The transition from genomics to phenomics in personalized population health.

Modern health care faces several serious challenges, including an ageing population and its inherent burden of chronic diseases, rising costs and marginal quality metrics. By assessing and optimizing the health trajectory of each individual using a data-driven personalized approach that reflects their genetics, behaviour and environment, we can start to address these challenges. This assessment includes longitudinal phenome measures, such as the blood proteome and metabolome, gut microbiome composition and function, and lifestyle and behaviour through wearables and questionnaires. Here, we review ongoing large-scale genomics and longitudinal phenomics efforts and the powerful insights they provide into wellness. We describe our vision for the transformation of the current health care from disease-oriented to data-driven, wellness-oriented and personalized population health.

Personalized Nutrition: Translating the Science of NutriGenomics Into Practice: Proceedings From the 2018 American College of Nutrition Meeting.

Adverse reactions to foods and adverse drug reactions are inherent in product defects, medication errors, and differences in individual drug exposure. Pharmacogenetics is the study of genetic causes of individual variations in drug response and pharmacogenomics more broadly involves genome-wide analysis of the genetic determinants of drug efficacy and toxicity. The similarity of nutritional genomics and pharmacogenomics stems from the innate goal to identify genetic variants associated with metabolism and disease. Thus, nutrigenomics can be thought of as encompassing gene-diet interactions involving diverse compounds that are present in even the simplest foods. The advances in the knowledge base of the complex interactions among genotype, diet, lifestyle, and environment is the cornerstone that continues to elicit changes in current medical practice to ultimately yield personalized nutrition recommendations for health and risk assessment. This information could be used to understand how foods and dietary supplements uniquely affect the health of individuals and, hence, wellness. The individual's gut microbiota is not only paramount but pivotal in embracing the multiple-functional relationships with complex metabolic mechanisms involved in maintaining cellular homeostasis. The genetic revolution has ushered in an exciting era, one in which many new opportunities are expected for nutrition professionals with expertise in nutritional genomics. The American College of Nutrition's conference focused on "Personalized Nutrition: Translating the Science of NutriGenomics Into Practice" was designed to help to provide the education needed for the professional engagement of providers in the personalized medicine era.

Circadian patterns of gene expression in the human brain and disruption in major depressive disorder.

A cardinal symptom of major depressive disorder (MDD) is the disruption of circadian patterns. However, to date, there is no direct evidence of circadian clock dysregulation in the brains of patients who have MDD. Circadian rhythmicity of gene expression has been observed in animals and peripheral human tissues, but its presence and variability in the human brain were difficult to characterize. Here, we applied time-of-death analysis to gene expression data from high-quality postmortem brains, examining 24-h cyclic patterns in six cortical and limbic regions of 55 subjects with no history of psychiatric or neurological illnesses ("controls") and 34 patients with MDD. Our dataset covered ~12,000 transcripts in the dorsolateral prefrontal cortex, anterior cingulate cortex, hippocampus, amygdala, nucleus accumbens, and cerebellum. Several hundred transcripts in each region showed 24-h cyclic patterns in controls, and >100 transcripts exhibited consistent rhythmicity and phase synchrony across regions. Among the top-ranked rhythmic genes were the canonical clock genes BMAL1(ARNTL), PER1-2-3, NR1D1(REV-ERBa), DBP, BHLHE40 (DEC1), and BHLHE41(DEC2). The phasing of known circadian genes was consistent with data derived from other diurnal mammals. Cyclic patterns were much weaker in the brains of patients with MDD due to shifted peak timing and potentially disrupted phase relationships between individual circadian genes. This transcriptome-wide analysis of the human brain demonstrates a rhythmic rise and fall of gene expression in regions outside of the suprachiasmatic nucleus in control subjects. The description of its breakdown in MDD suggests potentially important molecular targets for treatment of mood disorders.

Metabolic syndrome in bipolar disorder and schizophrenia: dietary and lifestyle factors compared to the general population.

