Huntington’s disease (HD) is a genetic, progressive neurodegenerative disorder caused by an expanded CAG/CAA repeat in exon 1 of the HTT gene (Sapp et al., 2001). When the CAG stretch exceeds approximately 40 repeats, the encoded HTT protein misfolds and sets off a toxic sequence of events inside the cell including transcriptional dysregulation, mitochondrial dysfunction, calcium signaling disruption, and altered neurotransmission that includes glutamatergic and dopaminergic dysregulation (Vonsattel et al., 1985). Accordingly, postmortem studies of HD patient brain tissues have shown significant neuropathology including mutant huntingtin protein (mHTT) aggregate formation, neuronal death, and gliosis (Sapp et al., 2001; Vonsattel et al., 1985; Waldvogel et al., 2015). The most highly affected regions are the caudate nucleus and putamen (together comprising the striatum); however, numerous brain regions that send afferent connections to the striatum are also affected, including widespread cortical and subcortical brain areas (Rosas et al., 2008; Allen et al., 2009; Glass et al., 2000; Glass et al., 1993; Majid et al., 2011). White matter (WM) fiber tracts interconnecting the striatum with the cortex also show extensive evidence of degeneration (Sprengelmeyer et al., 2014; Stoffers et al., 2010; Gregory et al., 2015; Saba et al., 2017), highlighting that HD is not only a striatal disorder, but rather a disease characterized by widespread cortico-basal ganglia involvement.

The symptoms of HD are extremely detrimental to quality of life, as patients suffer from a progressive movement disorder that is characterized by lack of balance and coordination, altered fine motor skills and hyperkinetic involuntary movements of the limbs, trunk, and face, known as chorea. In later stages of the disease patients can experience bradykinetic movements, dystonia, and rigidity (Mahant et al., 2003; Bates et al., 2015; Novak and Tabrizi, 2011). These motor phenotypes are often accompanied by deteriorating cognitive function, including working memory decline and a reduced capacity to plan and organize daily tasks. HD patients also exhibit profound personality changes and mood disturbances that can include depression, anxiety, and irritability (Tabrizi et al., 2009; Lawrence et al., 1996; Van den Stock et al., 2015; Dogan et al., 2014; Julayanont et al., 2020). Currently, there are no treatments capable of slowing disease progression. Therefore, to aid in the creation and evaluation of effective therapeutic interventions, it is critical to develop appropriate animal models of HD.

Genetically modified rodents have been key in advancing our understanding of pathophysiological mechanisms that are altered by the mHTT gene, and numerous mouse and rat models have been created over the past three decades, reviewed in Farshim and Bates, 2018. These models have played a critical role in characterizing HTT-mediated disease pathology, and several have been utilized to screen therapeutic strategies. However, an important consideration is that these models do not fully recapitulate the behavioral symptomology of humans with HD. Some HD mouse models display balance issues that can be measured via rotorod performance (Crook and Housman, 2011), but do not display the hallmark signs of chorea, bradykinesia nor fine motor skill deficits. Similarly, some mouse models exhibit spatial memory deficits but lack other signature features of HD (Crook and Housman, 2011). Furthermore, species differences in genetics, brain size, structure, and neural connectivity all limit the ability to translate findings from rodents to predict clinical responses in human patients. For example, there still exists an ambiguity on whether specific frontal cortical areas in monkeys and humans, such as the medial and lateral prefrontal cortices (areas known to be affected in HD) share cross-species homologies with rodents (Laubach et al., 2018). Perhaps most striking to consider is that none of the therapies that have shown efficacy in mouse models have resulted in success in clinical trials over the past several decades. For these reasons, large animal models including sheep, minipigs, and nonhuman primates (NHPs) have emerged more recently as a new and critical tool for the HD research community (Howland et al., 2020).

The earliest NHP models of HD were created by using neurotoxins to lesion the caudate and/or putamen in order to replicate the profound striatal atrophy and hyperkinetic movements seen in patients (Howland et al., 2020). However, the toxin-based approach decreased in popularity after the HTT gene mutation was identified. Subsequent NHP models have been created by viral-mediated delivery of a fragment of the human mHTT gene (Palfi et al., 2007; Weiss et al., 2020; Maxan et al., 2020) or via the development of transgenic HD macaques (Yang et al., 2008), both bearing HTT genes with expanded CAG repeats that encode mHTT proteins with elongated polyglutamine tracts (Q) at the N-terminus. Palfi et al. created the first viral-mediated NHP model of HD by injecting a lentiviral vector expressing a fragment of HTT with 82 CAG repeats (LV-HTT82Q) bilaterally into the dorsolateral posterior portion of the putamen in rhesus macaques (Palfi et al., 2007). LV-HTT82Q macaques developed dyskinetic movements of the limbs and trunk beginning at 15 weeks post-surgery and persisting out to 30 weeks post-surgery. Brain tissue revealed mHTT inclusion formation, neuronal loss, and astrocytosis in the circumscribed area of injection. More recently, Maxan et al., 2020 demonstrated mHTT seeding in the brain (spread of aggregates to nontransduced, neighboring cells), following circumscribed delivery of AAV6-HTT103Q-GFP into the posterior putamen of adult macaques (). Given that HD pathology in patients has been identified throughout the putamen, caudate nucleus, and in multiple other cortical and subcortical brain regions, it would be of value to create a virally mediated NHP model that more closely recapitulates this widespread pattern of neurodegeneration and circuit dysfunction. Moreover, because cognitive dysfunction dramatically alters the HD patient’s quality of life and autonomy, an NHP model that exhibits both motor and working memory decline will be more useful for evaluating promising therapeutics.

