A re-evaluation of the optimal liver copper concentrations for health, performance and fertility of replacement Holstein-Friesian heifers

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Marsh, Liam A. Sinclair, Alexander M. Mackenzie, Joe M. Roberts, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6360858/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Jun, 2025 Read the published version in Biological Trace Element Research → Version 1 posted 14 You are reading this latest preprint version Abstract Excessive copper (Cu) supplementation is common on dairy farms worldwide, despite a growing body of research highlighting the risks of over-supplementation, including liver damage, impaired growth, and reduced fertility. However, diagnosing Cu toxicity remains challenging due to the liver’s allostatic regulation of blood Cu levels and debate surrounding toxicity thresholds. This study utilised secondary data from a longitudinal study conducted between September 2016 and September 2018 involving eighty replacement Holstein-Friesian heifers. Data was utilised to generate receiver operating characteristic curves which established liver Cu thresholds associated with suboptimal liver function and fertility. Results indicated that hepatic Cu concentrations exceeding 167 mg/kg of dry matter (DM) were associated with reduced conception rates to first service, while concentrations above 260 mg/kg of DM reduced conception probability to first and second services. Hepatic Cu concentrations exceeding 322 mg/kg of DM were linked to impaired liver function, as evidenced by elevated serum glutamate dehydrogenase activity. In contrast, a toxicity threshold value could not be generated for plasma Cu, underscoring its inadequacy as a biomarker. The fertility thresholds identified in this study may be more closely related to optimizing Cu levels for animal performance rather than indicative of liver Cu toxicity, suggesting the need for further research. Dairy cattle Fertility Liver Glutamate dehydrogenase Plasma copper. Figures Figure 1 Introduction Copper (Cu) is an essential trace element required by all living organisms [ 1 ]. In mammals, Cu plays a critical role within metalloproteins, cofactors, and the function of metalloenzymes [ 2 ]. Decades of research has highlighted the adverse consequences of Cu deficiency within ruminants, as exemplified by impaired immune function [ 3 ], decreased haematological parameters [ 4 ] and ovarian inactivation leading to potential infertility [ 5 ]. In contrast, there is increasing evidence of an over supplementation of dietary Cu on dairy farms, particularly when cattle are continuously housed. For example, Sinclair and Atkins [ 6 ] surveyed early lactation diets from 50 farms across central and northern England, reporting a mean overall dietary Cu concentration of 27.9 mg/kg of dry matter (DM), which was 16.9 mg/kg of DM above the nutritional recommendation to meet cow requirements proposed by the National Research Council (NRC [ 7 ]) in 2001, and 17.9 mg/kg of DM above the revised guidelines proposed in 2021 [ 8 ]. The UK is not alone in reporting excessive levels of Cu supplementation on farm with Castillo et al. [ 9 ] surveying 39 Californian dairy herds and reporting a mean Cu intake of 18.0 mg/kg of DM, almost 1.9 times above NRC [ 7 ] recommendations. Similarly, Duplessis et al. [ 10 ] reported that 52% of surveyed Canadian dairy herds were feeding above NRC [ 7 ] guidelines, whilst 65% were feeding above the European equivalents [ 11 , 12 ]. This over supplementation is further reinforced by Kendall et al. [ 13 ] who reported that 40% of UK dairy cull cows had hepatic Cu concentrations exceeding 508 mg/kg of DM, a threshold above which cattle are generally considered to suffer from chronic Cu poisoning [ 14 ]. However, it should be taken into consideration that much debate surrounds the threshold for Cu toxicity with a considerable range in the proposed hepatic thresholds from 350 to 1500 mg/kg of DM [ 14 – 16 ]. The reasons for this increased Cu supplementation on-farm are unclear but could be multi-factorial [ 17 ]. It may simply be that in the absence of clinical Cu toxicity, there is a perception that “more is better!” from those within the industry leading to excess levels of Cu supplementation on-farm [ 18 ]. However, recent evidence would also suggest that other factors such as basal forage type (e.g. grass versus maize silage; [ 19 ]), rumen pH (e.g. high versus low; [ 20 ]), and copper source (e.g. oxide versus sulfate; [ 