Brain pH has a significant impact on human postmortem hippocampal gene expression profiles

Permutation-based adjustments for the significance of partial regression coefficients in microarray data analysis

The aim of this paper is to generalize permutation methods for multiple testing adjustment of significant partial regression coefficients in a linear regression model used for microarray data. Using a permutation method outlined by Anderson and Legendre [1999] and the permutation P-value adjustment from Simon et al. [2004], the significance of disease related gene expression will be determined and adjusted after accounting for the effects of covariates, which are not restricted to be categorical. We apply these methods to a microarray dataset containing confounders and illustrate the comparisons between the permutation-based adjustments and the normal theory adjustments. The application of a linear model is emphasized for data containing confounders and the permutation-based approaches are shown to be better suited for microarray data.

Effect of RNA quality on transcript intensity levels in microarray analysis of human post-mortem brain tissues

Background

Large-scale gene expression analysis of post-mortem brain tissue offers unique opportunities for investigating genetic mechanisms of psychiatric and neurodegenerative disorders. On the other hand microarray data analysis associated with these studies is a challenging task. In this publication we address the issue of low RNA quality data and corresponding data analysis strategies.

Results

A detailed analysis of effects of post chip RNA quality on the measured abundance of transcripts is presented. Overall Affymetrix GeneChip data (HG-U133_AB and HG-U133_Plus_2.0) derived from ten different brain regions was investigated. Post chip RNA quality being assessed by 5'/3' ratio of housekeeping genes was found to introduce a well pronounced systematic noise into the measured transcript expression levels. According to this study RNA quality effects have: 1) a "random" component which is introduced by the technology and 2) a systematic component which depends on the features of the transcripts and probes. Random components mainly account for numerous negative correlations of low-abundant transcripts. These negative correlations are not reproducible and are mainly introduced by an increased relative level of noise. Three major contributors to the systematic noise component were identified: the first is the probe set distribution, the second is the length of mRNA species, and the third is the stability of mRNA species. Positive correlations reflect the 5'-end to 3'-end direction of mRNA degradation whereas negative correlations result from the compensatory increase in stable and 3'-end probed transcripts. Systematic components affect the expressed transcripts by introducing irrelevant gene correlations and can strongly influence the results of the main experiment. A linear model correcting the effect of RNA quality on measured intensities was introduced.

In addition the contribution of a number of pre-mortem and post-mortem attributes to the overall detected RNA quality effect was investigated. Brain pH, duration of agonal stage, post-mortem interval before sampling and donor's age of death within considered limits were found to have no significant contribution.

Conclusion

Basic conclusions for data analysis in expression profiling study are as follows: 1) testing for RNA quality dependency should be included in the preprocessing of the data; 2) investigating inter-gene correlation without regard to RNA quality effects could be misleading; 3) data normalization procedures relying on housekeeping genes either do not influence the correlation structure (if 3'-end intensities are used) or increase it for negatively correlated transcripts (if 5'-end or median intensities are included in normalization procedure); 4) sample sets should be matched with regard to RNA quality; 5) RMA preprocessing is more sensitive to RNA quality effect, than MAS 5.0.

Mitochondrial involvement in psychiatric disorders

Recent findings of mitochondrial abnormalities in brains from subjects with neurological disorders have led to a renewed search for mitochondrial abnormalities in psychiatric disorders. A growing body of evidence suggests that there is mitochondrial dysfunction in schizophrenia, bipolar disorder, and major depressive disorder, including evidence from electron microscopy, imaging, gene expression, genotyping, and sequencing studies. Specific evidence of dysfunction such as increased common deletion and decreased gene expression in mitochondria in psychiatric illnesses suggests that direct examination of mitochondrial DNA from postmortem brain cells may provide further details of mitochondrial alterations in psychiatric disorders.

