Vascular Pathology and Trajectories of Late-Life Major Depressive Disorder in Secondary Psychiatric Care

OBJECTIVE

To examine 5-year trajectories of psychiatrist-treated late-life major depressive disorder (MDD), and evaluate whether previous vascular pathology is associated with more severe trajectories of late-life MDD.

METHODS

Data were obtained from nationally representative civil, psychiatric, hospital, and prescription registers in Denmark. The sample included 11,092 older adults (≥60 years) who received their first diagnosis of MDD in a psychiatric facility in Denmark between 2000 and 2007. Trajectories of inpatient or outpatient contact at psychiatric hospitals for MDD over the 5-year period following index MDD diagnosis were modeled using latent class growth analysis. Measures of vascular disease (stroke, heart disease, vascular dementia) and vascular risk factors (hypertension, diabetes) were defined based on medication prescriptions and hospital-based diagnoses. Other predictors included demographic characteristics and characteristics of the index MDD diagnosis.

RESULTS

The final model included 4 trajectories with consistently low (66% of the sample), high decreasing (19%), consistently high (9%), and moderate fluctuating (6%) probabilities of contact at a psychiatric hospital for MDD during the 5-year period following the index MDD diagnosis. We found no significant associations between any form of vascular pathology and trajectory class membership. Relative to the consistently low class, older age, greater severity and >12 months of prior antidepressant medication use predicted membership in the other three classes.

CONCLUSIONS

A notable proportion (34%) of individuals diagnosed with MDD in late-life require secondary psychiatric treatment for extended time periods. We did not find evidence that vascular pathology predicts hospital contact trajectories in secondary-treated late-life MDD.

Analysis of the Influence of microRNAs in Lithium Response in Bipolar Disorder

Bipolar disorder (BD) is a common, highly heritable neuropsychiatric disease characterized by recurrent episodes of mania and depression. Lithium is the best-established long-term treatment for BD, even though individual response is highly variable. Evidence suggests that some of this variability has a genetic basis. This is supported by the largest genome-wide association study (GWAS) of lithium response to date conducted by the International Consortium on Lithium Genetics (ConLiGen). Recently, we performed the first genome-wide analysis of the involvement of miRNAs in BD and identified nine BD-associated miRNAs. However, it is unknown whether these miRNAs are also associated with lithium response in BD. In the present study, we therefore tested whether common variants at these nine candidate miRNAs contribute to the variance in lithium response in BD. Furthermore, we systematically analyzed whether any other miRNA in the genome is implicated in the response to lithium. For this purpose, we performed gene-based tests for all known miRNA coding genes in the ConLiGen GWAS dataset (n = 2,563 patients) using a set-based testing approach adapted from the versatile gene-based test for GWAS (VEGAS2). In the candidate approach, miR-499a showed a nominally significant association with lithium response, providing some evidence for involvement in both development and treatment of BD. In the genome-wide miRNA analysis, 71 miRNAs showed nominally significant associations with the dichotomous phenotype and 106 with the continuous trait for treatment response. A total of 15 miRNAs revealed nominal significance in both phenotypes with miR-633 showing the strongest association with the continuous trait (p = 9.80E-04) and miR-607 with the dichotomous phenotype (p = 5.79E-04). No association between miRNAs and treatment response to lithium in BD in either of the tested conditions withstood multiple testing correction. Given the limited power of our study, the investigation of miRNAs in larger GWAS samples of BD and lithium response is warranted.

Association of Polygenic Score for Schizophrenia and HLA Antigen and Inflammation Genes With Response to Lithium in Bipolar Affective Disorder: A Genome-Wide Association Study

IMPORTANCE

Lithium is a first-line mood stabilizer for the treatment of bipolar affective disorder (BPAD). However, the efficacy of lithium varies widely, with a nonresponse rate of up to 30%. Biological response markers are lacking. Genetic factors are thought to mediate treatment response to lithium, and there is a previously reported genetic overlap between BPAD and schizophrenia (SCZ).

OBJECTIVES

To test whether a polygenic score for SCZ is associated with treatment response to lithium in BPAD and to explore the potential molecular underpinnings of this association.

DESIGN, SETTING, AND PARTICIPANTS

A total of 2586 patients with BPAD who had undergone lithium treatment were genotyped and assessed for long-term response to treatment between 2008 and 2013. Weighted SCZ polygenic scores were computed at different P value thresholds using summary statistics from an international multicenter genome-wide association study (GWAS) of 36 989 individuals with SCZ and genotype data from patients with BPAD from the Consortium on Lithium Genetics. For functional exploration, a cross-trait meta-GWAS and pathway analysis was performed, combining GWAS summary statistics on SCZ and response to treatment with lithium. Data analysis was performed from September 2016 to February 2017.

MAIN OUTCOMES AND MEASURES

Treatment response to lithium was defined on both the categorical and continuous scales using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. The effect measures include odds ratios and the proportion of variance explained.

RESULTS

Of the 2586 patients in the study (mean [SD] age, 47.2 [13.9] years), 1478 were women and 1108 were men. The polygenic score for SCZ was inversely associated with lithium treatment response in the categorical outcome, at a threshold P < 5 × 10-2. Patients with BPAD who had a low polygenic load for SCZ responded better to lithium, with odds ratios for lithium response ranging from 3.46 (95% CI, 1.42-8.41) at the first decile to 2.03 (95% CI, 0.86-4.81) at the ninth decile, compared with the patients in the 10th decile of SCZ risk. In the cross-trait meta-GWAS, 15 genetic loci that may have overlapping effects on lithium treatment response and susceptibility to SCZ were identified. Functional pathway and network analysis of these loci point to the HLA antigen complex and inflammatory cytokines.

CONCLUSIONS AND RELEVANCE

This study provides evidence for a negative association between high genetic loading for SCZ and poor response to lithium in patients with BPAD. These results suggest the potential for translational research aimed at personalized prescribing of lithium.

A precision medicine approach for psychiatric disease based on repeated symptom scores

For psychiatric diseases, rich information exists in the serial measurement of mental health symptom scores. We present a precision medicine framework for using the trajectories of multiple symptoms to make personalized predictions about future symptoms and related psychiatric events. Our approach fits a Bayesian hierarchical model that estimates a population-average trajectory for all symptoms and individual deviations from the average trajectory, then fits a second model that uses individual symptom trajectories to estimate the risk of experiencing an event. The fitted models are used to make clinically relevant predictions for new individuals. We demonstrate this approach on data from a study of antipsychotic therapy for schizophrenia, predicting future scores for positive, negative, and general symptoms, and the risk of treatment failure in 522 schizophrenic patients with observations over 8 weeks. While precision medicine has focused largely on genetic and molecular data, the complementary approach we present illustrates that innovative analytic methods for existing data can extend its reach more broadly. The systematic use of repeated measurements of psychiatric symptoms offers the promise of precision medicine in the field of mental health.

Assessment of Whole-Exome Sequence Data in Attempted Suicide within a Bipolar Disorder Cohort

Suicidal behavior is a complex and devastating phenotype with a heritable component that has not been fully explained by existing common genetic variant analyses. This study represents the first large-scale DNA sequencing project designed to assess the role of rare functional genetic variation in suicidal behavior risk. To accomplish this, whole-exome sequencing data for ∼19,000 genes were generated for 387 bipolar disorder subjects with a history of suicide attempt and 631 bipolar disorder subjects with no prior suicide attempts. Rare functional variants were assessed in all exome genes as well as pathways hypothesized to contribute to suicidal behavior risk. No result survived conservative Bonferroni correction, though many suggestive findings have arisen that merit additional attention. In addition, nominal support for past associations in genes, such as BDNF, and pathways, such as the hypothalamic-pituitary-adrenal axis, was also observed. Finally, a novel pathway was identified that is driven by aldehyde dehydrogenase genes. Ultimately, this investigation explores variation left largely untouched by existing efforts in suicidal behavior, providing a wealth of novel information to add to future investigations, such as meta-analyses.