Recent techniques using directed evolution approaches to develop new adeno-associated viruses (AAV) have produced novel capsid variants that exhibit enhanced properties of retrograde and/or anterograde transport in brains of both rodents and NHPs (Weiss et al., 2020; Naidoo et al., 2018; Lin et al., 2020; Tervo et al., 2016). Utilizing these new AAV capsid variants, it is now possible to transduce entire neural circuits, rather than individual brain regions. We recently demonstrated that delivery of AAV2.retro expressing a fragment of HTT with 85 CAG repeats (AAV2.retro-mHTT85Q) into the adult macaque caudate and putamen results in efficient retrograde transport resulting in mHTT expression and the formation of hallmark aggregates throughout dozens of cortical and subcortical striatal afferents (10 weeks post-surgery). In comparison, injection of the parent serotype, AAV2, expressing mHTT85Q resulted in mHTT inclusions primarily within the caudate and putamen, without appreciable retrograde transport (Weiss et al., 2020). This study laid the groundwork for generating a macaque model of HD that engages the entire cortico-basal ganglia circuit using this new viral vector-mediated approach.

Here, we expanded on these initial efforts and characterized the long-term effects of mHTT85Q expression throughout the macaque cortex and basal ganglia. Following surgery, we assessed cognitive and motor function in a cohort of HTT85Q-treated animals, as well as HTT10Q- and buffer-injected controls, for a period of 30 months. Additionally, we performed multimodal imaging to assess WM microstructure, regional brain atrophy and patterns of brain-wide functional connectivity. Together, this study describes a new macaque model that replicates several of the behavioral and neuropathological changes seen in the early stages of HD.

To elicit mHTT85Q expression throughout the caudate and putamen, as well as cortical- and basal ganglia afferents, we undertook a combinatorial approach and administered a 1:1 mixture of AAV2-HTT85Q and AAV2.retro-HTT85Q at a titer of 1e12 vg/ml (Group 85Q, n = 6). Control animals were injected with a 1:1 mixture of AAV2:AAV2retro-HTT10Q (control HTT fragment with 10 CAG repeats; Group 10Q, n = 6) or buffered saline only (Group Buffer, n = 5), see Table 1. Animals completed a longitudinal battery of cognitive and motor tasks and underwent repeated brain scans to collect structural (T1w/T2w) magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and resting-state fMRI (rs-fMRI) data.

HTT85Q administration leads to spatial working memory deficits

Disease onset in HD has historically been defined by the presence of disordered hyperkinetic movements, however HD patients also often experience cognitive decline characterized by working memory impairment, which sometimes precedes motor dysfunction (Tabrizi et al., 2009; Lawrence et al., 1996; Julayanont et al., 2020; Misiura et al., 2017; Paulsen et al., 2001). In NHPs, spatial working memory can be assessed using a 3-Choice Spatial Delayed Response (SDR) task. Monkeys in this study completed this task at baseline as well as 3, 6, 9, 14, 20, and 30 months post-surgery.

Prior to surgery, 15 animals met the pretraining criteria for the SDR task (Table 1), and therefore data from the two remaining subjects were excluded from analysis. For the SDR assay, animals were tasked at remembering the location of a treat-bated, recessed well after a delay of 1, 3, or 5 s (Figure 1A). A three-way analysis of variance (ANOVA) found significant main effects of group (F(2,11) = 17.109, p = 0.0004) and timepoint (F(5,55) = 2.978, p = 0.019), with no main effect of delay (F(2,22) = 0.038, p = 0.9630) nor interaction between any of these factors. Post hoc tests revealed that 85Q-treated monkeys performed significantly worse on the SDR task (fewer correct responses) than Buffer- (p = 0.00014) and 10Q- (p = 0.0028) treated monkeys (Figure 1B, delay and timepoint collapsed). Buffer- and 10Q-treated animal performance on the SDR task did not differ significantly (p = 0.06). To further explore the time-course of the group differences, we conducted planned comparisons between groups at each timepoint (Supplementary file 1). The results indicate that performance between 85Q- and Buffer-treated animals differed significantly at all timepoints. Significant group differences also emerged between 85Q- and 10Q-treated animals at the 6-month timepoint, which persisted through 30 months, with 85Q animals showing working memory deficits that were not exhibited by either control group. Buffer and 10Q groups differed significantly from one another at the 6- and 14-month timepoints, all p < 0.05, but both control groups exhibited improvement in their performance over the course of the study (Figure 1C, Supplementary file 1).

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Spatial Delayed Response (SDR), Lifesaver, and neurological rating scale (NRS) scores.

Table 1 reports scores from all the behavioral tasks at each of the post-surgical timepoints, as well as overall averages. All scores are reported as change from baseline measures.

