A greedy regression algorithm with coarse weights offers novel advantages.

Regularized regression analysis is a mature analytic approach to identify weighted sums of variables predicting outcomes. We present a novel Coarse Approximation Linear Function (CALF) to frugally select important predictors and build simple but powerful predictive models. CALF is a linear regression strategy applied to normalized data that uses nonzero weights + 1 or - 1. Qualitative (linearly invariant) metrics to be optimized can be (for binary response) Welch (Student) t-test p-value or area under curve (AUC) of receiver operating characteristic, or (for real response) Pearson correlation. Predictor weighting is critically important when developing risk prediction models. While counterintuitive, it is a fact that qualitative metrics can favor CALF with ± 1 weights over algorithms producing real number weights. Moreover, while regression methods may be expected to change most or all weight values upon even small changes in input data (e.g., discarding a single subject of hundreds) CALF weights generally do not so change. Similarly, some regression methods applied to collinear or nearly collinear variables yield unpredictable magnitude or the direction (in p-space) of the weights as a vector. In contrast, with CALF if some predictors are linearly dependent or nearly so, CALF simply chooses at most one (the most informative, if any) and ignores the others, thus avoiding the inclusion of two or more collinear variables in the model.

Pre-capture multiplexing provides additional power to detect copy number variation in exome sequencing.

BACKGROUND: As exome sequencing (ES) integrates into clinical practice, we should make every effort to utilize all information generated. Copy-number variation can lead to Mendelian disorders, but small copy-number variants (CNVs) often get overlooked or obscured by under-powered data collection. Many groups have developed methodology for detecting CNVs from ES, but existing methods often perform poorly for small CNVs and rely on large numbers of samples not always available to clinical laboratories. Furthermore, methods often rely on Bayesian approaches requiring user-defined priors in the setting of insufficient prior knowledge. This report first demonstrates the benefit of multiplexed exome capture (pooling samples prior to capture), then presents a novel detection algorithm, mcCNV ("multiplexed capture CNV"), built around multiplexed capture. RESULTS: We demonstrate: (1) multiplexed capture reduces inter-sample variance; (2) our mcCNV method, a novel depth-based algorithm for detecting CNVs from multiplexed capture ES data, improves the detection of small CNVs. We contrast our novel approach, agnostic to prior information, with the the commonly-used ExomeDepth. In a simulation study mcCNV demonstrated a favorable false discovery rate (FDR). When compared to calls made from matched genome sequencing, we find the mcCNV algorithm performs comparably to ExomeDepth. CONCLUSION: Implementing multiplexed capture increases power to detect single-exon CNVs. The novel mcCNV algorithm may provide a more favorable FDR than ExomeDepth. The greatest benefits of our approach derive from (1) not requiring a database of reference samples and (2) not requiring prior information about the prevalance or size of variants.

Clinician Recognition of First Episode Psychosis.

PURPOSE: Psychotic disorders develop during mid-adolescence through early adulthood, with the initial few months a "critical period" offering the greatest promise for recovery. However, the duration of untreated psychosis is typically over a year. This study aimed to identify aspects of care episodes contributing to delays in diagnosis of a first psychotic episode. METHODS: Study subjects included 161 adolescents and young adults referred to a first episode psychosis treatment program. We captured the various ways that people who experience a severe mental illness engage in treatment using standardized interviews with patients and informants (e.g., family member) and medical record review. RESULTS: A psychotic disorder diagnosis was not given for 38% of subjects at their initial episode of care. Time to first care episode was virtually the same for subjects that did and did not receive a psychosis diagnosis; 50% within 1 month and 84% within 6 months. Compared to initial care episodes with a psychosis diagnosis, those without a psychosis diagnosis less often involved emergency services (80% vs. 38%, respectively; p value = 1 × 10-7) and more often outpatient primary care (6% vs. 18%; p value = .032) and mental health (32% vs. 49%; p value = .045) services. However, dangerousness indicators were similar (29% vs. 28%; p value = 1). Dangerousness indicators increased to 54% (p value = .002) by the time of eventual diagnosis for those requiring multiple care episodes. CONCLUSIONS: Clinicians were important contributors to delays in diagnosis and treatment of psychosis. Interventions targeting outpatient health care providers may be fruitful in reducing the duration of untreated psychosis.