A targeted sequencing study of glutamatergic candidate genes in suicide attempters with bipolar disorder

Suicidal behavior has been shown to have a heritable component that is partly driven by psychiatric disorders [Brent and Mann, 2005]. However, there is also an independent factor contributing to the heritability of suicidal behavior. We previously conducted a genome-wide association study (GWAS) of bipolar suicide attempters and bipolar non-attempters to assess this independent factor [Willour et al., 2012]. This GWAS implicated glutamatergic neurotransmission in attempted suicide. In the current study, we have conducted a targeted next-generation sequencing study of the glutamatergic N-methyl-D-aspartate (NMDA) receptor, neurexin, and neuroligin gene families in 476 bipolar suicide attempters and 473 bipolar non-attempters. The goal of this study was to gather sequence information from coding and regulatory regions of these glutamatergic genes to identify variants associated with attempted suicide. We identified 186 coding variants and 4,298 regulatory variants predicted to be functional in these genes. No individual variants were overrepresented in cases or controls to a degree that was statistically significant after correction for multiple testing. Additionally, none of the gene-level results were statistically significant following correction. While this study provides no direct support for a role of the examined glutamatergic candidate genes, further sequencing in expanded gene sets and datasets will be required to ultimately determine whether genetic variation in glutamatergic signaling influences suicidal behavior. © 2016 Wiley Periodicals, Inc.

Whole-gene sequencing investigation of SAT1 in attempted suicide

Suicidal behavior imposes a tremendous cost, with current US estimates reporting approximately 1.3 million suicide attempts and more than 40,000 suicide deaths each year. Several recent research efforts have identified an association between suicidal behavior and the expression level of the spermidine/spermine N1-acetyltransferase 1 (SAT1) gene. To date, several SAT1 genetic variants have been inconsistently associated with altered gene expression and/or directly with suicidal behavior. To clarify the role SAT1 genetic variation plays in suicidal behavior risk, we present a whole-gene sequencing effort of SAT1 in 476 bipolar disorder subjects with a history of suicide attempt and 473 subjects with bipolar disorder but no suicide attempts. Agilent SureSelect target enrichment was used to sequence all exons, introns, promoter regions, and putative regulatory regions identified from the ENCODE project within 10 kb of SAT1. Individual variant, haplotype, and collapsing variant tests were performed. Our results identified no variant or assessed region of SAT1 that showed a significant association with attempted suicide, nor did any assessment show evidence for replication of previously reported associations. Overall, no evidence for SAT1 sequence variation contributing to the risk for attempted suicide could be identified. It is possible that past associations of SAT1 expression with suicidal behavior arise from variation not captured in this study, or that causal variants in the region are too rare to be detected within our sample. Larger sample sizes and broader sequencing efforts will likely be required to identify the source of SAT1 expression level associations with suicidal behavior. © 2016 Wiley Periodicals, Inc.

Polygenic Risk of Schizophrenia and Cognition in a Population-Based Survey of Older Adults

Cognitive impairment is a common feature of the major psychotic disorders, with deficits often present in at risk individuals and unaffected first-degree relatives. Previous studies have suggested that polygenic risk scores (PRS) for schizophrenia (SCZ) are associated with cognitive deficits, but there has been little examination of this association in longitudinal datasets, or comparison with other disorders. We used mixed models to study the association between PRS for 4 adult onset psychiatric disorders with cross-sectional cognitive performance and longitudinal cognitive decline in 8616 older adults from the Health and Retirement Study (HRS), followed for an average of 10 years. PRS were computed for SCZ, bipolar disorder (BD), Major Depressive Disorder (MDD), and Alzheimer's disease (ALZ). SCZ PRS associated with decreased cognitive function (z = -3.00, P = .001, ΔR (2) = 0.04%), which was largely driven by an association with impaired attention and orientation (z = -3.33, P = 4.3×10(-4), ΔR (2) = 0.08%). We found no effect of BD or MDD PRS on cognition, in contrast to a robust effect of the APOE4/TOMM40 locus (z = -5.05, P = 2.2×10(-7), ΔR (2) = 0.36%), which was primarily associated with impaired verbal memory (z = -5.15, P = 1.3×10(-7), ΔR (2) = 0.21%). APOE4/TOMM40 locus and the ALZ PRS, but not the PRS for SCZ, were associated with greater cognitive decline. In summary, using a large, representative sample of older adults, we found evidence for different degrees of association between polygenic risk for SCZ and genetic risk factors for ALZ on cognitive function and decline, highlighting potential differences in the pathophysiology of cognitive deficits seen in SCZ and ALZ.

Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder

Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behaviour. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ∼2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, P =  5.87 × 10 ^{-  9}; odds ratio (OR) = 1.12) and markers within ERBB2 (rs2517959, P =  4.53 × 10 ^{-  9}; OR = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.

Exome Sequencing of Familial Bipolar Disorder

IMPORTANCE

Complex disorders, such as bipolar disorder (BD), likely result from the influence of both common and rare susceptibility alleles. While common variation has been widely studied, rare variant discovery has only recently become feasible with next-generation sequencing.

OBJECTIVE

To utilize a combined family-based and case-control approach to exome sequencing in BD using multiplex families as an initial discovery strategy, followed by association testing in a large case-control meta-analysis.

DESIGN, SETTING, AND PARTICIPANTS

We performed exome sequencing of 36 affected members with BD from 8 multiplex families and tested rare, segregating variants in 3 independent case-control samples consisting of 3541 BD cases and 4774 controls.

MAIN OUTCOMES AND MEASURES

We used penalized logistic regression and 1-sided gene-burden analyses to test for association of rare, segregating damaging variants with BD. Permutation-based analyses were performed to test for overall enrichment with previously identified gene sets.

RESULTS

We found 84 rare (frequency <1%), segregating variants that were bioinformatically predicted to be damaging. These variants were found in 82 genes that were enriched for gene sets previously identified in de novo studies of autism (19 observed vs. 10.9 expected, P = .0066) and schizophrenia (11 observed vs. 5.1 expected, P = .0062) and for targets of the fragile X mental retardation protein (FMRP) pathway (10 observed vs. 4.4 expected, P = .0076). The case-control meta-analyses yielded 19 genes that were nominally associated with BD based either on individual variants or a gene-burden approach. Although no gene was individually significant after correction for multiple testing, this group of genes continued to show evidence for significant enrichment of de novo autism genes (6 observed vs 2.6 expected, P = .028).

CONCLUSIONS AND RELEVANCE

Our results are consistent with the presence of prominent locus and allelic heterogeneity in BD and suggest that very large samples will be required to definitively identify individual rare variants or genes conferring risk for this disorder. However, we also identify significant associations with gene sets composed of previously discovered de novo variants in autism and schizophrenia, as well as targets of the FRMP pathway, providing preliminary support for the overlap of potential autism and schizophrenia risk genes with rare, segregating variants in families with BD.

The Pharmacogenomics of Bipolar Disorder study (PGBD): identification of genes for lithium response in a prospective sample

BACKGROUND

Bipolar disorder is a serious and common psychiatric disorder characterized by manic and depressive mood switches and a relapsing and remitting course. The cornerstone of clinical management is stabilization and prophylaxis using mood-stabilizing medications to reduce both manic and depressive symptoms. Lithium remains the gold standard of treatment with the strongest data for both efficacy and suicide prevention. However, many patients do not respond to this medication, and clinically there is a great need for tools to aid the clinician in selecting the correct treatment. Large genome wide association studies (GWAS) investigating retrospectively the effect of lithium response are in the pipeline; however, few large prospective studies on genetic predictors to of lithium response have yet been conducted. The purpose of this project is to identify genes that are associated with lithium response in a large prospective cohort of bipolar patients and to better understand the mechanism of action of lithium and the variation in the genome that influences clinical response.