OBJECTIVE: Since a poor diet is often cited as a contributor to metabolic syndrome for subjects diagnosed with bipolar disorder and schizophrenia, we sought to examine dietary intake, cigarette smoking, and physical activity in these populations and compare them with those for the general population. METHODS: Individuals diagnosed with bipolar disorder (n = 116) and schizophrenia (n = 143) were assessed for dietary intake, lifestyle habits, and metabolic syndrome and compared to age-, gender-, and race-matched subjects from the National Health and Nutrition Examination Survey (NHANES) 1999-2000. Additionally, matched subgroups within the patient populations were compared to elicit any differences. RESULTS: As expected, the metabolic syndrome rate was higher in the samples with bipolar disorder (33%) and schizophrenia (47%) compared to matched NHANES controls (17% and 11%, respectively), and not different between the patient groups. Surprisingly, both subjects with bipolar disorder and those with schizophrenia consumed fewer total calories, carbohydrates and fats, as well as more fiber (p < 0.03), compared to NHANES controls. No dietary or activity differences between patient participants with and without metabolic syndrome were found. Subjects with schizophrenia had significantly lower total and low-density cholesterol levels (p < 0.0001) compared to NHANES controls. Subjects with bipolar disorder smoked less (p = 0.001), exercised more (p = 0.004), and had lower body mass indexes (p = 0.009) compared to subjects with schizophrenia. CONCLUSIONS: Counter to predictions, few dietary differences could be discerned between schizophrenia, bipolar disorder, and NHANES control groups. The subjects with bipolar disorder exhibited healthier behaviors than the patients with schizophrenia. Additional research regarding metabolic syndrome mechanisms, focusing on non-dietary contributions, is needed.

A pilot study investigating tumor necrosis factor-α as a potential intervening variable of atypical antipsychotic-associated metabolic syndrome in bipolar disorder.

BACKGROUND: Strong associations exist between tumor necrosis factor-α (TNF-α) and metabolic syndrome (MetS). Although TNF-α is associated with bipolar depression (BD), its role in atypical antipsychotic (AAP)-associated MetS in BD is unclear. Here, we investigate the potential intervening role of TNF-α in the indirect relationship between AAP treatment and MetS in BD. MATERIALS AND METHODS: Using a cross-sectional design, 99 euthymic BD volunteers were stratified by the presence or the absence of MetS (National Cholesterol Education Program Adult Treatment Panel III). Serum TNF-α concentration, determined via chemiluminescent immunometric assays, was compared between groups (ie, MetS or no MetS). We investigated the intervening effect of TNF-α on the relation between AAP treatment and MetS in BD using regression techniques. RESULTS: Treatment with those antipsychotics believed associated with a higher risk for MetS (ie, AAPs: olanzapine, quetiapine, risperidone, paliperidone, clozapine) was found to be associated with significantly greater TNF-α (F 1,88 = 11.2, P = 0.001, mean difference of 1.7 ± 0.51) and a higher likelihood of MetS (F 1,88 = 4.5, P = 0.036) than in those not receiving treatment with an AAP. Additionally, TNF-α was greater (trending toward significance; T 52 = 2.0, P = 0.05) in BD volunteers with MetS and was found to have a statistically significant effect on the indirect relationship between AAP treatment and elevated waist circumference in these BD volunteers. DISCUSSION: These results identify TNF-α as a potential intervening variable of AAP-associated MetS in BD, not previously identified in this population. Future prospective studies could assess the predictive potential of TNF-α in determining risk of AAP-associated MetS in BD. Given previous evidence relating TNF-α and mood state in BD, this study increases the importance in understanding the role of TNF-α in "mind-body" interactions and renews discussions of the utility of research into the clinical efficacy of TNF-α antagonist treatment in mood disorders.

Latent infection, inflammatory markers and suicide attempt history in depressive disorders.

