Alterations in Metal Homeostasis Occur Prior to Canonical Markers in Huntington Disease

Alterations in Metal Homeostasis Occur Prior to Canonical Markers in Huntington Disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Alterations in Metal Homeostasis Occur Prior to Canonical Markers in Huntington Disease Anna C Pfalzer, Yan Yan, Hakmook Kang, Melissa Totten, James Silverman, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-956730/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Objective: The importance of metal biology in neurodegenerative diseases such as Huntingtin Disease is well documented with evidence of direct interactions between metals such as copper, zinc, iron and manganese and mutant Huntingtin pathobiology. To date, it is unclear whether these interactions are observed in humans, how this impacts other metals, and how mutant Huntington alters homeostatic mechanisms governing levels of copper, zinc, iron and manganese in cerebrospinal fluid and blood in HD patients. Methods: Plasma and cerebrospinal fluid from control, pre-manifest, manifest and late manifest HD participants were collected as part of HD-Clarity. Levels of cerebrospinal fluid and plasma copper, zinc, iron and manganese were measured as well as levels of mutant Huntingtin and neurofilament in a sub-set of cerebrospinal fluid samples. Results: We find that elevations in cerebrospinal fluid copper, manganese and zinc levels are altered early in disease prior to alterations in canonical biomarkers of HD although these changes are not present in plasma. We also evidence that CSF iron is elevated in manifest patients. The relationships between plasma and cerebrospinal fluid metal are altered based on disease stage. Interpretation: These findings demonstrate that there are alterations in metal biology selectively in the CSF which occur prior to changes in known canonical biomarkers of disease. Our work indicates that there are pathological changes related to alterations in metal biology in individuals without elevations in neurofilament and mutant Huntingtin. Scientific Communication Neurology Health Economics & Outcomes Research metal biology neurodegenerative diseases Huntingtin Disease Alterations canonical markers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction: Essential trace metals play a vital role in several metabolic processes throughout the body including regions of the brain. Although their concentrations are lower compared to more bulk elements like calcium and sodium, they are necessary for the proper function and structure of many proteins. In fact, approximately 10% of human genes contain zinc (Zn)-finger domains 1 . The most abundant trace elements in human body are Iron (Fe), Zn, Copper (Cu), and manganese (Mn). These compounds have been shown to regulate mitochondrial function 2 , oxidative stress 3 , inflammation, synaptic signaling, cell signaling, glycobiology 4 , 5 , neurotransmitter synthesis and protein aggregation 6 . Both intracellular and extracellular essential metals are tightly regulated because deficiencies and excesses in result in detrimental effects on biological systems. Regulation predominantly occurs at the level of the gut which prevents dietary over-exposures through absorption and instances where toxic accumulations of metals occur typically bypass gastrointestinal regulation. For instance, over-exposure to manganese through various occupations results in a Parkinsonian-like condition called Manganism 7 . Copper accumulation in the brain due to Wilson’s disease results in involuntary movements and cognitive impairment 8 . Conversely, deficiencies in copper seen in Menke’s disease is also associated with cognitive and motor impairments 9 . The role of essential metals specifically in the context of Huntington Disease (HD) has been explored in in vivo and in vitro models of disease. There is a clear and consistent interaction between Mn and mutant Huntingtin (HTT) pathobiology in cell and rodent models. Manganese (Mn) exposure in HD cells can correct deficits in metabolic pathways implicated in HD pathology such as autophagy 10 and insulin signaling 11 . Mn exposure can also correct abnormalities in the striatal urea cycle in HD rodents 12 . We also observe global suppression of transcriptomic and metabolomic response to Mn in the same rodent model 13 , 14 – suggesting impairments in Mn trafficking in HD. Iron also accumulates in post-mortem HD brains as well as in HD animal models 2 . Iron chelation improves molecular and behavioral indicators of disease 15 . Alterations in Cu homeostasis has received considerable attention. Aberrations in Cu homeostasis have been observed in cell and rodent models of HD 6 as well as in cerebrospinal fluid 16 and post-mortem tissue 17 . Further, Xiao et al found a direct interaction between elemental Cu and mutant HTT aggregates 6 and that increases in intracellular Cu lead to increased mHTT aggregation 6 . Clinical application of these findings were tested in a clinical trial designed to investigate the effect of a Cu chelator on clinical outcomes in motor manifest HD, though this study did not meet its primary endpoint 18 . While there is consistent evidence for alterations in metal biology in HD, there are many unanswered questions regarding the stability of metal homeostasis and the timing over which these alterations take place. The establishment of HDClarity, a large biofluid collection initiative, has provided access to CSF and plasma samples from individuals with HD at different clinical stages of progression. Here we assessed levels of key metals (Cu, Fe, Mn and Zn) in CSF and plasma in HD Clarity samples. Our goal was to identify the timing and stability of changes in central and systemic metal biology in HD compared to canonical markers of disease. Results: Clinical Demographics Pre-manifest participants were significantly younger than the control and manifest groups as expected. Late manifest participants were significantly older than the other three study groups as shown in Table 1 , also as expected. There were no significant differences in trinucleotide C-A-G repeat length among the HD study groups ( Table 1 ). Among the behavioral and functional assessments, total functional capacity (TFC) and symbol digit modality test (SDMT) were similar between the Control and PRE groups with significant reductions in TFC in MAN and LATE groups (Table 1). Performance on the Stroop Word Reading (SWR) and total motor score (TMS) assessment incrementally decreased with disease progression (Table 1). The composite Unified Huntington Disease Rating Scale (cUHDRS) is an indicator of disease stage using assessments of cognitive capacity (SDMT, SWR), motor function (TMS) and functional capacity for activities of daily living (TFC). cUHDRS score decreases with disease severity, where a negative value is indicative of a more progressed patient compared to an individual with a positive cUHDRS score. cUHDRS scores do not significantly differ between the Control and PRE group; whereas there is a progressive decline between PRE, MAN and LATE ( Table 1 ). Table 1. Participant Baseline Demographics by Disease Stage Control (n=12) Pre-manifest (n=16) Manifest (n=16) Late Manifest (n=16) Age 47.75± 10.81 a 39.125± 9.78 b 47.0625± 7.34 a 57.6875± 8.74 c Sex (M,F) 7,5 8,8 7,9 9,7 CAG 19.75± 3.89 a 42.4375± 1.46 b 43.75± 1.77 b 43.8125± 1.87 b TFC 12.92± 0.29 a 12.625± 0.62 a 10.25± 3.34 b 5.0625± 4.25 c SDMT 55.67± 10.05 a 52.75± 15.93 a 34.25± 13.89 b 21.33± 16.09 c SWR 107.75± 17.51 a 84.1875± 28.03 b 62.4375± 19.17 c 43.82± 29.10 d TMS 1.42 ± 3.70 a 6.3125± 8.93 b 29.0625± 22.39 c 58.01± 29.97 d cUHDRS 17.71± 1.72 a 15.80± 2.73 a 10.30±4.99 a 5.80±6.76 b Table 1. Differences in baseline demographic variables were identified using a 1-way ANOVA with post-hoc testing after determination of a significant main effect (p<0.05). Participant age is reported in years as well as the proportion of males to females (M,F). The number of trinucleotide repeats (CAG) as well as performance on total functional capacity (TFC), symbol digit modality test (SDMT), stroop word reading (SWR), total motor score (TMS) and the compositive United Huntington Disease Rating Scale (cUHDRS) scores are reported here as mean ± S.D and values that do not significantly differ share a superscript. Metal stability The stability of metal homeostasis was assessed in Control and PRE groups by comparing baseline to the 4-8 week follow up CSF and plasma metal levels ( Table 2 ). Interestingly, there were no differences between baseline and follow up CSF or plasma metal levels in Control participants but in the PRE group, CSF Cu and plasma Zn (highlighted in grey) were significantly altered at the follow up visit compared to baseline. Table 2. Baseline and Follow-up Cerebrospinal Fluid and Plasma Metals in Control and Pre-manifest Participants Control (BL) Control (FU) Pre-manifest (BL) Pre-manifest (FU) CSF Mn (ug/L ± S.D) 7.20±6.47 a 4.44±4.93 a 7.23±3.41 a 13.21±9.06 a CSF Cu (ug/L ± S.D) 14.32±8.80 a 16.47±10.30 a 27.45±23.87 a 42.52±43.51 b CSF Fe (ug/L ± S.D) 111.07±66.93 a 114.45±53.41 a 192.71±92.22 a 162.12±107.2 a CSF Zn (ug/L ± S.D) 207.41±65.85 a 270.11±119.68 a 171.29±65.45 a 191.89±76.57 a Plasma Mn (ug/L ± S.D) 16.77±4.23 a 18.27±4.80 a 18.66±8.94 a 16.85±7.97 a Plasma Cu (ug/dL ± S.D) 121.76±19.38 a 124.13±41.63 a 139.84±41.47 a 157.79±44.08 a Plasma Fe (ug/dL ± S.D) 182.31±74.04 a 186.24±59.89 a 172.15±64.16 a 171.84±58.10 a Plasma Zn (ug/L ± S.D) 118.26.3±78.20 a 178.52±102.45 a 178.30±116.70 a 68.54±54.36 b Table 2. Differences between baseline and follow up cerebrospinal fluid and plasma metal levels in control and pre-manifest participants. Differences were examined using Mann-Whitney tests between visits and not explored across genotypes. Baseline (BL) and 4-8 week follow up (FU) cerebrospinal (CSF) and plasma manganese (Mn), Copper (Cu), Iron (Fe), Zinc (Zn) were measured using GF-AAS and shown here as mean ± S.D and values that do not significantly differ share a superscript. Significant differences in Pre-manifest FU metals are indicated with grey shading. Metals elevated in early HD CSF Cu, Mn and Fe significantly increase in HD ( Figure 1A, 1B and 1C ) compared to CSF Zn which decreases in HD samples. CSF Cu is significantly elevated in PRE and LATE participants compared to Control ( Figure 1C ); in contrast, CSF Zn is significantly reduced in PRE and LATE participants compared to Control ( Figure 1D ). CSF Fe consistently increases across disease stages and significantly differs between Control and MAN and LATE study groups. It is noteworthy that there were no significant correlations between CSF metal levels and age (data not included). It