Machine intelligence identifies soluble TNFa as a therapeutic target for spinal cord injury.

Traumatic spinal cord injury (SCI) produces a complex syndrome that is expressed across multiple endpoints ranging from molecular and cellular changes to functional behavioral deficits. Effective therapeutic strategies for CNS injury are therefore likely to manifest multi-factorial effects across a broad range of biological and functional outcome measures. Thus, multivariate analytic approaches are needed to capture the linkage between biological and neurobehavioral outcomes. Injury-induced neuroinflammation (NI) presents a particularly challenging therapeutic target, since NI is involved in both degeneration and repair. Here, we used big-data integration and large-scale analytics to examine a large dataset of preclinical efficacy tests combining five different blinded, fully counter-balanced treatment trials for different acute anti-inflammatory treatments for cervical spinal cord injury in rats. Multi-dimensional discovery, using topological data analysis (TDA) and principal components analysis (PCA) revealed that only one showed consistent multidimensional syndromic benefit: intrathecal application of recombinant soluble TNFα receptor 1 (sTNFR1), which showed an inverse-U dose response efficacy. Using the optimal acute dose, we showed that clinically-relevant 90 min delayed treatment profoundly affected multiple biological indices of NI in the first 48 h after injury, including reduction in pro-inflammatory cytokines and gene expression of a coherent complex of acute inflammatory mediators and receptors. Further, a 90 min delayed bolus dose of sTNFR1 reduced the expression of NI markers in the chronic perilesional spinal cord, and consistently improved neurological function over 6 weeks post SCI. These results provide validation of a novel strategy for precision preclinical drug discovery that is likely to improve translation in the difficult landscape of CNS trauma, and confirm the importance of TNFα signaling as a therapeutic target.

Genome-wide analyses of human perisylvian cerebral cortical patterning.

Despite the well established role of the frontal and posterior perisylvian cortices in many facets of human-cognitive specializations, including language, little is known about the developmental patterning of these regions in the human brain. We performed a genome-wide analysis of human cerebral patterning during midgestation, a critical epoch in cortical regionalization. A total of 345 genes were identified as differentially expressed between superior temporal gyrus (STG) and the remaining cerebral cortex. Gene ontology categories representing transcription factors were enriched in STG, whereas cell-adhesion and extracellular matrix molecules were enriched in the other cortical regions. Quantitative RT-PCR or in situ hybridization was performed to validate differential expression in a subset of 32 genes, most of which were confirmed. LIM domain-binding 1 (LDB1), which we show to be enriched in the STG, is a recently identified interactor of LIM domain only 4 (LMO4), a gene known to be involved in the asymmetric pattering of the perisylvian region in the developing human brain. Protocadherin 17 (PCDH17), a neuronal cell adhesion molecule, was highly enriched in focal regions of the human prefrontal cortex. Contactin associated protein-like 2 (CNTNAP2), in which mutations are known to cause autism, epilepsy, and language delay, showed a remarkable pattern of anterior-enriched cortical expression in human that was not observed in mouse or rat. These data highlight the importance of expression analysis of human brain and the utility of cross-species comparisons of gene expression. Genes identified here provide a foundation for understanding molecular aspects of human-cognitive specializations and the disorders that disrupt them.

Deconstructing language by comparative gene expression: from neurobiology to microarray.

Language is a defining characteristic of our species that has emerged quite recently on an evolutionary timescale. Understanding the neurobiological substrates and genetic underpinnings of language constitutes a basic challenge for both neuroscience and genetics. The functional localization of language in the brain has been progressively refined over the last century through studies of aphasics and more recently through neuroimaging. Concurrently, structural specializations in these brain regions have been identified by virtue of their lateralization in humans and also through comparisons with homologous brain regions in non-human primate species. Comparative genomics has revealed the genome of our closest living relative, the chimpanzee, to be astonishingly similar to our own. To explore the role that changes in the regulation of gene expression have had in recent human evolution, several groups have used microarrays to compare expression levels for thousands of genes in the brain between humans and chimpanzees. By applying this approach to the increasingly refined peri-sylvian network of brain regions involved in language, it may be possible to discern functionally significant changes in gene expression that are universal among humans but unique to our species, thus casting light on the molecular basis of language in the brain.