BACKGROUND: Numerous reports have described increased rates of exposure to Toxoplasma gondii levels in individuals with a history of suicide attempts in comparison with well controls, or psychiatrically ill individuals, with no suicide attempt history. Such findings suggest that the behavioral effects this parasite exerts on rodent hosts extends to humans though few studies have searched for underlying mechanisms. METHODS: The present study compared 96 patients with an active depressive disorder and a history of at least two suicide attempts to 126 depressed patients with no history of suicide attempts by IgG and IgM levels of Toxoplasma gondii and cytomegalovirus (CMV). The groups were also compared by IL_1b, TNF-alpha, CRP, IL_6, and IL_1ra titers. RESULTS: Toxoplasma gondii IgM levels were higher, and seropositivity more likely, in the suicide attempt group. CMV IgG levels were also higher among suicide attempters. Several of these immunoglobulin measures were more robustly associated with the number of suicide attempts than with the dichotomy of suicide attempter and non-attempter. These two antibody levels were also additive in their association with suicide attempter status. IL_1a levels were lower in suicide attempters and correlated negatively with levels of antibodies to Toxoplasma gondii and CMV. LIMITATIONS: These include a sample size insufficient to explore differences across mood disorder diagnoses or demographic groupings. CONCLUSIONS: These results indicate that exposure to common infectious agents such as Toxoplasma gondii and CMV are associated with increased risk of suicide attempts but the mechanism of association does not appear to involve the activation of cytokines. Elucidation of the mechanisms which define the relationship between infections and suicide attempts may lead to new methods for the prediction and prevention of suicide attempts.

Gene expression profiling of neurochemically defined regions of the human brain by in situ hybridization-guided laser capture microdissection.

Laser capture microdissection (LCM) permits isolation of specific cell types and cell groups based upon morphology, anatomical landmarks and histochemical properties. This powerful technique can be used for region-specific dissection if the target structure is clearly delineated. However, it is difficult to visualize anatomical boundaries in an unstained specimen, while histological staining can complicate the microdissection process and compromise downstream processing and analysis. We now introduce a novel method in which in situ hybridization (ISH) signal is used to guide LCM on adjacent unstained sections to collect tissue from neurochemically defined regions of the human postmortem brain to minimize sample manipulation prior to analysis. This approach was validated in nuclei that provide monoaminergic inputs to the forebrain, and likely contribute to the pathophysiology of mood disorders. This method was used successfully to carry out gene expression profiling and quantitative real-time PCR (qPCR) confirmation from the dissected material. When compared to traditional micropunch dissections, our ISH-guided LCM method provided enhanced signal intensity for mRNAs of specific monoaminergic marker genes as measured by genome-wide gene expression microarrays. Enriched expression of specific monoaminergic genes (as determined by microarrays and qPCR) was detected within appropriate anatomical locations validating the accuracy of microdissection. Together these results support the conclusion that ISH-guided LCM permits acquisition of enriched nucleus-specific RNA that can be successfully used for downstream gene expression investigations. Future studies will utilize this approach for gene expression profiling of neurochemically defined regions of postmortem brains collected from mood disorder patients.

Overexpressing the glucocorticoid receptor in forebrain causes an aging-like neuroendocrine phenotype and mild cognitive dysfunction.