Potential Roles of Redox Dysregulation in the Development of Schizophrenia.

Converging evidence implicates redox dysregulation as a pathological mechanism driving the emergence of psychosis. Increased oxidative damage and decreased capacity of intracellular redox modulatory systems are consistent findings in persons with schizophrenia as well as in persons at clinical high risk who subsequently developed frank psychosis. Levels of glutathione, a key regulator of cellular redox status, are reduced in the medial prefrontal cortex, striatum, and thalamus in schizophrenia. In humans with schizophrenia and in rodent models recapitulating various features of schizophrenia, redox dysregulation is linked to reductions of parvalbumin containing gamma-aminobutyric acid (GABA) interneurons and volumes of their perineuronal nets, white matter abnormalities, and microglia activation. Importantly, the activity of transcription factors, kinases, and phosphatases regulating diverse aspects of neurodevelopment and synaptic plasticity varies according to cellular redox state. Molecules regulating interneuron function under redox control include NMDA receptor subunits GluN1 and GluN2A as well as KEAP1 (regulator of transcription factor NRF2). In a rodent schizophrenia model characterized by impaired glutathione synthesis, the Gclm knockout mouse, oxidative stress activated MMP9 (matrix metalloprotease 9) via its redox-responsive regulatory sites, causing a cascade of molecular events leading to microglia activation, perineural net degradation, and impaired NMDA receptor function. Molecular pathways under redox control are implicated in the etiopathology of schizophrenia and are attractive drug targets for individualized drug therapy trials in the contexts of prevention and treatment of psychosis.

Polygenic Risk Score Contribution to Psychosis Prediction in a Target Population of Persons at Clinical High Risk.

OBJECTIVE: The 2-year risk of psychosis in persons who meet research criteria for a high-risk syndrome is about 15%-25%; improvements in risk prediction accuracy would benefit the development and implementation of preventive interventions. The authors sought to assess polygenic risk score (PRS) prediction of subsequent psychosis in persons at high risk and to determine the impact of adding the PRS to a previously validated psychosis risk calculator. METHODS: Persons meeting research criteria for psychosis high risk (N=764) and unaffected individuals (N=279) were followed for up to 2 years. The PRS was based on the latest schizophrenia and bipolar genome-wide association studies. Variables in the psychosis risk calculator included stressful life events, trauma, disordered thought content, verbal learning, information processing speed, and family history of psychosis. RESULTS: For Europeans, the PRS varied significantly by group and was higher in the psychosis converter group compared with both the nonconverter and unaffected groups, but was similar for the nonconverter group compared with the unaffected group. For non-Europeans, the PRS varied significantly by group; the difference between the converters and nonconverters was not significant, but the PRS was significantly higher in converters than in unaffected individuals, and it did not differ between nonconverters and unaffected individuals. The R2liability (R2 adjusted for the rate of disease risk in the population being studied, here assuming a 2-year psychosis risk between 10% and 30%) for Europeans varied between 9.2% and 12.3% and for non-Europeans between 3.5% and 4.8%. The amount of risk prediction information contributed by the addition of the PRS to the risk calculator was less than severity of disordered thoughts and similar to or greater than for other variables. For Europeans, the PRS was correlated with risk calculator variables of information processing speed and verbal memory. CONCLUSIONS: The PRS discriminates psychosis converters from nonconverters and modestly improves individualized psychosis risk prediction when added to a psychosis risk calculator. The schizophrenia PRS shows promise in enhancing risk prediction in persons at high risk for psychosis, although its potential utility is limited by poor performance in persons of non-European ancestry.

