mortality. In this review, we summarize an illustrative selection of studies that are laying the foundation towards personalizing medicine in major depressive disorder, bipolar disorder, and schizophrenia. In addition, we present emerging applications that are likely to advance personalized medicine in psychiatry, with an emphasis on novel biomarkers and neuroimaging.

Never-depressed females with a family history of depression demonstrate affective bias

According to cognitive theories of depression, individuals susceptible to depression attend selectively to negative information. The purpose of the study was to examine if such an affective processing bias is present in never-depressed individuals with a family history of major depressive disorder (MDD). Formerly depressed female patients having at least one first-degree relative with a history of MDD (n=23), their never-depressed female siblings (n=21) and never-depressed female controls (n=21) performed a conventional and an emotional Stroop task using negative, positive and neutral words. A significant effect was found of group on negative processing bias; post hoc comparisons indicated that never-depressed siblings showed a larger negative processing bias than never-depressed controls. No significant differences were observed in positive bias or conventional interference between the three groups. Our findings suggest that never-depressed females with a family history of depression, like depressed patients, have more difficulties to inhibit negative material and to direct their attention towards task-specific material. This adds to the existing evidence that affective processing bias is a trait characteristic that contributes to the onset of depression and that could be a useful endophenotype for MDD.

Association between a genetic variant in the serotonin transporter gene (SLC6A4) and suicidal behavior in patients with schizophrenia

Background

The serotonin (5-hydroxytryptamin; 5-HT) system has a central role in the circuitry of cognition and emotions. Multiple lines of evidence suggest that genetic variation in the serotonin transporter gene (SLC6A4; 5-HTT) is associated with schizophrenia and suicidal behavior. In this study, we wanted to elucidate whether SLC6A4 variations is involved in attempted suicide among patients with schizophrenia in a Scandinavian case–control sample.

Methods

Patients diagnosed with schizophrenia from three Scandinavian samples were assessed for presence or absence of suicide attempts, based on record reviews and interview data. Seven SLC6A4 single nucleotide polymorphisms (SNPs) were genotyped in 837 schizophrenia patients and 1,473 control individuals. Association analyses and statistical evaluations were performed with the program UNPHASED (version 3.0.9).

Results

We observed an allele association between the SNP rs16965628, located in intron one of SLC6A4, and attempted suicide (adjusted p-value 0.01), among patients with schizophrenia. No association was found to a diagnosis of schizophrenia, when patients were compared to healthy control individuals.

Conclusion

The gene SLC6A4 appears to be involved in suicidal ideation among patients with schizophrenia. Independent replication is needed before more firm conclusions can be drawn.

Comparative linkage meta-analysis reveals regionally-distinct, disparate genetic architectures: application to bipolar disorder and schizophrenia

New high-throughput, population-based methods and next-generation sequencing capabilities hold great promise in the quest for common and rare variant discovery and in the search for "missing heritability." However, the optimal analytic strategies for approaching such data are still actively debated, representing the latest rate-limiting step in genetic progress. Since it is likely a majority of common variants of modest effect have been identified through the application of tagSNP-based microarray platforms (i.e., GWAS), alternative approaches robust to detection of low-frequency (1-5% MAF) and rare (<1%) variants are of great importance. Of direct relevance, we have available an accumulated wealth of linkage data collected through traditional genetic methods over several decades, the full value of which has not been exhausted. To that end, we compare results from two different linkage meta-analysis methods--GSMA and MSP--applied to the same set of 13 bipolar disorder and 16 schizophrenia GWLS datasets. Interestingly, we find that the two methods implicate distinct, largely non-overlapping, genomic regions. Furthermore, based on the statistical methods themselves and our contextualization of these results within the larger genetic literatures, our findings suggest, for each disorder, distinct genetic architectures may reside within disparate genomic regions. Thus, comparative linkage meta-analysis (CLMA) may be used to optimize low-frequency and rare variant discovery in the modern genomic era.

Psychiatric molecular genetics and the ethics of social promises

A recent literature review of commentaries and 'state of the art' articles from researchers in psychiatric genetics (PMG) offers a consensus about progress in the science of genetics, disappointments in the discovery of new and effective treatments, and a general optimism about the future of the field. I argue that optimism for the field of psychiatric molecular genetics (PMG) is overwrought, and consider progress in the field in reference to a sample estimate of US National Institute of Mental Health funding for this paradigm for the years 2008 and 2009. I conclude that the amounts of financial investment in PMG is questionable from an ethical perspective, given other research and clinical needs in the USA.

