Protocol for the Systematic Fixation, Circuit-Based Sampling, and Qualitative and Quantitative Neuropathological Analysis of Human Brain Tissue

Human brain tissue has long been a critical resource for neuroanatomy and neuropathology, but with the advent of advanced imaging and molecular sequencing techniques, it has become possible to use human brain tissue to study, in great detail, the structural, molecular, and even functional underpinnings of human brain disease. In the century following the first description of Alzheimer's disease (AD), numerous technological advances applied to human tissue have enabled novel diagnostic approaches using diverse physical and molecular biomarkers, and many drug therapies have been tested in clinical trials (Schachter and Davis, Dialogues Clin Neurosci 2:91-100, 2000). The methods for brain procurement and tissue stabilization have remained somewhat consistently focused on formalin fixation and freezing. Although these methods have enabled research protocols of multiple modalities, new, more advanced technologies demand improved methodologies for the procurement, characterization, stabilization, and preparation of both normal and diseased human brain tissues. Here, we describe our current protocols for the procurement and characterization of fixed brain tissue, to enable systematic and precisely targeted diagnoses, and describe the novel, quantitative molecular, and neuroanatomical studies that broadly expand the use of formalin-fixed, paraffin-embedded (FFPE) tissue that will further our understanding of the mechanisms underlying human neuropathologies.

Identifying Plasma Biomarkers with high specificity for major depressive disorder: A multi-level proteomics study

BACKGROUND

There are currently no objective diagnostic biomarkers for major depressive disorder (MDD) due to the biological complexity of the disorder. The existence of blood-based biomarkers with high specificity would be convenient for the clinical diagnosis of MDD.

METHODS

A comprehensive plasma proteomic analysis was conducted in a highly homogeneous cohort [7 drug-naïve MDD patients and 7 healthy controls (HCs)], with bioinformatics analysis combined with machine learning used to screen candidate proteins. Verification of reproducibility and specificity was conducted in independent cohorts [60 HCs and 74 MDD, 42 schizophrenia (SZ) and 39 bipolar I disorder (BD-I) drug-naïve patients]. Furthermore, verification of consistency was accomplished by proteomic analysis of postmortem brain tissue from 16 MDD patients and 16 HCs.

RESULTS

Levels of C-reactive protein (CRP), antithrombin III (ATIII), inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4) and vitamin D-binding protein (VDB) were significantly higher in MDD patients, both in the discovery cohort and independent replication cohort. In comparison with SZ or BD-I patients, two proteins (VDB and ITIH4) were significantly elevated only in MDD patients. In addition, increased VDB and ITIH4 were observed consistently in both plasma and postmortem dorsolateral prefrontal cortex tissues of MDD patients. Furthermore, a panel consisting of all four plasma proteins was able to distinguish MDD patients from HCs or SZ or BD-I patients with the highest accuracy.

CONCLUSION

Plasma ITIH4 and VDB may be potential plasma biomarkers of MDD with high specificity. The four-protein panel is more suitable as a potential clinical diagnostic marker for MDD.

RNA-Seq reveals novel transcriptional reorganization in human alcoholic brain

DNA microarrays have been used for over a decade to profile gene expression on a genomic scale. While this technology has advanced our understanding of complex cellular function, the reliance of microarrays on hybridization kinetics results in several technical limitations. For example, knowledge of the sequences being probed is required, distinguishing similar sequences is difficult because of cross-hybridization, and the relatively narrow dynamic range of the signal limits sensitivity. Recently, new technologies have been introduced that are based on novel sequencing methodologies. These next-generation sequencing methods do not have the limitations inherent to microarrays. Next-generation sequencing is unique since it allows the detection of all known and novel RNAs present in biological samples without bias toward known transcripts. In addition, the expression of coding and noncoding RNAs, alternative splicing events, and expressed single nucleotide polymorphisms (SNPs) can be identified in a single experiment. Furthermore, this technology allows for remarkably higher throughput while lowering sequencing costs. This significant shift in throughput and pricing makes low-cost access to whole genomes possible and more importantly expands sequencing applications far beyond traditional uses (Morozova & Marra, 2008) to include sequencing the transcriptome (RNA-Seq), providing detail on gene structure, alternative splicing events, expressed SNPs, and transcript size (Mane et al., 2009; Tang et al., 2009; Walter et al., 2009), in a single experiment, while also quantifying the absolute abundance of genes, all with greater sensitivity and dynamic range than the competing cDNA microarray technology (Mortazavi, Williams, McCue, Schaeffer, & Wold, 2008).