Tobacco use and psychosis risk in persons at clinical high risk.

AIM: To evaluate the role of tobacco use in the development of psychosis in individuals at clinical high risk. METHOD: The North American Prodrome Longitudinal Study is a 2-year multi-site prospective case control study of persons at clinical high risk that aims to better understand predictors and mechanisms for the development of psychosis. The cohort consisted of 764 clinical high risk and 279 healthy comparison subjects. Clinical assessments included tobacco and substance use and several risk factors associated with smoking in general population studies. RESULTS: Clinical high risk subjects were more likely to smoke cigarettes than unaffected subjects (light smoking odds ratio [OR] = 3.0, 95% confidence interval [CI] = 1.9-5; heavy smoking OR = 4.8, 95% CI = 1.7-13.7). In both groups, smoking was associated with mood, substance use, stress and perceived discrimination and in clinical high risk subjects with childhood emotional neglect and adaption to school. Clinical high risk subjects reported higher rates of several factors previously associated with smoking, including substance use, anxiety, trauma and perceived discrimination. After controlling for these potential factors, the relationship between clinical high risk state and smoking was no longer significant (light smoking OR = 0.9, 95% CI = 0.4-2.2; heavy smoking OR = 0.3, 95% CI = 0.05-2.3). Moreover, baseline smoking status (hazard ratio [HR] = 1.16, 95% CI = 0.82-1.65) and categorization as ever smoked (HR = 1.3, 95% CI = 0.8-2.1) did not predict time to conversion. CONCLUSION: Persons at high risk for psychosis are more likely to smoke and have more factors associated with smoking than controls. Smoking status in clinical high risk subjects does not predict conversion. These findings do not support a causal relationship between smoking and psychosis.

Networks of blood proteins in the neuroimmunology of schizophrenia.

Levels of certain circulating cytokines and related immune system molecules are consistently altered in schizophrenia and related disorders. In addition to absolute analyte levels, we sought analytes in correlation networks that could be prognostic. We analyzed baseline blood plasma samples with a Luminex platform from 72 subjects meeting criteria for a psychosis clinical high-risk syndrome; 32 subjects converted to a diagnosis of psychotic disorder within two years while 40 other subjects did not. Another comparison group included 35 unaffected subjects. Assays of 141 analytes passed early quality control. We then used an unweighted co-expression network analysis to identify highly correlated modules in each group. Overall, there was a striking loss of network complexity going from unaffected subjects to nonconverters and thence to converters (applying standard, graph-theoretic metrics). Graph differences were largely driven by proteins regulating tissue remodeling (e.g. blood-brain barrier). In more detail, certain sets of antithetical proteins were highly correlated in unaffected subjects (e.g. SERPINE1 vs MMP9), as expected in homeostasis. However, for particular protein pairs this trend was reversed in converters (e.g. SERPINE1 vs TIMP1, being synthetical inhibitors of remodeling of extracellular matrix and vasculature). Thus, some correlation signals strongly predict impending conversion to a psychotic disorder and directly suggest pharmaceutical targets.

The Role of microRNA Expression in Cortical Development During Conversion to Psychosis.

In a recent report of the North American Prodrome Longitudinal Study (NAPLS), clinical high-risk individuals who converted to psychosis showed a steeper rate of cortical gray matter reduction compared with non-converters and healthy controls, and the rate of cortical thinning was correlated with levels of proinflammatory cytokines at baseline. These findings suggest a critical role for microglia, the resident macrophages in the brain, in perturbations of cortical maturation processes associated with onset of psychosis. Elucidating gene expression pathways promoting microglial action prior to disease onset would inform potential preventative intervention targets. Here we used a forward stepwise regression algorithm to build a classifier of baseline microRNA expression in peripheral leukocytes associated with annualized rate of cortical thinning in a subsample of the NAPLS cohort (N=74). Our cortical thinning classifier included nine microRNAs, p=3.63 × 10-08, R2=0.358, permutation-based p=0.039, the gene targets of which were enriched for intracellular signaling pathways that are important to coordinating inflammatory responses within immune cells (p<0.05, Benjamini-Hochberg corrected). The classifier was also related to proinflammatory cytokine levels in serum (p=0.038). Furthermore, miRNAs that predicted conversion status were found to do so in a manner partially mediated by rate of cortical thinning (point estimate=0.078 (95% CIs: 0.003, 0.168), p=0.03). Many of the miRNAs identified here have been previously implicated in brain development, synaptic plasticity, immune function and/or schizophrenia, showing some convergence across studies and methodologies. Altered intracellular signaling within the immune system may interact with cortical maturation in individuals at high risk for schizophrenia promoting disease onset.