Anxiety and depression in children and adults: influence of serotonergic and neurotrophic genes?

There are two major hypotheses regarding the etiology of anxiety and depression: the mono-amine hypothesis and the hypothesis of an abnormal stress response acting partly via reduced neurogenesis. Association studies have focused on genes involved in these processes, but with inconclusive results. This study investigated the effect of 45 single nucleotide polymorphisms (SNPs) in genes encoding for serotonin receptors 1A, 1D, 2A, catechol-O-methyltransferase (COMT), tryptophane hydroxylase type 2 (TPH2), brain derived neurotrophic factor (BDNF), PlexinA2 and regulators of G-protein-coupled signaling (RGS) 2, 4, 16. Anxious depression (A/D) symptoms were assessed five times in 11 years in over 11 000 adults with 1504 subjects genotyped and at age 7, 10, 12 and during adolescence in over 20 000 twins with 1078 subjects genotyped. In both cohorts, a longitudinal model with one latent factor loading on all A/D measures over time was analysed. The genetic association effect modeled at the level of this latent factor was 60% and 70% heritable in the children and adults, respectively, and explained around 50% of the total phenotypic variance. Power analyses showed that the samples contained 80% power to detect an effect explaining between 1.4% and 3.6% of the variance. However, no SNP showed a consistent effect on A/D. To conclude, this longitudinal study in children and adults found no association of SNPs in the serotonergic system or core regulators of neurogenesis with A/D. Overall, there has been no convincing evidence, so far, for a role of genetic variation in these pathways in the development of anxiety and depression.

Do 5HTTLPR and stress interact in risk for depression and suicidality? Item response analyses of a large sample

The reported interaction between the length polymorphism (5HTTLPR) in the serotonin transporter gene (SLC6A4) and stressful life events on depression has led to many attempts to replicate but with inconsistent results. This inconsistency may reflect, in part, small sample size and the unknown contribution of the long allele SNP, rs25531. Using a large twin sample of 3,243 individuals from 2,230 families aged 18-95 years (mean = 32.3, SD = 13.6) we investigate the interaction between 5HTTLPR (subtyped with SNP rs25531) and stressful events on risk of depression and suicidality using both ordinal regressions and item response theory analyses. Participants reported via mailed questionnaire (82% response rate) both stressful events in the preceeding 12 months and symptoms of depression. Stressful events were defined as "personal" (affecting the individual), or "network" (affecting close family or friends). One to 10 years later (mean = 4.2 years), participants completed a comprehensive clinical psychiatric telephone interview (83% response rate) which assessed DSM-IV major depression and ideation of suicidality. Self-reports of depression and an increase in depression/suicidality assessed by clinical interview are significantly associated with prior personal events (P < 0.001) after controlling for age and sex. However, they are inconsistently associated with prior network events (ranging, ns to P < 0.01) and are not significantly associated with any of the genotype main effects (5HTTLPR, 5HTTLPR + rs25531) or interactions (stress x genotype). We find no evidence to support the hypothesis of any 5HTTLPR genotype by stress interaction.

Gene- and evidence-based candidate gene selection for schizophrenia and gene feature analysis

OBJECTIVE

Schizophrenia is a chronic psychiatric disorder that affects about 1% of the population globally. A tremendous amount of effort has been expended in the past decade, including more than 2400 association studies, to identify genes influencing susceptibility to the disorder. However, few genes or markers have been reliably replicated. The wealth of this information calls for an integration of gene association data, evidence-based gene ranking, and follow-up replication in large sample. The objective of this study is to develop and evaluate evidence-based gene ranking methods and to examine the features of top-ranking candidate genes for schizophrenia.

METHODS

We proposed a gene-based approach for selecting and prioritizing candidate genes by combining odds ratios (ORs) of multiple markers in each association study and then combining ORs in multiple studies of a gene. We named it combination-combination OR method (CCOR). CCOR is similar to our recently published method, which first selects the largest OR of the markers in each study and then combines these ORs in multiple studies (i.e., selection-combination OR method, SCOR), but differs in selecting representative OR in each study. Features of top-ranking genes were examined by Gene Ontology terms and gene expression in tissues.