Repeated stress enhances vulnerability to neural dysfunction that is cumulative over the course of the lifespan. This dysfunction contributes to cognitive deficits observed during aging. In addition, aging is associated with dysregulation of the limbic-hypothalamic-pituitary-adrenal (LHPA) axis, leading to a delayed termination of the stress response. This delay, in turn, increases exposure to glucocorticoids and exacerbates the likelihood of neural damage. Here we asked whether similar effects could emerge at an early age as a result of genetic variations in the level or function of the brain glucocorticoid receptor (GR). We investigated the effect of forebrain-specific overexpression of GR on LHPA axis activity. Transgenic mice with GR overexpression in forebrain (GRov) display normal basal circulating adrenocorticotropic hormone and corticosterone levels. However, young GRov mice exhibit a number of LHPA alterations, including a blunted initial response to acute restraint stress followed by a delayed turn-off of the stress response. This deficit in negative feedback is paradoxical in the face of elevated GR levels, resembles the stress response in aged animals, and continues to worsen as GRov mice age. The neuroendocrine dysregulation in young GRov mice is coupled with a mild cognitive deficit, also consistent with the accelerated aging hypothesis. The molecular basis of this phenotype was examined using microarray analysis of the hippocampus, which revealed a broad downregulation of glutamate receptor signaling in GRov mice. Thus, even in the absence of chronic stress, elevation of GR gene expression can lead to an increased allostatic load and result in an "aging-like" phenotype in young animals.

Aggression, impulsivity and inflammatory markers as risk factors for suicidal behavior.

BACKGROUND: Increased inflammatory markers have been linked to suicidal behavior in numerous studies. Measures of aggression and of impulsivity also comprise risks factors for suicidal behavior and there is evidence that inflammatory markers correlate with these traits. The following analyses compare suicide attempters and non-attempters to determine whether inflammatory markers mediate relationships between aggression or impulsivity and proclivities to suicidal behavior. METHODS: Investigators at three academic centers recruited patients in major depressive episodes who had a history of two or more suicide attempts (n = 79), or who had no history of suicide attempts (n = 123). Analyses compared these groups by five inflammatory marker levels and by measures of aggression and of impulsivity. RESULTS: These results did not confirm the hypotheses that cytokine levels would explain relationships between aggressive behavior and suicide attempt history. However, scores for aggressive behavior and for impulsivity were significantly higher among suicide attempters. One of five of the inflammatory markers, (IL-1ß), distinguished the two groups with lower values in the suicide attempt group. IL-1ß levels correlated inversely with measures of aggression but neither impulsivity or aggressive behavior appear to explain the association between IL-1ß levels and suicide attempt status. CONCLUSION: These results identify recent aggressive behavior, higher levels of impulsivity, and lower levels of IL-1ß as risk factors for a history of multiple suicide attempts in a group suffering from major depressive episodes. These measures appear to be additive in their effects.

Sample matching by inferred agonal stress in gene expression analyses of the brain.

BACKGROUND: Gene expression patterns in the brain are strongly influenced by the severity and duration of physiological stress at the time of death. This agonal effect, if not well controlled, can lead to spurious findings and diminished statistical power in case-control comparisons. While some recent studies match samples by tissue pH and clinically recorded agonal conditions, we found that these indicators were sometimes at odds with observed stress-related gene expression patterns, and that matching by these criteria still sometimes results in identifying case-control differences that are primarily driven by residual agonal effects. This problem is analogous to the one encountered in genetic association studies, where self-reported race and ethnicity are often imprecise proxies for an individual's actual genetic ancestry. RESULTS: We developed an Agonal Stress Rating (ASR) system that evaluates each sample's degree of stress based on gene expression data, and used ASRs in post hoc sample matching or covariate analysis. While gene expression patterns are generally correlated across different brain regions, we found strong region-region differences in empirical ASRs in many subjects that likely reflect inter-individual variabilities in local structure or function, resulting in region-specific vulnerability to agonal stress. CONCLUSION: Variation of agonal stress across different brain regions differs between individuals, revealing a new level of complexity for gene expression studies of brain tissues. The Agonal Stress Ratings quantitatively assess each sample's extent of regulatory response to agonal stress, and allow a strong control of this important confounder.

Interaction Between Atypical Antipsychotics and the Gut Microbiome in a Bipolar Disease Cohort.