An Individualized Risk Calculator for Research in Prodromal Psychosis.

OBJECTIVE: Approximately 20%-35% of individuals 12-35 years old who meet criteria for a prodromal risk syndrome convert to psychosis within 2 years. However, this estimate ignores the fact that clinical high-risk cases vary considerably in risk. The authors sought to create a risk calculator, based on profiles of risk indicators, that can ascertain the probability of conversion to psychosis in individual patients. METHOD: The study subjects were 596 clinical high-risk participants from the second phase of the North American Prodrome Longitudinal Study who were followed up to the time of conversion to psychosis or last contact (up to 2 years). The predictors examined were limited to those that are supported by previous studies and are readily obtainable in general clinical settings. Time-to-event regression was used to build a multivariate model predicting conversion, with internal validation using 1,000 bootstrap resamples. RESULTS: The 2-year probability of conversion to psychosis was 16%. Higher levels of unusual thought content and suspiciousness, greater decline in social functioning, lower verbal learning and memory performance, slower speed of processing, and younger age at baseline each contributed to individual risk for psychosis. Stressful life events, trauma, and family history of schizophrenia were not significant predictors. The multivariate model achieved a concordance index of 0.71 and, as reported in an article by Carrión et al., published concurrently with this one, was validated in an independent external data set. The results are instantiated in a web-based risk prediction tool envisioned to be most useful in research protocols involving the psychosis prodrome. CONCLUSIONS: A risk calculator comparable in accuracy to those for cardiovascular disease and cancer is available to predict individualized conversion risks in newly ascertained clinical high-risk cases. Given that the risk calculator can be validly applied only for patients who screen positive on the Structured Clinical Interview for Psychosis Risk Syndromes, which requires training to administer, its most immediate uses will be in research on psychosis risk factors and in research-driven clinical (prevention) trials.

Severity of thought disorder predicts psychosis in persons at clinical high-risk.

BACKGROUND: Improving predictive accuracy is of paramount importance for early detection and prevention of psychosis. We sought a symptom severity classifier that would improve psychosis risk prediction. METHODS: Subjects were from two cohorts of the North American Prodrome Longitudinal Study. All subjects met Criteria of Psychosis-Risk States. In Cohort-1 (n=296) we developed a classifier that included those items of the Scale of Psychosis-Risk Symptoms that best distinguished subjects who converted to psychosis from nonconverters, with performance initially validated by randomization tests in Cohort-1. Cohort-2 (n=592) served as an independent test set. RESULTS: We derived 2-Item and 4-Item subscales. Both included unusual thought content and suspiciousness; the latter added reduced ideational richness and difficulties with focus/concentration. The Concordance Index (C-Index), a measure of discrimination, was similar for each subscale across cohorts (4-Item subscale Cohort-2: 0.71, 95% CI=[0.64, 0.77], Cohort-1: 0.74, 95% CI=[0.69, 0.80]; 2-Item subscale Cohort-2: 0.68, 95% CI=[0.3, 0.76], Cohort-1: 0.72, 95% CI=[0.66-0.79]). The 4-Item performed better than the 2-Item subscale in 742/1000 random selections of 80% subsets of Cohort-2 subjects (p-value=1.3E-55). Subscale calibration between cohorts was proportional (higher scores/lower survival), but absolute conversion risk predicted from Cohort-1 was higher than that observed in Cohort-2, reflecting the cohorts' differences in 2-year conversion rates (Cohort-2: 0.16, 95% CI=[0.13, 0.19]; Cohort-1: 0.30, 95% CI=[0.24, 0.36]). CONCLUSION: Severity of unusual thought content, suspiciousness, reduced ideational richness, and difficulty with focus/concentration informed psychosis risk prediction. Scales based on these symptoms may have utility in research and, assuming further validation, eventual clinical applications.