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mHTT delivery results in microstructural changes in several WM fiber tracts

Microstructural properties of WM fiber tracts can be imaged using DTI, with the most commonly reported metric being fractional anisotropy (FA). Reduced FA is observed in HD in many WM regions including the corpus callosum, superior and inferior longitudinal fasciculi, corona radiata, internal capsule, and cingulum, indicating microstructural changes to the axon including reduced axonal integrity and demyelination (Sprengelmeyer et al., 2014; Stoffers et al., 2010; Gregory et al., 2015; Saba et al., 2017). To query WM changes in our model, DTI data were collected pre-surgery and 3, 6, 9, 14, 20, and 30 months post-surgery. Parameter maps of FA, axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) were generated in ONPRC18 template space (Weiss et al., 2021). Figure 2A illustrates the results of voxel-wise comparisons of FA, using a WM mask, conducted between the baseline (pre-surgical) timepoint and subsequent timepoints for each group separately. As early as 3 months post-surgery, 85Q-treated monkeys had several regions of WM with significant (p < 0.01) reductions in FA that persisted through the 30-month timepoint; in contrast, no changes in FA were observed in 10Q- and Buffer-treated animals.

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Diffusion tensor imaging (DTI).

Table 1 reports the percent volume of regions of interest (ROIs) that had p < 0.01 significant changes in fractional anisotropy (FA) identified by voxel-wise analyses in Group 85Q. Both control groups (10Q and Buffer) did not have any significant (p < 0.01) changes and are not included in this table. Table 2 reports the average change in FA (from baseline) under the p < 0.01 voxels at each timepoint, for all 17 animals on study. These data were also averaged across timepoint and correlated with average behavioral scores (also included in Table 2).

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To characterize the distribution of the significant voxel-wise differences, WM labels from the ONPRC18 macaque brain atlas were applied to the thresholded p-value maps from 85Q-treated animals, and the percent volume of significant FA reduction was calculated for each WM region of interest (ROI) at each timepoint (Figure 2B). Broadly, there was an anterior–posterior spatial distribution of WM changes in 85Q animals, with larger relative volumes of reduced FA occurring in more anterior ROIs, without robust hemispheric differences. Of particular note was the large percentages of the corona radiata, dorsal and ventral prefrontal WM tracts, the external and internal capsule, as well as the body and genu of the corpus callosum exhibiting significant reductions in FA compared to baseline. To characterize the overall time-course of these changes, the average change in FA (from baseline) in the significant regions was calculated for each animal at each post-surgical timepoint, collapsed across ROI, and plotted in Figure 2C. A repeated measure ANOVA revealed significant main effects of Group (F(2,13) = 104.117, p < 0.0001) and Timepoint (F(5,65) = 4.088, p = 0.003), but no interaction between these factors (F(10,65) = 1.019, p = 0.438). Post hoc tests revealed that 85Q-treated animals had significantly greater decreases in FA after surgery compared to Buffer (p < 0.0001) and 10Q (p < 0.0001) animals, whereas Buffer- and 10Q-treated animals did not differ significantly in the magnitude of FA changes (p = 0.372). To query the relationship between the observed DTI changes and behavioral impairments, we computed correlations between FA changes and behavioral scores that were collapsed across all five post-surgical timepoints. FA decreases in WM were correlated with all three behavioral measures, such that greater decreases in FA were significantly associated with higher NRS scores (r(17) = −0.920, p <0.001) (Figure 2D), longer Lifesaver retrieval latencies (r(17) = −0.746, p < 0.001) (Figure 2E) and fewer correct responses on the 3-Choice SDR task (r(15) = 0.806, p < 0.001) (Figure 2F).

Additional analyses of DTI parameters including RD, MD, and AD were performed, following the same strategy described for FA. 85Q-treated animals showed significant elevations in RD (Figure 2—figure supplement 1) and MD (Figure 2—figure supplement 2), as well as significant decreases in AD (Figure 2—figure supplement 3), compared to controls (p < 0.01 for each measurement). These changes followed similar spatiotemporal trajectories to the changes observed in FA. In particular, there were areas of significant RD and MD increase in corresponding regions of FA decrease in the dorsal and ventral prefrontal WM tracts, as well as areas of the anterior/dorsal corona radiata, internal capsule, external capsule, and the genu and body of the corpus callosum. Brain-wide, the spatial distributions of RD and MD increases generally overlapped the FA decreases, whereas the significant decreases in AD were more widely distributed (Figure 2—figure supplement 4). None of the changes in AD, RD, or MD observed in the 10Q and Buffer groups survived thresholding at the p < 0.01 level.

Cortico-striatal atrophy revealed with tensor-based morphometry

Tensor-based morphometry (TBM) is a technique used to assess changes in brain morphometry by comparing deformation fields that align anatomical MR images to a template image. Applied longitudinally, changes in these deformation fields can be used to characterize 3D patterns of structural change. Atrophy of many brain regions (caudate, putamen, thalamus, multiple regions of cortex) has been described in symptomatic HD patients using this technique (Hobbs et al., 2010; Kassubek et al., 2004), and recent longitudinal data indicate that some changes begin prior to overt symptom development; particularly in regions of the putamen and globus pallidus (Stoffers et al., 2010; Hobbs et al., 2010; Kipps et al., 2005). High-resolution (0.5 mm isotropic) T2-weighted SPACE scans were collected pre-surgery and 3, 6, 9, 14, 20, and 30 months post-surgery. For each timepoint, deformation fields aligning with the ONPRC18 template were computed, and log Jacobian Determinant maps, reflecting local structural changes, were generated. In the resulting maps, positive values indicated areas where individual space was dilated to align with ONPRC18 space (and was therefore smaller), whereas negative values indicate areas where individual space was contracted to align with ONPRC18 space (and was therefore larger). Using a GM mask, voxel-wise comparisons were conducted to compare the baseline (pre-surgical) timepoint and subsequent timepoints. As early as 3 months post-surgery, 85Q-treated monkeys exhibited regions of the basal ganglia, prefrontal- and premotor-cortex with significant tissue contractions (larger log Jacobian Determinants), indicating tissue atrophy, compared to baseline that persisted through the 30-month timepoint (p < 0.01). In contrast, the none of the changes observed in 10Q and Buffer survived thresholding at the p < 0.01 level (Figure 3A). GM labels available in the ONPRC18 atlas were applied to the thresholded p-value maps from 85Q-treated animals, and the percent volumes of significant log Jacobian Determinant increases were calculated for each ROI at each timepoint. Major brain areas showing tissue contraction were the caudate, putamen, globus pallidus (internal and external segments), as well as numerous frontal and motor cortical areas, with no hemispheric differences (Figure 3B).