METHODS/DESIGN

This study is an 11-site prospective non-randomized open trial of lithium designed to ascertain a cohort of 700 subjects with bipolar I disorder who experience protocol-defined relapse prevention as a result of treatment with lithium monotherapy. All patients will be diagnosed using the Diagnostic Interview for Genetic Studies (DIGS) and will then enter a 2-year follow-up period on lithium monotherapy if and when they exhibit a score of 1 (normal, not ill), 2 (minimally ill) or 3 (mildly ill) on the Clinical Global Impressions of Severity Scale for Bipolar Disorder (CGI-S-BP Overall Bipolar Illness) for 4 of the 5 preceding weeks. Lithium will be titrated as clinically appropriate, not to exceed serum levels of 1.2 mEq/L. The sample will be evaluated longitudinally using a wide range of clinical scales, cognitive assessments and laboratory tests. On relapse, patients will be discontinued or crossed-over to treatment with valproic acid (VPA) or treatment as usual (TAU). Relapse is defined as a DSM-IV manic, major depressive or mixed episode or if the treating physician decides a change in medication is clinically necessary. The sample will be genotyped for GWAS. The outcome for lithium response will be analyzed as a time to event, where the event is defined as clinical relapse, using a Cox Proportional Hazards model. Positive single nucleotide polymorphisms (SNPs) from past genetic retrospective studies of lithium response, the Consortium on Lithium Genetics (ConLiGen), will be tested in this prospective study sample; a meta-analysis of these samples will then be performed. Finally, neurons will be derived from pluripotent stem cells from lithium responders and non-responders and tested in vivo for response to lithium by gene expression studies. SNPs in genes identified in these cellular studies will also be tested for association to response.

DISCUSSION

Lithium is an extraordinarily important therapeutic drug in the clinical management of patients suffering from bipolar disorder. However, a significant proportion of patients, 30-40 %, fail to respond, and there is currently no method to identify the good lithium responders before initiation of treatment. Converging evidence suggests that genetic factors play a strong role in the variation of response to lithium, but only a few genes have been tested and the samples have largely been retrospective or quite small. The current study will collect an entirely unique sample of 700 patients with bipolar disorder to be stabilized on lithium monotherapy and followed for up to 2 years. This study will produce useful information to improve the understanding of the mechanism of action of lithium and will add to the development of a method to predict individual response to lithium, thereby accelerating recovery and reducing suffering and cost.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01272531 Registered: January 6, 2011.

High-throughput sequencing of the synaptome in major depressive disorder

Major depressive disorder (MDD) is among the leading causes of worldwide disability. Despite its significant heritability, large-scale genome-wide association studies (GWASs) of MDD have yet to identify robustly associated common variants. Although increased sample sizes are being amassed for the next wave of GWAS, few studies have as yet focused on rare genetic variants in the study of MDD. We sequenced the exons of 1742 synaptic genes previously identified by proteomic experiments. PLINK/SEQ was used to perform single variant, gene burden and gene set analyses. The GeneMANIA interaction database was used to identify protein-protein interaction-based networks. Cases were selected from a familial collection of early-onset, recurrent depression and were compared with screened controls. After extensive quality control, we analyzed 259 cases with familial, early-onset MDD and 334 controls. The distribution of association test statistics for the single variant and gene burden analyses were consistent with the null hypothesis. However, analysis of prioritized gene sets showed a significant association with damaging singleton variants in a Cav2-adaptor gene set (odds ratio=2.6; P=0.0008) that survived correction for all gene sets and annotation categories tested (empirical P=0.049). In addition, we also found statistically significant evidence for an enrichment of rare variants in a protein-based network of 14 genes involved in actin polymerization and dendritic spine formation (nominal P=0.0031). In conclusion, we have identified a statistically significant gene set and gene network of rare variants that are over-represented in MDD, providing initial evidence that calcium signaling and dendrite regulation may be involved in the etiology of depression.

Heterogeneity in 10-Year Course Trajectories of Moderate to Severe Major Depressive Disorder: A Danish National Register-Based Study

IMPORTANCE

Evidence suggests that long-term trajectories of major depressive disorder (MDD) are heterogeneous. The Danish Psychiatric Central Research Register (DPCRR) provides a rare opportunity to examine patterns and correlates of long-term trajectories in a large sample of patients with moderate to severe MDD.

OBJECTIVE

To characterize patterns and correlates of 10-year course trajectories of MDD in the DPCRR.

DESIGN, SETTING, AND PARTICIPANTS

A cohort containing 11 640 individuals born in Denmark in 1955 or later with their first recorded MDD diagnosis in the DPCRR between 1995 and 2002 was established. Patients were followed for 10 years from the date of their initial MDD diagnosis. Data were obtained from Danish civil and psychiatric national registers in June 2013 and were analyzed from April 4, 2014, to December 17, 2015. Correlates of trajectory class membership were sex, characteristics of the first recorded MDD episode (ie, age, severity, inpatient treatment, and record of suicide attempt or self-harm), and psychiatric diagnoses in parents (ie, depression, bipolar disorder, schizophrenia-spectrum disorders, substance abuse, and anxiety or somatoform disorders).

MAIN OUTCOMES AND MEASURES

The outcome variable was past-year contact at a psychiatric hospital with a main diagnosis of MDD during each of the 10 years following the initial MDD diagnosis. Trajectories were modeled using latent class growth analysis.

RESULTS

The sample included 11 640 individuals (7493 [64.4%] women) aged 18 to 48 years (mean [SD], 31.4 [7.3]) at their first recorded MDD diagnosis. Four trajectory classes were identified: brief contact (77.0%) (characterized by low probability of contact after 2 years); prolonged initial contact (12.8%) (characterized by high decreasing probability of contact during the first 5 years); later reentry (7.1%) (characterized by moderate probability of contact during the second 5 years); and persistent contact (3.1%) (characterized by high or moderate probability of contact throughout). Female sex (odds ratio [OR] range, 1.82-2.22), inpatient treatment (OR range, 1.40-1.50), and severity at first recorded MDD episode (OR range: moderate, 1.61-1.84; severe, 1.93-2.23; and psychotic, 2.73-3.07) were associated with more severe trajectories. Parental anxiety (OR, 1.34 [95% CI, 1.10-1.63]) and depression (OR, 1.63 [95% CI, 1.28-2.09]) were associated with the prolonged initial contact and later reentry classes, respectively. Parental schizophrenia was associated with the persistent contact class (OR range, 2.55-3.04).

CONCLUSIONS AND RELEVANCE

Most people treated for moderate to severe MDD in Danish psychiatric hospitals do not receive additional MDD treatment after 2 years; however, a minority receive specialty treatment for up to a decade. Observable heterogeneity in the course may be indicative of underlying etiologic differences.

Genetic variants associated with response to lithium treatment in bipolar disorder: a genome-wide association study

BACKGROUND

Lithium is a first-line treatment in bipolar disorder, but individual response is variable. Previous studies have suggested that lithium response is a heritable trait. However, no genetic markers of treatment response have been reproducibly identified.

METHODS

Here, we report the results of a genome-wide association study of lithium response in 2563 patients collected by 22 participating sites from the International Consortium on Lithium Genetics (ConLiGen). Data from common single nucleotide polymorphisms (SNPs) were tested for association with categorical and continuous ratings of lithium response. Lithium response was measured using a well established scale (Alda scale). Genotyped SNPs were used to generate data at more than 6 million sites, using standard genomic imputation methods. Traits were regressed against genotype dosage. Results were combined across two batches by meta-analysis.

FINDINGS

A single locus of four linked SNPs on chromosome 21 met genome-wide significance criteria for association with lithium response (rs79663003, p=1·37 × 10(-8); rs78015114, p=1·31 × 10(-8); rs74795342, p=3·31 × 10(-9); and rs75222709, p=3·50 × 10(-9)). In an independent, prospective study of 73 patients treated with lithium monotherapy for a period of up to 2 years, carriers of the response-associated alleles had a significantly lower rate of relapse than carriers of the alternate alleles (p=0·03268, hazard ratio 3·8, 95% CI 1·1-13·0).