is well-known that Cu and Zn, Fe and Zn, and Mn and Fe are regulated in opposite directions by oxidative stress 19 and as a result, the ratio of Cu:Zn, Fe:Zn and Mn:Fe could be a more robust indicator of early-onset pathology 19 in HD. The ratio of CSF Cu:Zn and CSF Fe:Zn are elevated in the PRE and LATE study arms compared to Control ( Figure 1E and 1F ). We did not observe any significant changes in CSF Mn:Fe ratio. CSF Cu is positively correlated with cUHDRS score (p<0.01) while CSF Zu is negatively correlated with cUHDRS ( Figure 1G and 1H ) while there was no correlation between cUHDRS and CSF Mn or Fe. Interestingly, the plasma showed no significant differences between Control and HD metal levels or the levels of metal ratios between Cu, Fe and Zn ( Figure 2A-2G ). There were also no significant differences in plasma Mn:Fe ratio. The correlation between plasma Cu and cUHDRS was not significant; however, there was a significant positive correlation between plasma Zn and cUHDRS. The ratio of CSF to plasma metal levels has previously been implicated as a marker of blood-brain barrier integrity. The ratio of CSF:plasma Cu significantly increases with disease progression ( Figure 3C ) although individual pair-wise comparisons did not reach statistical significance. We observed no significant correlations between CSF and plasma metals across all samples (data not shown). We next investigated the potential for this relationship to be disease specific and found that disease (stage) impacts the relationship between CSF and plasma metals ( Figure 4 ). Specifically, CSF Mn x CSF Zn, CSF Zn x plasma Cu, and plasma Fe x plasma Cu are all significantly negatively correlated in Control participants whereas none of these correlations exist in PRE, MAN or LATE study arms ( Figure 4 ). CSF Mn x CSF Cu, and CSF Mn x CSF Fe are both positively correlated in PRE and MAN ( Figure 4B and 4C ) whereas this relationship does not exist for Control or LATE stage participants ( Figure 4A and 4D ). A significant negative correlation appears in LATE stage participants between plasma Zn x plasma Cu ( Figure 4D ). Metal levels change prior to elevations in biomarkers As expected, mutant Huntingtin (mHTT) levels increase with disease stage ( Figure 5A ), disease burden ( Figure 5B ) and clinical severity ( Figure 5C ). Similarly, Neurofilament light (NfL) levels also increase with disease stage ( Figure 5D ), disease burden ( Figure 5E ) and clinical severity ( Figure 5F ). Interestingly, mHTT and NfL levels were not significantly different between our Control and PRE groups ( Figures 5A and 5D ). We examined how increases in mHTT and NfL related to CSF metal levels ( Figure 6 and 7 ). CSF Cu levels increase with modest elevations in NfL, but are reduced in individuals with the highest levels of NfL (ANOVA p-value: 0.058; Figure 6C ). A reverse trend appears in CSF Zn, with reductions in Zn corresponding to modest elevations in NfL ( Figure 6D ). We found no clear indication that CSF metal levels were impacted by mHTT levels ( Figure 7 ). Discussion: The role of essential metals in neuronal health has been well-established 20 with deficiencies and excesses both resulting in neurological symptoms which include cognitive deficits and involuntary movements 21 . Metal levels are elevated in post-mortem tissue in HD 22 . Several in vivo and in vitro studies in HD disease models demonstrate that alterations in metal biology impact molecular pathways implicated in HD pathology 10 , 12 , 13 . There is also a direct interaction between elemental Cu and exon 1 of mutant Huntingtin (HTT) protein 6 . Despite these observations directly linking metal biology to HD pathology, the timing and stability of changes to the metallome are unknown as well as whether changes in the CNS are recapitulated in blood. Our work outlined below begins to address these unanswered questions. Here, we assessed CSF and plasma metal levels in a cohort of control and HD participants, and examined relationships between metals and HD biomarkers in a sub-set. Pre-manifest participants were significantly younger in age compared to control, but had similar scores on clinical indicators of cognitive function and quality of life. As expected, cognitive and motor function decline with disease progression. Prior to this decline, we note elevations in CSF Mn and Cu, and reductions in CSF Zn. That is, we infer the timing of these changes based on our findings in pre-manifest participants, but not manifest or late cohorts. There was no correlation between age, and metal levels (CSF or plasma). These elevations in CSF Cu (24-47µg/L) are not as substantial as that seen in Wilson’s disease, ~76 µg/L 21 . We do not observe these same alterations in Mn, Cu and Zn in plasma although we do find that the CSF:plasma ratio for Mn and Cu are significantly elevated in HD compared to controls (Figure 3 ). Taken together, these findings demonstrate that there are early alterations in metal homeostasis in the CSF, not observed in the plasma. These CSF-specific changes may reflect changes to the integrity of the blood-brain barrier (BBB) or metal transport across the blood-brain barrier, which is noted to be impaired early in disease in rodent models 23 . Additionally, we find that the interactions among essential metals changes with disease progression. Because of essential metal interdependency, dys-homeostasis of a single metal will result in aberration dys-homeostasis of others. For instance, increased Cu can replace Zn on Zinc-dependent enzymes which alters the functional status of those proteins 24 . Our results show a negative correlation between CSF Mn and Zn only in controls. Previous research demonstrates that increases in Mn levels are associated with reductions in Zn under control conditions. This suggests that CNS Mn- or Zn-dependent transport is also altered early in HD. Perhaps the most striking finding relates to our observed changes in CSF metals occur prior to elevations in canonical markers of HD. Specifically, the early changes in CSF Cu and Zn levels pre-date changes in mHTT and NfL in the pre-manifest participants compared to control. Despite there being no significant elevations in mHTT and NfL in pre-manifest participants, both biomarkers did correlate with markers of disease burden (CAP-score) and disease status (cUHDRS). These findings suggest that early sequelae of mutant Huntingtin may result in toxic alterations of essential metal regulation. There are several known physiologic mechanisms by which excess Cu exerts detrimental effects – which may contribute, in part, to the pathology of HD. The toxicity of Cu depends largely upon whether Cu is bound to transport proteins or a free ion. Unfortunately, our methodology does not allow us to differentiate between free and bound metals and thus, we cannot interrogate the possibility that elevations in metal levels reflect increases in free reactive ion species. It is known that excesses of extracellular free Cu ions dramatically increase oxidative stress through its role in free radical regulation 25 . Free Cu initiates the production of free radicals through the Fenton reaction which produces reactive hydroxyl groups 25 . Copper exposure also stimulates the secretion of pro-inflammatory cytokines such as IL-1, IL-4, TNFα in the brain and blood 26 . These same cytokines are elevated in blood of Huntington Disease patients 27 . Lastly, there is evidence that Cu (as well as Zn) regulates neurotransmission in the brain. Studies examining the role of copper in neurotransmitter secretion found that substances which induce Cu release from cells also induce the synthesis and secretion of the primary inhibitory neurotransmitter GABA 28 . Copper release has also been linked to NMDA receptor activation – where localization of the copper transporter to the plasma membrane activates NMDA receptors 29 . Imbalances to GABA homeostasis have been clearly delineated in Huntington Disease with the striatum being one of the most densely connected areas to GABA-ergic neurons 30 . It is feasible that elevations in Cu and reductions in Zn participate in the pathogenesis of HD through their involvement in the management of reactive oxygen species, inflammation and neurotransmission. Although we demonstrate clear elevations in CSF metals prior to elevations in canonical markers of disease, the cause of these extracellular changes and their intracellular consequences remain unclear. More so, it is unknown whether the extracellular space recapitulates what is occurring intracellularly. Based upon the known interaction between Cu and mutant Huntingtin aggregates, we postulate that the accumulation of aggregates with bound Cu accelerates neuronal death in two ways: i) Cu increases mutant Huntingtin aggregation and ii) deficiencies in Cu-dependent biological processes due to sequestration by mutant Huntingtin. Interestingly, there is considerable overlap between the molecular mechanisms implicated in HD pathology and Cu-dependent biological processes: mitochondrial function via cytochrome C oxidase, dopamine excess via dopamine β-hydroxylase, and oxidative stress via superoxide dismutase 1. Our observed elevations in CSF Cu early in disease may not recapitulate intracellular levels, in fact, we propose that in HD, Cu is sequestered by mutant HTT and thus creates conditions of intracellular Cu deficiency despite elevations in the extracellular space. In sum, our work provides important insights into metal biology under normal homeostatic mechanisms as well as alterations in these mechanisms in the context of HD. We report here that CSF Cu, Mn and Zn are altered prior to established disease biomarkers and track with indicators of clinical severity. Our findings provide a strong scientific premise to explore the mechanistic link between Cu and Zn and mHTT and how alterations in these intracellular/extracellular metal levels contribute to neuronal pathology. Together, these investigations might validate a novel biomarker of early HD pathology to utilize in the new phase of clinical investigations. Methods: Samples Plasma and cerebrospinal fluid (CSF) were collected from 60 participants as part of the CHDI HDClarity study. There were 16 pre-motor manifest (PRE), 16 manifest (MAN) and 16 moderate-late (LATE) manifest HD and 12 control participants. Disease stage was determined using the diagnostic confidence level (DCL), length of CAG expansion and burden of pathology 31 calculated from (CAG expansion – 35.5) x Age. Control participants were individuals without a known history of Huntington Disease (HD). All HD participants have a CAG expansion of ≥ 40. PRE individuals were not motor manifest as indicated by a DCL of 250. MAN participants