Benefits of global mutant huntingtin lowering diminish over time in a Huntington's disease mouse model.

We have developed an inducible Huntington's disease (HD) mouse model that allows temporal control of whole-body allele-specific mutant huntingtin (mHtt) expression. We asked whether moderate global lowering of mHtt (~50%) was sufficient for long-term amelioration of HD-related deficits and, if so, whether early mHtt lowering (before measurable deficits) was required. Both early and late mHtt lowering delayed behavioral dysfunction and mHTT protein aggregation, as measured biochemically. However, long-term follow-up revealed that the benefits, in all mHtt-lowering groups, attenuated by 12 months of age. While early mHtt lowering attenuated cortical and striatal transcriptional dysregulation evaluated at 6 months of age, the benefits diminished by 12 months of age, and late mHtt lowering did not ameliorate striatal transcriptional dysregulation at 12 months of age. Only early mHtt lowering delayed the elevation in cerebrospinal fluid neurofilament light chain that we observed in our model starting at 9 months of age. As small-molecule HTT-lowering therapeutics progress to the clinic, our findings suggest that moderate mHtt lowering allows disease progression to continue, albeit at a slower rate, and could be relevant to the degree of mHTT lowering required to sustain long-term benefits in humans.

HDinHD: A Rich Data Portal for Huntington's Disease Research.

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.

Shape deformation analysis reveals the temporal dynamics of cell-type-specific homeostatic and pathogenic responses to mutant huntingtin.

Loss of cellular homeostasis has been implicated in the etiology of several neurodegenerative diseases (NDs). However, the molecular mechanisms that underlie this loss remain poorly understood on a systems level in each case. Here, using a novel computational approach to integrate dimensional RNA-seq and in vivo neuron survival data, we map the temporal dynamics of homeostatic and pathogenic responses in four striatal cell types of Huntington's disease (HD) model mice. This map shows that most pathogenic responses are mitigated and most homeostatic responses are decreased over time, suggesting that neuronal death in HD is primarily driven by the loss of homeostatic responses. Moreover, different cell types may lose similar homeostatic processes, for example, endosome biogenesis and mitochondrial quality control in Drd1-expressing neurons and astrocytes. HD relevance is validated by human stem cell, genome-wide association study, and post-mortem brain data. These findings provide a new paradigm and framework for therapeutic discovery in HD and other NDs.

DNA methylation study of Huntington's disease and motor progression in patients and in animal models.

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.

Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington's disease mice.

BACKGROUND: MicroRNA (miRNA) regulation is associated with several diseases, including neurodegenerative diseases. Several approaches can be used for modeling miRNA regulation. However, their precision may be limited for analyzing multidimensional data. Here, we addressed this question by integrating shape analysis and feature selection into miRAMINT, a methodology that we used for analyzing multidimensional RNA-seq and proteomic data from a knock-in mouse model (Hdh mice) of Huntington's disease (HD), a disease caused by CAG repeat expansion in huntingtin (htt). This dataset covers 6 CAG repeat alleles and 3 age points in the striatum and cortex of Hdh mice. RESULTS: Remarkably, compared to previous analyzes of this multidimensional dataset, the miRAMINT approach retained only 31 explanatory striatal miRNA-mRNA pairs that are precisely associated with the shape of CAG repeat dependence over time, among which 5 pairs with a strong change of target expression levels. Several of these pairs were previously associated with neuronal homeostasis or HD pathogenesis, or both. Such miRNA-mRNA pairs were not detected in cortex. CONCLUSIONS: These data suggest that miRNA regulation has a limited global role in HD while providing accurately-selected miRNA-target pairs to study how the brain may compute molecular responses to HD over time. These data also provide a methodological framework for researchers to explore how shape analysis can enhance multidimensional data analytics in biology and disease.

Genetic cooperativity in multi-layer networks implicates cell survival and senescence in the striatum of Huntington's disease mice synchronous to symptoms.