OBJECTIVES: The atypical antipsychotic (AAP) class is often associated with metabolic disease, but the mechanistic underpinnings of this risk are not understood. Due to reports linking gut bacteria function to metabolic disease, we hypothesize that AAP treatment in adults results in gut dysbiosis potentiating metabolic criteria. This report describes recent findings linking AAP treatment with differences in gut microbiota communities in a human cohort with bipolar disorder (BD). METHODS: In a cross-sectional design, we obtained 16S ribosomal sequences from 117 BD patients (49 AAP treated, 68 non-AAP treated). Analysis of molecular variance (AMOVA) was used to detect significant clustering of microbial communities between groups, and the inverse Simpson Diversity Index was used to calculate alpha diversity. Detection of differentially abundant operational taxonomic units (OTUs) between groups was performed using linear discriminant analysis effect size. RESULTS: The AAP-treated cohort was significantly younger and had an increased body mass index compared with non-AAP-treated patients. Groups did not differ in other psychotropic medication use with the exception of higher use of benzodiazepines in the AAP cohort. We detected significant separation between microbiota communities of AAP-treated and nontreated patients (AMOVA; p=0.04). AAP-treated females showed significant decreased species diversity when compared with non-AAP-treated females (p=0.015). Males showed no significant diversity between treatment groups (p=0.8). Differentially abundant OTUs between treatment groups were OTU1, OTU25, and OTU32 that classified to Lachnospiraceae, Akkermansia, and Sutterella, respectively. CONCLUSIONS: These data suggest that AAP treatment is associated with specific representation of gut bacterial families in AAP-treated patients. In addition, AAP treatment is associated with decreased species richness in female AAP-treated patients.

Bipolar disorder moderates associations between linoleic acid and markers of inflammation.

Dietary polyunsaturated fatty acids (PUFA) and inflammatory proteins associate with immune activation and have been implicated in the pathophysiology of mood disorders. We have previously reported that individuals with bipolar disorder (BPD) have decreased PUFA intake, including eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and arachidonic acid (AA); and decreased PUFA concentration of plasma EPA and linoleic acid (LA). We have also reported an association between plasma LA and its metabolites and burden of disease measures in BPD. In the current cross-sectional study we collected blood samples and diet records from both bipolar (n = 91) and control subjects (n = 75) to quantify plasma cytokine concentrations and dietary LA intake, respectively. Using multiple linear regression techniques, we tested for case control differences in plasma cytokine levels and associations between cytokines and dietary LA intake, adjusting for sex, age, BMI, and total energy intake. We found significantly higher plasma levels of interleukin 18 (IL-18) (p = 0.036), IL-18 binding protein (IL-18BP) (p = 0.001), soluble tumor necrosis factor receptor (sTNFR) 1 (p = 0.006), and sTNFR2 (p = 0.007) in BPD compared with controls. Moreover, BPD significantly moderated the associations of dietary LA intake with plasma levels of IL-18, sTNFR1 and sTNFR2, which were inverse associations in bipolar individuals and positive associations in controls (p for dietary LA x BPD diagnosis interaction < 0.05 for all three). These findings suggest potential dysregulation of LA metabolism in BPD, which may extend to a modified influence of dietary LA on specific inflammatory pathways in individuals with BPD compared to healthy controls.

The gut microbiome composition associates with bipolar disorder and illness severity.

The gut microbiome is emerging as an important factor in regulating mental health yet it remains unclear what the target should be for psychiatric treatment. We aimed to elucidate the complement of the gut-microbiome community for individuals with bipolar disorder relative to controls; and test for relationships with burden of disease measures. We compared the stool microbiome from individuals with bipolar disorder (n = 115) and control subjects (n = 64) using 16S ribosomal RNA (rRNA) gene sequence analysis. Analysis of molecular variance (AMOVA) revealed global community case-control differences (AMOVA p = 0.047). Operational Taxonomical Unit (OTU) level analysis revealed significantly decreased fractional representation (p < 0.001) of Faecalibacterium after adjustment for age, sex, BMI and false discovery rate (FDR) correction at the p < 0.05 level. Within individuals with bipolar disorder, the fractional representation of Faecalibacterium associated with better self-reported health outcomes based on the Short Form Health Survey (SF12); the Patient Health Questionnaire (PHQ9); the Pittsburg Sleep Quality Index (PSQI); the Generalized Anxiety Disorder scale (GAD7); and the Altman Mania Rating Scale (ASRM), independent of covariates. This study provides the first detailed analysis of the gut microbiome relationships with multiple psychiatric domains from a bipolar population. The data support the hypothesis that targeting the microbiome may be an effective treatment paradigm for bipolar disorder.