21 , 22 ]) can greatly alter dietary Cu absorption. There are various clinical signs which can present due to excessive Cu loading, including liver damage [ 5 ] impaired growth [ 23 ], and death due to haemolytic crisis [ 24 ], with the Animal and Plant Health Agency reporting 80 cases of clinical Cu toxicity in UK cattle between 2016 and 2023 [ 25 ]. Determining an elevated Cu status on-farm can be difficult, predominantly due to the allostatic control of blood Cu concentration by the liver, which results in plasma or serum concentrations that are a poor indicator of hepatic Cu status [ 26 ]. For example, Dias et al. [ 27 ] conducted a meta-analysis to determine if plasma Cu could be utilised as an indicator of animal status, concluding that it may only be useful when animals experience either exceptionally high or low hepatic Cu concentrations. Alternative indicators of an increased Cu status rely on blood enzymes, although not a direct indicator of hepatic Cu status, glutamate dehydrogenase (GLDH) has been shown to be a sensitive indicator of hepatotoxicity which could result from increased Cu levels [ 28 ]. However, misdiagnosis may be problematic as other conditions can produce similar enzyme profiles [ 29 ]. It is widely accepted that liver biopsies are the most accurate method for assessing Cu status, but sampling is an invasive procedure requiring veterinary training, with cost also being a limiting factor on farms [ 30 – 32 ]. However, utilizing cull cattle for liver sampling may help mitigate these challenges by providing a less invasive and more cost-effective alternative [ 30 ]. Overall, the difficulty in assessing Cu status may serve to perpetuate the existence of chronic Cu poisoning as a silent epidemic within the dairy industry. Further to this, emerging studies are now raising concerns of harmful subclinical consequences associated with an elevated Cu status. For example, McCaughern et al. [ 28 ] reported that Cu supplementation above requirements but below typical farm levels resulted in a 17.5 % reduction in the conception ate (73.7 % versus 91.2 %) of replacemen Holstein-Frisian heifers. Additionally, practicing vets have suggested anecdotal evidence of a link between increased dairy cow Cu status with a concurrent increase in disease incidence [ 28 ]. In conclusion, there is an oversupply of Cu within the dairy industry, which exceeds the nutritional requirements of cattle. When this environment is combined with recent evidence that liver copper concentrations below historic toxicity thresholds can negatively impact dairy cattle health and performance, there arises a need to reassess hepatic thresholds pertaining to optimal hepatic Cu concentrations within dairy cattle. The objectives of the current study were therefore to re-evaluate the associations between hepatic Cu concentration and the health and performance of replacement Holstein-Friesian heifers, with a view to determining critical thresholds at which these parameters are negatively affected. Materials and methods This article is the second paper from a study conducted between September 2016 and September 2018 at the Harper Adams University Dairy Unit, Newport, Shropshire, UK. The initial study evaluated the effect of Cu supply during the rearing phase on the health, performance and fertility of replacement Holstein-Friesian heifers [ 28 ]. The aim of this paper was to utilise the secondary data generated to determine the hepatic Cu thresholds above which the fertility, performance and health of Holstein-Friesian dairy heifers is affected. Briefly, the animal management undertaken by McCaughern et al.[ 28 ] can be summarised as follows. A longitudinal study was completed, where Eighty Holstein-Friesian heifers with a liveweight of 137 ± 2.4 kg (mean ± standard error) at 4.1 ± 0.1 months of age where fed either a recommended (16 mg/kg of DM; n = 40) or a high dietary Cu concentration (32 mg/kg of DM; n = 40) until six weeks before calving. The recommended level was provided to avoid deficiency and be marginally in excess of animal requirements [ 7 ], whilst the higher dietary concentration was selected to reflect the mean Cu concentration reported on UK farms by Sinclair and Atkins [ 6 ]. All heifer rearing was performed to reflect typical commercial management conditions in the UK. Data collection Liver biopsies were performed at 12.4 months of age according to Davies and Jebbett [ 33 ], by insertion of a needle through the 11th intercostal space. Biopsy samples were immediately snap-frozen in