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Tensor-based morphometry (TBM).

Table 1 reports the percent volume of regions of interest (ROIs) that had p < 0.01 significant changes in log Jacobian Determinants identified by voxel-wise analyses in Group 85Q. Both control groups (10Q and Buffer) did not have any significant (p < 0.01) changes and are not included in this table. Table 2 reports the average change in log JD (from baseline) under the p < 0.01 voxels at each timepoint, for all 17 animals on study. These data were also averaged across timepoint and correlated with average behavioral scores (also included in Table 2).

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To characterize the overall time-course of these changes, masks of thresholded p-value maps from each timepoint were created for areas of significant contraction. The change in the log Jacobian Determinant maps (from baseline) under the masks was then calculated for each animal at each post-surgical timepoint and plotted in Figure 3C. In the regions with significant increases in log Jacobian Determinants, a two-way repeated measure ANOVA revealed significant main effects of Group (F(2,13) = 19.568, p < 0.001) and Timepoint (F(5,65) = 22.180, p < 0.001), but no interaction between these factors (F(10,65) = 0.938, p = 0.505). Post hoc tests indicated that 85Q-treated animals had significantly greater tissue contractions (greater increases in average log Jacobian Determinant values) compared to Buffer- (p < 0.001) and 10Q- (p < 0.001) treated animals, with no differences between control groups (p = 0.203).

Similar to other imaging measurements, correlations were characterized between the observed TBM results and the behavioral measures; one-tailed Pearson correlations were computed between log Jacobian Determinant changes and behavioral change scores that had been collapsed across all five post-surgical timepoints. In regions with significant tissue atrophy, TBM changes in GM were correlated with all three behavioral measures, such that greater contractions were significantly associated with higher NRS scores (r(17) = 0.786, p < 0.001) (Figure 3D), longer Lifesaver retrieval latencies (r(17) = 0.730, p < 0.001) (Figure 3E) and fewer correct responses on the 3-Choice SDR task (r(15) = −0.683, p = 0.002; Figure 3F).

Reduced cortico-basal ganglia functional connectivity

rs-fMRI is a technique used to identify areas of the brain that exhibit correlated fluctuations in blood oxygenation level-dependent (BOLD) MR signal intensity in the absence of a specific stimulus (hence, ‘resting state’; Lv et al., 2018). Independent component analysis (ICA) of rs-fMRI is a data-driven computational method used to decompose correlated patterns of BOLD signals into networks (or ‘components’) with distinct spatial and temporal characteristics, without the reliance on pre-established user-defined ROIs for seed-based correlations. Using ICA, we identified four independent resting-state components (ICs) of interest using data collected at the baseline timepoint from all of the study animals. IC1 includes areas of the occipital cortex and ventrolateral PFC; IC2 includes the caudate, putamen, ventral sensory-motor cortex, and medial PFC; IC3 includes the caudate and several prefrontal and temporal cortical regions; and IC4 includes the caudate, putamen, cingulate, dorsal-prefrontal, and dorsal-motor areas (Figure 4—figure supplement 1). To facilitate longitudinal group-level comparisons, dual-regression (DR) analysis was applied to each timepoint, focusing on these four ICs, and z-score connectivity maps for each of the four ICs from each monkey at each timepoint were subsequently generated.

In the field of HD, studies applying rs-fMRI with ICA-DR (Dumas et al., 2013; Hohenfeld et al., 2018; Seibert et al., 2012; Werner et al., 2014) indicate that areas of decreased RSFC emerge first in premanifest HD-gene carriers, which shifts later in disease stages to increased RSFC, potentially as a compensatory mechanism. To define changes in RSFC in our model, we conducted voxel-wise comparisons for each IC between z-score maps from the baseline (pre-surgical) timepoint and subsequent timepoints using a whole brain mask. The network exhibiting the most protracted changes over the study timeline was component IC2, which involves striatal and sensory-motor areas (Figure 4, Figure 4—figure supplement 1). As early as 3 months post-surgery and continuing through the 30-month timepoint, 85Q-treated monkeys showed significant decreases in IC2 z-scores in many cortical and subcortical areas (p < 0.01). In contrast, none of the changes observed in 10Q and Buffer survived thresholding at the p < 0.01 level (Figure 4A). The percent volume of significant change in z-scores with IC2 were calculated for each ROI in the ONPRC18 labelmap at each timepoint and plotted in Figure 4B. The results highlighted regions of the VLPFC, VMPFC, SSC, IC as well as areas of the putamen, substantia nigra, globus pallidus, amygdala, and hippocampus with significantly reduced connectivity (p <0.01) to the IC2 network over the 30-month study timeline.

