<scp>RNA</scp> sequencing in post‐mortem human brains of neuropsychiatric disorders

Chun, Wang; Bendriem, Raphael M.; Garamszegi, Susanna P.; Song, Lei; Lee, Chun-Ting

doi:10.1111/pcn.12550

Cited by 17 publications

(11 citation statements)

References 88 publications

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“…It has also enabled the identification of gene expression differences between healthy and diseased tissues 38 . However, one major challenge with gene expression studies of human tissues is that many investigations use tissues that were collected post-mortem 23–31,39 and thus, how these findings reflect RNA expression levels of living tissues remains to be characterized 40 . A recent study using tissues obtained through GTEx (Genotype-Tissue Expression) analyzed the RNA expression of 41 human tissues post-mortem and provides access to tissue samples from donors with PMIs ranging from immediately after death up to 24 h post-mortem 41 .…”

Section: Discussionmentioning

confidence: 99%

Tissue- and Species-Specific Patterns of RNA metabolism in Post-Mortem Mammalian Retina and Retinal Pigment Epithelium

Kallestad

Blackshaw

Khalil

et al. 2019

Sci Rep

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Accurate analysis of gene expression in human tissues using RNA sequencing is dependent on the quality of source material. One major source of variation in mRNA quality is post-mortem time. While it is known that individual transcripts show differential post-mortem stability, few studies have directly and comprehensively analyzed mRNA stability following death, and in particular the extent to which tissue- and species-specific factors influence post-mortem mRNA stability are poorly understood. This knowledge is particularly important for ocular tissues studies, where tissues obtained post-mortem are frequently used for research or therapeutic applications. To directly investigate this question, we profiled mRNA levels in both neuroretina and retinal pigment epithelium (RPE) from mouse and baboon over a series of post-mortem intervals. We found substantial changes in gene expression as early as 15 minutes in the mouse and as early as three hours in the baboon eye tissues. Importantly, our findings demonstrate both tissue- and species- specific patterns of RNA metabolism, by identifying a set of genes that are either rapidly degraded or very stable in both species and/or tissues. Taken together, the data from this study lay the foundation for understanding RNA regulation post-mortem and provide novel insights into RNA metabolism in the tissues of the mammalian eye.

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Section: Discussionmentioning

confidence: 99%

Tissue- and Species-Specific Patterns of RNA metabolism in Post-Mortem Mammalian Retina and Retinal Pigment Epithelium

Kallestad

Blackshaw

Khalil

et al. 2019

Sci Rep

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“…Bipolar is a serious mental illness with considerable public health implications. However, our understanding of biological mechanisms of bipolar remain frustratingly limited in part due to difficulty in accessing human brain samples (Wu et al, 2017a). Many individual bipolar transcriptomics studies contain only tens of samples (Table 1), which may contribute to a lack of reproducibility in genes and pathways identified from each study.…”

Section: Discussionmentioning

confidence: 99%

“…Transcriptomics technologies such as next-generation sequencing (NGS) based RNA-Sequencing (RNA-Seq) and DNA chip based gene expression microarray provide a high-throughput and cost-effective solution to evaluate whole-genome gene expression signatures (Ramasamy et al, 2008; Wu et al, 2017a). These platforms enable researchers to measure tens of thousands of genes simultaneously and have become one of the most widely used approaches in biological research.…”

Section: Introductionmentioning

confidence: 99%

“…These studies typically use postmortem brain tissues, which is the most relevant for bipolar. However, due to the relative instability of RNA, these gene expression studies are often influenced by factors such as postmortem interval (PMI) (Li et al, 2003), freezer interval and cause of death (Tomita et al, 2004; Wu et al, 2017a). As a result, the genes and pathways identified from individual studies have largely been inconsistent.…”

