Despite the need for more effective treatments for psychiatric disorders, development of new medications has stalled. Here we discuss the promise of personalized medicine in developing more efficacious and individualized pharmacotherapies that take into account genetic variation and target groups of patients who share biology, not just symptoms.
The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) Study revealed poorer antidepressant treatment response among black compared with white participants. This racial disparity persisted even after socioeconomic and baseline clinical factors were taken into account. Some studies have suggested genetic contributions to this disparity, but none have attempted to disentangle race and genetic ancestry. Here we used genome-wide single-nucleotide polymorphism (SNP) data to examine independent contributions of race and genetic ancestry to citalopram response. Secondary data analyses included 1877 STAR*D participants who completed an average of 10 weeks of citalopram treatment and provided DNA samples. Participants reported their race as White (n=1464), black (n=299) or other/mixed (n=114). Genetic ancestry was estimated by multidimensional scaling (MDS) analyses of about 500 000 SNPs. Ancestry proportions were estimated by STRUCTURE. Structural equation modeling was used to examine the direct and indirect effects of observed and latent predictors of response, defined as change in the Quick Inventory of Depressive Symptomatology (QIDS) score from baseline to exit. Socioeconomic and baseline clinical factors, race, and anxiety significantly predicted response, as previously reported. However, direct effects of race disappeared in all models that included genetic ancestry. Genetic African ancestry predicted lower treatment response in all models. Although socioeconomic and baseline clinical factors drive racial differences in antidepressant response, genetic ancestry, rather than self-reported race, explains a significant fraction of the residual differences. Larger samples would be needed to identify the specific genetic mechanisms that may be involved, but these findings underscore the importance of including more African-American patients in drug trials.
African Americans; Clinical Pharmacology/Clinical Trials; depression; unipolar/bipolar; ethnicity; health disparities; pharmacogenetics/pharmacogenomics; psychiatry & behavioral sciences; Pharmacology; Genetics; Ethnicity; African Americans; SSRI
High attrition rates among African-Americans (AA) volunteers are a persistent problem that makes clinical trials less representative and complicates estimation of treatment outcomes. Many studies contrast AA with other ethnic/racial groups, but few compare the AA volunteers who remain in treatment with those who leave. Here, in addition to comparing patterns of attrition between African Americans and whites, we identify predictors of overall and early attrition among African Americans.
Sample comprised non-Hispanic African-American (n=673) and white (n=2,549) participants in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. Chi-square tests were used to examine racial group differences in reasons for exit. Multivariate logistic regression was used to examine predictors of overall attrition, early attrition (by Level 2) and top reasons cited for attrition among African Americans.
For both African-American and white dropouts, non-compliance reasons for attrition were most commonly cited during the earlier phases of the study while reasons related to efficacy and medication side effects were cited later in the study. Satisfaction with treatment strongly predicted overall attrition among African Americans independent of socioeconomic, clinical, medical or psychosocial factors. Early attrition among African American dropouts was associated with less psychiatric comorbidity, and higher perceived physical functioning but greater severity of clinician-rated depression.
The decision to drop out is a dynamic process that changes over the course of a clinical trial. Strategies aimed at retaining African Americans in such trials should emphasize engagement with treatment and patient satisfaction immediately following enrollment and after treatment initiation.
Research Volunteers; Ethnic Groups; Blacks; Depression; Disparities; Treatment
Genetic contributions to major depressive disorder (MDD) are thought to result from multiple genes interacting with each other. Different procedures have been proposed to detect such interactions. Which approach is best for explaining the risk of developing disease is unclear.
This study sought to elucidate the genetic interaction landscape in candidate genes for MDD by conducting a SNP-SNP interaction analysis using an exhaustive search through 3,704 SNP-markers in 1,732 cases and 1,783 controls provided from the GAIN MDD study. We used three different methods to detect interactions, two logistic regressions models (multiplicative and additive) and one data mining and machine learning (MDR) approach.