RESULTS

Our evaluation suggested that the SCOR method overall outperforms the CCOR method. Using the SCOR, a list of 75 top-ranking genes was selected for schizophrenia candidate genes (SZGenes). We found that SZGenes had strong correlation with neuro-related functional terms and were highly expressed in brain-related tissues.

CONCLUSION

The scientific landscape for schizophrenia genetics and other complex disease studies is expected to change dramatically in the next a few years, thus, the gene-based combined OR method is useful in candidate gene selection for follow-up association studies and in further artificial intelligence in medicine. This method for prioritization of candidate genes can be applied to other complex diseases such as depression, anxiety, nicotine dependence, alcohol dependence, and cardiovascular diseases.

Psychiatric GWAS Consortium Coordinating Committee, Cichon S, Craddock N, Daly M, Faraone SV, Gejman PV, Kelsoe J, Lehner T, Levinson DF, Moran A, Sklar P, Sullivan PF. Genomewide association studies: history, rationale, and prospects for psychiatric disorders

OBJECTIVE

The authors conducted a review of the history and empirical basis of genomewide association studies (GWAS), the rationale for GWAS of psychiatric disorders, results to date, limitations, and plans for GWAS meta-analyses.

METHOD

A literature review was carried out, power and other issues discussed, and planned studies assessed.

RESULTS

Most of the genomic DNA sequence differences between any two people are common (frequency >5%) single nucleotide polymorphisms (SNPs). Because of localized patterns of correlation (linkage disequilibrium), 500,000 to 1,000,000 of these SNPs can test the hypothesis that one or more common variants explain part of the genetic risk for a disease. GWAS technologies can also detect some of the copy number variants (deletions and duplications) in the genome. Systematic study of rare variants will require large-scale resequencing analyses. GWAS methods have detected a remarkable number of robust genetic associations for dozens of common diseases and traits, leading to new pathophysiological hypotheses, although only small proportions of genetic variance have been explained thus far and therapeutic applications will require substantial further effort. Study design issues, power, and limitations are discussed. For psychiatric disorders, there are initial significant findings for common SNPs and for rare copy number variants, and many other studies are in progress.

CONCLUSIONS

GWAS of large samples have detected associations of common SNPs and of rare copy number variants with psychiatric disorders. More findings are likely, since larger GWAS samples detect larger numbers of common susceptibility variants, with smaller effects. The Psychiatric GWAS Consortium is conducting GWAS meta-analyses for schizophrenia, bipolar disorder, major depressive disorder, autism, and attention deficit hyperactivity disorder. Based on results for other diseases, larger samples will be required. The contribution of GWAS will depend on the true genetic architecture of each disorder.

Neurotransmission and bipolar disorder: a systematic family-based association study

Neurotransmission pathways/systems have been proposed to be involved in the pathophysiology and treatment of bipolar disorder for over 40 years. In order to test the hypothesis that common variants of genes in one or more of five neurotransmission systems confer risk for bipolar disorder, we analyzed 1,005 tag single nucleotide polymorphisms in 90 genes from dopaminergic, serotonergic, noradrenergic, GABAergic, and glutamatergic neurotransmitter systems in 101 trios and 203 quads from Caucasian bipolar families. Our sample has 80% power to detect ORs >or= 1.82 and >or=1.57 for minor allele frequencies of 0.1 and 0.5, respectively. Nominally significant allelic and haplotypic associations were found for genes from each neurotransmission system, with several reaching gene-wide significance (allelic: GRIA1, GRIN2D, and QDPR; haplotypic: GRIN2C, QDPR, and SLC6A3). However, none of these associations survived correction for multiple testing in an individual system, or in all systems considered together. Significant single nucleotide polymorphism associations were not found with sub-phenotypes (alcoholism, psychosis, substance abuse, and suicide attempts) or significant gene-gene interactions. These results suggest that, within the detectable odds ratios of this study, common variants of the selected genes in the five neurotransmission systems do not play major roles in influencing the risk for bipolar disorder or comorbid sub-phenotypes.

