Matthew D. Li

Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases

IntroductionNeurodegenerative diseases share common pathologic features including neuroinflammation, mitochondrial dysfunction and protein aggregation, suggesting common underlying mechanisms of neurodegeneration. We undertook a meta-analysis of public gene expression data for neurodegenerative diseases to identify a common transcriptional signature of neurodegeneration.ResultsUsing 1,270 post-mortem central nervous system tissue samples from 13 patient cohorts covering four neurodegenerative diseases, we identified 243 differentially expressed genes, which were similarly dysregulated in 15 additional patient cohorts of 205 samples including seven neurodegenerative diseases. This gene signature correlated with histologic disease severity. Metallothioneins featured prominently among differentially expressed genes, and functional pathway analysis identified specific convergent themes of dysregulation. MetaCore network analyses revealed various novel candidate hub genes (e.g. STAU2). Genes associated with M1-polarized macrophages and reactive astrocytes were strongly enriched in the meta-analysis data. Evaluation of genes enriched in neurons revealed 70 down-regulated genes, over half not previously associated with neurodegeneration. Comparison with aging brain data (3 patient cohorts, 221 samples) revealed 53 of these to be unique to neurodegenerative disease, many of which are strong candidates to be important in neuropathogenesis (e.g. NDN, NAP1L2). ENCODE ChIP-seq analysis predicted common upstream transcriptional regulators not associated with normal aging (REST, RBBP5, SIN3A, SP2, YY1, ZNF143, IKZF1). Finally, we removed genes common to neurodegeneration from disease-specific gene signatures, revealing uniquely robust immune response and JAK-STAT signaling in amyotrophic lateral sclerosis.ConclusionsOur results implicate pervasive bioenergetic deficits, M1-type microglial activation and gliosis as unifying themes of neurodegeneration, and identify numerous novel genes associated with neurodegenerative processes.

Mouse models rarely mimic the transcriptome of human neurodegenerative diseases: A systematic bioinformatics-based critique of preclinical models

Translational research for neurodegenerative disease depends intimately upon animal models. Unfortunately, promising therapies developed using mouse models mostly fail in clinical trials, highlighting uncertainty about how well mouse models mimic human neurodegenerative disease at the molecular level. We compared the transcriptional signature of neurodegeneration in mouse models of Alzheimer׳s disease (AD), Parkinson׳s disease (PD), Huntington׳s disease (HD) and amyotrophic lateral sclerosis (ALS) to human disease. In contrast to aging, which demonstrated a conserved transcriptome between humans and mice, only 3 of 19 animal models showed significant enrichment for gene sets comprising the most dysregulated up- and down-regulated human genes. Spearman׳s correlation analysis revealed even healthy human aging to be more closely related to human neurodegeneration than any mouse model of AD, PD, ALS or HD. Remarkably, mouse models frequently upregulated stress response genes that were consistently downregulated in human diseases. Among potential alternate models of neurodegeneration, mouse prion disease outperformed all other disease-specific models. Even among the best available animal models, conserved differences between mouse and human transcriptomes were found across multiple animal model versus human disease comparisons, surprisingly, even including aging. Relative to mouse models, mouse disease signatures demonstrated consistent trends toward preserved mitochondrial function protein catabolism, DNA repair responses, and chromatin maintenance. These findings suggest a more complex and multifactorial pathophysiology in human neurodegeneration than is captured through standard animal models, and suggest that even among conserved physiological processes such as aging, mice are less prone to exhibit neurodegeneration-like changes. This work may help explain the poor track record of mouse-based translational therapies for neurodegeneration and provides a path forward to critically evaluate and improve animal models of human disease.

Aging-Like Changes in the Transcriptome of Irradiated Microglia

Whole brain irradiation remains important in the management of brain tumors. Although necessary for improving survival outcomes, cranial irradiation also results in cognitive decline in long‐term survivors. A chronic inflammatory state characterized by microglial activation has been implicated in radiation‐induced brain injury. We here provide the first comprehensive transcriptional profile of irradiated microglia. Fluorescence‐activated cell sorting was used to isolate CD11b+ microglia from the hippocampi of C57BL/6 and Balb/c mice 1 month after 10 Gy cranial irradiation. Affymetrix gene expression profiles were evaluated using linear modeling and rank product analyses. One month after irradiation, a conserved irradiation signature across strains was identified, comprising 448 and 85 differentially up‐ and downregulated genes, respectively. Gene set enrichment analysis demonstrated enrichment for inflammation, including M1 macrophage‐associated genes, but also an unexpected enrichment for extracellular matrix and blood coagulation‐related gene sets, in contrast previously described microglial states. Weighted gene coexpression network analysis confirmed these findings and further revealed alterations in mitochondrial function. The RNA‐seq transcriptome of microglia 24‐h postradiation proved similar to the 1‐month transcriptome, but additionally featured alterations in apoptotic and lysosomal gene expression. Reanalysis of published aging mouse microglia transcriptome data demonstrated striking similarity to the 1‐month irradiated microglia transcriptome, suggesting that shared mechanisms may underlie aging and chronic irradiation‐induced cognitive decline. GLIA 2015;63:754–767

EMPOWERING MULTI-COHORT GENE EXPRESSION ANALYSIS TO INCREASE REPRODUCIBILITY.