INTERPRETATION

The response-associated region contains two genes for long, non-coding RNAs (lncRNAs), AL157359.3 and AL157359.4. LncRNAs are increasingly appreciated as important regulators of gene expression, particularly in the CNS. Confirmed biomarkers of lithium response would constitute an important step forward in the clinical management of bipolar disorder. Further studies are needed to establish the biological context and potential clinical utility of these findings.

FUNDING

Deutsche Forschungsgemeinschaft, National Institute of Mental Health Intramural Research Program.

Heterogeneity in long-term trajectories of depressive symptoms: Patterns, predictors and outcomes

BACKGROUND

Evidence suggests that long-term trajectories of depressive symptoms vary greatly throughout the population, with some individuals experiencing few or no symptoms, some experiencing transient symptoms and others experiencing chronic depression. The goal of this paper is to review studies that examined heterogeneity in long-term trajectories of depressive symptoms and summarize the current knowledge regarding (a) the number and patterns of trajectories and (b) antecedents and outcomes associated with different trajectory patterns.

METHODS

We conducted a systematic review of literature in the Medline and PsychINFO databases. Articles were included if they (a) modeled trajectories of depressive symptoms, (b) used a group-based trajectory modeling approach, (c) followed participants for 5+ years and (d) had a sample size of at least 200.

RESULTS

We identified 25 studies from 24 separate cohorts. Most of the studies identified either 3 or 4 distinct trajectory classes. Trajectories varied in terms of severity (low, medium, high) and stability (stable, increasing, decreasing). In most studies, the majority of participants had consistently few or no depressive symptoms, but a notable minority (usually <10%) reported persistent symptoms. Predictors of trajectories with greater symptom burden included female gender, lower income/education and non-white race. Other predictors were specific to different populations (e.g. mothers, older adults). High symptom burden trajectories were associated with poor psychiatric and social outcomes.

LIMITATIONS

Comparisons between studies were qualitative.

CONCLUSIONS

Trajectories of depression symptoms in the general population are heterogeneous, with most individuals showing minimal symptoms but a notable minority experiencing chronic high symptom burden.

Whole Genome Sequencing Defines the Genetic Heterogeneity of Familial Pancreatic Cancer

Pancreatic cancer is projected to become the second leading cause of cancer-related death in the United States by 2020. A familial aggregation of pancreatic cancer has been established, but the cause of this aggregation in most families is unknown. To determine the genetic basis of susceptibility in these families, we sequenced the germline genomes of 638 patients with familial pancreatic cancer and the tumor exomes of 39 familial pancreatic adenocarcinomas. Our analyses support the role of previously identified familial pancreatic cancer susceptibility genes such as BRCA2, CDKN2A, and ATM, and identify novel candidate genes harboring rare, deleterious germline variants for further characterization. We also show how somatic point mutations that occur during hematopoiesis can affect the interpretation of genome-wide studies of hereditary traits. Our observations have important implications for the etiology of pancreatic cancer and for the identification of susceptibility genes in other common cancer types.

SIGNIFICANCE

The genetic basis of disease susceptibility in the majority of patients with familial pancreatic cancer is unknown. We whole genome sequenced 638 patients with familial pancreatic cancer and demonstrate that the genetic underpinning of inherited pancreatic cancer is highly heterogeneous. This has significant implications for the management of patients with familial pancreatic cancer.

Differential responses to lithium in hyperexcitable neurons from patients with bipolar disorder

Bipolar disorder is a complex neuropsychiatric disorder that is characterized by intermittent episodes of mania and depression; without treatment, 15% of patients commit suicide. Hence, it has been ranked by the World Health Organization as a top disorder of morbidity and lost productivity. Previous neuropathological studies have revealed a series of alterations in the brains of patients with bipolar disorder or animal models, such as reduced glial cell number in the prefrontal cortex of patients, upregulated activities of the protein kinase A and C pathways and changes in neurotransmission. However, the roles and causation of these changes in bipolar disorder have been too complex to exactly determine the pathology of the disease. Furthermore, although some patients show remarkable improvement with lithium treatment for yet unknown reasons, others are refractory to lithium treatment. Therefore, developing an accurate and powerful biological model for bipolar disorder has been a challenge. The introduction of induced pluripotent stem-cell (iPSC) technology has provided a new approach. Here we have developed an iPSC model for human bipolar disorder and investigated the cellular phenotypes of hippocampal dentate gyrus-like neurons derived from iPSCs of patients with bipolar disorder. Guided by RNA sequencing expression profiling, we have detected mitochondrial abnormalities in young neurons from patients with bipolar disorder by using mitochondrial assays; in addition, using both patch-clamp recording and somatic Ca(2+) imaging, we have observed hyperactive action-potential firing. This hyperexcitability phenotype of young neurons in bipolar disorder was selectively reversed by lithium treatment only in neurons derived from patients who also responded to lithium treatment. Therefore, hyperexcitability is one early endophenotype of bipolar disorder, and our model of iPSCs in this disease might be useful in developing new therapies and drugs aimed at its clinical treatment.

Parental history of psychiatric diagnoses and unipolar depression: a Danish National Register-based cohort study

BACKGROUND

Depression is known to run in families, but the effects of parental history of other psychiatric diagnoses on depression rates are less well studied. Few studies have examined the impact of parental psychopathology on depression rates in older age groups.

METHOD

We established a population-based cohort including all individuals born in Denmark after 1954 and alive on their 10th birthday (N = 29 76 264). Exposure variables were maternal and paternal history of schizophrenia, bipolar disorder, depression, anxiety or 'other' psychiatric diagnoses. Incidence rate ratios (IRRs) were estimated using Poisson regressions.

RESULTS

Parental history of any psychiatric diagnosis increased incidence rates of outpatient (maternal: IRR 1.88, p < 0.0001; paternal: IRR 1.68, p < 0.0001) and inpatient (maternal: IRR 1.99, p < 0.0001; paternal: IRR 1.83, p < 0.0001) depression relative to no parental history. IRRs for parental history of non-affective disorders remained relatively stable across age groups, while IRRs for parental affective disorders (unipolar or bipolar) decreased with age from 2.29-3.96 in the youngest age group to 1.53-1.90 in the oldest group. IRR estimates for all parental diagnoses were similar among individuals aged ⩾41 years (IRR range 1.51-1.90).

CONCLUSIONS

Parental history of any psychiatric diagnosis is associated with increased incidence rates of unipolar depression. In younger age groups, parental history of affective diagnoses is more strongly associated with rates of unipolar depression than non-affective diagnoses; however, this distinction disappears after age 40, suggesting that parental psychopathology in general, rather than any one disorder, confers risk for depression in middle life.

Enhanced conversion of induced neuronal cells (iN cells) from human fibroblasts: Utility in uncovering cellular deficits in mental illness-associated chromosomal abnormalities

The novel technology of induced neuronal cells (iN cells) is promising for translational neuroscience, as it allows the conversion of human fibroblasts into cells with postmitotic neuronal traits. However, a major technical barrier is the low conversion rate. To overcome this problem, we optimized the conversion media. Using our improved formulation, we studied how major mental illness-associated chromosomal abnormalities may impact the characteristics of iN cells. We demonstrated that our new iN cell culture protocol enabled us to obtain more precise measurement of neuronal cellular phenotypes than previous iN cell methods. Thus, this iN cell culture provides a platform to efficiently obtain possible cellular phenotypes caused by genetic differences, which can be more thoroughly studied in research using other human cell models such as induced pluripotent stem cells.

Polygenic risk, stressful life events and depressive symptoms in older adults: a polygenic score analysis

BACKGROUND

Previous studies suggest that the relationship between genetic risk and depression may be moderated by stressful life events (SLEs). The goal of this study was to assess whether SLEs moderate the association between polygenic risk of major depressive disorder (MDD) and depressive symptoms in older adults.