Section: Introductionmentioning

confidence: 99%

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Integrative Analysis of DiseaseLand Omics Database for Disease Signatures and Treatments: A Bipolar Case Study

et al. 2019

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Transcriptomics technologies such as next-generation sequencing and microarray platforms provide exciting opportunities for improving diagnosis and treatment of complex diseases. Transcriptomics studies often share similar hypotheses, but are carried out on different platforms, in different conditions, and with different analysis approaches. These factors, in addition to small sample sizes, can result in a lack of reproducibility. A clear understanding and unified picture of many complex diseases are still elusive, highlighting an urgent need to effectively integrate multiple transcriptomic studies for disease signatures. We have integrated more than 3,000 high-quality transcriptomic datasets in oncology, immunology, neuroscience, cardiovascular and metabolic disease, and from both public and internal sources (DiseaseLand database). We established a systematic data integration and meta-analysis approach, which can be applied in multiple disease areas to create a unified picture of the disease signature and prioritize drug targets, pathways, and compounds. In this bipolar case study, we provided an illustrative example using our approach to combine a total of 30 genome-wide gene expression studies using postmortem human brain samples. First, the studies were integrated by extracting raw FASTQ or CEL files, then undergoing the same procedures for preprocessing, normalization, and statistical inference. Second, both p -value and effect size based meta-analysis algorithms were used to identify a total of 204 differentially expressed (DE) genes (FDR < 0.05) genes in the prefrontal cortex. Among these were BDNF , VGF , WFS1 , DUSP6 , CRHBP , MAOA , and RELN , which have previously been implicated in bipolar disorder. Finally, pathway enrichment analysis revealed a role for GPCR, MAPK, immune, and Reelin pathways. Compound profiling analysis revealed MAPK and other inhibitors may modulate the DE genes. The ability to robustly combine and synthesize the information from multiple studies enables a more powerful understanding of this complex disease.

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“…Again, in the case of the brain, regional changes in gene expression can be enormous. 17 It is a complex tissue and choosing the right regions for comparison is often the most important decision for the analysis. For example, in the case of targeted mutation mouse models generated by homologous recombination the changes in the transcriptome of the brain are regionally very different.…”

Section: Sources Of the Transcriptomementioning

confidence: 99%

At the dawn of the transcriptomic medicine

Kõks¹,

Pfaff

Bubb

et al. 2020

Exp Biol Med (Maywood)

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Impact statement This review describes the impact of transcriptomics on experimental biology and its integration into medical practice. Transcriptomics is an essential part of modern biomedical research based on highly sophisticated and reliable technology. Transcriptomics can aid clinical practice and improve the precision of clinical diagnoses and decision-making by complementing existing clinical best practice. The power of which will be increased when combined with genomic variation from genome wide association studies and next generation sequencing. We are witnessing the implementation of RNA-based technologies in clinical practice that will eventually lead to the establishment of transcriptional medicine as a routine tool in diagnosis. Progress in genomic analytical technologies has improved our possibilities to obtain information regarding DNA, RNA, and their dynamic changes that occur over time or in response to specific challenges. This information describes the blueprint for cells, tissues, and organisms and has fundamental importance for all living organisms. This review focuses on the technological challenges to analyze the transcriptome and what is the impact of transcriptomics on precision medicine. The transcriptome is a term that covers all RNA present in cells and a substantial part of it will never be translated into protein but is nevertheless functional in determining cell phenotype. Recent developments in transcriptomics have challenged the fundamentals of the central dogma of biology by providing evidence of pervasive transcription of the genome. Such massive transcriptional activity is challenging the definition of a gene and especially the term “pseudogene” that has now been demonstrated in many examples to be both transcribed and translated. We also review the common sources of biomaterials for transcriptomics and justify the suitability of whole blood RNA as the current optimal analyte for clinical transcriptomics. At the end of the review, a brief overview of the clinical implications of transcriptomics in clinical trial design and clinical diagnosis is given. Finally, we introduce the transcriptome as a target for modern drug development as a tool for extending our capacity for precision medicine in multiple diseases.

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RNA sequencing in post‐mortem human brains of neuropsychiatric disorders

Cited by 17 publications

References 88 publications

Tissue- and Species-Specific Patterns of RNA metabolism in Post-Mortem Mammalian Retina and Retinal Pigment Epithelium

Tissue- and Species-Specific Patterns of RNA metabolism in Post-Mortem Mammalian Retina and Retinal Pigment Epithelium

Integrative Analysis of DiseaseLand Omics Database for Disease Signatures and Treatments: A Bipolar Case Study

At the dawn of the transcriptomic medicine

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