liquid nitrogen and stored at -80°C. Liver Cu concentration was determined by inductively coupled plasma mass-spectrometry (ICP-MS) as described by McCaughern et al. [ 20 ]. Blood samples were collected via jugular venipuncture using Becton Dickson vacutainers containing silica gel to determine serum GLDH and dipotassium EDTA to determine plasma minerals. Initial blood samples were collected in the week prior to commencing the study and continued at eight-week intervals throughout. After collection, all samples were centrifuged and stored at -20°C until analysis. Serum GLDH was measured using Randox Laboratories kits (GLDH: Catalogue No. GL441) and analyzed with a Cobas Miras Plus autoanalyzer (ABX Diagnostics). Plasma Cu concentrations were determined using ICP-MS, according to McCaughern et al. [ 20 ]. Heifers were weighed and body condition scored (BCS; 1–5 scale with 0.25 increments) fortnightly throughout the duration of the study. Oestrus detection commenced at five months of age as described by Van Erdenburg et al. [ 34 ]. The breeding period began after 13 months of age, with insemination performed 12 hours after observed oestrus. Conception rate was calculated as the proportion of inseminated heifers confirmed pregnant by trans-rectal ultrasound. Heifers diagnosed as non-pregnant were returned to mating or excluded from the study if 260 days beyond the start of mating. Statistical analysis All statistical analyses were carried out using R (version 4.4.1). Packages included: lme4[ 35 ], ROCit [ 36 ], mvnormtest [ 37 ], mgcv [ 38 ], OptimalCutpoints [ 39 ], Outliers [ 40 ], magrittr [ 41 ], EnvStats [ 42 ], and nlme [ 43 ]. Rosner’s test was utilised to identify and remove outliers, while the Shapiro–Wilk test was conducted to assess the data distribution for each variable. Variables that deviated from a Gaussian distribution were transformed using an inverse cubic root. Subsequently, a Mann–Whitney U test was applied to compare hepatic Cu concentrations at 12.4 months of age with the values reported for the UK cattle population by Kendall et al. [ 13 ]. Descriptive statistics were also performed to demonstrate the data spread for each continuous variable, consisting of a mean, standard deviation, range, and interquartile range. In contrast, percentages were presented for the dichotomous variables in addition to the underlying numerical counts. Generalised Additive Models (GAMs) were employed to examine the relationships between hepatic Cu concentrations at 12.4 months of age and dependant variables related to health or performance. The models calculated either the adjusted coefficient of determination ( \(\:{R}_{adj}^{2}\) ) for continuous variables, or McFadden’s coefficient of determination for dichotomous variables ( \(\:{R}_{McFadden}^{2}\) ). Following Gupta et al. [ 44 ], an \(\:{R}_{adj}^{2}\) > 0.5 was interpreted as indicative of a strong significant relationship, whilst, in line with McFadden [ 45 ] an \(\:{R}_{McFadden}^{2}\) > 0.3 was considered significantly important. Dependent variables that demonstrated significant relationships with hepatic Cu concentrations were carried forward into receiver operator characteristic (ROC) curves to identify subclinical disease thresholds. These ROC curves evaluated the sensitivity and specificity of hepatic Cu concentrations in predicting disease outcomes as follows: Sensitivity= \(\:\frac{Number\:of\:true\:positives}{Number\:of\:true\:positives+number\:of\:false\:negatives}\times\:100\) Specificity= \(\:\frac{Number\:of\:true\:negatives\:}{Number\:of\:true\:negatives+number\:of\:false\:positives\:}\times\:100\) For the fertility ROC curves, heifers confirmed to be in calf were considered the ‘healthy’ outcome. For serum GLDH activity 25 or > 50 µmol/l were examined in accordance with current published thresholds [ 15 , 47 ]. Finally, Youden’s J statistic was calculated by finding the maximal vertical distance between the ROC curve and a 45° diagonal line passing through the origin using: J = Sensitivity + Specificity-1 The hepatic Cu concentration yielding the maximum J was deemed the threshold at which disease breakdown occurred, thereby affecting the dependent variable. Results Seventy-five animals completed the study, with no signs of clinical hepatic Cu toxicity or deficiency observed throughout the duration of the study. The Mann–Whitney U test determined that the mean hepatic Cu concentration of 298 ± 124 mg/kg of DM at 12.4 months (Table 1 ) was in line with UK values published by Kendall et al. [ 13 ]. Table 