Genetic associations with schizophrenia: meta-analyses of 12 candidate genes

Genetic association studies on schizophrenia (SZ) have been repeatedly performed over the last two decades, resulting in a consensus that results are generally inconsistent. This consensus has begun to change as a result of meta-analyses (e.g., [Glatt, S.J. and Jonsson, E.G., 2006. The Cys allele of the DRD2 Ser311Cys polymorphism has a dominant effect on risk for schizophrenia: evidence from fixed- and random-effects meta-analyses. Am. J. Med. Genet. B. Neuropsychiatr. Genet. 141, 149-154.]). The SchizophreniaGene database (http://www.schizophreniaforum.org/res/sczgene/default.asp) has been a leader in meta-analyses of SZ association data, by dynamically and comprehensively cataloging all public genetic association studies, and preparing meta-analyses of case-control data. There are 19 "top" candidate genes from these analyses (access on December 20, 2007), showing the highest effect sizes and nominally significant associations of at least one variant in the meta-analyses of all ethnic samples or of samples of Caucasian ancestry. We selected 40 polymorphisms in 12 selected "top" genes for additional meta-analyses, which had at least one familial association data. We found gene-wide (correction for the number of meta-analyses for each gene) significant allelic association evidence for seven genes in the combined samples. The odds ratios (ORs) of the associated minor risk alleles range from 1.072 to 1.121, for DRD4, MTHFR, PPP3CC and TP53. For protective allele associations, the ORs are between 0.842 and 0.886, for DAO, IL1B, and SLC6A4. In population-based sub-analyses, we found significant results in four genes in Asians (ORs between 1.084 and 1.309 for DRD4, GABRB2, PPP3CC, and TP53), and one gene in European (OR of 0.888 for SLC6A4). The association of rs1816072 of GABRB2 with SZ in Asians was significant (adjusted P=0.048 after correction for 80 tests). No significant heterogeneity between case-control and family-based study designs was detected in 35 out of 40 polymorphisms. Our results further support eight potential SZ candidate genes and suggest that family data can reasonably be included in the meta-analysis of genetic associations.

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).

[The genetics of depressive disorders]

Among the most common severe psychiatric disorders worldwide, depressive disorders are a leading cause of morbidity, the onset usually occurring during childhood or adolescence. Symptomatology, prevalence, outcome and treatment differentiate depressive disorder nosologically as being either unipolar depression or bipolar disorder, which is characterized by one or more episodes of mania with or without episodes of depression. Genetic factors decisively influence the susceptibility to depressive disorders. Family studies and twin studies have been essential in defining the magnitude of familial risk and liability to heritability, particularly in the case of bipolar disorder. In recent years, linkage and association studies have made great strides towards identifying candidate genes. Particularly the s-allele of the serotonin transporter has been repeatedly confirmed to be a risk factor. Meta-analyses suggest, however, that the genetic contributions of the ascertained loci are relatively small. Along with genetic factors, environmental factors are heavily involved. Gene-environment action plays a pivotal role, particularly in unipolar depression. The genetic disposition seems to be modulated by a protective or pathogenic environment. Early-onset disorders must be further investigated in future as studies to date are somewhat limited.

Depressive Störungen

Das Spektrum depressiver Erkrankungen macht den Hauptteil affektiver Störungen aus und gehört mit einer Inzidenz von ca. 8–20% zu den häufigsten psychischen Erkrankungen. Depressionen werden nach wie vor zu selten einer adäquaten Therapie (Antidepressiva, störungsspezifische Psychotherapie wie z. B. kognitive Verhaltenstherapie) zugeführt.

Consensus paper of the WFSBP Task Force on Biological Markers: biological markers in depression

Biological markers for depression are of great interest to aid in elucidating the causes of major depression. We assess currently available biological markers to query their validity for aiding in the diagnosis of major depression. We specifically focus on neurotrophic factors, serotonergic markers, biochemical markers, immunological markers, neuroimaging, neurophysiological findings, and neuropsychological markers. We delineate the most robust biological markers of major depression. These include decreased platelet imipramine binding, decreased 5-HT1A receptor expression, increase of soluble interleukin-2 receptor and interleukin-6 in serum, decreased brain-derived neurotrophic factor in serum, hypocholesterolemia, low blood folate levels, and impaired suppression of the dexamethasone suppression test. To date, however, none of these markers are sufficiently specific to contribute to the diagnosis of major depression. Thus, with regard to new diagnostic manuals such as DSM-V and ICD-11 which are currently assessing whether biological markers may be included in diagnostic criteria, no biological markers for major depression are currently available for inclusion in the diagnostic criteria.

The genetics of bipolar affective disorder

PURPOSE OF REVIEW

Molecular genetic studies of bipolar affective disorder are beginning to show some positive and reproducible findings. The most relevant of these will be reviewed.