had a DCL =4 and a total functional capacity (TFC) between 7-13. The LATE group had all the above criteria for MAN and a TFC score between 0-6. Repeat CSF and blood samples collected 4-8 weeks after a baseline visit are provided for all control and PRE participants. Participant age and gender are reported here. Three participants (2 PRE, 1 MAN) were taking supplemental vitamins however, their metal levels were similar to those in their corresponding participant group and thus, the data from these participants are included. Basic demographics like age and gender are reported here in addition to participants scores on a battery of cognitive, behavioral and motor assessments including the symbol digit modality test (SDMT), Stroop Word Reading (SWR), total functional capacity (TFC) and total motor score (TMS). Schobel et al recently proposed a novel indicator of clinical severity, the composite Unified Huntington Disease Rating Scale (cUHDRS) which incorporates a participants performance on the four aforementioned functional, cognitive and motor tasks: TMS, SWR, SDMT and TFC 32 . Metals Plasma and CSF iron (Fe), manganese (Mn), copper (Cu) and zinc (Zn) concentrations were measured with graphite furnace atomic absorption spectrometry (GFAAS, Varian AA240, Varian, Inc., Palo Alto, CA). Fifty microliters of plasma and CSF were digested in ultrapure nitric acid (1:10 wt/vol dilution) for 48–72 h in a sand bath (60°C); 50 µL of digested sample was brought to 1 mL of total volume with 2% nitric acid and analyzed for Mn, Fe, Cu and Zn. CSF samples were diluted 1:4 for Cu and Mn and diluted 1:32 or 1:64 for Fe and Zn. Plasma samples were diluted 1:20 for Mn, 1:40 for Cu, 1:100 for Fe and up to 1:1000 for Zn. The dilutions for these samples were based upon a standard curve specific to each metal. A bovine liver (NBS Standard Reference Material, USDC, Washington, DC) was digested in ultra-pure nitric acid and used as an internal standard for analysis. Biomarkers An interim analysis of known HD biomarkers was conducted by a research team at CHDI which analyzed Neurofilament light (NfL), mutant Huntingtin (mHTT), total Huntingtin (totHtt), total protein (totPro) and Hemoglobin (Hb). Specific information regarding assays are available on the CHDI website 33 . As this was an interim analysis, cerebrospinal fluid biomarker data was only available for a sub-set of samples (n=9 control, n=12 pre-manifest, n=13 manifest and n=11 late manifest). There were no samples which had both a baseline and follow-up visit and to date, no biomarker data in blood. Data are reported here as picograms/milliliter (pg/mL) of NfL or femtomolar (fM) mHTT adjusted by total protein levels (i.e. NfL/total protein and mHTT/total protein) to account for differences in CSF protein levels. Associations between essential metals and biomarkers were analyzed by grouping mHTT and NfL into low, medium, high and very high categories based upon previous categorizations. Statistics We utilized a parametric, univariate ANOVA to analyze differences in (baseline participant demographics and assessments: age, CAG repeat length and scores for total functional capacity, symbol digit modality test, stroop word reading, total motor score from the Unified Huntington Disease Rating Scale (UHDRS) and composite UHDRS (cUHDRS) (Table 1 ). We utilized non-parametric models for all metal and biomarker analyses to prevent assumptions of normality as previous work examining metals in biofluids display normal 34 and non-normal distributions 35 . A univariate ANOVA was used to identify differences in CSF and plasma metal (ratio) levels between disease groups as well as differences between levels of the HD biomarkers mutant HTT and NfL. Data are reported as the median with quartiles and 95% confidence interval. Tukey’s post-hoc testing was completed after determination of a significant (p<0.05) main effect. Group values which do not significantly differ share the same superscript. To investigate the stability of metal homeostasis, we only examined the effect of time within a genotype (i.e. baseline vs follow up) using Mann-Whitney tests. Correlations between CSF and plasma metal levels were assessed using Spearman correlations for non-parametric data with Spearman correlation coefficients and p-values adjusted for multiple comparisons reported. Ethics There samples were provided by CHDI as de-identified samples with select pieces of medical and clinical information which did not pose additional risk for participant identification. The molecular work outlined in this manuscript was approved by the Vanderbilt University Medical Center Internal Review Board (IRB# 191615) and adhered to all relevant guidelines and regulations. Informed Consent was obtained at each HDClarity study site prior to conducting any study procedures performed in accordance with the Declaration of Helsinki. Declarations ACKNOWLEDGEMENTS: Data used in this work was generously provided by the participants in the Enroll-HD study and made available by CHDI Foundation, Inc. Enroll-HD is a global clinical research platform intended to accelerate progress towards therapeutics for Huntington's disease; core datasets are collected annually on all research participants as part of this multi-center longitudinal observational study. Enroll-HD is sponsored by CHDI Foundation, Inc., a nonprofit biomedical research organization exclusively dedicated to developing therapeutics for Huntington's disease. Enroll-HD would not be possible without the vital contribution of the research participants and their families. Data used in this work would not be possible without the vital contribution of the research participants and their families in the HD-Clarity and HD-CSF studies. HD-Clarity and HD-CSF are cerebrospinal fluid collection initiatives designed to facilitate therapeutic development for Huntington's disease. HD-Clarity and HD-CSF are led by Dr. Edward Wild and sponsored by University College London. HD-Clarity is funded by CHDI Foundation, Inc., a nonprofit biomedical research organization exclusively dedicated to developing therapeutics that will substantially improve the lives of those affected by Huntington's disease. The Medical Research Council UK (MR/M008592/1) funded HD-CSF. The work outlined in this manuscript project was supported by CTSA award No. UL1 TR002243 from the National Center for Advancing Translational Sciences. Its contents are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. AUTHORSHIP: ACP received the study samples and funding to complete the work; MT and KE completed the metal analysis; ACP, DC, YY and HK conducted the statistical analyses; ACP drafted the manuscript; JS, MT, ABB and DOC edited the manuscript. CONFLICTS OF INTEREST ACP, YY, HK, MT, JS, ABB, KE, DOC have no commercial conflicts of interest relevant to this study. References De Benedictis, C. A., Vilella, A. & Grabrucker, A. M. The Role of Trace Metals in Alzheimer’s Disease. in Alzheimer’s Disease (ed. Wisniewski, T.) (Codon Publications, 2019). Agrawal, S., Fox, J., Thyagarajan, B. & Fox, J. H. Brain mitochondrial iron accumulates in Huntington’s disease, mediates mitochondrial dysfunction, and can be removed pharmacologically. Free Radic. Biol. Med. 120,317–329(2018). Cornett, C. R., Markesbery, W. R. & Ehmann, W. D. Imbalances of trace elements related to oxidative damage in Alzheimer’s disease brain. Neurotoxicology 19,339–345(1998). Bendiak, B. & Schachter, H. 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Aluminum and copper in drinking water enhance inflammatory or oxidative events specifically in the brain. J. Neuroimmunol. 176,16–23(2006). Björkqvist, M. et al. A novel pathogenic pathway of immune activation detectable before clinical onset in Huntington’s disease. J. Exp. Med. 205,1869–1877(2008). Kardos, J., Kovács, I., Hajós, F., Kálmán, M. & Simonyi, M. Nerve endings from rat brain tissue release copper upon depolarization. A possible role in regulating neuronal excitability. Neurosci. Lett. 103,139–144(1989). Schlief, M. L., Craig, A. M. & Gitlin, J. D. NMDA receptor activation mediates copper homeostasis in hippocampal neurons. J. Neurosci. Off. J. Soc. Neurosci. 25,239–246(2005). Hsu, Y. T., Chang, Y. G. & Chern, Y. Insights into GABAAergic system alteration in Huntington’s disease. Open Biol. 8,180165(2018). Penney, J. B., Vonsattel, J. P., MacDonald, M. E., Gusella, J. F. & Myers, R. H. CAG repeat number governs the development rate of pathology in Huntington’s disease. Ann. Neurol. 41,689–692(1997). Schobel, S. A. et al. Motor, cognitive, and functional declines contribute to a single progressive factor in early HD. Neurology 89,2495–2502(2017). Research tools & reagents | CHDI Foundation. https://chdifoundation.org/research-tools-reagents/ . Hozumi, I. et al. Patterns of levels of biological metals in CSF differ among neurodegenerative diseases. J. Neurol. Sci. 303,95–99(2011). Patti, F. et al. CSF neurotoxic metals/metalloids levels in amyotrophic lateral sclerosis patients: comparison between bulbar and spinal onset. Environ. Res. 188,109820(2020). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 31 Jan, 2022 Reviews received at journal 28 Jan, 2022 Reviewers agreed at journal 19 Jan, 2022 Reviews received at journal 30 Dec, 2021 Reviewers agreed at journal 20 Dec, 2021 Reviewers agreed at journal 19 Dec, 2021 Reviewers invited by journal 17 Dec, 2021 Editor assigned by journal 17 Dec, 2021 Editor invited by journal 11 Oct, 2021 Submission checks completed at journal 11 Oct, 2021 First submitted to journal 05 Oct, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-956730","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":56221177,"identity":"18d812f7-989c-436e-a7dc-9fc7596d9863","order_by":0,"name":"Anna C Pfalzer","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYDAD9gbmBiBlQ4IWngOMIC1ppGs5TFgl/+zegx8YahjyeNgPNn/4uOd84oZrhx8wfNxTi1OLxJ1zyRIMxxiKeXgSGwxnPLuduOF2mgHjjGfHcVtzI8dAAuikxP0MiQ3JPAduGxvczmFg5jlwDKcO+Rs5xj9AWnr4HzYc/nPgHGEtBjdyzMC29EgkNjYzHDggB9VSg1OLIVCLRcIxiWIeiYfNjD0HkuUkgX45OOPAAZxa5IAOu/GhxiaPhz/58IcfB+x4+G4nP3zw4UAdbu+DQAKDRAKKwAFiIigBXYCALaNgFIyCUTCSAAB2T1nn3z8ThgAAAABJRU5ErkJggg==","orcid":"","institution":"Vanderbilt University Medical Center","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Anna","middleName":"C","lastName":"Pfalzer","suffix":""},{"id":56221178,"identity":"1bc6b9f0-fd33-42c1-a8e4-190129454360","order_by":1,"name":"Yan Yan","email":"","orcid":"","institution":"Vanderbilt University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Yan","suffix":""},{"id":56221179,"identity":"e132dbe7-2686-4162-ba6e-54dd9aa9fb45","order_by":2,"name":"Hakmook Kang","email":"","orcid":"","institution":"Vanderbilt University Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hakmook","middleName":"","lastName":"Kang","suffix":""},{"id":56221180,"identity":"f3092fae-1193-489b-a03c-26c48cc54cec","order_by":3,"name":"Melissa Totten","email":"","orcid":"","institution":"University of North Carolina at Greensboro","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Melissa","middleName":"","lastName":"Totten","suffix":""},{"id":56221181,"identity":"2b741f7c-dd66-4513-9011-6967c1f6094b","order_by":4,"name":"James Silverman","email":"","orcid":"","institution":"Vanderbilt University Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"James","middleName":"","lastName":"Silverman","suffix":""},{"id":56221182,"identity":"5ce56861-260e-49d1-aa0a-542fd95c4747","order_by":5,"name":"Aaron B Bowman","email":"","orcid":"","institution":"Purdue University West Lafayette","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Aaron","middleName":"B","lastName":"Bowman","suffix":""},{"id":56221183,"identity":"5036e7a5-bcb1-4318-85d9-640b03b2651d","order_by":6,"name":"Keith Erikson","email":"","orcid":"","institution":"University of North Carolina at Greensboro","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Keith","middleName":"","lastName":"Erikson","suffix":""},{"id":56221184,"identity":"40331b9a-ec3d-4ca6-96d8-d61706e6f57b","order_by":7,"name":"Daniel O Claassen","email":"","orcid":"","institution":"Vanderbilt University Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"O","lastName":"Claassen","suffix":""}],"badges":[],"createdAt":"2021-10-05 17:14:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-956730/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-956730/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":14490966,"identity":"3bae310a-28d9-4770-ab8f-ae03bf54488b","added_by":"auto","created_at":"2021-10-13 14:58:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":469004,"visible":true,"origin":"","legend":"Cerebrospinal fluid (CSF) A) manganese (Mn), B) iron (Fe), C) copper (Cu), D) zinc (Zn) metal levels with the ratio of D) Cu:Zn and E) Fe:Zn between control and HD participants analyzed using 1-way ANOVA with post-hoc testing after determination of significant (p\u003c0.05) main effects. Data are shown as the mean, quartiles and 95% confidence interval. An asterisk indicates a p-value \u003c0.05. The relationship between CSF Cu and Zn and composite Unified Huntingtin Diease Rating Scale (cUHDRS) are depicted in F) and G) with participant disease status indicated by yellow, green or red dots.","description":"","filename":"Figure1csf.png","url":"https://assets-eu.researchsquare.com/files/rs-956730/v1/5259b61d07859422559029e0.png"},{"id":14491386,"identity":"fa282676-469b-4a2e-ad49-736805a59cb4","added_by":"auto","created_at":"2021-10-13 15:01:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":451677,"visible":true,"origin":"","legend":"Plasma A) manganese (Mn), B) iron (Fe), C) copper (Cu), D) zinc (Zn) metal levels with the ratio of plasma E) Cu:Zn and F) Fe:Zn between control and HD participants analyzed using 1-way ANOVA with post-hoc testing after determination of significant (p\u003c0.05) main effects. Data are shown as median, quartiles and 95% confidence interval. The relationship between plasma Cu and Zn and composite Unified Huntingtin Diease Rating Scale (cUHDRS) are depicted in G) and H) with participant disease status indicated by yellow, green or red dots.","description":"","filename":"Figure2plasma.png","url":"https://assets-eu.researchsquare.com/files/rs-956730/v1/e94078197a6a2fa58a4ec421.png"},{"id":14490967,"identity":"00f79ce6-9c38-4400-90b8-72f8c0c15a99","added_by":"auto","created_at":"2021-10-13 14:58:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":196956,"visible":true,"origin":"","legend":"The ratio of cerebrospinal fluid (CSF) and plasma A) manganese (Mn), B) Iron (Fe), C) Copper (Cu), and D) Zinc (Zn) in control and HD participants. Data are shown as median, quartiles and 95% confidence interval. Differences in CSF: plasma metal ratio were analyzed using a 1-way ANOVA with post-hoc testing after determination of significant (p\u003c0.05) main effects. ","description":"","filename":"Figure3CSFplasmametals.png","url":"https://assets-eu.researchsquare.com/files/rs-956730/v1/9ad8383e2d90a2bc0a71dc14.png"},{"id":14490971,"identity":"cd55001c-959c-4d1c-8b3d-a86403103b2f","added_by":"auto","created_at":"2021-10-13 14:58:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":587375,"visible":true,"origin":"","legend":"Correlation matrix between CSF and plasma metals in A) Controls, B) Pre-manifest, C) Manifest and D) Late Manifest HD participants. The size and color of the circle indicate the strength and direction of the correlation. Shades of red indicate negative correlations whereas blues indicate positive correlations. An asterisk (*) indicates p\u003c0.05 and (**) indicates p\u003c0.01. Cerebrospinal fluid (CSF), Copper (Cu), Iron (Fe), Zinc (Zn), Manganese (Mn). ","description":"","filename":"Figure4correlationmatrix.png","url":"https://assets-eu.researchsquare.com/files/rs-956730/v1/a0304b52246f6f4dc6550a5e.png"},{"id":14491385,"identity":"2bb79db8-a836-4251-8edf-5f43b38d171c","added_by":"auto","created_at":"2021-10-13 15:01:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":394760,"visible":true,"origin":"","legend":"Cerebrospinal fluid mutant Huntingtin (mHTT) and Neurofilament light (NfL) in HD participants. CSF mHTT significantly increase with HD stage (A) and positively correlates with CAP-score (B) and negatively correlates with the composite Unified Huntington Disease Rating Scale (cUHDRS). CSF NfL significantly increases with HD stage (D), and positively correlates with CAP-score (E) and negatively correlates with cUHDRS (F). An asterisk (*) indicates a p\u003c0.05 for post-hoc comparisons. Data are shown as median, quartiles and 95% confidence interval. ","description":"","filename":"Figure5mHTTNfL.png","url":"https://assets-eu.researchsquare.com/files/rs-956730/v1/5553be364572cb3f809ca9f2.png"},{"id":14490969,"identity":"e4a2a82b-bdd9-4dc0-8152-dc74badd9a72","added_by":"auto","created_at":"2021-10-13 14:58:56","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":215558,"visible":true,"origin":"","legend":"Cerebrospinal fluid A) Mn, B) Fe, C) Cu and D) Zn by Neurofilament light (NfL) in HD participants. NfL was categorized into low (0-1500 pg/mL), medium (1501-5000 pg/mL), high (5001-10000 pg/mL) and very high (10,000+ pg/mL). Differences in CSF metal level by NfL accumulation was assessed using 1-way ANOVA with post-hoc testing after determination of a significant (p\u003c0.05) main effect. An asterisk (*) indicates significant (p\u003c0.05) two-way comparison. Data are shown as the median, quartiles and 95% confidence interval.","description":"","filename":"Figure6NfLmetals.png","url":"https://assets-eu.researchsquare.com/files/rs-956730/v1/1a88a34043ed817d546788ae.png"},{"id":14490968,"identity":"f919067f-e3a1-46c1-ac14-84a51e20c26f","added_by":"auto","created_at":"2021-10-13 14:58:55","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":215514,"visible":true,"origin":"","legend":"Cerebrospinal fluid metal levels by mutant Huntingtin (mHTT) accumulation in HD participants. mHTT was categorized into low (0-10fM), medium (11-49 fM), high (50-100 fM), very high (101+ fM). Differences in CSF A) Mn, B) Fe, C) Cu and D) Zn by mHTT concentration were assessed using 1-way ANOVA. Data are shown as median, quartiles and 95% confidence interval.","description":"","filename":"Figure7mHTTmetals.png","url":"https://assets-eu.researchsquare.com/files/rs-956730/v1/0483c1efe53672ce5e3e0905.png"},{"id":14491387,"identity":"bdbb8628-88e9-43c7-ac9d-51a10820d0be","added_by":"auto","created_at":"2021-10-13 15:02:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1472171,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-956730/v1/c919f13c-d844-4a08-9c28-c3b5889ed58d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAlterations in Metal Homeostasis Occur Prior to Canonical Markers in Huntington Disease\u003c/p\u003e","fulltext":[{"header":"Introduction:","content":"\u003cp\u003eEssential trace metals play a vital role in several metabolic processes throughout the body including regions of the brain. Although their concentrations are lower compared to more bulk elements like calcium and sodium, they are necessary for the proper function and structure of many proteins. In fact, approximately 10% of human genes contain zinc (Zn)-finger domains\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The most abundant trace elements in human body are Iron (Fe), Zn, Copper (Cu), and manganese (Mn). These compounds have been shown to regulate mitochondrial function\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, oxidative stress\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, inflammation, synaptic signaling, cell signaling, glycobiology\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, neurotransmitter synthesis and protein aggregation\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Both intracellular and extracellular essential metals are tightly regulated because deficiencies and excesses in result in detrimental effects on biological systems. Regulation predominantly occurs at the level of the gut which prevents dietary over-exposures through absorption and instances where toxic accumulations of metals occur typically bypass gastrointestinal regulation. For instance, over-exposure to manganese through various occupations results in a Parkinsonian-like condition called Manganism\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Copper accumulation in the brain due to Wilson\u0026rsquo;s disease results in involuntary movements and cognitive impairment\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Conversely, deficiencies in copper seen in Menke\u0026rsquo;s disease is also associated with cognitive and motor impairments\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe role of essential metals specifically in the context of Huntington Disease (HD) has been explored in \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e models of disease. There is a clear and consistent interaction between Mn and mutant Huntingtin (HTT) pathobiology in cell and rodent models. Manganese (Mn) exposure in HD cells can correct deficits in metabolic pathways implicated in HD pathology such as autophagy\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e and insulin signaling\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Mn exposure can also correct abnormalities in the striatal urea cycle in HD rodents\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. We also observe global suppression of transcriptomic and metabolomic response