Although none of the interaction survived correction for multiple comparisons, the results provide important information for future genetic interaction studies in complex disorders. Among the 0.5% most significant observations, none had been reported previously for risk to MDD. Within this group of interactions, less than 0.03% would have been detectable based on main effect approach or an a priori algorithm. We evaluated correlations among the three different models and conclude that all three algorithms detected the same interactions to a low degree. Although the top interactions had a surprisingly large effect size for MDD (e.g. additive dominant model Puncorrected = 9.10E-9 with attributable proportion (AP) value = 0.58 and multiplicative recessive model with Puncorrected = 6.95E-5 with odds ratio (OR estimated from β3) value = 4.99) the area under the curve (AUC) estimates were low (< 0.54). Moreover, the population attributable fraction (PAF) estimates were also low (< 0.15).
We conclude that the top interactions on their own did not explain much of the genetic variance of MDD. The different statistical interaction methods we used in the present study did not identify the same pairs of interacting markers. Genetic interaction studies may uncover previously unsuspected effects that could provide novel insights into MDD risk, but much larger sample sizes are needed before this strategy can be powerfully applied.
Additive interaction; Multiplicative interaction; Logistic regression; Data mining and machine learning; Major depressive disorder
Bipolar disorder is one of the most common and devastating psychiatric disorders whose mechanisms remain largely unknown. Despite a strong genetic contribution demonstrated by twin and adoption studies, a polygenic background influences this multifactorial and heterogeneous psychiatric disorder. To identify susceptibility genes on a severe and more familial sub-form of the disease, we conducted a genome-wide association study focused on 211 patients of French origin with an early age at onset and 1,719 controls, and then replicated our data on a German sample of 159 patients with early-onset bipolar disorder and 998 controls. Replication study and subsequent meta-analysis revealed two genes encoding proteins involved in phosphoinositide signalling pathway (PLEKHA5 and PLCXD3). We performed additional replication studies in two datasets from the WTCCC (764 patients and 2,938 controls) and the GAIN-TGen cohorts (1,524 patients and 1,436 controls) and found nominal P-values both in the PLCXD3 and PLEKHA5 loci with the WTCCC sample. In addition, we identified in the French cohort one affected individual with a deletion at the PLCXD3 locus and another one carrying a missense variation in PLCXD3 (p.R93H), both supporting a role of the phosphatidylinositol pathway in early-onset bipolar disorder vulnerability. Although the current nominally significant findings should be interpreted with caution and need replication in independent cohorts, this study supports the strategy to combine genetic approaches to determine the molecular mechanisms underlying bipolar disorder.
To evaluate the hypothesis that functionally over-expressing alleles of the serotonin transporter gene SLC6A4 are present in Tourette disorder (TD), just as we have found in obsessive compulsive disorder (OCD), we evaluated TD probands (N=151) and controls (N=858).
We genotyped the refined 5-HTTLPR/rs25531 locus and the associated rs25532 variant in the SLC6A4 promoter plus the rare coding variant SERT I425V.
The higher-expressing 5-HTTLPR/rs25531 LA allele was more prevalent in TD probands than controls (χ2=5.75, p=0.017, OR=1.35), and in a secondary analysis, surprisingly found to be significantly more frequent in probands with TD alone than in those with TD plus OCD (Fisher's exact test, p=0.0006, OR=2.29). Likewise, the higher-expressing LAC haplotype (5-HTTLPR/rs25531/rs25532) was more frequent in TD probands than controls (p=0.024, OR=1.33) and likewise in the TD alone versus TD plus OCD group (p=0.0013, OR=2.14). Further, the rare gain-of-function SERT I425V variant was found in three male siblings with TD and/or OCD and in their father. The cumulative count of SERT I425V thus becomes 1.57% in OCD/TD spectrum conditions vs. 0.15% in controls, with a recalculated, family-adjusted significance of χ2=15.03, p < 0.0001, OR=9.0 (total worldwide genotyped=2914).