RECENT FINDINGS

Obtaining consistent findings from whole genome scans has been hampered by small sample sizes and phenotypic heterogeneity. Recently, there have been concerted efforts to overcome these problems by combining data for meta-analysis. What has become increasingly clear is that several regions that are likely to contain genes contributing to bipolar affective disorder are also relevant to schizophrenia, a finding supported by recent twin data. Studies to date have implicated the D-amino acid oxidase activator complex (also known as G72/G30), disrupted in schizophrenia-1 and neuregulin, and have pointed to several promising linkage regions in which the genes have not yet been identified. In addition, there is some evidence to support the involvement of genetic variants in catechol-o-methyl transferase and brain-derived neurotrophic factor in the aetiology of bipolar affective disorder.

SUMMARY

Molecular genetic research in bipolar affective disorder may lead to the development of new diagnostic paradigms for classifying the psychoses and affective states. In addition, determining the functional significance of the susceptibility genes will pave the way for enhanced diagnostic accuracy and improved treatments.

Panic comorbidity with bipolar disorder: what is the manic-panic connection?

CONTEXT

Bipolar/panic comorbidity has been observed in clinical, community and familial samples. As both are episodic disorders of affect regulation, the common pathophysiological mechanism is likely to involve deficits in amygdala-mediated, plasticity-dependent emotional conditioning.

EVIDENCE

Neuronal genesis and synaptic remodeling occur in the amygdala; bipolar and panic disorders have both been associated with abnormality in the amygdala and related structures, as well as in molecules that modulate plasticity, such as serotonin, norepinephrine, brain-derived neurotrophic factor (BDNF) and corticotrophin releasing factor (CRF). These biological elements are involved in behavioral conditioning to threat and reward.

MODEL

Panic attacks resemble the normal acute fear response, but are abnormally dissociated from any relevant threat. Abnormal reward-seeking behavior is central to both manic and depressive syndromes. Appetites can be elevated or depressed; satisfaction of a drive may fail to condition future behavior. These dissociations may be the result of deficits in plasticity-dependent processes of conditioning within different amygdala subregions.

CONCLUSIONS

This speculative model may be a useful framework with which to connect molecular, cellular, anatomic and behavioral processes in panic and bipolar disorders. The primary clinical implication is that behavioral treatment may be critical to restore function in some bipolar patients who respond only partially to medications.

Association of an Asn40Asp (A118G) polymorphism in the mu-opioid receptor gene with substance dependence: a meta-analysis

INTRODUCTION

The mu-opioid receptor has been implicated in the pathogenesis of dependence on opioids, alcohol, nicotine, and cocaine. Studies examining the association of the mu-opioid receptor gene (genetic locus OPRM1) with substance dependence (SD) have focused on the Asn40Asp (A118G) single nucleotide polymorphism (SNP).

METHOD

We used meta-analysis to examine the literature on the association of Asn40Asp with SD. Twenty-two articles describing 28 distinct samples and over 8000 subjects were included. A variety of factors (i.e., ethnicity, type of SD, rigor with which controls were screened, severity of SD among cases) were examined as potential moderators of the association.

RESULTS

Four studies showed a significantly higher frequency of the Asp40 allele among SD cases, while three studies showed a significantly higher frequency of the Asp40 allele among controls. There was no significant association between Asn40Asp and SD (OR=1.01, 95%CI=0.86-1.19), nor was there substantial evidence of a moderator effect.

CONCLUSION

The Asn40Asp SNP in OPRM1 does not appear to affect risk for SD. Additional research is needed to determine whether these findings reflect no role for OPRM1 in determining risk for SD or whether another polymorphism in the gene influences receptor function and risk for SD.

The genetics of depression: a review

Major depressive disorder (MDD) is common and moderately heritable. Recurrence and early age at onset characterize cases with the greatest familial risk. Major depressive disorder and the neuroticism personality trait have overlapping genetic susceptibilities. Most genetic studies of MDD have considered a small set of functional polymorphisms relevant to monoaminergic neurotransmission. Meta-analyses suggest small positive associations between the polymorphism in the serotonin transporter promoter region (5-HTTLPR) and bipolar disorder, suicidal behavior, and depression-related personality traits but not yet to MDD itself. This polymorphism might also influence traits related to stress vulnerability. Newer hypotheses of depression neurobiology suggest closer study of genes related to neurotoxic and neuroprotective (neurotrophic) processes and to overactivation of the hypothalamic-pituitary axis, with mixed evidence regarding association of MDD with polymorphisms in one such gene (brain-derived neurotrophic factor [BDNF]). Several genome-wide linkage studies of MDD and related traits have been reported or are near completion. There is some evidence for convergence of linkage findings across studies, but more data are needed to permit meta-analysis. Future directions will include more intensive, systematic study of linkage candidate regions and of the whole genome for genetic association; gene expression array studies; and larger-scale studies of gene-environment interactions and of depression-related endophenotypes.