to Mn in the same rodent model\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e \u0026ndash; suggesting impairments in Mn trafficking in HD. Iron also accumulates in post-mortem HD brains as well as in HD animal models\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Iron chelation improves molecular and behavioral indicators of disease\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Alterations in Cu homeostasis has received considerable attention. Aberrations in Cu homeostasis have been observed in cell and rodent models of HD\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e as well as in cerebrospinal fluid\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e and post-mortem tissue\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Further, Xiao et al found a direct interaction between elemental Cu and mutant HTT aggregates\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e and that increases in intracellular Cu lead to increased mHTT aggregation\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Clinical application of these findings were tested in a clinical trial designed to investigate the effect of a Cu chelator on clinical outcomes in motor manifest HD, though this study did not meet its primary endpoint\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile there is consistent evidence for alterations in metal biology in HD, there are many unanswered questions regarding the stability of metal homeostasis and the timing over which these alterations take place. The establishment of HDClarity, a large biofluid collection initiative, has provided access to CSF and plasma samples from individuals with HD at different clinical stages of progression. Here we assessed levels of key metals (Cu, Fe, Mn and Zn) in CSF and plasma in HD Clarity samples. Our goal was to identify the timing and stability of changes in central and systemic metal biology in HD compared to canonical markers of disease.\u003c/p\u003e"},{"header":"Results:","content":"\u003ch2\u003e\u003cem\u003eClinical Demographics\u0026nbsp;\u003c/em\u003e\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003ePre-manifest participants were significantly younger than the control and manifest groups as expected. Late manifest participants were significantly older than the other three study groups as shown in \u003cstrong\u003eTable 1\u003c/strong\u003e, also as expected. There were no significant differences in trinucleotide C-A-G repeat length among the HD study groups (\u003cstrong\u003eTable 1\u003c/strong\u003e). Among the behavioral and functional assessments, total functional capacity (TFC) and symbol digit modality test (SDMT) were similar between the Control and PRE groups with significant reductions in TFC in MAN and LATE groups (Table 1). Performance on the Stroop Word Reading (SWR) and total motor score (TMS) assessment incrementally decreased with disease progression (Table 1). The composite Unified Huntington Disease Rating Scale (cUHDRS) is an indicator of disease stage using assessments of cognitive capacity (SDMT, SWR), motor function (TMS) and functional capacity for activities of daily living (TFC). cUHDRS score decreases with disease severity, where a negative value is indicative of a more progressed patient compared to an individual with a positive cUHDRS score. cUHDRS scores do not significantly differ between the Control and PRE group; whereas there is a progressive decline between PRE, MAN and LATE (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" width=\"78.65013774104683%\"\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTable 1. Participant Baseline Demographics by Disease Stage\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.59504132231405%\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.00275482093664%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-manifest \u0026nbsp; \u0026nbsp; (n=16)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.9366391184573%\"\u003e\n \u003cp\u003e\u003cstrong\u003eManifest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=16)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.349862258953166%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLate Manifest (n=16)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.59504132231405%\"\u003e\n \u003cp\u003e47.75\u0026plusmn; 10.81\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.00275482093664%\"\u003e\n \u003cp\u003e39.125\u0026plusmn; 9.78\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.9366391184573%\"\u003e\n \u003cp\u003e47.0625\u0026plusmn; 7.34\u003csup\u003ea\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.349862258953166%\"\u003e\n \u003cp\u003e57.6875\u0026plusmn; 8.74\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex (M,F)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.59504132231405%\"\u003e\n \u003cp\u003e7,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.00275482093664%\"\u003e\n \u003cp\u003e8,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.9366391184573%\"\u003e\n \u003cp\u003e7,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.349862258953166%\"\u003e\n \u003cp\u003e9,7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.59504132231405%\"\u003e\n \u003cp\u003e19.75\u0026plusmn; 3.89\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.00275482093664%\"\u003e\n \u003cp\u003e42.4375\u0026plusmn; 1.46\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.9366391184573%\"\u003e\n \u003cp\u003e43.75\u0026plusmn; 1.77\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.349862258953166%\"\u003e\n \u003cp\u003e43.8125\u0026plusmn; 1.87\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTFC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.59504132231405%\"\u003e\n \u003cp\u003e12.92\u0026plusmn; 0.29\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.00275482093664%\"\u003e\n \u003cp\u003e12.625\u0026plusmn; 0.62\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.9366391184573%\"\u003e\n \u003cp\u003e10.25\u0026plusmn; 3.34\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.349862258953166%\"\u003e\n \u003cp\u003e5.0625\u0026plusmn; \u0026nbsp;4.25\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDMT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.59504132231405%\"\u003e\n \u003cp\u003e55.67\u0026plusmn; 10.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.00275482093664%\"\u003e\n \u003cp\u003e52.75\u0026plusmn; 15.93\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.9366391184573%\"\u003e\n \u003cp\u003e34.25\u0026plusmn; 13.89\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.349862258953166%\"\u003e\n \u003cp\u003e21.33\u0026plusmn; \u0026nbsp;16.09\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSWR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.59504132231405%\"\u003e\n \u003cp\u003e107.75\u0026plusmn; 17.51\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.00275482093664%\"\u003e\n \u003cp\u003e84.1875\u0026plusmn; 28.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.9366391184573%\"\u003e\n \u003cp\u003e62.4375\u0026plusmn; \u0026nbsp;19.17\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.349862258953166%\"\u003e\n \u003cp\u003e43.82\u0026plusmn; \u0026nbsp;29.10\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTMS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.59504132231405%\"\u003e\n \u003cp\u003e1.42 \u0026plusmn; 3.70\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.00275482093664%\"\u003e\n \u003cp\u003e6.3125\u0026plusmn; 8.93\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.9366391184573%\"\u003e\n \u003cp\u003e29.0625\u0026plusmn; 22.39\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.349862258953166%\"\u003e\n \u003cp\u003e58.01\u0026plusmn; \u0026nbsp;29.97\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.115702479338843%\"\u003e\n \u003cp\u003e\u003cstrong\u003ecUHDRS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.59504132231405%\"\u003e\n \u003cp\u003e17.71\u0026plusmn; 1.72\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.00275482093664%\"\u003e\n \u003cp\u003e15.80\u0026plusmn; 2.73\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.9366391184573%\"\u003e\n \u003cp\u003e10.30\u0026plusmn;4.99\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.349862258953166%\"\u003e\n \u003cp\u003e5.80\u0026plusmn;6.76\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eTable 1. Differences in baseline demographic variables were identified using a 1-way ANOVA with post-hoc testing after determination of a significant main effect (p\u0026lt;0.05). \u0026nbsp;Participant age is reported in years as well as the proportion of males to females (M,F). The number of trinucleotide repeats (CAG) as well as performance on total functional capacity (TFC), symbol digit modality test (SDMT), stroop word reading (SWR), total motor score (TMS) and the compositive United Huntington Disease Rating Scale (cUHDRS) scores are reported here as mean \u0026plusmn; S.D and values that do not significantly differ share a superscript.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003e\u003cem\u003eMetal stability\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe stability of metal homeostasis was assessed in Control and PRE groups by comparing baseline to the 4-8 week follow up CSF and plasma metal levels (\u003cstrong\u003eTable 2\u003c/strong\u003e). Interestingly, there were no differences between baseline and follow up CSF or plasma metal levels in Control participants but in the PRE group, CSF Cu and plasma Zn (highlighted in grey) were significantly altered at the follow up visit compared to baseline.