This report provides a unique combination of common and rare variants in one gene in TD, all found to be associated with SLC6A4 gain of function. Thus, altered SERT activity represents a potential contributor to serotonergic abnormalities in TD. Present results call for replication in a similarly intensively evaluated sample.
SLC6A4; SERT; Tourette; serotonin; 5-HTTLPR; SERT I425V
Neuroinflammation is a pathological hallmark of Alzheimer’s disease, but its role in cognitive impairment and its course of development during the disease are largely unknown. To address these unknowns, we used positron emission tomography with 11C-PBR28 to measure translocator protein 18 kDa (TSPO), a putative biomarker for inflammation. Patients with Alzheimer’s disease, patients with mild cognitive impairment and older control subjects were also scanned with 11C-Pittsburgh Compound B to measure amyloid burden. Twenty-nine amyloid-positive patients (19 Alzheimer’s, 10 mild cognitive impairment) and 13 amyloid-negative control subjects were studied. The primary goal of this study was to determine whether TSPO binding is elevated in patients with Alzheimer’s disease, and the secondary goal was to determine whether TSPO binding correlates with neuropsychological measures, grey matter volume, 11C-Pittsburgh Compound B binding, or age of onset. Patients with Alzheimer’s disease, but not those with mild cognitive impairment, had greater 11C-PBR28 binding in cortical brain regions than controls. The largest differences were seen in the parietal and temporal cortices, with no difference in subcortical regions or cerebellum. 11C-PBR28 binding inversely correlated with performance on Folstein Mini-Mental State Examination, Clinical Dementia Rating Scale Sum of Boxes, Logical Memory Immediate (Wechsler Memory Scale Third Edition), Trail Making part B and Block Design (Wechsler Adult Intelligence Scale Third Edition) tasks, with the largest correlations observed in the inferior parietal lobule. 11C-PBR28 binding also inversely correlated with grey matter volume. Early-onset (<65 years) patients had greater 11C-PBR28 binding than late-onset patients, and in parietal cortex and striatum 11C-PBR28 binding correlated with lower age of onset. Partial volume corrected and uncorrected results were generally in agreement; however, the correlation between 11C-PBR28 and 11C-Pittsburgh Compound B binding was seen only after partial volume correction. The results suggest that neuroinflammation, indicated by increased 11C-PBR28 binding to TSPO, occurs after conversion of mild cognitive impairment to Alzheimer’s disease and worsens with disease progression. Greater inflammation may contribute to the precipitous disease course typically seen in early-onset patients. 11C-PBR28 may be useful in longitudinal studies to mark the conversion from mild cognitive impairment or to assess response to experimental treatments of Alzheimer’s disease.
Alzheimer’s disease; mild cognitive impairment; neuroinflammation; positron emission tomography
As large-scale genome sequencing technology advances, concerns surrounding the reporting of individual findings to study volunteers have grown and fueled controversy. This is especially true in mental health research, where the clinical importance of sequencing results is particularly unclear. The ethical, legal, and social issues are being widely debated, but less is known about the attitudes of actual study volunteers toward sequencing studies or what they wish to learn about their DNA sequence and its health implications. This study provides information on psychiatric research volunteers’ attitudes, beliefs, and concerns with respect to participation in DNA sequencing studies and reporting of individual results.
We conducted a pilot study using a questionnaire that we developed to assess what information volunteers in an ongoing family study of bipolar disorder would like to receive if they underwent genome sequencing, what they would do with that information, and what concerns they may have.
Almost all of the respondents were willing to participate in genome sequencing. Most respondents wished to be informed about all their health-related genetic risks, including risks for diseases without known prevention or treatment. However, few respondents felt well informed about the nature of genome sequencing or its implications for their health, insurability, or offspring.
Despite generally positive attitudes toward genome sequencing among study volunteers, most are not fully aware of the special issues raised by genome sequencing. The attitudes of study volunteers should be considered in the debate about the reporting of individual findings from genome sequencing.