Towards a psychosis risk blood diagnostic for persons experiencing high-risk symptoms: preliminary results from the NAPLS project.

INTRODUCTION: A barrier to preventative treatments for psychosis is the absence of accurate identification of persons at highest risk. A blood test that could substantially increase diagnostic accuracy would enhance development of psychosis prevention interventions. METHODS: The North American Prodrome Longitudinal Study project is a multisite endeavor that aims to better understand predictors and mechanisms for the development of psychosis. In this study, we measured expression of plasma analytes reflecting inflammation, oxidative stress, hormones, and metabolism. A "greedy algorithm" selected analytes that best distinguished persons with clinical high-risk symptoms who developed psychosis (CHR-P; n = 32) from unaffected comparison (UC) subjects (n = 35) and from those who did not develop psychosis during a 2-year follow-up (CHR-NP; n = 40). RESULTS: The classifier included 15 analytes (selected from 117), with an area under the receiver operating curve for CHR-P vs UC of 0.91 and CHR-P vs CHR-NP of 0.88. Randomly scrambled group membership followed by reconstructions of the entire classifier method yielded consistently weak classifiers, indicating that the true classifier is highly unlikely to be a chance occurrence. Such randomization methods robustly imply the assays contain consistent information distinguishing the groups which was not obscured by the data normalization method and was revealed by classifier construction. These results support the hypothesis that inflammation, oxidative stress, and dysregulation of hypothalamic-pituitary axes may be prominent in the earliest stages of psychosis. CONCLUSION: If confirmed in other groups of persons at elevated risk of psychosis, a multiplex blood assay has the potential for high clinical utility.

A flexible and qualitatively stable model for cell cycle dynamics including DNA damage effects.

This paper includes a conceptual framework for cell cycle modeling into which the experimenter can map observed data and evaluate mechanisms of cell cycle control. The basic model exhibits qualitative stability, meaning that regardless of magnitudes of system parameters its instances are guaranteed to be stable in the sense that all feasible trajectories converge to a certain trajectory. Qualitative stability can also be described by the signs of real parts of eigenvalues of the system matrix. On the biological side, the resulting model can be tuned to approximate experimental data pertaining to human fibroblast cell lines treated with ionizing radiation, with or without disabled DNA damage checkpoints. Together these properties validate a fundamental, first order systems view of cell dynamics. Classification Codes: 15A68.

Nuclear and cytoplasmic localization of neural stem cell microRNAs.

Although generally regarded as functional in the cytoplasm, a number of microRNAs (miRNAs) have been found in the nucleus, possibly with a role in gene regulation. Here we report that, in fact, a substantial fraction of all human miRNAs are present in the nucleus of neural stem cells. Further, subsets of these miRNAs display consistently higher standardized rank in the nucleus than in the cytoplasm of these cells, as identified with an RT-qPCR technology and confirmed by microarray analysis. Likewise, other miRNAs display higher cytoplasmic standardized ranks. Three samples were partitioned into nuclear and cytoplasmic fractions in six assays for 373 miRNAs. From the 100 most highly expressed miRNAs, standard scores of nuclear and cytoplasmic concentrations were determined. Among those, 21 miRNAs had all three nuclear standard scores higher than all three cytoplasmic scores; likewise, 31 miRNAs had consistently higher cytoplasmic scores. Random concentrations would result in only five in each set. Remarkably, if one miRNA has a high standard score in a compartment, then other miRNAs having the same 5' seeds and certain similar 3' end patterns are also highly scored in the same way. That is, in addition to the seed sequence, 3' sequence similarity criteria identify families of mature miRNAs with consistently high nuclear or cytoplasmic expression.