\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" width=\"100%\"\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTable 2. Baseline and Follow-up Cerebrospinal Fluid and Plasma Metals in Control and Pre-manifest Participants\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"25.663716814159294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.446270543615675%\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl (BL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.20480404551201%\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl (FU)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.963337547408344%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-manifest (BL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.721871049304678%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-manifest (FU)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"25.663716814159294%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCSF Mn (ug/L \u0026plusmn; S.D)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.446270543615675%\"\u003e\n \u003cp\u003e7.20\u0026plusmn;6.47\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.20480404551201%\"\u003e\n \u003cp\u003e4.44\u0026plusmn;4.93\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.963337547408344%\"\u003e\n \u003cp\u003e7.23\u0026plusmn;3.41\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.721871049304678%\"\u003e\n \u003cp\u003e13.21\u0026plusmn;9.06\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"25.663716814159294%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCSF Cu (ug/L \u0026plusmn; S.D)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.446270543615675%\"\u003e\n \u003cp\u003e14.32\u0026plusmn;8.80\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.20480404551201%\"\u003e\n \u003cp\u003e16.47\u0026plusmn;10.30\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.963337547408344%\"\u003e\n \u003cp\u003e27.45\u0026plusmn;23.87\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.721871049304678%\"\u003e\n \u003cp\u003e42.52\u0026plusmn;43.51\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"25.663716814159294%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCSF Fe (ug/L \u0026plusmn; S.D)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.446270543615675%\"\u003e\n \u003cp\u003e111.07\u0026plusmn;66.93\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.20480404551201%\"\u003e\n \u003cp\u003e114.45\u0026plusmn;53.41\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.963337547408344%\"\u003e\n \u003cp\u003e192.71\u0026plusmn;92.22\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.721871049304678%\"\u003e\n \u003cp\u003e162.12\u0026plusmn;107.2\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"25.663716814159294%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCSF Zn (ug/L \u0026plusmn; S.D)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.446270543615675%\"\u003e\n \u003cp\u003e207.41\u0026plusmn;65.85\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.20480404551201%\"\u003e\n \u003cp\u003e270.11\u0026plusmn;119.68\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.963337547408344%\"\u003e\n \u003cp\u003e171.29\u0026plusmn;65.45\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.721871049304678%\"\u003e\n \u003cp\u003e191.89\u0026plusmn;76.57\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"25.663716814159294%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlasma Mn (ug/L \u0026plusmn; S.D)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.446270543615675%\"\u003e\n \u003cp\u003e16.77\u0026plusmn;4.23\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.20480404551201%\"\u003e\n \u003cp\u003e18.27\u0026plusmn;4.80\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.963337547408344%\"\u003e\n \u003cp\u003e18.66\u0026plusmn;8.94\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.721871049304678%\"\u003e\n \u003cp\u003e16.85\u0026plusmn;7.97\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"25.663716814159294%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlasma Cu (ug/dL \u0026plusmn; S.D)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.446270543615675%\"\u003e\n \u003cp\u003e121.76\u0026plusmn;19.38\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.20480404551201%\"\u003e\n \u003cp\u003e124.13\u0026plusmn;41.63\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.963337547408344%\"\u003e\n \u003cp\u003e139.84\u0026plusmn;41.47\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.721871049304678%\"\u003e\n \u003cp\u003e157.79\u0026plusmn;44.08\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"25.663716814159294%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlasma Fe (ug/dL \u0026plusmn; S.D)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.446270543615675%\"\u003e\n \u003cp\u003e182.31\u0026plusmn;74.04\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.20480404551201%\"\u003e\n \u003cp\u003e186.24\u0026plusmn;59.89\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.963337547408344%\"\u003e\n \u003cp\u003e172.15\u0026plusmn;64.16\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.721871049304678%\"\u003e\n \u003cp\u003e171.84\u0026plusmn;58.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"25.663716814159294%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlasma Zn (ug/L \u0026plusmn; S.D)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.446270543615675%\"\u003e\n \u003cp\u003e118.26.3\u0026plusmn;78.20\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.20480404551201%\"\u003e\n \u003cp\u003e178.52\u0026plusmn;102.45\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.963337547408344%\"\u003e\n \u003cp\u003e178.30\u0026plusmn;116.70\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"19.721871049304678%\"\u003e\n \u003cp\u003e68.54\u0026plusmn;54.36\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cbr\u003eTable 2. Differences between baseline and follow up cerebrospinal fluid and plasma metal levels in control and pre-manifest participants. Differences were examined using Mann-Whitney tests between visits and not explored across genotypes. Baseline (BL) and 4-8 week follow up (FU) cerebrospinal (CSF) and plasma manganese (Mn), Copper (Cu), Iron (Fe), Zinc (Zn) were measured using GF-AAS and shown here as mean \u0026plusmn; S.D and values that do not significantly differ share a superscript. Significant differences in Pre-manifest FU metals are indicated with grey shading. \u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003e\u003cem\u003eMetals elevated in early HD\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eCSF Cu, Mn and Fe significantly increase in HD (\u003cstrong\u003eFigure 1A, 1B and 1C\u003c/strong\u003e) compared to CSF Zn which decreases in HD samples. CSF Cu is significantly elevated in PRE and LATE participants compared to Control (\u003cstrong\u003eFigure 1C\u003c/strong\u003e); in contrast, CSF Zn is significantly reduced in PRE and LATE participants compared to Control (\u003cstrong\u003eFigure 1D\u003c/strong\u003e). \u0026nbsp;CSF Fe consistently increases across disease stages and significantly differs between Control and MAN and LATE study groups. It is noteworthy that there were no significant correlations between CSF metal levels and age (data not included). It is well-known that Cu and Zn, Fe and Zn, and Mn and Fe are regulated in opposite directions by oxidative stress\u003csup\u003e19\u003c/sup\u003e and as a result, the ratio of Cu:Zn, Fe:Zn and Mn:Fe could be a more robust indicator of early-onset pathology\u003csup\u003e19\u003c/sup\u003e in HD. The ratio of CSF Cu:Zn and CSF Fe:Zn are elevated in the PRE and LATE study arms compared to Control (\u003cstrong\u003eFigure 1E and 1F\u003c/strong\u003e). We did not observe any significant changes in CSF Mn:Fe ratio. CSF Cu is positively correlated with cUHDRS score (p\u0026lt;0.01) while CSF Zu is negatively correlated with cUHDRS (\u003cstrong\u003eFigure 1G and 1H\u003c/strong\u003e) while there was no correlation between cUHDRS and CSF Mn or Fe. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInterestingly, the plasma showed no significant differences between Control and HD metal levels or the levels of metal ratios between Cu, Fe and Zn (\u003cstrong\u003eFigure 2A-2G\u003c/strong\u003e). There were also no significant differences in plasma Mn:Fe ratio. The correlation between plasma Cu and cUHDRS was not significant; however, there was a significant positive correlation between plasma Zn and cUHDRS. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe ratio of CSF to plasma metal levels has previously been implicated as a marker of blood-brain barrier integrity. The ratio of CSF:plasma Cu significantly increases with disease progression (\u003cstrong\u003eFigure 3C\u003c/strong\u003e) although individual pair-wise comparisons did not reach statistical significance. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe observed no significant correlations between CSF and plasma metals across all samples (data not shown). We next investigated the potential for this relationship to be disease specific and found that disease (stage) impacts the relationship between CSF and plasma metals (\u003cstrong\u003eFigure 4\u003c/strong\u003e). Specifically, CSF Mn x CSF Zn, CSF Zn x plasma Cu, and plasma Fe x plasma Cu are all significantly negatively correlated in Control participants whereas none of these correlations exist in PRE, MAN or LATE study arms (\u003cstrong\u003eFigure 4\u003c/strong\u003e). CSF Mn x CSF Cu, and CSF Mn x CSF Fe are both positively correlated in PRE and MAN (\u003cstrong\u003eFigure 4B and 4C\u003c/strong\u003e) whereas this relationship does not exist for Control or LATE stage participants (\u003cstrong\u003eFigure 4A and 4D\u003c/strong\u003e). \u0026nbsp;A significant negative correlation appears in LATE stage participants between plasma Zn x plasma Cu (\u003cstrong\u003eFigure 4D\u003c/strong\u003e). \u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eMetal levels change prior to elevations in biomarkers\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eAs expected, mutant Huntingtin (mHTT) levels increase with disease stage (\u003cstrong\u003eFigure 5A\u003c/strong\u003e), disease burden (\u003cstrong\u003eFigure 5B\u003c/strong\u003e) and clinical severity (\u003cstrong\u003eFigure 5C\u003c/strong\u003e). Similarly, Neurofilament light (NfL) levels also increase with disease stage (\u003cstrong\u003eFigure 5D\u003c/strong\u003e), disease burden (\u003cstrong\u003eFigure 5E\u003c/strong\u003e) and clinical severity (\u003cstrong\u003eFigure 5F\u003c/strong\u003e). Interestingly, mHTT and NfL levels were not significantly different between our Control and PRE groups (\u003cstrong\u003eFigures 5A and 5D\u003c/strong\u003e). We examined how increases in mHTT and NfL related to CSF metal levels (\u003cstrong\u003eFigure 6 and 7\u003c/strong\u003e). CSF Cu levels increase with modest elevations in NfL, but are reduced in individuals with the highest levels of NfL (ANOVA p-value: 0.058; \u003cstrong\u003eFigure 6C\u003c/strong\u003e). A reverse trend appears in CSF Zn, with reductions in Zn corresponding to modest elevations in NfL (\u003cstrong\u003eFigure 6D\u003c/strong\u003e). We found no clear indication that CSF metal levels were impacted by mHTT levels (\u003cstrong\u003eFigure 7\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion:","content":"\u003cp\u003eThe role of essential metals in neuronal health has been well-established\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e with deficiencies and excesses both resulting in neurological symptoms which include cognitive deficits and involuntary movements\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Metal levels are elevated in post-mortem tissue in HD\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Several \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e studies in HD disease models demonstrate that alterations in metal biology impact molecular pathways implicated in HD pathology\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. There is also a direct interaction between elemental Cu and exon 1 of mutant Huntingtin (HTT) protein\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Despite these observations directly linking metal biology to HD pathology, the timing and stability of changes to the metallome are unknown as well as whether changes in the CNS are recapitulated in blood. Our work outlined below begins to address these unanswered questions.