The major mood disorders, which include bipolar disorder (BD) and major depressive disorder (MDD), are substantially heritable, but few risk loci have been identified. We performed a meta-analysis of 5 major mood disorder case-control samples, including over 13,600 unique individuals genotyped with approximately 500,000 to 1 million single nucleotide polymorphism (SNP) markers on high-density arrays. Allele-wise association results were meta-analyzed with a method that weights results by sample size. We found genome-wide significant evidence that SNPs in a region of chromosome 3p21.1were associated with major mood disorders. The SNP rs2251219 returned the smallest meta-analysis p-value, 3.63 × 10−8, with a pooled odds ratio of 0.87. Supportive results were observed in 2 out of 3 independent samples tested in a replication study. These results implicate one or more genes in this region in the etiology of major mood disorders and suggest that BD and MDD share genetic risk factors.
bipolar; depression; GAIN; STAB1; NT5DC2; PBRM1; NEK4; SPCS1; GNL3; GLT8D1; ITIH
Anatomical differences in the corpus callosum have been found in various psychiatric disorders, but data on the genetic contributions to these differences have been limited. The current study used morphometric MRI data to assess the heritability of corpus callosum size and the genetic correlations among anatomical sub-regions of the corpus callosum among individuals with and without mood disorders. The corpus callosum (CC) was manually segmented at the mid-sagittal plane in 42 women (healthy, n = 14; major depressive disorder, n = 15; bipolar disorder, n = 13) and their 86 child or adolescent offspring. Four anatomical sub-regions (CC-genu, CC2, CC3 and CC-splenium) and total CC were measured and analyzed. Heritability and genetic correlations were estimated using a variance components method, with adjustment for age, sex, diagnosis, and diagnosis x age, where appropriate. Significant heritability was found for several CC sub-regions (P<0.01), with estimated values ranging from 48% (splenium) to 67% (total CC). There were strong and significant genetic correlations among most sub regions. Correlations between the genu and mid-body, between the genu and total corpus callosum, and between anterior and mid body were all >90%, but no significant genetic correlations were detected between ventral and rostral regions in this sample. Genetic factors play an important role in corpus callosum size among individuals. Distinct genetic factors seem to be involved in caudal and rostral regions, consistent with the divergent functional specialization of these brain areas.
The Neuregulin 1 gene (NRG1) has been associated with schizophrenia, and, to a lesser extent, with bipolar disorder (BP). We investigated the association of NRG1 with BP in a large family sample, and then performed analyses according to the presence of psychotic features or mood-incongruent psychotic features. We genotyped 116 tagSNPs and four Icelandic “core” SNPs in 1,199 subjects from 314 nuclear families. Of 515 BP offspring, 341 had psychotic features, and 103 had mood-incongruent psychotic features. In single-marker and sliding window haplotype analyses using FBAT, there was little association using the standard BP or mood-incongruent psychotic BP phenotypes, but stronger signals were seen in the psychotic BP phenotype. The most significant associations with psychotic BP were in haplotypes within the 5′ “core” region. The strongest global P-value was across three SNPs: NRG241930-NRG243177-rs7819063 (P=0.0016), with an undertransmitted haplotype showing an individual P=0.0007. The most significant individual haplotype was an undertransmitted two-allele subset of the above (NRG243177-rs7819063, P=0.0004). Additional associations with psychotic BP were found across six SNPs in a 270 kb central region of the gene. The most 3′ of these, rs7005606 (P=0.0029), is located ∼4 kb from the type I NRG1 isoform promoter. In sum, our study suggests that NRG1 may be specifically associated with the psychotic subset of BP; however, our results should be interpreted cautiously since they do not meet correction for multiple testing and await independent replication.