METHOD

We used logistic and negative binomial regressions to assess the associations between polygenic risk, SLEs and depressive symptoms in a sample of 8761 participants from the Health and Retirement Study. Polygenic scores were derived from the Psychiatric Genomics Consortium genome-wide association study of MDD. SLEs were operationalized as a dichotomous variable indicating whether participants had experienced at least one stressful event during the previous 2 years. Depressive symptoms were measured using an eight-item Center for Epidemiologic Studies Depression Scale subscale and operationalized as both a dichotomous and a count variable.

RESULTS

The odds of reporting four or more depressive symptoms were over twice as high among individuals who experienced at least one SLE (odds ratio 2.19, 95% confidence interval 1.86-2.58). Polygenic scores were significantly associated with depressive symptoms (β = 0.21, p ⩽ 0.0001), although the variance explained was modest (pseudo r 2 = 0.0095). None of the interaction terms for polygenic scores and SLEs was statistically significant.

CONCLUSIONS

Polygenic risk and SLEs are robust, independent predictors of depressive symptoms in older adults. Consistent with an additive model, we found no evidence that SLEs moderated the association between common variant polygenic risk and depressive symptoms.

Whole-genome CNV analysis: advances in computational approaches

Accumulating evidence indicates that DNA copy number variation (CNV) is likely to make a significant contribution to human diversity and also play an important role in disease susceptibility. Recent advances in genome sequencing technologies have enabled the characterization of a variety of genomic features, including CNVs. This has led to the development of several bioinformatics approaches to detect CNVs from next-generation sequencing data. Here, we review recent advances in CNV detection from whole genome sequencing. We discuss the informatics approaches and current computational tools that have been developed as well as their strengths and limitations. This review will assist researchers and analysts in choosing the most suitable tools for CNV analysis as well as provide suggestions for new directions in future development.

Test-retest reliability of a new questionnaire for the retrospective assessment of long-term lithium use in bipolar disorder

BACKGROUND

The identification of predictors of treatment response holds tremendous potential for the improvement of clinical outcomes in bipolar disorder (BP). The goal of this project is to evaluate the test-retest reliability of a new clinical tool, the Lithium Questionnaire (LQ), for the retrospective assessment of long-term lithium use in research participants with BP.

METHODS

Twenty-nine individuals with BP-I (n=27), major depression (n=1), or schizoaffective disorder (n=1) were recruited for participation. The LQ was administered to all participants at two time-points, spaced 17 months apart on average, and used to determine each subject׳s score on the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder Scale, or the Alda Scale. Scores were confirmed through a best-estimate procedure, and test-retest reliability (intra-class correlation coefficient [ICC]) of the LQ was calculated.

RESULTS

The correlation between the total Alda Scale scores at the two time-points was in the moderate range (ICC=0.60). Relevant clinical factors such as age or presence of Axis I psychiatric comorbidity did not influence the reliability.

LIMITATIONS

The validity of the LQ was not examined. Inclusion of two participants with non-BP diagnoses may have affected the LQ׳s reliability, but re-analysis of our data after exclusion of these participants did not influence the reliability. The absence of measures of mood and cognition at time of LQ may be a limitation of this work.

CONCLUSIONS

The LQ holds promise for the standardization of the retrospective assessment of long-term treatment in BP.

Use of diuretics is associated with reduced risk of Alzheimer's disease: the Cache County Study

Although the use of antihypertensive medications has been associated with reduced risk of Alzheimer's disease (AD), it remains unclear which class provides the most benefit. The Cache County Study of Memory Health and Aging is a prospective longitudinal cohort study of dementing illnesses among the elderly population of Cache County, Utah. Using waves I to IV data of the Cache County Study, 3417 participants had a mean of 7.1 years of follow-up. Time-varying use of antihypertensive medications including different class of diuretics, angiotensin converting enzyme inhibitors, β-blockers, and calcium channel blockers was used to predict the incidence of AD using Cox proportional hazards analyses. During follow-up, 325 AD cases were ascertained with a total of 23,590 person-years. Use of any antihypertensive medication was associated with lower incidence of AD (adjusted hazard ratio [aHR], 0.77; 95% confidence interval [CI], 0.61-0.97). Among different classes of antihypertensive medications, thiazide (aHR, 0.7; 95% CI, 0.53-0.93), and potassium-sparing diuretics (aHR, 0.69; 95% CI, 0.48-0.99) were associated with the greatest reduction of AD risk. Thiazide and potassium-sparing diuretics were associated with decreased risk of AD. The inverse association of potassium-sparing diuretics confirms an earlier finding in this cohort, now with longer follow-up, and merits further investigation.

The Cache County Study on Memory in Aging: factors affecting risk of Alzheimer's disease and its progression after onset

The Cache County Study on Memory in Aging is a longitudinal, population-based study of Alzheimer's disease (AD) and other dementias. Initiated in 1995 and extending to 2013, the study has followed over 5,000 elderly residents of Cache County, Utah (USA) for over twelve years. Achieving a 90% participation rate at enrolment, and spawning two ancillary projects, the study has contributed to the literature on genetic, psychosocial and environmental risk factors for AD, late-life cognitive decline, and the clinical progression of dementia after its onset. This paper describes the major study contributions to the literature on AD and dementia.

Systematic review of genome-wide gene expression studies of bipolar disorder

BACKGROUND

Numerous genome-wide gene expression studies of bipolar disorder (BP) have been carried out. These studies are heterogeneous, underpowered and use overlapping samples. We conducted a systematic review of these studies to synthesize the current findings.

METHODS

We identified all genome-wide gene expression studies on BP in humans. We then carried out a quantitative mega-analysis of studies done with post-mortem brain tissue. We obtained raw data from each study and used standardized procedures to process and analyze the data. We then combined the data and conducted three separate mega-analyses on samples from 1) any region of the brain (9 studies); 2) the prefrontal cortex (PFC) (6 studies); and 3) the hippocampus (2 studies). To minimize heterogeneity across studies, we focused primarily on the most numerous, recent and comprehensive studies.

RESULTS

A total of 30 genome-wide gene expression studies of BP done with blood or brain tissue were identified. We included 10 studies with data on 211 microarrays on 57 unique BP cases and 229 microarrays on 60 unique controls in the quantitative mega-analysis. A total of 382 genes were identified as significantly differentially expressed by the three analyses. Eleven genes survived correction for multiple testing with a q-value < 0.05 in the PFC. Among these were FKBP5 and WFS1, which have been previously implicated in mood disorders. Pathway analyses suggested a role for metallothionein proteins, MAP Kinase phosphotases, and neuropeptides.

CONCLUSION

We provided an up-to-date summary of results from gene expression studies of the brain in BP. Our analyses focused on the highest quality data available and provided results by brain region so that similarities and differences can be examined relative to disease status. The results are available for closer inspection on-line at Metamoodics [http://metamoodics.igm.jhmi.edu/], where investigators can look up any genes of interest and view the current results in their genomic context and in relation to leading findings from other genomic experiments in bipolar disorder.

Assessment of Response to Lithium Maintenance Treatment in Bipolar Disorder: A Consortium on Lithium Genetics (ConLiGen) Report

OBJECTIVE

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.

RESULTS

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).

CONCLUSIONS

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.

A review of potassium channels in bipolar disorder

Although bipolar disorder (BP) is one of the most heritable psychiatric conditions, susceptibility genes for the disorder have yet to be conclusively identified. It is likely that variants in multiple genes across multiple pathways contribute to the genotype–phenotype relationship in the affected population. Recent evidence from genome-wide association studies implicates an entire class of genes related to the structure and regulation of ion channels, suggesting that the etiology of BP may arise from channelopathies. In this review, we examine the evidence for this hypothesis, with a focus on the potential role of voltage-gated potassium channels. We consider evidence from genetic and expression studies, and discuss the potential underlying biology. We consider animal models and treatment implications of the involvement of potassium ion channelopathy in BP. Finally, we explore intriguing parallels between BP and epilepsy, the signature channelopathy of the central nervous system.