The fibroblast growth factor system and mood disorders.

Recent evidence now suggests the involvement of the fibroblast growth factor (FGF) system in mood disorders. Specifically, several members of the FGF family have been shown to be dysregulated in individuals with major depression. In this review, we will introduce the FGF system in terms of structure and function during development, in adulthood, and in various regions and cell types. We will also review the FGF system as a mediator of neural plasticity. Furthermore, this review will summarize animal as well as human studies. The majority of animal studies have focused on stress, environmental enrichment, pharmacological manipulations, and the hippocampus. By contrast, human studies have focused on volumetric measurements, antidepressant literature, and, most recently, post-mortem microarray experiments. In summary, a reduced tone in the FGF system might alter brain development or remodeling and result in a predisposition or vulnerability to mood disorders, including major depression.

Combining laser capture microdissection with quantitative real-time PCR: effects of tissue manipulation on RNA quality and gene expression.

Laser capture microdissection (LCM) is increasingly being used in quantitative gene expression studies of the nervous system. The current study aimed at determining the impact of various tissue manipulations on the integrity of extracted RNA in LCM studies. Our data indicate that various tissue preparation strategies prior to microdissection may decrease RNA quality by as much as 25%, thus affecting expression profiles of some genes. To circumvent this problem, we developed a strategy for reverse transcriptase real-time PCR that has considerable sensitivity and can be used to calculate relative changes in gene expression. This approach was validated in subregions of the rat cerebellum. Accordingly, expression of glial gene markers - myelin-associated glycoprotein and proteolipid protein 1 - was found 70-160-fold higher in the white matter layer of the cerebellar cortex as compared to the neuron-enriched granular layer. In contrast, expression of a specific neuronal maker, neuron-specific enolase, was found seven-fold higher in the granular layer, as compared to the white matter layer. Furthermore, this approach had high sensitivity and specificity as we were able to detect a 38% decrease in the expression of neuron-specific enolase without a change in the expression of glial markers following administration of the neurotoxin, ibotenic acid. These results demonstrate feasibility of performing accurate semi-quantitative gene expression analyses in LCM samples.

An Untargeted Metabolomics Analysis of Antipsychotic Use in Bipolar Disorder.

BACKGROUND: Second generation antipsychotic (SGA) use in bipolar disorder is common and has proven effective in short-term trials. There continues to be a lack of understanding of the mechanisms underlying many of their positive and negative effects in bipolar disorder. This study aimed to describe the metabolite profiles of bipolar subjects treated with SGAs by comparing to metabolite profiles of bipolar subjects treated with lithium, and schizophrenia subjects treated with SGAs. METHODS: Cross-sectional, fasting untargeted serum metabolomic profiling was conducted in 82 subjects diagnosed with bipolar I disorder (n = 30 on SGAs and n = 32 on lithium) or schizophrenia (n = 20). Metabolomic profiles of bipolar subjects treated with SGAs were compared to bipolar subjects treated with lithium and schizophrenia subjects treated with SGAs using multivariate methods. RESULTS: Partial lease square discriminant analysis (PLS-DA) plots showed separation between bipolar subjects treated with SGAs, bipolar subjects treated with lithium, or schizophrenia subjects treated with SGAs. Top influential metabolite features were associated with several pathways including that of polyunsaturated fatty acids, pyruvate, glucose, and branched chain amino acids. CONCLUSIONS: The findings from this study require further validation in pre- and posttreated bipolar and schizophrenia subjects, but suggest that the pharmacometabolome may be diagnosis specific.