Gene processing control loops suggested by sequencing, splicing, and RNA folding.

BACKGROUND: Small RNAs are known to regulate diverse gene expression processes including translation, transcription, and splicing. Among small RNAs, the microRNAs (miRNAs) of 17 to 27 nucleotides (nts) undergo biogeneses including primary transcription, RNA excision and folding, nuclear export, cytoplasmic processing, and then bioactivity as regulatory agents. We propose that analogous hairpins from RNA molecules that function as part of the spliceosome might also be the source of small, regulatory RNAs (somewhat smaller than miRNAs). RESULTS: Deep sequencing technology has enabled discovery of a novel 16-nt RNA sequence in total RNA from human brain that we propose is derived from RNU1, an RNA component of spliceosome assembly. Bioinformatic alignments compel inquiring whether the novel 16-nt sequence or its precursor have a regulatory function as well as determining aspects of how processing intersects with the miRNA biogenesis pathway. Specifically, our preliminary in silico investigations reveal the sequence could regulate splicing factor Arg/Ser rich 1 (SFRS1), a gene coding an essential protein component of the spliceosome. All 16-base source sequences in the UCSC Human Genome Browser are within the 14 instances of RNU1 genes listed in wgEncodeGencodeAutoV3. Furthermore, 10 of the 14 instances of the sequence are also within a common 28-nt hairpin-forming subsequence of RNU1. CONCLUSIONS: An abundant 16-nt RNA sequence is sourced from a spliceosomal RNA, lies in a stem of a predicted RNA hairpin, and includes reverse complements of subsequences of the 3'UTR of a gene coding for a spliceosome protein. Thus RNU1 could function both as a component of spliceosome assembly and as inhibitor of production of the essential, spliceosome protein coded by SFRS1. Beyond this example, a general procedure is needed for systematic discovery of multiple alignments of sequencing, splicing, and RNA folding data.

CHI conference on microRNAs: dramatic expansion of research tools and discoveries.

The Cambridge Health Institute's sixth annual conference on microRNAs integrated exceedingly diverse academic and commercial interests. Included were novel technologies for microRNA profiling and nucleic acid sequencing, drug delivery technologies using gene therapy, and promising diagnoses and treatments for various diseases, especially types of cancer. The conference format comprised 42 presentations, each 25 min in length. This article gives telegraphic descriptions of ten of the presentations, to illustrate the range of conference topics. At least two other mutually nonintersecting choices of ten could have been used with equal effect.

Additional layers of gene regulatory complexity from recently discovered microRNA mechanisms.

In recent years microRNAs have become recognized as pervasive, versatile agents of gene regulation. Some widely embraced rules involving Watson-Crick hybridization of microRNAs with mRNAs have generated great interest as scientists envision potential RNA cargoes for gene therapy and other experimental systems. However, while researchers ardently seek simplifying principles, nature seems very uncooperative. This article reviews some small RNA mechanisms that potentially regulate genes and which are not covered by previous microRNAs characterizations. In addition, we report here results of fluorescence microscopy experiments to directly demonstrate nuclear import of small RNAs equal in length to typical mature microRNAs, implying that gene regulation at the locus of transcription might be possible.

Diagnostic microRNA markers for screening sporadic human colon cancer and active ulcerative colitis in stool and tissue.