A major contributor to the scientific reproducibility crisis has been that the results from homogeneous, single-center studies do not generalize to heterogeneous, real world populations. Multi-cohort gene expression analysis has helped to increase reproducibility by aggregating data from diverse populations into a single analysis. To make the multi-cohort analysis process more feasible, we have assembled an analysis pipeline which implements rigorously studied meta-analysis best practices. We have compiled and made publicly available the results of our own multi-cohort gene expression analysis of 103 diseases, spanning 615 studies and 36,915 samples, through a novel and interactive web application. As a result, we have made both the process of and the results from multi-cohort gene expression analysis more approachable for non-technical users.

Brain Perfusion and Diffusion Abnormalities in Children Treated for Posterior Fossa Brain Tumors

Objective To compare cerebral perfusion and diffusion in survivors of childhood posterior fossa brain tumor with neurologically normal controls and correlate differences with cognitive dysfunction. Study design We analyzed retrospectively arterial spin‐labeled cerebral blood flow (CBF) and apparent diffusion coefficient (ADC) in 21 patients with medulloblastoma (MB), 18 patients with pilocytic astrocytoma (PA), and 64 neurologically normal children. We generated ANCOVA models to evaluate treatment effects on the cerebral cortex, thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, nucleus accumbens, and cerebral white matter at time points an average of 5.7 years after original diagnosis. A retrospective review of patient charts identified 12 patients with neurocognitive data and in whom the relationship between IQ and magnetic resonance imaging variables was assessed for each brain structure. Results Patients with MB (all treated with surgery, chemotherapy, and radiation) had significantly lower global CBF relative to controls (10%‐23% lower, varying by anatomic region, all adjusted P < .05), whereas patients with PA (all treated with surgery alone) had normal CBF. ADC was decreased specifically in the hippocampus and amygdala of patients with MB and within the amygdala of patients with PA but otherwise remained normal after therapy. In the patients with tumor previously evaluated for IQ, regional ADC, but not CBF, correlated with IQ (R2 = 0.33‐0.75). Conclusions The treatment for MB, but not PA, was associated with globally reduced CBF. Treatment in both tumor types was associated with diffusion abnormalities of the mesial temporal lobe structures. Despite significant perfusion abnormalities in patients with MB, diffusion, but not perfusion, correlated with cognitive outcomes.

Radiation-induced brain injury: low-hanging fruit for neuroregeneration

Brain radiation is a fundamental tool in neurooncology to improve local tumor control, but it leads to profound and progressive impairments in cognitive function. Increased attention to quality of life in neurooncology has accelerated efforts to understand and ameliorate radiation-induced cognitive sequelae. Such progress has coincided with a new understanding of the role of CNS progenitor cell populations in normal cognition and in their potential utility for the treatment of neurological diseases. The irradiated brain exhibits a host of biochemical and cellular derangements, including loss of endogenous neurogenesis, demyelination, and ablation of endogenous oligodendrocyte progenitor cells. These changes, in combination with a state of chronic neuroinflammation, underlie impairments in memory, attention, executive function, and acquisition of motor and language skills. Animal models of radiation-induced brain injury have demonstrated a robust capacity of both neural stem cells and oligodendrocyte progenitor cells to restore cognitive function after brain irradiation, likely through a combination of cell replacement and trophic effects. Oligodendrocyte progenitor cells exhibit a remarkable capacity to migrate, integrate, and functionally remyelinate damaged white matter tracts in a variety of preclinical models. The authors here critically address the opportunities and challenges in translating regenerative cell therapies from rodents to humans. Although valiant attempts to translate neuroprotective therapies in recent decades have almost uniformly failed, the authors make the case that harnessing human radiation-induced brain injury as a scientific tool represents a unique opportunity to both successfully translate a neuroregenerative therapy and to acquire tools to facilitate future restorative therapies for human traumatic and degenerative diseases of the central nervous system.

Gray Matter Growth Is Accompanied by Increasing Blood Flow and Decreasing Apparent Diffusion Coefficient during Childhood.

BACKGROUND AND PURPOSE: Normal values of gray matter volume, cerebral blood flow, and water diffusion have not been established for healthy children. We sought to determine reference values for age-dependent changes of these parameters in healthy children. MATERIALS AND METHODS: We retrospectively reviewed MR imaging data from 100 healthy children. Using an atlas-based approach, age-related normal values for regional CBF, apparent diffusion coefficient, and volume were determined for the cerebral cortex, hippocampus, thalamus, caudate, putamen, globus pallidus, amygdala, and nucleus accumbens. RESULTS: All gray matter structures grew rapidly before the age of 10 years and then plateaued or slightly declined thereafter. The ADC of all structures decreased with age, with the most rapid changes occurring prior to the age of 5 years. With the exception of the globus pallidus, CBF increased rather linearly with age. CONCLUSIONS: Normal brain gray matter is characterized by rapid early volume growth and increasing CBF with concomitantly decreasing ADC. The extracted reference data that combine CBF and ADC parameters during brain growth may provide a useful resource when assessing pathologic changes in children.

MULTIPLEX META-ANALYSIS OF MEDULLOBLASTOMA EXPRESSION STUDIES WITH EXTERNAL CONTROLS

We propose and discuss a method for doing gene expression meta-analysis (multiple datasets) across multiplex measurement modalities measuring the expression of many genes simultaneously (e.g. microarrays and RNAseq) using external control samples and a method of heterogeneity detection to identify and filter on comparable gene expression measurements. We demonstrate this approach on publicly available gene expression datasets from samples of medulloblastoma and normal cerebellar tissue and identify some potential new targets in the treatment of medulloblastoma.