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IC2 RSFC.

Table 1 reports the percent volume of regions of interest (ROIs) that had p < 0.01 significant changes in IC2 z-scores identified by voxel-wise analyses in Group 85Q. Both control groups (10Q and Buffer) did not have any significant (p < 0.01) changes and are not included in this table. Table 2 reports the average change in z-score (from baseline) under the p < 0.01 voxels at each timepoint, for all 17 animals on study. These data were also averaged across timepoint and correlated with average behavioral scores (also included in Table 2).

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To characterize the overall time-course of these changes, the change in IC2 z-scores (from baseline) in these significant regions were calculated for each animal at each post-surgical timepoint and plotted in Figure 4C. A two-way repeated measure ANOVA revealed a significant main effect of Group (F(2,13) = 51.108, p < 0.0001), but no effect of Timepoint (F(5,65) = 0.666, p = 0.650) nor interaction (F(10,65) = 0.735, p = 0.689). Post hoc tests indicated that 85Q animals had significantly larger decreases in IC2 z-scores after surgery compared to the Buffer (p < 0.0001), and 10Q (p < 0.0001) animals, with no significant differences in the magnitude of z-score changes between controls (p = 0.742).

To probe the relationship between the changes in IC2 connectivity and the behavioral measures, correlations were computed between the z-score changes and behavioral change scores, collapsed across all five post-surgical timepoints. Similar to the changes we observed using the other imaging modalities, the magnitude of decreases in RSFC with IC2 correlated with all three behavioral measures such that larger decreases in RSFC were associated with higher NRS scores (r(17) = −0.924, p < 0.001) (Figure 4D), longer Lifesaver retrieval latencies (r(17) = −0.672, p = 0.003) (Figure 4E) and lower percent correct on the 3-Choice SDR task (r(15) = 0.857, p < 0.001) (Figure 4F).

In addition, significant changes emerged in IC3 at the 30-month timepoint, such that 85Q animals exhibited large regions of reduced functional connectivity with this network that were not apparent at the earlier times (Figure 4—figure supplement 4). Areas of the prefrontal cortex, caudate, and medial thalamus were particularly impacted. There were also modest, and transient changes in the functional connectivity of IC1, and IC4 over the 30-month study timeline. In 85Q-treated monkeys, areas of the occipital and prefrontal cortex exhibited an initial increase in connectivity with IC1 that returned to baseline levels by 6 months post-surgery (Figure 4—figure supplement 3). The changes observed in IC4 were more subtle (Figure 4—figure supplement 5), showing only small regions of cortex with altered RSFC compared to baseline. In all cases, however, none of the changes in IC1, IC3, or IC4 observed in 10Q and Buffer survived thresholding at the p < 0.01 level.

HTT85Q expression leads to aggregate formation

Following the final data collection point at 30 months post-surgery, animals were taken to necropsy and brains were collected for postmortem histological evaluation. Serial tissue sections throughout the brains of all animals were immunohistochemically stained using em48, an antibody that preferentially binds to polyQ-expanded HTT (82–150Q) and has been used widely to detect mHTT protein aggregates in human HD tissue samples as well as tissues from various animal models. We detected a mixture of both small and large em48+ aggregates in numerous brain regions of 85Q-treated macaques, but not in 10Q- or buffer-injected controls. Specifically, em48+ aggregates were found throughout the head of the caudate and throughout the putamen, corresponding to the areas of injection, as well in the deeper layers (V/VI) of several of cortical regions that send afferent projections to these regions, including expression in the dorsal and ventral prefrontal, dorsal and ventral premotor, supplemental motor, anterior cingulate, primary motor, and insular cortices, as well as lower levels of expression in the orbitofrontal, somatosensory, temporal and parietal cortices. Subcortical regions that contained em48+ aggregates included the amygdala, thalamus, globus pallidus, claustrum, and to a lesser extent, the hippocampus and substantia nigra. Figure 5A shows low (×4) and high (×20) magnification brightfield photomicrographs depicting examples of highly transduced cortical and subcortical brain regions. Triple-label immunofluorescence staining determined that em48+ mHTT aggregates were located in neurons (Figure 5B) but not detected in astrocytes (Figure 5C) in both the areas of injection (example from the putamen) as well as in distal cortical areas (example from the supplemental motor cortex). Expression was primarily restricted to the nucleus (Figure 5B, C; em48/Hoechst coexpression), where both diffuse and aggregated mHTT expression was routinely observed; however, small extracellular em48+ foci could also be observed in the neuropil in several gray matter regions. Additionally, em48+ aggregates were seen in localized areas in some WM tracts, including the corona radiata, corpus callosum, superior cingulum, internal capsule, external capsule, and prefrontal WM tracts (data not shown).

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Immunohistochemical staining with the N-terminal HTT antibody, 1–82 aa (2B4 clone), which recognizes both mutant and wildtype HTT, matched the same pattern of nuclear em48 expression seen in 85Q-treated animals, but showed diffuse, cytoplasmic staining in neurons from 10Q-treated control animals in the same brain regions. Buffer-treated animals showed only very light, near background levels of staining throughout the brain, likely owing to HTT sequence homology between humans and macaques from aa 1 to 82. This pattern of staining is similar to what has been reported in human HD and control cases (dark 2B4+ nuclear staining in HD cases and diffuse, lighter cytoplasmic staining in control cases; Herndon et al., 2009).