1 Descriptive characteristics of the replacement Holstein-Friesian dairy heifer population used to model potential relationships between liver copper status and animal health, performance, and fertility. Lower bound (minimum) Lower quartile (Q1) Mean ± SD Upper quartile (Q3) Upper bound (maximum) Hepatic copper (mg/kg of DM) a 83.9 236 298 ± 124 356 669 Liver function Glutamate dehydrogenase (U/L) a 3.40 17.9 30.5 ± 22.8 30.5 120 Plasma copper (µmol/L) a 13.0 14.4 15.6 ± 1.63 16.3 22.2 Fertility Days to first observed oestrus 210 280 327 ± 64.7 353 549 BCS at PSM b 2.50 3.00 3.09 ± 0.29 3.25 3.75 LW at PSM (kg) b 408 500 532 ± 44.9 555 650 Days between PSM b and conception 6.00 62.0 110 ± 60.6 152 262 Conception rate to first service c 51.3% (38/74) Conception rate to first and second service c 82.4% (61/74) Abbreviations: BCS, body condition score; PSM, planned start of mating; LW, live weight. a Data collected from the heifers at 12.4 months of age. b Planned start of mating occurred at 13.0 months of age. c Presented as percentage of animals pregnant within the total population. Parentheses denote the number of animals who conceived out of the total number of animals served. Liver copper concentration and plasma glutamate dehydrogenase Generalised additive modelling determined that hepatic Cu concentrations at 12.4 months of age explained 67.6% of the variation in serum GLDH activity during this period ( \(\:{R}_{adj}^{2}\) = 0.649, P < 0.001). An ROC curve analysis (Fig. 1 ) combined with Youden’s J statistic, identified a hepatic Cu threshold of 322 mg/kg of DM, above which serum GLDH activity exceeded 16 U/L. Liver copper concentration and plasma copper concentration A positive correlation was observed between hepatic Cu concentration and plasma Cu concentration at 12.4 months ( \(\:{R}_{adj}^{2}\:\) = 0.49, P = 0.02) of age. Two disease threshold values for plasma Cu concentrations were assessed: 25 µmol/l [ 15 ] and 50 µmol/l [ 47 ], however, despite the positive correlation, the number of heifers which fitted into diseased categories was too small to meet statistical power requirements. Liver copper concentration and fertility parameters There was no association between hepatic Cu concentration at 12.4 months and the number of days to first observed oestrus ( \(\:{R}_{adj}^{2}\:\) = 0.001, p = 0.33). However, conception rates to either first service, or first and second service were both lowered by higher hepatic Cu concentrations at 12.4 months of age with \(\:{R}_{McFadden\:}^{2}\) values of 0.35 and 0.31, respectively. This led to the production of ROC curves with conception rates and hepatic Cu values which in turn allowed Youden’s J statistics of 167 mg/kg of DM and 260 mg/kg of DM to be generated for first, or first and second services respectively. Discussion Copper toxicity, hepatic copper concentrations and glutamate dehydrogenase Despite multiple historic case reports of Cu poisoning in dairy cattle [ 48 – 50 ], and a decline in annual UK cases from a mean of 34 between 2000 and 2004 [ 51 ] to 10 between 2020 and 2024, the disorder is still the most commonly diagnosed mineral toxicity within cattle [ 25 ]. The liver plays a critical role in this discourse, not only is it the primary organ responsible for Cu storage, but it also maintains Cu homeostasis within the animal [ 52 ]. Sites of Cu storage within each hepatocyte include the nucleus, cytosol, and the large granule fraction which accounts for the greatest proportion of the element [ 53 ]. The development of Cu toxicity within the animal is generally considered to be a two-stage process [ 47 ]. The initial pre-haemolytic stage consists of Cu accumulating sub-clinically in the liver, accompanied by an increase in blood enzymes indicative of liver breakdown, as exemplified by GLDH [ 28 , 54 ]. Literature to date has not attempted to determine the precise liver Cu concentration above which an increase in GLDH can be expected. However, Suttle [ 15 ] reported that biochemical changes could be observed within a marginal hepatic toxicity range with a lower limit of 350 mg/kg of DM, which would broadly agree with the current study’s threshold hepatic Cu value of 322 mg/kg of DM, above which serum GLDH activity becomes abnormal. Indeed, a linear relationship is hypothesised to exist between the pattern of Cu storage within the hepatocyte and overall hepatic Cu concentration throughout both the healthy and pre-haemolytic phases, respectively [ 53 ]. The second stage of Cu toxicity involves a haemolytic crisis characterised by extensive liver damage and the mass release of Cu into circulation leading to increased kidney Cu levels [ 47 ]. Much debate surrounds the chain of events associated with this haemolytic phase. Lopez-Alonso et al.