HTT silencing delays onset and slows progression of Huntington disease like phenotype: Monitoring with a novel neurovascular biomarker
Liu, H.; Zhang, C.; Xu, J.; Jin, J.; Cheng, l.; Wu, Q.; Wei, Z.; Liu, P.; Lu, H.; van Zijl, P.; Ross, C. A.; Hua, J.; Duan, W.
Show abstract
Huntingtons disease (HD) is a dominantly inherited, fatal neurodegenerative disorder caused by a CAG expansion in the Huntingtin (HTT) gene, coding for pathologic mutant HTT protein (mHTT). Because of its gain-of-function mechanism and monogenic etiology, strategies to lower HTT are being actively investigated as disease-modifying therapies. Most approaches are currently targeted at the manifest HD stage, when clinical outcomes are used to evaluate the effectiveness of therapy. However, as almost 50% of striatal volume has been lost at the time of onset of manifest HD it would be preferable to begin therapy in the premanifest period. An unmet challenge is how to evaluate therapeutic efficacy before the presence of clinical symptoms as outcome measures. To address this, we have been developing more sensitive biomarkers such as functional neuroimaging with the goal of identifying noninvasive biomarkers that provide insight into the best time to introduce HTT-lowering treatment. In this study, we mapped the temporal trajectories of arteriolar cerebral blood volumes (CBVa) using inflow-based vascular-space-occupancy (iVASO) MRI technique in an HD mouse model. Significantly elevated CBVa was evident in premanifest zQ175 HD mice prior to motor deficits and striatal atrophy, recapitulating altered CBVa in human premanifest HD. CRISPR/Cas9-mediated non-allele-specific HTT silencing in striatal neurons restored altered CBVa in premanifest zQ175 mice, delayed onset of striatal atrophy, and slowed the progression of motor phenotype and brain pathology. This study showed the potential of CBVa as a noninvasive fMRI biomarker for premanifest HD clinical trials and demonstrates long-term benefits of introducing an HTT lowering treatment in the premanifest HD.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Suppression of Huntington's Disease Somatic Instability by Transcriptional Repression and Direct CAG Repeat Binding 96%
- Parallel Labeled-Line Organization of Sympathetic Outflow for Selective Organ Regulation in Mice 96%
- CryoET Reveals Organelle Phenotypes in Huntington Disease Patient iPSC-Derived and Mouse Primary Neurons 96%
Similar papers in this journal
- Single cell spatial transcriptomic and translatomic profiling of dopaminergic neurons in health, aging and disease 97%
- Abnormal hyperactivity of specific striatal ensembles encodes distinct dyskinetic behaviors revealed by high-resolution clustering 96%
- Spatiotemporal analysis of gene expression in the human dentate gyrus reveals age-associated changes in cellular maturation and neuroinflammation 95%
Similar papers in this journal
- Cellular taxonomy and spatial organization of the ventral posterior hypothalamus reveals neuroanatomical parcellation of the mammillary bodies 95%
- Distinctive Whole-brain Cell-Types Predict Tissue Damage Patterns in Thirteen Neurodegenerative Conditions 94%
- Molecular and spatial transcriptomic classification of midbrain dopamine neurons and their alterations in a LRRK2G2019S model of Parkinson's disease 94%
Similar papers in this journal
Similar papers in this journal
- LINE-1 activation in the cerebellum drives ataxia 97%
- SEQUIN multiscale imaging of mammalian central synapses reveals loss of synaptic microconnectivity resulting from diffuse traumatic brain injury 95%
- Transient developmental increase of prefrontal activity alters network maturation and causes cognitive dysfunction in adult mice 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.