Neuregulin 1; bipolar disorder; psychosis; mood-incongruent psychosis; genetic association
Epidemiological studies, such as family, twin, and adoption studies, demonstrate the presence of a heritable component to both attempted and completed suicide. Some of this heritability is accounted for by the presence of comorbid psychiatric disorders, but the evidence also indicates that a portion of this heritability is specific to suicidality. The serotonergic system has been studied extensively in this phenotype, but findings have been inconsistent, possibly due to the presence of multiple susceptibility variants and/or gene-gene interactions. In this study, we genotyped 174 tag and coding single nucleotide polymorphisms (SNPs) from 17 genes within the serotonin pathway on 516 subjects with a major mood disorder and a history of a suicide attempt (cases) and 515 healthy controls, with the goal of capturing the common genetic variation across each of these candidate genes. We tested the 174 markers in single-SNP, haplotype, gene-based, and epistasis analyses. While these association analyses identified multiple marginally significant SNPs, haplotypes, genes, and interactions, none of them survived correction for multiple testing. Additional studies, including assessment in larger sample sets and deep resequencing to identify rare causal variants, may be required to fully understand the role that the serotonin pathway plays in suicidal behavior.
suicidal behavior; bipolar disorder; major depression
The heritable component to attempted and completed suicide is partly related to psychiatric disorders and also partly independent of them. While attempted suicide linkage regions have been identified on 2p11–12 and 6q25–26, there are likely many more such loci, the discovery of which will require a much higher resolution approach, such as the genome-wide association study (GWAS). With this in mind, we conducted an attempted suicide GWAS that compared the single nucleotide polymorphism (SNP) genotypes of 1,201 bipolar (BP) subjects with a history of suicide attempts to the genotypes of 1,497 BP subjects without a history of suicide attempts. 2,507 SNPs with evidence for association at p<0.001 were identified. These associated SNPs were subsequently tested for association in a large and independent BP sample set. None of these SNPs were significantly associated in the replication sample after correcting for multiple testing, but the combined analysis of the two sample sets produced an association signal on 2p25 (rs300774) at the threshold of genome-wide significance (p= 5.07 × 10−8). The associated SNPs on 2p25 fall in a large linkage disequilibrium block containing the ACP1 gene, a gene whose expression is significantly elevated in BP subjects who have completed suicide. Furthermore, the ACP1 protein is a tyrosine phosphatase that influences Wnt signaling, a pathway regulated by lithium, making ACP1 a functional candidate for involvement in the phenotype. Larger GWAS sample sets will be required to confirm the signal on 2p25 and to identify additional genetic risk factors increasing susceptibility for attempted suicide.
Genome-wide association studies (GWAS) in complex phenotypes, including psychiatric disorders, have yielded many replicated findings, yet individual markers account for only a small fraction of the inherited differences in risk. We tested the performance of polygenic models in discriminating between cases and healthy controls and among cases with distinct psychiatric diagnoses.
GWAS results in bipolar disorder (BD), major depressive disorder (MDD), schizophrenia (SZ), and Parkinson’s disease (PD) were used to assign weights to individual alleles, based on odds ratios. These weights were used to calculate allele scores for individual cases and controls in independent samples, summing across many single nucleotide polymorphisms (SNPs). How well allele scores discriminated between cases and controls and between cases with different disorders was tested by logistic regression.
Large sets of SNPs were needed to achieve even modest discrimination between cases and controls. The most informative SNPs were overlapping in BD, SZ, and MDD, with correlated effect sizes. Little or no overlap was seen between allele scores for psychiatric disorders and those for PD.