[ 53 ] associated its occurrence with an increase in hepatic Cu storage within the lysosomal fraction at approximately 1500 mg/kg of DM. Suttle[ 15 ] appears to broadly agree with this by capping the marginal toxicity band at a threshold of 1500 mg/kg of DM. However, Hunter et al.[ 46 ] observed cases of fatal Cu toxicity without haemolytic crisis, suggesting that alternative biochemical pathways may be involved. Livesey et al.[ 14 ] defined chronic Cu poisoning as the occurrence of liver and kidney degeneration upon histopathological examination, in addition to a hepatic Cu concentration above a threshold value of 508 mg/kg of DM, and a kidney Cu concentration above 41.3 mg/kg of DM. The reasons for this varying case presentation surrounding Cu induced fatality are unclear but may result from differences in breed type and/or stage of production [ 55 , 56 ]. It is well understood for example, that Jersey cattle have a greater susceptibility to Cu toxicity than other dairy breeds [ 55 ]. Additionally, lactating cattle may have a reduced hepatic Cu tolerance due to the stress associated with milk production [ 56 ], negative energy balance[ 57 , 58 ] and greater liver triglyceride levels [ 59 ]. However, it should be noted that the maximum threshold values of 167 and 260 mg/kg of DM identified for optimal conception rates in the present study, are well below those associated with the various defined stages of Cu toxicity within the literature [ 15 , 46 , 53 ]. Plasma copper concentration as a biomarker for hepatic Cu concentration Plasma Cu concentrations for all heifers in the current study population were well above the 9 µmol/L considered to denote an adequate Cu status [ 14 ]. Much debate surrounds the plasma Cu toxicity threshold, with Suttle[ 15 ] associating toxicity with a plasma Cu concentration of 25 µmol/L or higher, whereas Laven and Livesey[ 47 ] suggested a diagnosis of Cu poisoning in live animals above 50 µmol/L with appropriate associated clinical signs including increased kidney and blood plasma Cu concentration. Indeed, a positive relationship between plasma Cu and hepatic Cu concentration was observed in the current study. However, due to insufficient numbers of heifers meeting toxicity thresholds, this study was unable to generate a suitable ROC curve which associated hepatic Cu accumulation with toxicity risk. These findings align with those of others who question the reliability of plasma Cu as a biomarker for an elevated hepatic Cu status [ 60 , 61 ]. Instead, plasma Cu concentration may only become diagnostically relevant in animals with a low Cu status[ 27 ] or advanced stages of Cu accumulation, such as when hepatic Cu levels exceed 1500 mg/kg of DM at which point haemolysis occurs, thereby releasing Cu into the bloodstream immediately prior to death [ 53 ]. Liver Cu status and fertility Fertility is critically important for dairy cattle, as cows must produce a calf to initiate each lactation throughout the production cycle [ 62 ]. A key component of optimal fertility and long-term productivity is ensuring that heifers calve at an age which optimises that animals' lifetime production [ 63 ]. Calving early at 18 to 22 months has been shown to decrease milk yield by 593 kg per lactation, similarly, increasing age at first calving beyond 26 months has been reported to decrease the total number of lactations and associated productive days [ 64 ]. Several studies have explored the impact of Cu intake on fertility parameters in dairy cattle, yielding mixed results. Hamali et al. [ 65 ] reported improved fertility as identified by a reduced interval between calving and observed oestrus, when multiparous Holstein dairy cows were supplemented with 2.5 gram slow-release Cu capsules. In contrast, Hawkins [ 66 ] observed a decrease in 21-day submission and conception rates when 200 mg of Cu as Ca-Cu-EDTA was injected 10 days before the PSM in seven New-Zealand dairy herds. It should, however, be taken into consideration that indicators of animal Cu status and basal dietary Cu concentration were not monitored in either study [ 65 , 66 ]. In contrast, McCaughern et al. [ 28 ] was the first to report a 17.5% reduction in the conception rate of replacement Holstein-Friesian heifers fed above their Cu requirements, with mean hepatic Cu