Stress-induced changes in primate prefrontal profiles of gene expression

Stressful experiences that consistently increase cortisol levels appear to alter the expression of hundreds of genes in prefrontal limbic brain regions. Here, we investigate this hypothesis in monkeys exposed to intermittent social stress-induced episodes of hypercortisolism or a no-stress control condition. Prefrontal profiles of gene expression compiled from Affymetrix microarray data for monkeys randomized to the no-stress condition were consistent with microarray results published for healthy humans. In monkeys exposed to intermittent social stress, more genes than expected by chance appeared to be differentially expressed in ventromedial prefrontal cortex compared to monkeys not exposed to adult social stress. Most of these stress responsive candidate genes were modestly downregulated, including ubiquitin conjugation enzymes and ligases involved in synaptic plasticity, cell cycle progression and nuclear receptor signaling. Social stress did not affect gene expression beyond that expected by chance in dorsolateral prefrontal cortex or prefrontal white matter. Thirty four of 48 comparisons chosen for verification by quantitative real-time polymerase chain reaction (qPCR) were consistent with the microarray-predicted result. Furthermore, qPCR and microarray data were highly correlated. These results provide new insights on the regulation of gene expression in a prefrontal corticolimbic region involved in the pathophysiology of stress and major depression. Comparisons between these data from monkeys and those for ventromedial prefrontal cortex in humans with a history of major depression may help to distinguish the molecular signature of stress from other confounding factors in human postmortem brain research.

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.

Lack of RIC-3 congruence with β2 subunit-containing nicotinic acetylcholine receptors in bipolar disorder

Nicotinic acetylcholine receptor (nAChR) dysfunction occurs in individuals with schizophrenia (SZ) and may also affect individuals with bipolar disorder (BP). The molecular mechanisms for these disease-associated cholinergic deficits are not known. In vitro, the protein RIC-3 (resistance to inhibitors of cholinesterase-3) aids the assembly and trafficking of alpha7-nAChRs but has unclear action on the biogenesis of alpha4/beta2-nAChRs. To evaluate RIC-3/nAChR dynamics in diseased and normal human brain tissue, we measured RIC-3, alpha7-, alpha4- and beta2-nAChRs transcript levels in postmortem prefrontal cortex of individuals with SZ (n=31), BP (n=28) and unaffected controls (NC, n=33). Of the 28 individuals with BP, 20 had a history of psychotic symptoms. We compared relative message abundances between diagnostic groups and tested correlations of RIC-3 with each nAChR message subtype. RIC-3 and alpha4 messages were significantly increased in BP compared with NC (RIC-3, P< or =0.002; alpha4, P< or =0.04). RIC-3 message was also upregulated in SZ (P< or =0.04). In BP with psychoses, RIC-3 and alpha4 levels were increased compared with BP without psychoses (both P< or =0.02) and compared with NC (RIC-3, P< or =0.0003; alpha4, P< or =0.004). In correlation regression analyses, RIC-3 expression was very highly correlated to alpha7, alpha4 and beta2 in NC (alpha7, P< or =2.5e-05; alpha4, P< or =2.5e-09; beta2, P< or =0.003) and in SZ (alpha7, P< or =1e-07; alpha4, P< or =7e-07; beta2, P< or =3e-09). RIC-3 also strongly correlated with alpha7 and alpha4 in BP (alpha7, P< or =0.003; alpha4, P< or =3.5e-07). RIC-3 was modestly correlated with beta2 in BP overall (P< or =0.04), but showed no significant correlation in BP with psychoses (P< or =0.31) compared with a significant correlation in BP without psychoses (P< or =0.007). In conclusion, coordinated RIC-3/alpha4 upregulation and discordant RIC-3/beta2 levels suggest that alpha4/beta2 nAChR deficits in BP may occur from dysregulated RIC-3 chaperoning of the beta2 nAChR subunit in a subset of patients affected by psychotic features.