BD, SZ, and MDD all share a similar polygenic component, but the polygenic models tested lack discriminative accuracy and are unlikely to be useful for clinical diagnosis.
genome-wide association; polygenic model; allele burden; psychosis; prediction
The rapid development of next-generation sequencing (NGS) technology has led to renewed interest in the potential contribution of rarer forms of genetic variation to complex, non-Mendelian phenotypes, such as psychiatric illnesses. Although challenging, family-based studies offer some advantages, especially in communities with large families and a limited number of founders. Here we revisit family-based studies of mental illnesses in traditional Amish and Mennonite communities -- known collectively as the Plain people. We discuss the new opportunities for NGS in these populations, with a particular emphasis on investigating psychiatric disorders. We also address some of the challenges facing NGS-based studies of complex phenotypes in founder populations.
bipolar disorder; identity by descent; homozygosity; Mennonite; Anabaptist
While it is known that rare copy-number variants (CNVs) contribute to risk for some neuropsychiatric disorders, the role of CNVs in bipolar disorder is unclear. Here, we reasoned that a contribution of CNVs to mood disorders might be most evident for de novo mutations. We performed a genome-wide analysis of de novo CNVs in a cohort of 788 trios. Diagnoses of offspring included bipolar disorder (n = 185), schizophrenia (n= 177), and healthy controls (n= 426). Frequencies of de novo CNVs were significantly higher in bipolar disorder as compared with controls (OR= 4.8 [1.4,16.0], p= 0.009). De novo CNVs were particularly enriched among cases with an age at onset younger than 18 (OR= 6.3 [1.7,22.6], p= 0.006). We also confirmed a significant enrichment of de novo CNVs in schizophrenia (OR= 5.0 [1.5,16.8], p= 0.007). Our results suggest that rare spontaneous mutations are an important contributor to risk for bipolar disorder and other major neuropsychiatric diseases.
YWHAH is a positional and functional candidate gene for both schizophrenia and bipolar disorder (BP). This gene has been previously shown to be associated with both disorders, and the chromosome location (22q12.3) has been repeatedly implicated in linkage studies for these disorders. It codes for the η subtype of the 14-3-3 protein family, is expressed mainly in brain, and is involved in HPA axis regulation. We investigated the association of YWHAH with BP in a large sample, consisting of 1211 subjects from 318 nuclear families including 554 affected offspring. We tested for association with the standard BP phenotype as well as subtypes defined by psychotic and mood-incongruent features. We genotyped five tag SNPs and the (GCCTGCA)n polymorphic locus present in this gene. Using a family-based association test, we found that rs2246704 was associated with BP (OR 1.31, P = 0.03) and psychotic BP (OR = 1.66, P = 0.002). The polymorphic repeat and two other SNPs were also modestly associated with psychotic BP. We have provided additional evidence for association of variants in YWHAH with major mental illness. Additional association analyses of larger sample sets will be required to clarify the role of YWHAH in schizophrenia and BP. The use of clinical sub-phenotypes such as psychotic features or other potential schizophrenia/BP overlap variables including cognitive abnormalities and poor functioning might shed further light on the potential subtypes of illness most closely associated with genetic variation in YWHAH.
Nine cancer patients were treated with adoptive cell therapy using autologous anti-MAGE-A3 TCR engineered T cells. Five patients experienced clinical regression of their cancers including two on-going responders. Beginning 1–2 days post-infusion, three patients (#’s 5, 7, and 8) experienced mental status changes, and two patients (5 and 8) lapsed into comas and subsequently died. Magnetic resonance imagining analysis of patients 5 and 8 demonstrated periventricular leukomalacia, and examination of their brains at autopsy revealed necrotizing leukoencephalopathy with extensive white matter defects associated with infiltration of CD3+/CD8+ T cells. Patient 7, developed Parkinson-like symptoms, which resolved over 4 weeks and fully recovered. Immunohistochemical staining of patient and normal brain samples demonstrated rare positively staining neurons with an antibody that recognizes multiple MAGE-A family members. The TCR used in this study recognized epitopes in MAGE-A3/A9/A12. Molecular assays of human brain samples using Q-RT-PCR, Nano string quantitation, and deep-sequencing indicated that MAGE -A12 was expressed in human brain (and possibly MAGE-A1, MAGE-A8, and MAGE-A9). This previously unrecognized expression of MAGE-A12 in human brain was possibly the initiating event of a TCR-mediated inflammatory response that resulted in neuronal cell destruction and raises caution for clinical applications targeting MAGE-A family members with highly active immunotherapies.
