Neuroimaging, Urinary, and Plasma Biomarkers of Treatment Response in Huntington's Disease: Preclinical Evidence with the p75NTR Ligand LM11A-31.

Huntington's disease (HD) is caused by an expansion of the CAG repeat in the huntingtin gene leading to preferential neurodegeneration of the striatum. Disease-modifying treatments are not yet available to HD patients and their development would be facilitated by translatable pharmacodynamic biomarkers. Multi-modal magnetic resonance imaging (MRI) and plasma cytokines have been suggested as disease onset/progression biomarkers, but their ability to detect treatment efficacy is understudied. This study used the R6/2 mouse model of HD to assess if structural neuroimaging and biofluid assays can detect treatment response using as a prototype the small molecule p75NTR ligand LM11A-31, shown previously to reduce HD phenotypes in these mice. LM11A-31 alleviated volume reductions in multiple brain regions, including striatum, of vehicle-treated R6/2 mice relative to wild-types (WTs), as assessed with in vivo MRI. LM11A-31 also normalized changes in diffusion tensor imaging (DTI) metrics and diminished increases in certain plasma cytokine levels, including tumor necrosis factor-alpha and interleukin-6, in R6/2 mice. Finally, R6/2-vehicle mice had increased urinary levels of the p75NTR extracellular domain (ecd), a cleavage product released with pro-apoptotic ligand binding that detects the progression of other neurodegenerative diseases; LM11A-31 reduced this increase. These results are the first to show that urinary p75NTR-ecd levels are elevated in an HD mouse model and can be used to detect therapeutic effects. These data also indicate that multi-modal MRI and plasma cytokine levels may be effective pharmacodynamic biomarkers and that using combinations of these markers would be a viable and powerful option for clinical trials.

The Genetic Relevance of Human Induced Pluripotent Stem Cell-Derived Microglia to Alzheimer's Disease and Major Neuropsychiatric Disorders.

Microglia are the primary innate immune cell type in the brain that have been implicated in the pathogenesis of several neurodegenerative and neuropsychiatric disorders, most notably Alzheimer's disease (AD) and schizophrenia. Microglia generated from human induced pluripotent stem cells (hiPSCs) represent a promising in vitro cellular model for studying the neuroimmune interactions involved in these disorders. Among several methods of generating -hiPSC-derived microglia (iMG) - varying in duration and resultant purity - a recent protocol by Brownjohn et al. [Stem Cell Reports. 2018 Apr;10(4):1294-307] is particularly simple and efficient. However, the replicability of this method, transcriptomic similarity of these iMG to primary adult microglia, and their genetic relevance to disease (i.e., enrichment of disease risk loci in genes preferentially expressed in these cells) remains unclear. Using two hiPSC lines, we demonstrated that Brownjohn's protocol can rapidly generate iMG that morphologically and functionally resembled microglia. The iMG cells we generated were found to be transcriptionally similar to previously reported iMG, as well as fetal and adult microglia. Furthermore, by using cell type-specific gene expression to partition disease heritability, we showed that iMG cells are genetically relevant to AD but found no significant enrichments of risk loci of Parkinson's disease, schizophrenia, major depressive disorder, bipolar disorder, autism spectrum disorder, or body mass index. Across a range of neuronal and immune cell types, we found only iMG, primary microglia, and microglia-like cell types exhibited a significant enrichment for AD heritability. Our results thus support the use of iMG as a human cellular model for understanding AD biology and underlying genetic factors, as well as for developing and efficiently screening new therapeutics.

Clinotator: analyzing ClinVar variation reports to prioritize reclassification efforts.

While ClinVar has become an indispensable resource for clinical variant interpretation, its sophisticated structure provides it with a daunting learning curve. Often the sheer depth of types of information provided can make it difficult to analyze variant information with high throughput. Clinotator is a fast and lightweight tool to extract important aspects of criteria-based clinical assertions; it uses that information to generate several metrics to assess the strength and consistency of the evidence supporting the variant clinical significance. Clinical assertions are weighted by significance type, age of submission and submitter expertise category to filter outdated or incomplete assertions that otherwise confound interpretation. This can be accomplished in batches: either lists of Variation IDs or dbSNP rsIDs, or with vcf files that are additionally annotated. Using sample sets ranging from 15,000-50,000 variants, we slice out problem variants in minutes without extensive computational effort (using only a personal computer) and corroborate recently reported trends of discordance hiding amongst the curated masses. With the rapidly growing body of variant evidence, most submitters and researchers have limited resources to devote to variant curation. Clinotator provides efficient, systematic prioritization of discordant variants in need of reclassification. The hope is that this tool can inform ClinVar curation and encourage submitters to keep their clinical assertions current by focusing their efforts. Additionally, researchers can utilize new metrics to analyze variants of interest in pursuit of new insights into pathogenicity.