\u003c/p\u003e \u003cp\u003eHere, we assessed CSF and plasma metal levels in a cohort of control and HD participants, and examined relationships between metals and HD biomarkers in a sub-set. Pre-manifest participants were significantly younger in age compared to control, but had similar scores on clinical indicators of cognitive function and quality of life. As expected, cognitive and motor function decline with disease progression. Prior to this decline, we note elevations in CSF Mn and Cu, and reductions in CSF Zn. That is, we infer the timing of these changes based on our findings in pre-manifest participants, but not manifest or late cohorts. There was no correlation between age, and metal levels (CSF or plasma). These elevations in CSF Cu (24-47\u0026micro;g/L) are not as substantial as that seen in Wilson\u0026rsquo;s disease, ~76 \u0026micro;g/L\u003csup\u003e21\u003c/sup\u003e. We do not observe these same alterations in Mn, Cu and Zn in plasma although we do find that the CSF:plasma ratio for Mn and Cu are significantly elevated in HD compared to controls (Figure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Taken together, these findings demonstrate that there are early alterations in metal homeostasis in the CSF, not observed in the plasma. These CSF-specific changes may reflect changes to the integrity of the blood-brain barrier (BBB) or metal transport across the blood-brain barrier, which is noted to be impaired early in disease in rodent models\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAdditionally, we find that the interactions among essential metals changes with disease progression. Because of essential metal interdependency, dys-homeostasis of a single metal will result in aberration dys-homeostasis of others. For instance, increased Cu can replace Zn on Zinc-dependent enzymes which alters the functional status of those proteins\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Our results show a negative correlation between CSF Mn and Zn only in controls. Previous research demonstrates that increases in Mn levels are associated with reductions in Zn under control conditions. This suggests that CNS Mn- or Zn-dependent transport is also altered early in HD.\u003c/p\u003e \u003cp\u003ePerhaps the most striking finding relates to our observed changes in CSF metals occur prior to elevations in canonical markers of HD. Specifically, the early changes in CSF Cu and Zn levels pre-date changes in mHTT and NfL in the pre-manifest participants compared to control. Despite there being no significant elevations in mHTT and NfL in pre-manifest participants, both biomarkers did correlate with markers of disease burden (CAP-score) and disease status (cUHDRS). These findings suggest that early sequelae of mutant Huntingtin may result in toxic alterations of essential metal regulation. There are several known physiologic mechanisms by which excess Cu exerts detrimental effects \u0026ndash; which may contribute, in part, to the pathology of HD. The toxicity of Cu depends largely upon whether Cu is bound to transport proteins or a free ion. Unfortunately, our methodology does not allow us to differentiate between free and bound metals and thus, we cannot interrogate the possibility that elevations in metal levels reflect increases in free reactive ion species. It is known that excesses of extracellular free Cu ions dramatically increase oxidative stress through its role in free radical regulation\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Free Cu initiates the production of free radicals through the Fenton reaction which produces reactive hydroxyl groups\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Copper exposure also stimulates the secretion of pro-inflammatory cytokines such as IL-1, IL-4, TNFα in the brain and blood\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. These same cytokines are elevated in blood of Huntington Disease patients\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Lastly, there is evidence that Cu (as well as Zn) regulates neurotransmission in the brain. Studies examining the role of copper in neurotransmitter secretion found that substances which induce Cu release from cells also induce the synthesis and secretion of the primary inhibitory neurotransmitter GABA\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Copper release has also been linked to NMDA receptor activation \u0026ndash; where localization of the copper transporter to the plasma membrane activates NMDA receptors\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Imbalances to GABA homeostasis have been clearly delineated in Huntington Disease with the striatum being one of the most densely connected areas to GABA-ergic neurons\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. It is feasible that elevations in Cu and reductions in Zn participate in the pathogenesis of HD through their involvement in the management of reactive oxygen species, inflammation and neurotransmission.\u003c/p\u003e \u003cp\u003eAlthough we demonstrate clear elevations in CSF metals prior to elevations in canonical markers of disease, the cause of these \u003cem\u003eextracellular\u003c/em\u003e changes and their \u003cem\u003eintracellular\u003c/em\u003e consequences remain unclear. More so, it is unknown whether the extracellular space recapitulates what is occurring intracellularly. Based upon the known interaction between Cu and mutant Huntingtin aggregates, we postulate that the accumulation of aggregates with bound Cu accelerates neuronal death in two ways: i) Cu increases mutant Huntingtin aggregation and ii) deficiencies in Cu-dependent biological processes due to sequestration by mutant Huntingtin. Interestingly, there is considerable overlap between the molecular mechanisms implicated in HD pathology and Cu-dependent biological processes: mitochondrial function via cytochrome C oxidase, dopamine excess via dopamine β-hydroxylase, and oxidative stress via superoxide dismutase 1. Our observed elevations in CSF Cu early in disease may not recapitulate intracellular levels, in fact, we propose that in HD, Cu is sequestered by mutant HTT and thus creates conditions of intracellular Cu deficiency despite elevations in the extracellular space.\u003c/p\u003e \u003cp\u003eIn sum, our work provides important insights into metal biology under normal homeostatic mechanisms as well as alterations in these mechanisms in the context of HD. We report here that CSF Cu, Mn and Zn are altered prior to established disease biomarkers and track with indicators of clinical severity. Our findings provide a strong scientific premise to explore the mechanistic link between Cu and Zn and mHTT and how alterations in these intracellular/extracellular metal levels contribute to neuronal pathology. Together, these investigations might validate a novel biomarker of early HD pathology to utilize in the new phase of clinical investigations.\u003c/p\u003e"},{"header":"Methods:","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSamples\u003c/h2\u003e \u003cp\u003ePlasma and cerebrospinal fluid (CSF) were collected from 60 participants as part of the CHDI HDClarity study. There were 16 pre-motor manifest (PRE), 16 manifest (MAN) and 16 moderate-late (LATE) manifest HD and 12 control participants. Disease stage was determined using the diagnostic confidence level (DCL), length of CAG expansion and burden of pathology\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e calculated from (CAG expansion \u0026ndash; 35.5) x Age. Control participants were individuals without a known history of Huntington Disease (HD). All HD participants have a CAG expansion of \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e 40. PRE individuals were not motor manifest as indicated by a DCL of \u0026lt;4 and a burden of pathology of \u0026gt; 250. MAN participants had a DCL =4 and a total functional capacity (TFC) between 7-13. The LATE group had all the above criteria for MAN and a TFC score between 0-6. Repeat CSF and blood samples collected 4-8 weeks after a baseline visit are provided for all control and PRE participants. Participant age and gender are reported here. Three participants (2 PRE, 1 MAN) were taking supplemental vitamins however, their metal levels were similar to those in their corresponding participant group and thus, the data from these participants are included. Basic demographics like age and gender are reported here in addition to participants scores on a battery of cognitive, behavioral and motor assessments including the symbol digit modality test (SDMT), Stroop Word Reading (SWR), total functional capacity (TFC) and total motor score (TMS). Schobel et al recently proposed a novel indicator of clinical severity, the composite Unified Huntington Disease Rating Scale (cUHDRS) which incorporates a participants performance on the four aforementioned functional, cognitive and motor tasks: TMS, SWR, SDMT and TFC\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMetals\u003c/h2\u003e \u003cp\u003ePlasma and CSF iron (Fe), manganese (Mn), copper (Cu) and zinc (Zn) concentrations were measured with graphite furnace atomic absorption spectrometry (GFAAS, Varian AA240, Varian, Inc., Palo Alto, CA). Fifty microliters of plasma and CSF were digested in ultrapure nitric acid (1:10 wt/vol dilution) for 48\u0026ndash;72 h in a sand bath (60\u0026deg;C); 50 \u0026micro;L of digested sample was brought to 1 mL of total volume with 2% nitric acid and analyzed for Mn, Fe, Cu and Zn. CSF samples were diluted 1:4 for Cu and Mn and diluted 1:32 or 1:64 for Fe and Zn. Plasma samples were diluted 1:20 for Mn, 1:40 for Cu, 1:100 for Fe and up to 1:1000 for Zn. The dilutions for these samples were based upon a standard curve specific to each metal. A bovine liver (NBS Standard Reference Material, USDC, Washington, DC) was digested in ultra-pure nitric acid and used as an internal standard for analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBiomarkers\u003c/h2\u003e \u003cp\u003eAn interim analysis of known HD biomarkers was conducted by a research team at CHDI which analyzed Neurofilament light (NfL), mutant Huntingtin (mHTT), total Huntingtin (totHtt), total protein (totPro) and Hemoglobin (Hb). Specific information regarding assays are available on the CHDI website\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. As this was an interim analysis, cerebrospinal fluid biomarker data was only available for a sub-set of samples (n=9 control, n=12 pre-manifest, n=13 manifest and n=11 late manifest). There were no samples which had both a baseline and follow-up visit and to date, no biomarker data in blood. Data are reported here as picograms/milliliter (pg/mL) of NfL or femtomolar (fM) mHTT adjusted by total protein levels (i.e. NfL/total protein and mHTT/total protein) to account for differences in CSF protein levels. Associations between essential metals and biomarkers were analyzed by grouping mHTT and NfL into low, medium, high and very high categories based upon previous categorizations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStatistics\u003c/h2\u003e \u003cp\u003eWe utilized a parametric, univariate ANOVA to analyze differences in (baseline participant demographics and assessments: age, CAG repeat length and scores for total functional capacity, symbol digit modality test, stroop word reading, total motor score from the Unified Huntington Disease Rating Scale (UHDRS) and composite UHDRS (cUHDRS) (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We utilized non-parametric models for all metal and biomarker analyses to prevent assumptions of normality as previous work examining metals in biofluids display normal\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e and non-normal distributions\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. A univariate ANOVA was used to identify differences in CSF and plasma metal (ratio) levels between disease groups as well as differences between levels of the HD biomarkers mutant HTT and NfL. Data are reported as the median with quartiles and 95% confidence interval. Tukey\u0026rsquo;s post-hoc testing was completed after determination of a significant (p\u0026lt;0.05) main effect. Group values which \u003cem\u003edo not\u003c/em\u003e significantly differ share the same superscript. To investigate the stability of metal homeostasis, we only examined the effect of time within a genotype (i.e. baseline vs follow up) using Mann-Whitney tests. Correlations between CSF and plasma metal levels were assessed using Spearman correlations for non-parametric data with Spearman correlation coefficients and p-values adjusted for multiple comparisons reported.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEthics\u003c/h2\u003e \u003cp\u003eThere samples were provided by CHDI as de-identified samples with select pieces of medical and clinical information which did not pose additional risk for participant identification. The molecular work outlined in this manuscript was approved by the Vanderbilt University Medical Center Internal Review Board (IRB# 191615) and adhered to all relevant guidelines and regulations. Informed Consent was obtained at each HDClarity study site prior to conducting any study procedures performed in accordance with the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eACKNOWLEDGEMENTS:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eData used in this work was generously provided by the participants in the Enroll-HD study and made available by CHDI Foundation, Inc. Enroll-HD is a global clinical research platform intended to accelerate progress towards therapeutics for Huntington\u0026apos;s disease; core datasets are collected annually on all research participants as part of this multi-center longitudinal observational study. Enroll-HD is sponsored by CHDI Foundation, Inc., a nonprofit biomedical research organization exclusively dedicated to developing therapeutics for Huntington\u0026apos;s disease. Enroll-HD would not be possible without the vital contribution of the research participants and their families.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData used in this work would not be possible without the vital contribution of the research participants and their families in the HD-Clarity and HD-CSF studies. HD-Clarity and HD-CSF are cerebrospinal fluid collection initiatives designed to facilitate therapeutic development for Huntington\u0026apos;s disease. HD-Clarity and HD-CSF are led by Dr. Edward Wild and sponsored by University College London. HD-Clarity is funded by CHDI Foundation, Inc., a nonprofit biomedical research organization exclusively dedicated to developing therapeutics that will substantially improve the lives of those affected by Huntington\u0026apos;s disease. The Medical Research Council UK (MR/M008592/1) funded HD-CSF.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe work outlined in this manuscript project was supported by CTSA award No. \u003cstrong\u003eUL1 TR002243\u003c/strong\u003e from the National Center for Advancing Translational Sciences. Its contents are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health.\u003c/p\u003e\n\u003ch2\u003eAUTHORSHIP:\u003c/h2\u003e\n\u003cp\u003e\u0026nbsp;ACP received the study samples and funding to complete the work; MT and KE completed the metal analysis; ACP, DC, YY and HK conducted the statistical analyses; ACP drafted the manuscript; JS, MT, ABB and DOC edited the manuscript. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eCONFLICTS OF INTEREST\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eACP, YY, HK, MT, JS, ABB, KE, DOC have no commercial conflicts of interest relevant to this study. \u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDe Benedictis, C. A., Vilella, A. \u0026amp; Grabrucker, A. M. The Role of Trace Metals in Alzheimer\u0026rsquo;s Disease. in Alzheimer\u0026rsquo;s Disease (ed. 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Neurol.\u003c/em\u003e41,689\u0026ndash;692(1997).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchobel, S. A. \u003cem\u003eet al.\u003c/em\u003e Motor, cognitive, and functional declines contribute to a single progressive factor in early HD.\u003cem\u003eNeurology\u003c/em\u003e89,2495\u0026ndash;2502(2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eResearch tools \u0026amp; reagents | CHDI Foundation. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://chdifoundation.org/research-tools-reagents/\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHozumi, I. \u003cem\u003eet al.\u003c/em\u003e Patterns of levels of biological metals in CSF differ among neurodegenerative diseases.\u003cem\u003eJ. Neurol. Sci.\u003c/em\u003e303,95\u0026ndash;99(2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatti, F. \u003cem\u003eet al.\u003c/em\u003e CSF neurotoxic metals/metalloids levels in amyotrophic lateral sclerosis patients: comparison between bulbar and spinal onset.\u003cem\u003eEnviron. Res.\u003c/em\u003e188,109820(2020).\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"metal biology , neurodegenerative diseases, Huntingtin Disease, Alterations , canonical markers","lastPublishedDoi":"10.21203/rs.3.rs-956730/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-956730/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eObjective: The importance of metal biology in neurodegenerative diseases such as Huntingtin Disease is well documented with evidence of direct interactions between metals such as copper, zinc, iron and manganese and mutant Huntingtin pathobiology. To date, it is unclear whether these interactions are observed in humans, how this impacts other metals, and how mutant Huntington alters homeostatic mechanisms governing levels of copper, zinc, iron and manganese in cerebrospinal fluid and blood in HD patients.\u003c/p\u003e\u003cp\u003eMethods: Plasma and cerebrospinal fluid from control, pre-manifest, manifest and late manifest HD participants were collected as part of HD-Clarity. Levels of cerebrospinal fluid and plasma copper, zinc, iron and manganese were measured as well as levels of mutant Huntingtin and neurofilament in a sub-set of cerebrospinal fluid samples.\u003c/p\u003e\u003cp\u003eResults: We find that elevations in cerebrospinal fluid copper, manganese and zinc levels are altered early in disease prior to alterations in canonical biomarkers of HD although these changes are not present in plasma. We also evidence that CSF iron is elevated in manifest patients. The relationships between plasma and cerebrospinal fluid metal are altered based on disease stage.\u003c/p\u003e\u003cp\u003eInterpretation: These findings demonstrate that there are alterations in metal biology selectively in the CSF which occur prior to changes in known canonical biomarkers of disease. Our work indicates that there are pathological changes related to alterations in metal biology in individuals without elevations in neurofilament and mutant Huntingtin.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Alterations in Metal Homeostasis Occur Prior to Canonical Markers in Huntington Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-10-13 14:58:53","doi":"10.21203/rs.3.rs-956730/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-01-31T10:40:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-01-28T21:16:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"891cc56a-9ccb-4e2b-93ab-6486d5f128e6","date":"2022-01-19T16:48:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-12-30T17:35:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"e3e8fefb-a4dd-4fd5-baa4-624ccb348be0","date":"2021-12-20T14:07:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"28dfa019-9fae-4979-bd1a-db7b00fd2809","date":"2021-12-19T17:44:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-12-17T22:05:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-12-17T22:00:40+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-10-11T18:25:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-10-11T18:24:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2021-10-05T17:02:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d1ec5586-1be9-42f4-b7a2-679c24af32c1","owner":[],"postedDate":"October 13th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":7820577,"name":"Scientific Communication"},{"id":7820578,"name":"Neurology"},{"id":7820579,"name":"Health Economics \u0026 Outcomes Research"}],"tags":[],"updatedAt":"2022-06-02T05:14:05+00:00","versionOfRecord":[],"versionCreatedAt":"2021-10-13 14:58:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-956730","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-956730","identity":"rs-956730","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}