Converging Evidence for Epistasis between ANK3 and Potassium Channel Gene KCNQ2 in Bipolar Disorder

Genome-wide association studies (GWAS) have implicated ANK3 as a susceptibility gene for bipolar disorder (BP). We examined whether epistasis with ANK3 may contribute to the “missing heritability” in BP. We first identified via the STRING database 14 genes encoding proteins with prior biological evidence that they interact molecularly with ANK3. We then tested for statistical evidence of interactions between SNPs in these genes in association with BP in a discovery GWAS dataset and two replication GWAS datasets. The most significant interaction in the discovery GWAS was between SNPs in ANK3 and KCNQ2 (p = 3.18 × 10⁻⁸). A total of 31 pair-wise interactions involving combinations between two SNPs from KCNQ2 and 16 different SNPs in ANK3 were significant after permutation. Of these, 28 pair-wise interactions were significant in the first replication GWAS. None were significant in the second replication GWAS, but the two SNPs from KCNQ2 were found to significantly interact with five other SNPs in ANK3, suggesting possible allelic heterogeneity. KCNQ2 forms homo- and hetero-meric complexes with KCNQ3 that constitute voltage-gated potassium channels in neurons. ANK3 is an adaptor protein that, through its interaction with KCNQ2 and KCNQ3, directs the localization of this channel in the axon initial segment (AIS). At the AIS, the KCNQ2/3 complex gives rise to the M-current, which stabilizes the neuronal resting potential and inhibits repetitive firing of action potentials. Thus, these channels act as “dampening” components and prevent neuronal hyperactivity. The interactions between ANK3 and KCNQ2 merit further investigation, and if confirmed, may motivate a new line of research into a novel therapeutic target for BP.

Genetic association of FKBP5 and CRHR1 with cortisol response to acute psychosocial stress in healthy adults

RATIONALE

Chronic dysregulation of hypothalamus-pituitary-adrenal (HPA) axis activity is related to several neuropsychiatric disorders. Studies suggest that cortisol response to stress has a strong genetic etiology, and that FK506 binding protein 5 (FKBP5) and G-protein coupled type-I CRH receptor (CRHR1) are key proteins regulating response. Variations in the genes encoding these proteins, FKBP5 and CRHR1, have been associated with several neuropsychiatric disorders.

OBJECTIVES

We examined variation in these genes in relation to cortisol response to psychological stress in one of the largest Trier Social Stress Test (TSST) cohorts yet examined.

METHODS

A total of 368 healthy, young adults underwent the TSST. Salivary cortisol was measured at multiple time points before and after the stressor. Nine variants in FKBP5 and four in CRHR1 were assessed. Single marker analyses were conducted. Secondary analyses assessed haplotypes and interaction with stress-related variables.

RESULTS

The strongest association was for rs4713902 in FKBP5 with baseline cortisol (p dom = 0.0004). We also identified a male-specific effect of FKBP5 polymorphisms on peak response and response area under the curve (p = 0.0028 for rs3800374). In CRHR1, rs7209436, rs110402, and rs242924 were nominally associated with peak response (p rec = 0.0029-0.0047). We observed interactions between trait anxiety and rs7209436 and rs110402 in CRHR1 in association with baseline cortisol (p LRT = 0.0272 and p LRT = 0.0483, respectively).

CONCLUSIONS

We show association of variants in FKBP5 and CRHR1 with cortisol response to psychosocial stress. These variants were previously shown to be associated with neuropsychiatric disorders. These findings have implications for interindividual variation in HPA axis activity and potentially for the etiology of neuropsychiatric disorders.

SVAw - a web-based application tool for automated surrogate variable analysis of gene expression studies

BACKGROUND

Surrogate variable analysis (SVA) is a powerful method to identify, estimate, and utilize the components of gene expression heterogeneity due to unknown and/or unmeasured technical, genetic, environmental, or demographic factors. These sources of heterogeneity are common in gene expression studies, and failing to incorporate them into the analysis can obscure results. Using SVA increases the biological accuracy and reproducibility of gene expression studies by identifying these sources of heterogeneity and correctly accounting for them in the analysis.

RESULTS

Here we have developed a web application called SVAw (Surrogate variable analysis Web app) that provides a user friendly interface for SVA analyses of genome-wide expression studies. The software has been developed based on open source bioconductor SVA package. In our software, we have extended the SVA program functionality in three aspects: (i) the SVAw performs a fully automated and user friendly analysis workflow; (ii) It calculates probe/gene Statistics for both pre and post SVA analysis and provides a table of results for the regression of gene expression on the primary variable of interest before and after correcting for surrogate variables; and (iii) it generates a comprehensive report file, including graphical comparison of the outcome for the user.

CONCLUSIONS

SVAw is a web server freely accessible solution for the surrogate variant analysis of high-throughput datasets and facilitates removing all unwanted and unknown sources of variation. It is freely available for use at http://psychiatry.igm.jhmi.edu/sva. The executable packages for both web and standalone application and the instruction for installation can be downloaded from our web site.

Enrichment of cis-regulatory gene expression SNPs and methylation quantitative trait loci among bipolar disorder susceptibility variants

We conducted a systematic study of top susceptibility variants from a genome-wide association (GWA) study of bipolar disorder to gain insight into the functional consequences of genetic variation influencing disease risk. We report here the results of experiments to explore the effects of these susceptibility variants on DNA methylation and mRNA expression in human cerebellum samples. Among the top susceptibility variants, we identified an enrichment of cis regulatory loci on mRNA expression (eQTLs), and a significant excess of quantitative trait loci for DNA CpG methylation, hereafter referred to as methylation quantitative trait loci (mQTLs). Bipolar disorder susceptibility variants that cis regulate both cerebellar expression and methylation of the same gene are a very small proportion of bipolar disorder susceptibility variants. This finding suggests that mQTLs and eQTLs provide orthogonal ways of functionally annotating genetic variation within the context of studies of pathophysiology in brain. No lymphocyte mQTL enrichment was found, suggesting that mQTL enrichment was specific to the cerebellum, in contrast to eQTLs. Separately, we found that using mQTL information to restrict the number of single-nucleotide polymorphisms studied enhances our ability to detect a significant association. With this restriction a priori informed by the observed functional enrichment, we identified a significant association (rs12618769, P(bonferroni)<0.05) from two other GWA studies (TGen+GAIN; 2191 cases and 1434 controls) of bipolar disorder, which we replicated in an independent GWA study (WTCCC). Collectively, our findings highlight the importance of integrating functional annotation of genetic variants for gene expression and DNA methylation to advance the biological understanding of bipolar disorder.

A hybrid likelihood model for sequence-based disease association studies

In the past few years, case-control studies of common diseases have shifted their focus from single genes to whole exomes. New sequencing technologies now routinely detect hundreds of thousands of sequence variants in a single study, many of which are rare or even novel. The limitation of classical single-marker association analysis for rare variants has been a challenge in such studies. A new generation of statistical methods for case-control association studies has been developed to meet this challenge. A common approach to association analysis of rare variants is the burden-style collapsing methods to combine rare variant data within individuals across or within genes. Here, we propose a new hybrid likelihood model that combines a burden test with a test of the position distribution of variants. In extensive simulations and on empirical data from the Dallas Heart Study, the new model demonstrates consistently good power, in particular when applied to a gene set (e.g., multiple candidate genes with shared biological function or pathway), when rare variants cluster in key functional regions of a gene, and when protective variants are present. When applied to data from an ongoing sequencing study of bipolar disorder (191 cases, 107 controls), the model identifies seven gene sets with nominal p-values0.05, of which one MAPK signaling pathway (KEGG) reaches trend-level significance after correcting for multiple testing.

Inexpensive, high-throughput sequencing has transformed the field of case-control association studies. For the first time, it may be possible to identify the genetic underpinnings of complex diseases, by sequencing the DNA of hundreds (even thousands) of cases and controls and comparing patterns of DNA sequence variation. However, complex diseases are likely to be caused by many variants, some of which are very rare. Taken one at a time, the association between variant and disease phenotype may not be detectable by current statistical methods. One strategy is to identify regions where important variants occur by “collapsing” variants into groups. Here, we present a new collapsing approach, capable of detecting subtle genetic differences between cases and controls. We show, in extensive simulations and using a benchmark set of genes involved in human triglyceride levels, that the approach is potentially more powerful than existing methods. We apply the new method to an ongoing sequencing study of bipolar cases and controls and identify a set of genes found in neuronal synapses, which may be implicated in bipolar disorder.