The goal of this study was to develop a macaque model of HD that recapitulates neurodegenerative changes throughout the cortico-basal ganglia network and gives rise to characteristic motor and cognitive decline seen in early-stage human HD patients. Secondarily, we sought to characterize the potential relationships between behavioral phenotypes and neuroimaging findings of disease progression in order to define a set of reliable outcome measures that can be used in future translational studies of candidate HD therapeutics in this model. Because the striatum is the earliest and most severe brain region affected in HD, with degeneration extending to WM and eventually widespread regions of the cortex (Vonsattel et al., 2011), we undertook a unique approach delivering a mixture of AAV2 and AAV2.retro in order to express mHTT throughout the entire macaque cortico-striatal circuit.

Over the 2.5-year (30-month) study timeline, HTT85Q animals displayed motor and cognitive deficits that were accompanied by microstructural alterations, atrophy, and reduced functional connectivity throughout the cortico-basal ganglia network. Due to the long scanning times achievable with anesthetized NHPs, high-resolution DTI enabled a more detailed analyses of WM tracts than has been previously achieved. The reduction in WM FA seen in HTT85Q macaques, a biomarker associated with myelin breakdown and axonal swelling, closely mirrors changes seen in human HD patient WM tracts, including the prefrontal WM tracts, corona radiata, internal and external capsules, and the corpus callosum (Estevez-Fraga et al., 2020). In addition to microstructural changes detected by DTI, HTT85Q-treated animals also exhibited subtle striatal and cortical atrophy, along with mild reductions in network connectivity, which were present by the first timepoint of analysis (3 months post-AAV-administration). The overall patterns of neurodegeneration that we characterized in this study models similar changes detected in prodromal and early-stage HD patients (Stoffers et al., 2010; Hobbs et al., 2010; Kipps et al., 2005; Dumas et al., 2013; Hohenfeld et al., 2018; Seibert et al., 2012; Werner et al., 2014). Future evaluation at even earlier timepoints will help address whether degenerative processes begin in the striatum first, before being detectable in WM and afferent cortical areas – as is seen in human HD cases – or whether these pathological changes occur simultaneously in this AAV-based model.

Beginning at 3 months post-surgery, 85Q-treated macaques developed mild motor phenotypes similar to those experienced by HD patients including incoordination, forelimb and orofacial chorea, hindlimb tremor and postural changes in the distal portion of the forelimbs. Over time, these behaviors worsened in severity, and further changes were observed including evidence of delayed gait initiation and hindlimb bradykinesia during locomotion. Furthermore, the severity of these phenotypes was exacerbated by the dopamine agonist, apomorphine (Figure 1H). Apomorphine has a high binding affinity for dopamine D₂, D₃, and D₅ receptors, and altered dopamine neurotransmission has been well documented in HD; for review, Cepeda et al., 2014. Positron emission tomography (PET) studies have confirmed a progressive loss of striatal D2 and D1 receptor density throughout the course of disease that correlate with clinical severity assessed using motor UHDRS and Total Functional Capacity (TFC) scales (Weeks et al., 1996; Andrews et al., 1999). PET studies are planned to characterize potential dopamine receptor density alterations in this model. Overall, the cognitive and motor phenotypes exhibited in HTT85Q macaques model some of the same symptoms experienced by patients in the early stages of their disease development.

Histological evaluation of brain tissue at 30 months post-surgery confirmed the presence of mHTT protein expression and pathological aggregate formation in the brains of 85Q-treated animals compared to controls. em48+ mHTT aggregates were detected in the same cortical and subcortical brain regions throughout the cortico-basal ganglia circuit that we previously characterized in animals assessed at 10 weeks post-administration of AAV2.retro-HTT85Q (Weiss et al., 2020). This finding suggests that mHTT aggregation in this macaque model is stable and does not involve additional brain regions over time. These data are in line with evidence from human HD postmortem brain tissues, showing that mHTT aggregate density in most cortical regions does not increase with worsening Vonsattel Grading (i.e., no difference between Grades 1–4), but rather is more dependent on the CAG repeat length, with higher CAG repeats correlating with mHTT aggregate density (Hickman et al., 2022). Our data show an anterior to posterior gradient of em48+ expression, with the highest levels of expression in prefrontal and premotor cortices, moderate levels in motor and somatosensory cortices, less expression in temporal and parietal cortices and little to no expression in the occipital cortices. These findings are in concordance with the pattern of aggregate density seen in human HD cases, with successive decreases in density seen from rostral to caudal cortices (BA9 > BA4 > BA7 > BA17) (Hickman et al., 2022). Our observations of em48+ inclusions predominantly in deeper cortical layers (V/VI) in 85Q-treated animals also matches the pattern seen in human HD brain tissue, where HTT+ aggregates predominate in the deeper, infragranular layers of the cortex (V/VI). These cortical layers serve as the primary output layers sending axons to subcortical structures, including the caudate and putamen (Hickman et al., 2022).

