Background A major challenge in neurodegenerative diseases concerns identifying biological disease signatures that track with disease progression or respond to an intervention. Several clinical trials in Huntington disease (HD), an inherited, progressive neurodegenerative disease, are currently ongoing. Therefore, we examine whether peripheral tissues can serve as a source of readily accessible biological signatures at the RNA and protein level in HD patients. Results We generate large, high-quality human datasets from skeletal muscle, skin and adipose tissue to probe molecular changes in human premanifest and early manifest HD patients—those most likely involved in clinical trials. The analysis of the transcriptomics and proteomics data shows robust, stage-dependent dysregulation. Gene ontology analysis confirms the involvement of inflammation and energy metabolism in peripheral HD pathogenesis. Furthermore, we observe changes in the homeostasis of extracellular vesicles, where we find consistent changes of genes and proteins involved in this process. In-depth single nucleotide polymorphism data across the HTT gene are derived from the generated primary cell lines. Conclusions Our ‘omics data document the involvement of inflammation, energy metabolism, and extracellular vesicle homeostasis. This demonstrates the potential to identify biological signatures from peripheral tissues in HD suitable as biomarkers in clinical trials. The generated data, complemented by the primary cell lines established from peripheral tissues, and a large panel of iPSC lines that can serve as human models of HD are a valuable and unique resource to advance the current understanding of molecular mechanisms driving HD pathogenesis.

Huntington’s disease is caused by expanded trinucleotide repeats in the huntingtin gene (HTT), and a higher number of repeats is associated with an earlier age of disease onset. Although the causative gene has been identified, its connections to the observed disease phenotypes is still unclear. Mouse models engineered to contain increasing numbers of trinucleotide repeats were sacrificed at different ages to detect RNA-level and protein-level changes specific to each repeat length and age in order to examine the transcriptional and translational characteristics of the disease. RNA-seq and quantitative proteomics data were collected on 14 types of tissues at up to 8 repeat lengths and in up to 3 different ages, and differential gene and protein expression were examined. A modified method of imputing missing proteomics data was employed and is described here. The most dysregulated tissue at both the RNA and protein levels was the striatum, and a strong gender effect was observed in all of the liver experiments. The full differential expression results are available to the research community on the HDinHD.org website. The results of multiple expression tests in the striatum were combined to generate an RNA disease signature and a protein disease signature, and the signatures were validated in external data sets. These signatures represent molecular readouts of disease progression in HD mice, which further characterizes their HD-related phenotype and can be useful in the preclinical evaluation of candidate therapeutic interventions. Author Summary Mouse models of Huntington’s disease were engineered to allow a detailed examination of how the disease causes changes in gene activity in a variety of tissues. Among the 14 tissues studied, the one most affected by the disease in our experiments was the striatum, a brain region involved in voluntary movement. The liver results showed large differences in gene activity between the male and female mice. In our analysis, we propose a minor change in how proteomics data is typically analyzed in order to improve the ranking of significant results. Using the striatum data in this study and in others, we identified robust genetic signatures of disease at both the RNA and protein levels.

HDinHD (Huntington’s Disease in High Definition; HDinHD.org) is an open online portal for the HD research community that presents a synthesized view of HD-related scientific data. Here, we present a broad overview of HDinHD and highlight the newly launched HDinHD Explorer tool that enables researchers to discover and explore a wide range of diverse yet interconnected HD-related data. We demonstrate the utility of HDinHD Explorer through data mining of a single collection of newly released in vivo therapeutic intervention study reports alongside previously published reports.

Although Huntington’s disease (HD) is a well studied Mendelian genetic disorder, less is known about its associated epigenetic changes. Here, we characterize DNA methylation levels in six different tissues from 3 species: a mouse huntingtin (Htt) gene knock-in model, a transgenic HTT sheep model, and humans. Our epigenome-wide association study (EWAS) of human blood reveals that HD mutation status is significantly ( p < 10 −7 ) associated with 33 CpG sites, including the HTT gene ( p = 6.5 × 10 −26 ). These Htt/HTT associations were replicated in the Q175 Htt knock-in mouse model ( p = 6.0 × 10 −8 ) and in the transgenic sheep model ( p = 2.4 × 10 −88 ). We define a measure of HD motor score progression among manifest HD cases based on multiple clinical assessments. EWAS of motor progression in manifest HD cases exhibits significant ( p < 10 −7 ) associations with methylation levels at three loci: near PEX14 ( p = 9.3 × 10 −9 ), GRIK4 ( p = 3.0 × 10 −8 ), and COX4I2 ( p = 6.5 × 10 −8 ). We conclude that HD is accompanied by profound changes of DNA methylation levels in three mammalian species.