Cancer Testes Antigen; Immunotherapy; TCR; Gene Therapy
The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA’s first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
Genetics; MRI; GWAS; Consortium; Meta-analysis; Multi-site
Second-generation radioligands for translocator protein (TSPO), an inflammation marker, are confounded by the codominant rs6971 polymorphism that affects binding affinity. The resulting three groups are homozygous for high-affinity state (HH), homozygous for low-affinity state (LL), or heterozygous (HL). We tested if in vitro binding to leukocytes distinguished TSPO genotypes and if genotype could affect clinical studies using the TSPO radioligand [11C]PBR28. In vitro binding to leukocytes and [11C]PBR28 brain imaging were performed in 27 human subjects with known TSPO genotype. Specific [3H]PBR28 binding was measured in prefrontal cortex of 45 schizophrenia patients and 47 controls. Leukocyte binding to PBR28 predicted genotype in all subjects. Brain uptake was ∼40% higher in HH than HL subjects. Specific [3H]PBR28 binding in LL controls was negligible, while HH controls had ∼80% higher binding than HL controls. After excluding LL subjects, specific binding was 16% greater in schizophrenia patients than controls. This difference was insignificant by itself (P=0.085), but was significant after correcting for TSPO genotype (P=0.011). Our results show that TSPO genotype influences PBR28 binding in vitro and in vivo. Correcting for this genotype increased statistical power in our postmortem study and is recommended for in vivo positron emission tomography studies.
neuroinflammation; PBR28; schizophrenia; translocator protein
In a previous study we showed that genetic variation in HTR2A, which encodes the serotonin 2A receptor, influenced outcome of citalopram treatment in patients with major depressive disorder (MDD). Since chronic administration of citalopram, which selectively and potently inhibits the serotonin transporter (5-HTT), putatively enhances serotonergic transmission, it is conceivable that genetic variation within HTR2A also influences pretreatment 5-HTT function or serotonergic transmission. The present study used positron emission tomography (PET) and the selective 5-HTT ligand, [11C]DASB, to investigate whether the HTR2A marker alleles that predict treatment outcome also predict differences in 5-HTT binding.
Brain levels of 5-HTT were assessed in vivo using PET measures of the nondisplaceable component of the [11C]DASB binding potential (BPND). DNA from 43 patients and healthy volunteers, all unmedicated, was genotyped with 14 single nucleotide polymorphisms (SNPs) located within or around HTR2A. Allelic association with BPND was assessed in 8 brain regions, with covariates to control for race and ethnicity.
We detected allelic association between [11C]DASB BPND in thalamus and 3 markers in a region spanning the 3′ untranslated region and second intron of HTR2A (rs7333412, p=0.000045; rs7997012, p= 0.000086; rs977003, p=0.000069). The association signal at rs7333412 remained significant (p<0.05) after applying corrections for multiple testing via permutation.
Genetic variation in HTR2A that previously was associated with citalopram treatment outcome also was associated with thalamic 5-HTT binding. While further work is needed to identify the actual functional genetic variants involved, these results suggest that a relationship exists between genetic variation in HTR2A and either 5-HTT expression or central serotonergic transmission that influences the therapeutic response to 5-HTT inhibition in major depression.
Genetic Association; Positron Emission Tomography; Serotonin Transporter; [11C]DASB; HTR2A
Family and twin studies suggest that liability for suicide attempts is heritable and distinct from mood disorder susceptibility. The authors therefore examined the association between common genomewide variation and lifetime suicide attempts.
The authors analyzed data on lifetime suicide attempts from genomewide association studies of bipolar I and II disorder as well as major depressive disorder. Bipolar disorder subjects were drawn from the Systematic Treatment Enhancement Program for Bipolar Disorder cohort, the Wellcome Trust Case Control Consortium bipolar cohort, and the University College London cohort. Replication was pursued in the NIMH Genetic Association Information Network bipolar disorder project and a German clinical cohort. Depression subjects were drawn from the Sequential Treatment Alternatives to Relieve Depression cohort, with replication in the Netherlands Study of Depression and Anxiety/Netherlands Twin Register depression cohort.