MOTIVATION: Huntington's disease (HD) may evolve through gene deregulation. However, the impact of gene deregulation on the dynamics of genetic cooperativity in HD remains poorly understood. Here, we built a multi-layer network model of temporal dynamics of genetic cooperativity in the brain of HD knock-in mice (allelic series of Hdh mice). To enhance biological precision and gene prioritization, we integrated three complementary families of source networks, all inferred from the same RNA-seq time series data in Hdh mice, into weighted-edge networks where an edge recapitulates path-length variation across source-networks and age-points. RESULTS: Weighted edge networks identify two consecutive waves of tight genetic cooperativity enriched in deregulated genes (critical phases), pre-symptomatically in the cortex, implicating neurotransmission, and symptomatically in the striatum, implicating cell survival (e.g. Hipk4) intertwined with cell proliferation (e.g. Scn4b) and cellular senescence (e.g. Cdkn2a products) responses. Top striatal weighted edges are enriched in modulators of defective behavior in invertebrate models of HD pathogenesis, validating their relevance to neuronal dysfunction in vivo. Collectively, these findings reveal highly dynamic temporal features of genetic cooperativity in the brain of Hdh mice where a 2-step logic highlights the importance of cellular maintenance and senescence in the striatum of symptomatic mice, providing highly prioritized targets. AVAILABILITY AND IMPLEMENTATION: Weighted edge network analysis (WENA) data and source codes for performing spectral decomposition of the signal (SDS) and WENA analysis, both written using Python, are available at http://www.broca.inserm.fr/HD-WENA/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Huntington's disease accelerates epigenetic aging of human brain and disrupts DNA methylation levels.

Age of Huntington's disease (HD) motoric onset is strongly related to the number of CAG trinucleotide repeats in the huntingtin gene, suggesting that biological tissue age plays an important role in disease etiology. Recently, a DNA methylation based biomarker of tissue age has been advanced as an epigenetic aging clock. We sought to inquire if HD is associated with an accelerated epigenetic age. DNA methylation data was generated for 475 brain samples from various brain regions of 26 HD cases and 39 controls. Overall, brain regions from HD cases exhibit a significant epigenetic age acceleration effect (p=0.0012). A multivariate model analysis suggests that HD status increases biological age by 3.2 years. Accelerated epigenetic age can be observed in specific brain regions (frontal lobe, parietal lobe, and cingulate gyrus). After excluding controls, we observe a negative correlation (r=-0.41, p=5.5×10-8) between HD gene CAG repeat length and the epigenetic age of HD brain samples. Using correlation network analysis, we identify 11 co-methylation modules with a significant association with HD status across 3 broad cortical regions. In conclusion, HD is associated with an accelerated epigenetic age of specific brain regions and more broadly with substantial changes in brain methylation levels.

Large-scale phenome analysis defines a behavioral signature for Huntington's disease genotype in mice.

Rapid technological advances for the frequent monitoring of health parameters have raised the intriguing possibility that an individual's genotype could be predicted from phenotypic data alone. Here we used a machine learning approach to analyze the phenotypic effects of polymorphic mutations in a mouse model of Huntington's disease that determine disease presentation and age of onset. The resulting model correlated variation across 3,086 behavioral traits with seven different CAG-repeat lengths in the huntingtin gene (Htt). We selected behavioral signatures for age and CAG-repeat length that most robustly distinguished between mouse lines and validated the model by correctly predicting the repeat length of a blinded mouse line. Sufficient discriminatory power to accurately predict genotype required combined analysis of >200 phenotypic features. Our results suggest that autosomal dominant disease-causing mutations could be predicted through the use of subtle behavioral signatures that emerge in large-scale, combinatorial analyses. Our work provides an open data platform that we now share with the research community to aid efforts focused on understanding the pathways that link behavioral consequences to genetic variation in Huntington's disease.

Computational design and experimental characterization of peptides intended for pH-dependent membrane insertion and pore formation.

There are many opportunities to use macromolecules, such as peptides and oligonucleotides, for intracellular applications. Despite this, general methods for delivering these molecules to the cytosol in a safe and efficient manner are not available. Efforts to develop a variety of intracellular drug delivery systems such as viral vectors, lipoplexes, nanoparticles, and amphiphilic peptides have been made, but various challenges such as delivery efficiency, toxicity, and controllability remain. A central challenge is the ability to selectively perturb, not destroy, the membrane to facilitate cargo introduction. Herein, we describe our efforts to design and characterize peptides that form pores inside membranes at acidic pH, so-called pH-switchable pore formation (PSPF) peptides, as a potential means for facilitating cargo translocation through membranes. Consistent with pore formation, these peptides exhibit low-pH-triggered selective release of ATP and miRNA, but not hemoglobin, from red blood cells. Consistent with these observations, biophysical studies (tryptophan fluorescence, circular dichroism, size-exclusion chromatography, analytical ultracentrifugation, and attenuated total reflectance Fourier transformed infrared spectroscopy) show that decreased pH destabilizes the PSPF peptides in aqueous systems while promoting their membrane insertion. Together, these results suggest that reduced pH drives insertion of PSPF peptides into membranes, leading to target-specific escape through a proposed pore formation mechanism.