Association study of X chromosome SNPs in attempted suicide

We report the results of a high-density attempted suicide association study of the X chromosome, which genotyped 23,141 SNPs on 983 attempters and 1143 non-attempters and generated modest evidence for association for SH3KBP1 (P=1.07×10(-4)) and GRIA3 (P=4.01×10(-4)). These findings highlight the need for larger sample sets and meta-analytic approaches.

Evidence for association of bipolar disorder to haplotypes in the 22q12.3 region near the genes stargazin, IFT27 and parvalbumin

We have previously reported genome-wide significant linkage of bipolar disorder to a region on 22q12.3 near the marker D22S278. Towards identifying the susceptibility gene, we have conducted a fine-mapping association study of the region in two independent family samples, an independent case-control sample and a genome-wide association dataset. Two hundred SNPs were first examined in a 5 Mb region surrounding the D22S278 marker in a sample of 169 families and analyzed using PLINK. The peak of association was a haplotype near the genes stargazin (CACNG2), intraflagellar transport protein homolog 27 (IFT27) and parvalbumin (PVALB; P = 4.69 × 10(-4)). This peak overlapped a significant haplotype in a family based association study of a second independent sample of 294 families (P = 1.42 × 10(-5)). Analysis of the combined family sample yielded statistically significant evidence of association to a rare three SNP haplotype in the gene IFT27 (P = 8.89 × 10(-6)). Twelve SNPs comprising these haplotypes were genotyped in an independent sample of 574 bipolar I cases and 550 controls. Statistically significant association was found for a haplotype window that overlapped the region from the first two family samples (P = 3.43 × 10(-4)). However, analyses of the two family samples using the program LAMP, found no evidence for association in this region, but did yield significant evidence for association to a haplotype 3' of CACNG2 (P = 1.76 × 10(-6)). Furthermore, no evidence for association was found in a large genome-wide association dataset. The replication of association to overlapping haplotypes in three independent datasets suggests the presence of a bipolar disorder susceptibility gene in this region.

Hormone therapy and Alzheimer disease dementia: new findings from the Cache County Study

OBJECTIVES

Observational studies suggest reduced risk of Alzheimer disease (AD) in users of hormone therapy (HT), but trials show higher risk. We examined whether the association of HT with AD varies with timing or type of HT use.

METHODS

Between 1995 and 2006, the population-based Cache County Study followed 1,768 women who had provided a detailed history on age at menopause and use of HT. During this interval, 176 women developed incident AD. Cox proportional hazard models evaluated the association of HT use with AD, overall and in relation to timing, duration of use, and type (opposed vs unopposed) of HT.

RESULTS

Women who used any type of HT within 5 years of menopause had 30% less risk of AD (95% confidence interval 0.49-0.99), especially if use was for 10 or more years. By contrast, AD risk was not reduced among those who had initiated HT 5 or more years after menopause. Instead, rates were increased among those who began "opposed" estrogen-progestin compounds within the 3 years preceding the Cache County Study baseline (adjusted hazard ratio 1.93; 95% confidence interval 0.94-3.96). This last hazard ratio was similar to the ratio of 2.05 reported in randomized trial participants assigned to opposed HT.

CONCLUSIONS

Association of HT use and risk of AD may depend on timing of use. Although possibly beneficial if taken during a critical window near menopause, HT (especially opposed compounds) initiated in later life may be associated with increased risk. The relation of AD risk to timing and type of HT deserves further study.

Genome-wide association of mood-incongruent psychotic bipolar disorder

Mood-incongruent psychotic features (MICP) are familial symptoms of bipolar disorder (BP) that also occur in schizophrenia (SZ), and may represent manifestations of shared etiology between the major psychoses. In this study we have analyzed three large samples of BP with imputed genome-wide association data and have performed a meta-analysis of 2196 cases with MICP and 8148 controls. We found several regions with suggestive evidence of association (P<10(-6)), although no marker met genome-wide significance criteria. The top associations were on chromosomes: 6q14.2 within the PRSS35/SNAP91 gene complex (rs1171113, P=9.67 × 10(-8)); 3p22.2 downstream of TRANK/LBA1 (rs9834970, P=9.71 × 10(-8)); and 14q24.2 in an intron of NUMB (rs2333194, P=7.03 × 10(-7)). These associations were present in all three samples, and both rs1171113 and rs2333194 were found to be overrepresented in an analysis of MICP cases compared with all other BP cases. To test the relationship of MICP with SZ, we performed polygenic analysis using the Psychiatric GWAS Consortium SZ results and found evidence of association between SZ polygenes and the presence of MICP in BP cases (meta-analysis P=0.003). In summary, our analysis of the MICP phenotype in BP has provided suggestive evidence for association of common variants in several genes expressed in the nervous system. The results of our polygenic analysis provides support for a modest degree of genetic overlap between BP with MICP and SZ, highlighting that phenotypic correlations across syndromes may be due to the influence of polygenic risk factors.

Role of APOE and Age at Enrollment in the Alzheimer's Disease Anti-Inflammatory Prevention Trial (ADAPT)

BACKGROUND

The Alzheimer's Disease Anti-inflammatory Prevention Trial (ADAPT) tested whether non-steroidal anti-inflammatory drugs (NSAIDs) can prevent Alzheimer's disease (AD). The results were null. We analyzed ADAPT data to examine if the effects of NSAIDs on AD risk differed depending upon APOE genotype or age as has been suggested by previous observational studies.

METHODS

ADAPT randomized 2,528 cognitively intact older adults to either celecoxib, naproxen sodium or placebo; 2,388 participants provided blood samples for APOE genotyping. Proportional hazards regression was used to estimate the effects of naproxen or celecoxib versus placebo on incident AD by age at enrollment and APOE genotype.

RESULTS

The proportion of subjects providing a biological sample did not differ between the treatment groups. In models of AD risk, none of the tests for 2-way interactions between either NSAID and age or APOE genotype were significant (p > 0.05).

CONCLUSIONS

The data did not support the hypothesis that the association between NSAIDs and AD risk differed by age or APOE genotype.

Meta-analysis of genetic association studies on bipolar disorder

Numerous candidate gene association studies of bipolar disorder (BP) have been carried out, but the results have been inconsistent. Individual studies are typically underpowered to detect associations with genes of small effect sizes. We conducted a meta-analysis of published candidate gene studies to evaluate the cumulative evidence. We systematically searched for all published candidate gene association studies of BP. We then carried out a random-effects meta-analysis on all polymorphisms that were reported on by three or more case-control studies. The results from meta-analyses of these genes were compared with the findings from a recent mega-analysis of eleven genome-wide association studies (GWAS) in BP performed by the Psychiatric GWAS Consortium (PGC). A total of 487 articles were included in our review. Among these, 33 polymorphisms in 18 genes were reported on by three or more case-control studies and included in the random-effects meta-analysis. Polymorphisms in BDNF, DRD4, DAOA, and TPH1, were found to be nominally significant with a P-value < 0.05. However, none of the findings were significant after correction for multiple testing. Moreover, none of these polymorphisms were nominally significant in the PGC-BP GWAS. A number of plausible candidate genes have been previously associated with BP. However, the lack of robust findings in our review of these candidate genes highlights the need for more atheoretical approaches to study the genetics of BP afforded by GWAS. The results of this meta-analysis and from other on-going genomic experiments in BP are available online at Metamoodics (http://metamoodics.igm.jhmi.edu).

A genome-wide association study of attempted suicide

The heritable component to attempted and completed suicide is partly related to psychiatric disorders and also partly independent of them. Although 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 1201 bipolar (BP) subjects with a history of suicide attempts to the genotypes of 1497 BP subjects without a history of suicide attempts. In all, 2507 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 (acid phosphatase 1) 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.