Strongest evidence of association for suicide attempt in bipolar disorder was observed in a region without identified genes (rs1466846); five loci also showed suggestive evidence of association. In major depression, strongest evidence of association was observed for a single nucleotide polymorphism in ABI3BP, with six loci also showing suggestive association. Replication cohorts did not provide further support for these loci. However, meta-analysis incorporating approximately 8,700 mood disorder subjects identified four additional regions that met the threshold for suggestive association, including the locus containing the gene coding for protein kinase C-epsilon, previously implicated in models of mood and anxiety.
The results suggest that inherited risk for suicide among mood disorder patients is unlikely to be the result of individual common variants of large effect. They nonetheless provide suggestive evidence for multiple loci, which merit further investigation.
Several lines of evidence support an important genetic contribution to the wide individual variation in therapeutic response to antidepressant medications. The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study provided the largest cohort assembled to date of DNA from patients with nonpsychotic major depressive disorder, uniformly treated with citalopram and followed prospectively for up to 12 weeks. This pivotal study changed the face of pharmacogenetics research by increasing the sample size by an order of magnitude as well as by providing detailed prospective information about antidepressant response and tolerability. Several groups have identified markers in genes and tested the replication of previous findings of genes associated with outcome and side effects of antidepressant treatment. Variants in HTR2A, GRIK4, and KCNK2 were associated with citalopram treatment outcome. Replication was achieved in markers in the FKBP5 gene. Other findings in PDE11A and BDNF were not successfully replicated, and reports of potential confounders in previous associations with serotonin transporter variation (SLC6A4) were identified. Polymorphisms in pharmacokinetic genes involved in metabolism and transmembrane transport were also not associated with antidepressant response. Adverse events were also tested. Treatment-emergent suicidal ideation was associated with GRIK2, GRIA3, PAPLN, IL28RA, and CREB1. Sexual dysfunction was linked with variation in GRIN3A, GRIA1 GRIA3, and GRIK2. Reported and future findings of pharmacogenetics studies in STAR*D could help elucidate pathways involved in major depression and those pertinent to antidepressant outcome and side effects. Replication of these findings in independent samples could lead to the development of new treatments and to optimization of available treatments.
The assessment of response to lithium maintenance treatment in bipolar disorder (BD) is complicated by variable length of treatment, unpredictable clinical course, and often inconsistent compliance. Prospective and retrospective methods of assessment of lithium response have been proposed in the literature. In this study we report the key phenotypic measures of the “Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder” scale currently used in the Consortium on Lithium Genetics (ConLiGen) study.
Materials and Methods
Twenty-nine ConLiGen sites took part in a two-stage case-vignette rating procedure to examine inter-rater agreement [Kappa (κ)] and reliability [intra-class correlation coefficient (ICC)] of lithium response. Annotated first-round vignettes and rating guidelines were circulated to expert research clinicians for training purposes between the two stages. Further, we analyzed the distributional properties of the treatment response scores available for 1,308 patients using mixture modeling.
Substantial and moderate agreement was shown across sites in the first and second sets of vignettes (κ = 0.66 and κ = 0.54, respectively), without significant improvement from training. However, definition of response using the A score as a quantitative trait and selecting cases with B criteria of 4 or less showed an improvement between the two stages (ICC1 = 0.71 and ICC2 = 0.75, respectively). Mixture modeling of score distribution indicated three subpopulations (full responders, partial responders, non responders).
We identified two definitions of lithium response, one dichotomous and the other continuous, with moderate to substantial inter-rater agreement and reliability. Accurate phenotypic measurement of lithium response is crucial for the ongoing ConLiGen pharmacogenomic study.