concentrations that would be considered normal, with no clinical signs of Cu toxicity [ 46 ]. Findings from the present study further support the potential of animal Cu status to impact fertility, with conception rate to first service declining at hepatic Cu concentrations above 167 mg/kg of DM, whilst conception rates to first and second service declined above 260 mg/kg of DM. This is particularly pertinent, as extrapolation from Kendall et al. [ 13 ] in relation to the latter threshold would place 96.7% of UK Holstein-Friesian cull cows at a hepatic Cu status that has the potential to alter their fertility [ 13 ] although, it is important to note that Kendall et al. [ 13 ] did not include replacement Holstein-Friesian heifers in their survey. With the exact mechanisms by which Cu could influence fertility remaining unclear, requiring further research. Conclusion Relationships exist between hepatic Cu concentrations, blood GLDH activity, and measures of fertility in replacement Holstein-Friesian dairy heifers. Alterations in liver function as indicated by a diseased level of GLDH occurs at hepatic Cu concentrations above 322 mg/kg of DM. A hepatic Cu concentration above 167 mg/kg of DM lowers the probability of conception to first service in Holstein-Friesian heifers, whilst hepatic Cu concentrations above 260 mg/kg of DM lowers conception probability to first and second service. It should be considered that all liver Cu thresholds pertaining to fertility in this study, are well below current published values relating to Cu toxicity and would indicate that performance can be altered at concentrations considered to be normal. Indeed, these findings may warrant a discussion of the definitions surrounding Cu toxicity, as the thresholds identified in this study may be better associated with Cu status optimization for maximal animal performance, as opposed to toxicity. The reasons for these relationships between liver Cu concentrations and measures of fertility are unclear and warrant further investigation, but findings highlight the need to consider dietary Cu supply for optimal animal performance. Declarations Acknowledgements Funding The financial support for the original study was provided by the Agricultural and Horticultural Development Board (Warwickshire, UK). The further analysis presented in this paper was funded by the Harper Adams University Deputy Vice-Chancellor Early Career Researcher PhD fund. Competing interests The authors declare they have no conflicts of interest. Author contributions Study conception, design, and planning were undertaken by Amy Marsh, James McCaughern, Liam Sinclair and Alexander Mackenzie. Analysis of the data was performed by Amy Marsh and Joe Roberts, with all authors contributing to the interpretation of research findings. All authors also participated in drafting and approval of the submitted manuscript. Data availability The data that supports the findings of this study are available from the corresponding author upon reasonable request. Ethics approval The analysis of this secondary data is in keeping with the principles of replacement, reduction and refinement as defined under the UK Animals (Scientific Procedures) Act 1986 (amended 2012). All further data analyses presented in this manuscript received local ethical approval from the Harper Adams University Research Ethics Committee (18101200PHD-P0583). References Davies IJ (2013 Oct) The clinical significance of the essential biological metals. 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Yearly trends 1998–2005 Cattle (2005) https://webarchive.nationalarchives.gov.uk/ukgwa/20140307033105/http://www.defra.gov.uk/ahvla-en/publication/vida05/ (accessed 17/02/25) López-Alonso M, Miranda M (2020) Copper supplementation, a challenge in cattle. Animals 10(10):1890 López-Alonso M, Prieto F, Miranda M, Castillo C, Hernández JR, Benedito JL (2005) Intracellular distribution of copper and zinc in the liver of copper-exposed cattle from northwest Spain. Vet J 170(3):332–338 Kaneko JJ, Harvey JW, Bruss ML (eds) (2008) Clinical biochemistry of domestic animals. Academic. Sep 4 Du Z, Hemken RW, Harmon RJ (1996) Copper metabolism of Holstein and Jersey cows and heifers fed diets high in cupric sulfate or copper proteinate. J Dairy Sci 79(10):1873–1880 Jóźwik A, Strzałkowska N, Bagnicka E, Grzybek W, Krzyżewski J, Poławska E, Kołataj A, Horbańczuk JO (2012) Relationship between milk yield, stage of lactation, and some blood serum metabolic parameters of dairy cows. Czech J Anim Sci 