By routinely and systematically being able to perform quantitative stem-loop reverse transcriptase followed by TaqMan PCR expression analysis on stool and tissue samples using fifteen human (Homo sapiens, hsa) micro(mi)RNA genes selected by careful analysis of the peer-reviewed literature, we were able to monitor changes at various stages of CRC, allowing for reliable diagnostic screening of colon cancer particularly at the early, pre-malignant stages, and for difficult-to-treat active ulcerative colitis (UC). Although the expression of some of the miRNA genes tested in tissue showed less variability in CRC or UC patients than in stool, the stool by itself appears well-suited to screening. A miRNA approach using stool samples promises to offer more sensitivity and specificity than currently used screening genomic, methylomic or proteomic methods for colon cancer. Larger prospective clinical studies utilizing stool derived from many control, colon cancer or UC patients, to allow for a statistically valid analysis, are now urgently required to standardize test performance and determine the true sensitivity and specificity of the miRNA screening approach, and to provide a numerical underpinning for these diseases as a function of total RNA. Moreover, when a miRNA screening test is combined with analysis of a messenger(m)RNA expression test, which has also been considered in earlier studies to be a highly sensitive and a very specific and reliable transcriptomic approach, as outlined in this article, bioinformatics can be used to correlate microRNA seed data with mRNA target data in order to gain a mechanistic understanding of how miRNAs regulate gene expression, enabling understanding of why these miRNA genes should be informative in a screening test.

Discovering collectively informative descriptors from high-throughput experiments.

BACKGROUND: Improvements in high-throughput technology and its increasing use have led to the generation of many highly complex datasets that often address similar biological questions. Combining information from these studies can increase the reliability and generalizability of results and also yield new insights that guide future research. RESULTS: This paper describes a novel algorithm called BLANKET for symmetric analysis of two experiments that assess informativeness of descriptors. The experiments are required to be related only in that their descriptor sets intersect substantially and their definitions of case and control are consistent. From resulting lists of n descriptors ranked by informativeness, BLANKET determines shortlists of descriptors from each experiment, generally of different lengths p and q. For any pair of shortlists, four numbers are evident: the number of descriptors appearing in both shortlists, in exactly one shortlist, or in neither shortlist. From the associated contingency table, BLANKET computes Right Fisher Exact Test (RFET) values used as scores over a plane of possible pairs of shortlist lengths 12. BLANKET then chooses a pair or pairs with RFET score less than a threshold; the threshold depends upon n and shortlist length limits and represents a quality of intersection achieved by less than 5% of random lists. CONCLUSIONS: Researchers seek within a universe of descriptors some minimal subset that collectively and efficiently predicts experimental outcomes. Ideally, any smaller subset should be insufficient for reliable prediction and any larger subset should have little additional accuracy. As a method, BLANKET is easy to conceptualize and presents only moderate computational complexity. Many existing databases could be mined using BLANKET to suggest optimal sets of predictive descriptors.

microRNA expression in the prefrontal cortex of individuals with schizophrenia and schizoaffective disorder.

BACKGROUND: microRNAs (miRNAs) are small, noncoding RNA molecules that are now thought to regulate the expression of many mRNAs. They have been implicated in the etiology of a variety of complex diseases, including Tourette's syndrome, Fragile x syndrome, and several types of cancer. RESULTS: We hypothesized that schizophrenia might be associated with altered miRNA profiles. To investigate this possibility we compared the expression of 264 human miRNAs from postmortem prefrontal cortex tissue of individuals with schizophrenia (n = 13) or schizoaffective disorder (n = 2) to tissue of 21 psychiatrically unaffected individuals using a custom miRNA microarray. Allowing a 5% false discovery rate, we found that 16 miRNAs were differentially expressed in prefrontal cortex of patient subjects, with 15 expressed at lower levels (fold change 0.63 to 0.89) and 1 at a higher level (fold change 1.77) than in the psychiatrically unaffected comparison subjects. The expression levels of 12 selected miRNAs were also determined by quantitative RT-PCR in our lab. For the eight miRNAs distinguished by being expressed at lower microarray levels in schizophrenia samples versus comparison samples, seven were also expressed at lower levels with quantitative RT-PCR. CONCLUSION: This study is the first to find altered miRNA profiles in postmortem prefrontal cortex from schizophrenia patients.