The Cys allele of the DRD2 Ser311Cys polymorphism has a dominant effect on risk for schizophrenia: evidence from fixed- and random-effects meta-analyses

Previously we derived independent estimates of the effect of the dopamine D2 receptor (DRD2) Ser311Cys polymorphism on risk for schizophrenia using fixed- and random-effects meta-analyses. Both analyses identified a significant association between the Cys allele and schizophrenia, but neither included all available data. Furthermore, genotype data were not evaluated in either analysis, thus precluding any determination of the mode of inheritance. The present study was conducted to resolve discrepancies between the existing meta-analyses, and provide more comprehensive and accurate estimates of the nature and magnitude of the influence of the Ser311Cys polymorphism on risk for schizophrenia. All discrepancies between the two sets of previously meta-analyzed studies were identified and resolved to the mutual satisfaction of the authors, and the final dataset was analyzed independently by fixed- and random-effects meta-analyses. A total of 27 samples, comprising 3,707 schizophrenia patients and 5,363 control subjects, were included in the analyses of allelic association, while smaller numbers of studies and subjects were included in each of the genotypic association analyses. A significant effect of the Cys allele was observed under both fixed-effects (odds ratio [OR] = 1.4; P = 0.002) and random-effects (OR = 1.4; P = 0.007) models. Cys/Ser heterozygotes were at elevated risk for schizophrenia when compared to Ser/Ser homozygotes (fixed- and random-effects OR = 1.4, p(s) or= 0.948). There was no evidence of heterogeneity, excessive influence of any single study, or publication bias in any of the analyses, suggesting that the effect of this DRD2 polymorphism on schizophrenia risk is reliable and uniform across populations, and our estimates of its magnitude are robust and accurate.

Human genetics and pharmacology of neurotransmitter transporters

Biogenic amine neurotransmitters are released from nerve terminals and activate pre- and postsynaptic receptors. Released neurotransmitters are sequestered by transporters into presynaptic neurons, a major mode of their inactivation in the brain. Genetic studies of human biogenic amine transporter genes, including the dopamine transporter (hDAT; SLC6A3), the serotonin transporter (hSERT; SLC6A4), and the norepinephrine transporter (hNET; SLC6A2) have provided insight into how genomic variations in these transporter genes influence pharmacology and brain physiology. Genetic variants can influence transporter function by various mechanisms, including substrate affinities, transport velocity, transporter expression levels (density), extracellular membrane expression, trafficking and turnover, and neurotransmitter release. It is increasingly apparent that genetic variants of monoamine transporters also contribute to individual differences in behavior and neuropsychiatric disorders. This chapter summarizes current knowledge of transporters with a focus on genomic variations, expression variations, pharmacology of protein variants, and known association with human diseases.

Future contributions on genetics

It has become obvious from epidemiological studies in families of patients affected or from twin studies, that most psychiatric disorders are in part genetically determined. Genetics have raised incredible hopes that the complex nature of psychiatric disorders might be unravelled. However, progress in psychiatry genetics have met major difficulties that have hampered psychiatry taking advantage of the new technologies as compared to other fields, such as neurology. In this non-exhaustive review, we propose an overview from the initial evidence to the expected future, through a critical statement on the current situation.

New approaches to the genetic analysis of neuroticism and anxiety

The completion of the human genome project and the complementary genome projects for other species has broadened the scope for novel bioinformatic approaches to quantitative trait locus (QTL) identification. A key issue for quantitative trait nucleotide (QTN) identification is progressing from a large QTL peak, spanning perhaps 50 cM and many hundreds of genes, to a gene or nucleotide variant which is responsible for that QTL effect. The complementary use of mouse models to dissect large syntenic loci in humans is a powerful method for reducing QTL intervals to the order of 1 Mb. This paper presents an overview of the approaches used in our laboratory to ultra-fine map QTLs for anxiety-related traits, and to identify quantitative trait genes (QTG). As new genetic techniques and statistical approaches arise, we are getting closer to identifying those long sought after QTNs.