57(8):353–360 Mohsin MA, Yu H, He R, Wang P, Gan L, Du Y, Huang Y, Abro MB, Sohaib S, Pierzchala M, Sobiech P (2022) Differentiation of subclinical ketosis and liver function test indices in adipose tissues associated with hyperketonemia in postpartum dairy cattle. Front Veterinary Sci 8:796494 Du X, Chen L, Huang D, Peng Z, Zhao C, Zhang Y, Zhu Y, Wang Z, Li X, Liu G (2017) Elevated apoptosis in the liver of dairy cows with ketosis. Cell Physiol Biochem 43(2):568–578 Theinert KB, Snedec T, Pietsch F, Theile S, Leonhardt AS, Spilke J, Pichelmann S, Bannert E, Reichelt K, Dobeleit G, Fuhrmann H (2022) Qualitative and quantitative changes in total lipid concentration and lipid fractions in liver tissue of periparturient German Holstein dairy cows of two age groups. Front Veterinary Sci 9:814808 López-Alonso M, Crespo A, Miranda M, Castillo C, Hernández J, Benedito JL (2006) Assessment of some blood parameters as potential markers of hepatic copper accumulation in cattle. J Vet Diagn Invest 18(1):71–75 Balemi SC, Grace ND, West DM, Smith SL, Knowles SO (2010) Accumulation and depletion of liver copper stores in dairy cows challenged with a Cu-deficient diet and oral and injectable forms of Cu supplementation. N Z Vet J 58(3):137–141 Dobson H, Smith RF, Royal MD, Knight CH, Sheldon IM (2007) The high-producing dairy cow and its reproductive performance. Reprod Domest Anim 42:17–23 Eastham NT, Coates A, Cripps P, Richardson H, Smith R, Oikonomou G (2018) Associations between age at first calving and subsequent lactation performance in UK Holstein and Holstein-Friesian dairy cows. PLoS ONE 13(6):e0197764 Macrae A, Esslemont R (2015 May) The prevalence and cost of important endemic diseases and fertility in dairy herds in the UK. Bovine Med 26:323–337 Hamali H, Nikan M, Navaee H (2023) The Efficacy of Slow-Release Copper Capsule Administration on Postpartum Anes-trus in Dairy Cows. Med Discoveries 2(10):1084 Hawkins D (2014) Effects of subcutaneously injected Ca Cu EDTA on concentrations of Cu in liver, milk production and reproductive performance in New Zealand dairy cows. N Z Vet J 62(5):244–249 Additional Declarations No competing interests reported. Supplementary Files Rscriptpublish.r Cite Share Download PDF Status: Published Journal Publication published 04 Jun, 2025 Read the published version in Biological Trace Element Research → Version 1 posted Editorial decision: Revision requested 25 Apr, 2025 Reviews received at journal 25 Apr, 2025 Reviews received at journal 25 Apr, 2025 Reviews received at journal 23 Apr, 2025 Reviewers agreed at journal 22 Apr, 2025 Reviewers agreed at journal 19 Apr, 2025 Reviews received at journal 08 Apr, 2025 Reviewers agreed at journal 04 Apr, 2025 Reviewers agreed at journal 04 Apr, 2025 Reviewers agreed at journal 04 Apr, 2025 Reviewers invited by journal 03 Apr, 2025 Editor assigned by journal 02 Apr, 2025 Submission checks completed at journal 02 Apr, 2025 First submitted to journal 02 Apr, 2025 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6360858","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":446864214,"identity":"8bf8c90f-d05b-49da-b91a-ca21e0aa197e","order_by":0,"name":"Amy P. Marsh","email":"","orcid":"","institution":"Harper Adams University","correspondingAuthor":false,"prefix":"","firstName":"Amy","middleName":"P.","lastName":"Marsh","suffix":""},{"id":446864215,"identity":"2fc33f50-e100-4bb9-822e-59f07846f550","order_by":1,"name":"Liam A. Sinclair","email":"","orcid":"","institution":"Harper Adams University","correspondingAuthor":false,"prefix":"","firstName":"Liam","middleName":"A.","lastName":"Sinclair","suffix":""},{"id":446864220,"identity":"0eca5dbc-ddaa-4989-b50a-8e6b1dbbf966","order_by":2,"name":"Alexander M. Mackenzie","email":"","orcid":"","institution":"Harper Adams University","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"M.","lastName":"Mackenzie","suffix":""},{"id":446864221,"identity":"1feef7cd-98f0-4f48-9d4a-cac61fc2722f","order_by":3,"name":"Joe M. Roberts","email":"","orcid":"","institution":"Harper Adams University","correspondingAuthor":false,"prefix":"","firstName":"Joe","middleName":"M.","lastName":"Roberts","suffix":""},{"id":446864225,"identity":"674fb6c3-14fd-4de5-b2dc-028e35891fc0","order_by":4,"name":"James H. McCaughern","email":"data:image/png;base64,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","orcid":"","institution":"Harper Adams University","correspondingAuthor":true,"prefix":"","firstName":"James","middleName":"H.","lastName":"McCaughern","suffix":""}],"badges":[],"createdAt":"2025-04-02 