We confirmed robust levels of em48+ mHTT aggregates 85Q-treated animals in the same brain regions that showed the most significant changes in brain atrophy identified using TBM, including the caudate, putamen, prefrontal, premotor supplemental motor and anterior cingulate cortices. Moreover, em48+ inclusions were detected in the same WM tracts showing significant reduction in FA via DTI, including the ventral and dorsal prefrontal WM tracts, the anterior and superior corona radiata, the genu and body of the corpus callosum and the superior cingulum. em48+ aggregates in WM were largely located in, and in regions surrounding, the needle tracts. To prevent clogging of the needle, the infusion pump was run at a low rate (1 ul/min) while the needle was being lowered into the target brain regions; therefore, a small amount of viral vector was dispersed into WM along the needle tract.

Future histological studies are planned in this model to investigate potential gray matter neuronal loss, WM fiber loss and/or changes in myelin density. These data will be correlated with the imaging, behavioral and histopathological findings reported here. Additionally, given that the HTT fragment used in this model contains 83 pure CAGs, followed by a CAA/CAG cassette (single CAA interruption), the possibility for somatic instability cannot be ruled out and will be investigated using brain tissues collected from this same cohort. If present, we hypothesize that repeat expansion will be the greatest in the caudate and putamen, based on similar findings in human HD cases (Swami et al., 2009).

While the mouse models of HD developed to date have clear advantages (e.g., the relative ease of generating transgenic and knock-in animals, and the fact that they model some of the mHTT-mediated genetic changes (e.g., somatic instability) and neuropathological intracellular cascades seen in human HD), they do not replicate the complex array of behavioral symptoms seen in human patients, including chorea. Moreover, their much smaller brain size (~3700-fold smaller by weight) makes scaling up drug delivery strategies to humans an arduous task, particularly with a delivery that requires complex neurosurgery to deep brain structures. Work with large animal models of HD has accelerated greatly over the past decade due to the development of viral-based and genetically modified sheep, minipigs, and NHPs (Palfi et al., 2007; Yang et al., 2008; Jacobsen et al., 2010; Baxa et al., 2013). For a comprehensive review, see Howland et al., 2020. Transgenic HD sheep do not exhibit many of the overt behavioral phenotypes seen in human HD patients, aside from circadian disturbances, but do show signatures of mHTT-mediated pathology including the development of cortical mHTT-positive inclusions, evidence of increased brain urea, as well as loss of cannabinoid receptor 1 (CB1) and dopamine- and cyclic AMP-regulated phosphoprotein (DARPP-32) in the globus pallidus (Jacobsen et al., 2010; Reid et al., 2013; Handley et al., 2016; Handley et al., 2017). While HD sheep do not develop cognitive and motor phenotypes, at least out to 5 years of age, an advantage of this model over existing transgenic and viral-mediated minipig and NHP HD models is that it was created using cDNA for full length human mHTT (67 exons), providing a full landscape for HTT-lowering therapeutic constructs (Baxa et al., 2013). Transgenic HD minipigs have a long prodromal period, show evidence of mHTT-positive inclusions in striatum and cortex, reduced DARPP-32 expression, microgliosis and mild WM demyelination beginning at 2 years of age (Vidinská et al., 2018). At 4–6 years of age, HD minipigs show more profound neuropathological changes and only at 6–8 years of age do they develop a mild motor phenotype, including impaired gait and reduced treat retrieval by tongue. More recently, a knock-in minipig model has been created by Exemplar Genetics that expresses full-length mHTT-150Q in all tissues evaluated, and piglets show uncoordinated hindlimb movement (unpublished data). The sheep and pig models have been employed in preclinical HD research to screen promising HTT-lowering therapeutics and one of these approaches, AAV-mediated delivery of a mHTT-specific microRNA, has recently advanced to the clinical trial stage (AMT-130), illustrating how critical these large animal models are to the field (Vallès et al., 2021; Evers et al., 2018).

In comparison to the transgenic HD sheep and minipigs, the HD NHPs reported here have a much shorter premanifest period and display many of the cardinal features of HD that are often used as primary and secondary outcome measures in HD human clinical trials, including motor and cognitive decline measured via the UHDRS and TFC (via the NHP clinical rating scale and SDR task in this model) and regional brain atrophy that is quantified using MRI/DTI. Importantly, the behavioral and imaging findings in HTT85Q macaques correlated strongly with each other and constitute a comprehensive set of outcome measures that are be able to be used in future therapeutic evaluations in this model.

An advantage of viral-mediated HD macaques over the transgenic macaque models that have been created to date is that they can be generated in large enough numbers to appropriately power studies investigating new biomarkers of disease progression and promising therapeutics. While the transgenic HD macaque model (exons 1–10 of the hHTT gene with 67–73Q) created by Chan et al. showed several key disease symptoms (progressive motor phenotypes, evidence of impulsivity, and changes in temperament), along with WM microstructural changes, striatal atrophy, and aggregate formation, they only generated and characterized a small cohort of three transgenic animals, along with controls, precluding evaluation of any therapeutics (Chan et al., 2014; Chan et al., 2015; Raper et al., 2016; Meng et al., 2017; Lallani et al., 2019). In addition to being able to generate larger cohorts of animals, viral-vector-based macaque models allow for leeway in model design including the ability to assess different promoters, HTT fragment lengths, CAG repeat lengths, capsid serotypes (and combinations thereof) in a shorter timeframe, and with less expense, compared to transgenic and knock-in NHP models. For example, if desired, a longer prodromal phase in this AAV-based macaque model may be achievable by expanding the HTT fragment length (i.e., expressing the first 10 exons of human mHTT cDNA vs. the first 3 exons). Increasing the mHTT fragment length would also expand the real estate available for mHTT- lowering therapeutics. A longer prodromal phase may also be achieved by lowering the CAG repeat number, particularly given that HD patients show a direct correlation between CAG repeat length and age at disease onset (Lee et al., 2012). As the CAA/CAG cassette has been recently shown to associate with disease progression scores in human HD patients (Ciosi et al., 2019), removal or duplication of this cassette may be another mechanism by which the rate of disease progression can be hastened or prolonged, respectively. Another possibility is to engineer patient-relevant single nucleotide polymorphisms into the mHTT transgene for evaluation of allele-specific HTT-lowering therapeutics.