Data mining approaches for genome-wide association of mood disorders

BACKGROUND

Mood disorders are highly heritable forms of major mental illness. A major breakthrough in elucidating the genetic architecture of mood disorders was anticipated with the advent of genome-wide association studies (GWAS). However, to date few susceptibility loci have been conclusively identified. The genetic etiology of mood disorders appears to be quite complex, and as a result, alternative approaches for analyzing GWAS data are needed. Recently, a polygenic scoring approach that captures the effects of alleles across multiple loci was successfully applied to the analysis of GWAS data in schizophrenia and bipolar disorder (BP). However, this method may be overly simplistic in its approach to the complexity of genetic effects. Data mining methods are available that may be applied to analyze the high dimensional data generated by GWAS of complex psychiatric disorders.

RESULTS

We sought to compare the performance of five data mining methods, namely, Bayesian networks, support vector machine, random forest, radial basis function network, and logistic regression, against the polygenic scoring approach in the analysis of GWAS data on BP. The different classification methods were trained on GWAS datasets from the Bipolar Genome Study (2191 cases with BP and 1434 controls) and their ability to accurately classify case/control status was tested on a GWAS dataset from the Wellcome Trust Case Control Consortium.

CONCLUSION

The performance of the classifiers in the test dataset was evaluated by comparing area under the receiver operating characteristic curves. Bayesian networks performed the best of all the data mining classifiers, but none of these did significantly better than the polygenic score approach. We further examined a subset of single-nucleotide polymorphisms (SNPs) in genes that are expressed in the brain, under the hypothesis that these might be most relevant to BP susceptibility, but all the classifiers performed worse with this reduced set of SNPs. The discriminative accuracy of all of these methods is unlikely to be of diagnostic or clinical utility at the present time. Further research is needed to develop strategies for selecting sets of SNPs likely to be relevant to disease susceptibility and to determine if other data mining classifiers that utilize other algorithms for inferring relationships among the sets of SNPs may perform better.

SynaptomeDB: an ontology-based knowledgebase for synaptic genes

MOTIVATION

The synapse is integral to the function of the brain and may be an important source of dysfunction underlying many neuropsychiatric disorders. Consequently, it is an excellent candidate for large-scale genomic and proteomic study. However, while the tools and databases available for the annotation of high-throughput DNA and protein are generally robust, a comprehensive resource dedicated to the integration of information about the synapse is lacking.

RESULTS

We present an integrated database, called SynaptomeDB, to retrieve and annotate genes comprising the synaptome. These genes encode components of the synapse including neurotransmitters and their receptors, adhesion/cytoskeletal proteins, scaffold proteins, membrane transporters. SynaptomeDB integrates various and complex data sources for synaptic genes and proteins.

Association study of serotonin pathway genes in attempted suicide

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.

Genome-wide association analysis of age at onset and psychotic symptoms in bipolar disorder

Genome-wide association studies (GWAS) have identified several susceptibility loci for bipolar disorder (BP), most notably ANK3. However, most of the inherited risk for BP remains unexplained. One reason for the limited success may be the genetic heterogeneity of BP. Clinical sub-phenotypes of BP may identify more etiologically homogeneous subsets of patients, which can be studied with increased power to detect genetic variation. Here, we report on a mega-analysis of two widely studied sub-phenotypes of BP, age at onset and psychotic symptoms, which are familial and clinically significant. We combined data from three GWAS: NIMH Bipolar Disorder Genetic Association Information Network (GAIN-BP), NIMH Bipolar Disorder Genome Study (BiGS), and a German sample. The combined sample consisted of 2,836 BP cases with information on sub-phenotypes and 2,744 controls. Imputation was performed, resulting in 2.3 million SNPs available for analysis. No SNP reached genome-wide significance for either sub-phenotype. In addition, no SNP reached genome-wide significance in a meta-analysis with an independent replication sample. We had 80% power to detect associations with a common SNP at an OR of 1.6 for psychotic symptoms and a mean difference of 1.8 years in age at onset. Age at onset and psychotic symptoms in BP may be influenced by many genes of smaller effect sizes or other variants not measured well by SNP arrays, such as rare alleles.

The promise and reality of pharmacogenetics in psychiatry

Existing psychotropic medications for the treatment of mental illnesses, including antidepressants, mood stabilizers, and antipsychotics, are clinically suboptimal. They are effective in only a subset of patients or produce partial responses, and they are often associated with debilitating side effects that discourage adherence. There is growing enthusiasm in the promise of pharmacogenetics to personalize the use of these treatments to maximize their efficacy and tolerability; however, there is still a long way to go before this promise becomes a reality. This article reviews the progress that has been made in research toward understanding how genetic factors influence psychotropic drug responses and the challenges that lie ahead in translating the research findings into clinical practices that yield tangible benefits for patients with mental illnesses.

Incorporating scientific knowledge into phenotype development: penalized latent class regression

The field of psychiatric genetics is hampered by the lack of a clear taxonomy for disorders. Building on the work of Houseman and colleagues (Feature-specific penalized latent class analysis for genomic data. Harvard University Biostatistics Working Paper Series, Working Paper 22, 2005), we describe a penalized latent class regression aimed at allowing additional scientific information to influence the estimation of the measurement model, while retaining the standard assumption of non-differential measurement. In simulation studies, ridge and LASSO penalty functions improved the precision of estimates and, in some cases of differential measurement, also reduced bias. Class-specific penalization enhanced separation of latent classes with respect to covariates, but only in scenarios where there was a true separation. Penalization proved to be less computationally intensive than an analogous Bayesian analysis by a factor of 37. This methodology was then applied to data from normal elderly subjects from the Cache County Study on Memory and Aging. Addition of APO-E genotype and a number of baseline clinical covariates improved the dementia prediction utility of the latent classes; application of class-specific penalization improved precision while retaining that prediction utility. This methodology may be useful in scenarios with large numbers of collinear covariates or in certain cases where latent class model assumptions are violated. Investigation of novel penalty functions may prove fruitful in further refining psychiatric phenotypes.

Genome-wide association study of suicide attempts in mood disorder patients

OBJECTIVE

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.

METHOD

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.

RESULTS

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.

CONCLUSIONS

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.

The 32-year relationship between cholesterol and dementia from midlife to late life

BACKGROUND

Cellular and animal studies suggest that hypercholesterolemia contributes to Alzheimer disease (AD). However, the relationship between cholesterol and dementia at the population level is less clear and may vary over the lifespan.

METHODS

The Prospective Population Study of Women, consisting of 1,462 women without dementia aged 38-60 years, was initiated in 1968-1969 in Gothenburg, Sweden. Follow-ups were conducted in 1974-1975, 1980-1981, 1992-1993, and 2000-2001. All-cause dementia was diagnosed according to DSM-III-R criteria and AD according to National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association criteria. Cox proportional hazards regression examined baseline, time-dependent, and change in cholesterol levels in relation to incident dementia and AD among all participants. Analyses were repeated among participants who survived to the age of 70 years or older and participated in the 2000-2001 examination.

RESULTS

Higher cholesterol level in 1968 was not associated with an increased risk of AD (highest vs lowest quartile: hazard ratio [HR] 2.82, 95% confidence interval [CI] 0.94-8.43) among those who survived to and participated in the 2000-2001 examination. While there was no association between cholesterol level and dementia when considering all participants over 32 years, a time-dependent decrease in cholesterol over the follow-up was associated with an increased risk of dementia (HR 2.35, 95% CI 1.22-4.58).

CONCLUSION

These data suggest that midlife cholesterol level is not associated with an increased risk of AD. However, there may be a slight risk among those surviving to an age at risk for dementia. Declining cholesterol levels from midlife to late life may better predict AD risk than levels obtained at one timepoint prior to dementia onset. Analytic strategies examining this and other risk factors across the lifespan may affect interpretation of results.