Methodological considerations for gene expression profiling of human brain

Gene expression profiles of postmortem brain tissue represent important resources for understanding neuropsychiatric illnesses. The impact(s) of quality covariables on the analysis and results of gene expression studies are important questions. This paper addressed critical variables which might affect gene expression in two brain regions. Four broad groups of quality indicators in gene expression profiling studies (clinical, tissue, RNA, and microarray quality) were identified. These quality control indicators were significantly correlated, however one quality variable did not account for the total variance in microarray gene expression. The data showed that agonal factors and low pH correlated with decreased integrity of extracted RNA in two brain regions. These three parameters also modulated the significance of alterations in mitochondrial-related genes. The average F-ratio summaries across all transcripts showed that RNA degradation from the AffyRNAdeg program accounted for higher variation than all other quality factors. Taken together, these findings confirmed prior studies, which indicated that quality parameters including RNA integrity, agonal factors, and pH are related to differences in gene expression profiles in postmortem brain. Individual candidate genes can be evaluated with these quality parameters in post hoc analysis to help strengthen the relevance to psychiatric disorders. We find that clinical, tissue, RNA, and microarray quality are all useful variables for collection and consideration in study design, analysis, and interpretation of gene expression results in human postmortem studies.

Quality control for microarray analysis of human brain samples: The impact of postmortem factors, RNA characteristics, and histopathology

The quality of results from microarray studies depends on RNA quality, which can be significantly influenced by postmortem factors. The aim of this study was to determine which postmortem factors and/or RNA electropherogram characteristics best correspond to microarray output and can be used to prospectively screen RNA prior to microarray analysis. Total RNA was extracted (N=125) from gray and white matter of postmortem frontal and occipital lobe tissue, acquired from normal controls, and patients with schizophrenia, bipolar disorder or major depression. Electropherograms were generated by the Agilent BioAnalyzer 2100, allowing calculation of the 28S/18S ratio, the 18S/baseline peak ratio and the RNA Integrity Number (RIN). These values were compared to post-hybridization image analysis of Affymetrix microarrays. The postmortem variables correlated with some quality measures but could not be used as effective screening tools. Logistic regression demonstrated that all three electropherogram measures were predictive for microarray quality, and that the RIN threshold predictive of "good quality" (>35% present calls) was most consistent with that of prior studies. The optimal RIN must be determined by the investigator's specifications for false inclusion and false exclusion. In contrast to RIN, the quality threshold for the 28S/18S ratio has proven unacceptably variable, due to sensitivity to slight differences in protocol and/or tissue source. In conclusion, the measures we found useful as screening criteria do not replace the need to exclude samples after a microarray analysis is performed, as an acceptable percent call rate and other measures of microarray quality represent the desired endpoint.

Novel alpha7 nicotinic receptor isoforms and deficient cholinergic transcription in schizophrenia

Abnormal alpha7 nicotinic acetylcholine receptor activity contributes to sensory gating and cognitive deficits in schizophrenic individuals. Negligible differences in alpha7 mRNA levels between disease and control states have led to conclusions that cholinergic dysfunction in schizophrenia (SZ) must occur post-transcriptionally. Alternatively, we propose that the dysregulation of splice variants of the alpha7 receptor could account for cholinergic deficiencies observed in this disease. Here, we isolated multiple alpha7 splice variants including exon deletions and those associated with a novel 124-127 base insertion following exon 4. Transcripts containing this new exon originated from sense strand-oriented RNA (vs. antisense), and in silico translations produced putative subunits with unique amino termini. Quantitative real-time polymerase chain reaction analyses indicated that one novel isoform was significantly downregulated (P < or = 0.03) in post-mortem prefrontal cortex of individuals with SZ (n = 35) compared with controls (n = 34). Ten brain regions (cerebellum, thalamus, corpus callosum, caudate, putamen and five areas of the cortex) were further screened for alpha7 isoforms in three individuals of each group. Semiquantitative analyses showed that each alpha7 mRNA subtype was present in each brain region, but all were particularly deficient in the corpus callosum in schizophrenics vs. controls (P < or = 0.0002 to 0.05 for different isoforms). Our data demonstrate that alpha7 transcription is altered in several ways in SZ, suggesting that transcription-level mechanisms could account in part for the impaired cholinergic neurotransmission observed in this disease.