While the AAV2:2retro-HTT85Q model presented here offers advantages over some of the existing small and large HD animal models, there are limitations to acknowledge as well. Current viral vector packaging capacity limitations preclude expression of the full-length HTT gene and the N171 N-terminal fragment of mHTT is expressed instead. This size restriction extends to the control construct as well, and may be responsible for some of the intermediate behavioral effects that we observed in the 10Q group, as wildtype HTT is not typically cleaved by cellular proteases into smaller N-terminal fragments. Other limitations of this model include expression of HTT from a strong promoter (CAG) versus an endogenous HTT promoter and the fact that HTT85Q macaques have two wildtype, endogenous HTT alleles, in addition to the pathogenic human mHTT transgene. The HTT85Q transgene lacks introns, which precludes the formation of alternatively spliced variants (e.g., HTTexon1), known to contribute to mHTT-mediated toxicity (Sathasivam et al., 2013). Future optimization of the transgene design to include intron 1 may be able to get around this limitation. Finally, expression of mHTT in viral-based models is limited to areas of transduction, while HTT is expressed throughout the brain and in peripheral tissues. The current model employed a mixture of AAV2 and AAV2.retro delivered into the caudate and putamen, which achieved a much broader expression of mHTT throughout the brain compared to previous vector-based models, but expression is not ubiquitous.

As some of the HTT-lowering therapeutics currently under preclinical investigation are delivered using viral vectors (i.e., miRNAs, zinc finger protein-repressors, CRISPR-mediated gene editing, etc.) it will be critical to investigate the potential immune considerations of AAV-based therapeutics in this model, where neutralizing antibodies generated from creating the model could potentially reduce the efficacy of a second AAV vector to deliver its gene cargo. Should this be an issue, plasmapheresis, immunosuppression and/or capsid serotype switching using AAVs from distinct clades may be viable options. Other therapeutics also amendable to testing in this model include antisense oligonucleotides, stem cell-based therapeutics, small molecules, neurotransmitter-modulating pharmacotherapeutics, among others. Taken together, we are hopeful that the AAV2:AAV2retro macaque model will become a new resource for the HD research community, both for identifying novel biomarkers of disease progression as well as testing promising therapeutic candidates.

The rhesus macaque brain atlas used to assess neuroimaging data has been previously published and uploaded to the Neuroimaging Tools and Resources Collaboratory (NITRC) https://www.nitrc.org/projects/onprc18_atlas. Statistical results reported in Supplementary Files 1, 2, 4, 5.

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Author details

1. Alison R Weiss

   Division of Neuroscience, Oregon National Primate Research Center, Beaverton, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1821-8193

2. William A Liguore

   Division of Neuroscience, Oregon National Primate Research Center, Beaverton, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

3. Kristin Brandon

   Division of Neuroscience, Oregon National Primate Research Center, Beaverton, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

4. Xiaojie Wang

   1. Division of Neuroscience, Oregon National Primate Research Center, Beaverton, United States
   2. Advanced Imaging Research Center, Oregon Health and Science University, Portland, United States

   Contribution

   Formal analysis, Supervision, Visualization, Writing – review and editing

   Competing interests

   No competing interests declared

5. Zheng Liu

   1. Division of Neuroscience, Oregon National Primate Research Center, Beaverton, United States
   2. Advanced Imaging Research Center, Oregon Health and Science University, Portland, United States

   Contribution

   Formal analysis, Supervision, Visualization, Writing – review and editing

   Competing interests

   No competing interests declared

6. Jacqueline S Domire

   Division of Neuroscience, Oregon National Primate Research Center, Beaverton, United States

   Contribution

   Supervision, Project administration

   Competing interests

   No competing interests declared

7. Dana Button

   Division of Neuroscience, Oregon National Primate Research Center, Beaverton, United States

   Contribution

   Supervision, Visualization, Writing – review and editing

   Competing interests

   No competing interests declared

8. Sathya Srinivasan

   Imaging and Morphology Support Core, Oregon National Primate Research Center, Beaverton, United States

   Contribution

   Methodology, Resources, Visualization

   Competing interests

   No competing interests declared

9. Christopher D Kroenke

   1. Division of Neuroscience, Oregon National Primate Research Center, Beaverton, United States
   2. Advanced Imaging Research Center, Oregon Health and Science University, Portland, United States
   3. Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Funding acquisition, Methodology, Supervision, Validation, Visualization, Writing – review and editing

   Competing interests

   No competing interests declared

10. Jodi L McBride

    1. Division of Neuroscience, Oregon National Primate Research Center, Beaverton, United States
    2. Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, United States

    Contribution

    Conceptualization, Formal analysis, Investigation, Funding acquisition, Supervision, Validation, Visualization, Writing – original draft, Project administration, Writing – review and editing

    For correspondence

    mcbridej@ohsu.edu

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-4816-7569

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