Plasma linoleic acid partially mediates the association of bipolar disorder on self-reported mental health scales.

We have shown that bipolar individuals have reduced quality diets, including lower intake of polyunsaturated fatty acids (PUFA). We have also reported reduced plasma levels of the n-6 PUFA, linoleic acid (LA), and the n-3 PUFA, eicosapentaenoic acid (EPA) in bipolar subjects. In the current analysis we hypothesized that LA and EPA plasma levels would mediate lower self-reported mental health and life functioning scores in bipolar subjects. In a cross-sectional study, we collected a 7-day diet record in bipolar (n = 56) and control subjects (n = 46) followed by a fasted blood draw. We used structured equation modeling path analysis to test for mediating effects of dietary intake and plasma levels of LA and EPA on self-reported mental health questionnaire scores, including the Life Functioning Questionnaire (LFQ), the Patient Health Questionnaire (PHQ9), and the Short Form Health Survey (SF12), extracting the mental health component summary score (SF12-MH). We adjusted for age, gender, psychiatric medication use, body mass index (BMI), and total caloric intake as covariates with bipolar disorder as the primary predictor. We found a significant path association from bipolar disorder to lower plasma LA levels (p = 0.03) and significant paths from plasma LA to PHQ9 (p = 0.05), LFQ (p = 0.01) and SF12-MH (p = 0.05) scores, such that lower plasma LA predicted worse outcomes. We found no significant paths from plasma EPA levels to any of the outcome measures. These findings suggest that plasma LA levels partially mediate the effect of bipolar disorder on self-reported measures of mental health and life functioning.

Effect of agonal and postmortem factors on gene expression profile: quality control in microarray analyses of postmortem human brain.

There are major concerns that specific agonal conditions, including coma and hypoxia, might affect ribonucleic acid (RNA) integrity in postmortem brain studies. We report that agonal factors significantly affect RNA integrity and have a major impact on gene expression profiles in microarrays. In contrast to agonal factors, gender, age, and postmortem factors have less effect on gene expression profiles. The Average Correlation Index is proposed as a method for evaluating RNA integrity on the basis of similarity of microarray profiles. Reducing the variance due to agonal factors is critical in investigating small but validated gene expression differences in messenger RNA levels between psychiatric patients and control subjects.

Microarray technology: a review of new strategies to discover candidate vulnerability genes in psychiatric disorders.

OBJECTIVE: An international effort is in progress to discover candidate genes and pathways associated with psychiatric disorders, including two of the most serious diseases, schizophrenia and mood disorders, through the use of new technology-microarrays. Instead of studying one gene at a time, microarrays provide the opportunity to analyze thousands of genes at once. METHOD: This article reviews the steps in this discovery process, including the acquisition and characterization of high-quality postmortem brain tissue, RNA extraction, and preparation and use of microarray technology. Two alternative microarray methods and factors affecting the quality of array data are reviewed. RESULTS: New analytical strategies are being developed to process the massive data sets generated by microarray studies and to define the significance of implicated genes. Array results must be validated by other methods, including in situ hybridization and real-time polymerase chain reaction. Identified genes can also be evaluated in terms of their chromosomal locations and possible overlap with regions of suggestive linkage or association identified with genome-wide linkage analysis in psychiatry and in terms of overlap with genes identified by microarray studies in animals administered psychoactive drugs. Microarray studies are only the first major step in the process. Further efforts in the investigation involve multiple strategies for studying function and gene structure, including transgenic and knockout animal studies. CONCLUSIONS: Microarrays present a methodology that can identify genes or pathways for new and unique potential drug targets, determine premorbid diagnosis, predict drug responsiveness for individual patients, and, eventually, initiate gene therapy and prevention strategies.