11:38:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6360858/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6360858/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12011-025-04668-0","type":"published","date":"2025-06-04T15:56:51+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81321673,"identity":"49692702-3cd6-483b-b9d3-c13675ef412d","added_by":"auto","created_at":"2025-04-24 17:50:36","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":705901,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristics (ROC) curves displaying sensitivity and specificity for determining optimal hepatic Cu concentrations utilising GLDH (glutamate dehydrogenase; a), conception rate to first service (b), and conception rate to first and second service (c) for replacement Holstein Friesian heifers.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6360858/v1/4f46bc99f484eb363f3417a7.jpeg"},{"id":84242499,"identity":"7fd6e406-8dce-4e0e-b1c2-d869837c273a","added_by":"auto","created_at":"2025-06-09 16:08:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1431655,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6360858/v1/7f2ae702-58ce-419a-a6ac-6b20a279af2d.pdf"},{"id":81321672,"identity":"0fbd23d8-4c69-4637-b6b0-be291b99b0b5","added_by":"auto","created_at":"2025-04-24 17:50:36","extension":"r","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":12014,"visible":true,"origin":"","legend":"","description":"","filename":"Rscriptpublish.r","url":"https://assets-eu.researchsquare.com/files/rs-6360858/v1/8ebb371d83720064c0f8aa3a.r"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eA re-evaluation of the optimal liver copper concentrations for health, performance and fertility of replacement Holstein-Friesian heifers\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCopper (Cu) is an essential trace element required by all living organisms [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In mammals, Cu plays a critical role within metalloproteins, cofactors, and the function of metalloenzymes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Decades of research has highlighted the adverse consequences of Cu deficiency within ruminants, as exemplified by impaired immune function [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], decreased haematological parameters [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and ovarian inactivation leading to potential infertility [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In contrast, there is increasing evidence of an over supplementation of dietary Cu on dairy farms, particularly when cattle are continuously housed. For example, Sinclair and Atkins [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] surveyed early lactation diets from 50 farms across central and northern England, reporting a mean overall dietary Cu concentration of 27.9 mg/kg of dry matter (DM), which was 16.9 mg/kg of DM above the nutritional recommendation to meet cow requirements proposed by the National Research Council (NRC [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]) in 2001, and 17.9 mg/kg of DM above the revised guidelines proposed in 2021 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The UK is not alone in reporting excessive levels of Cu supplementation on farm with Castillo et al. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] surveying 39 Californian dairy herds and reporting a mean Cu intake of 18.0 mg/kg of DM, almost 1.9 times above NRC [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] recommendations. Similarly, Duplessis et al. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] reported that 52% of surveyed Canadian dairy herds were feeding above NRC [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] guidelines, whilst 65% were feeding above the European equivalents [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This over supplementation is further reinforced by Kendall et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] who reported that 40% of UK dairy cull cows had hepatic Cu concentrations exceeding 508 mg/kg of DM, a threshold above which cattle are generally considered to suffer from chronic Cu poisoning [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, it should be taken into consideration that much debate surrounds the threshold for Cu toxicity with a considerable range in the proposed hepatic thresholds from 350 to 1500 mg/kg of DM [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe reasons for this increased Cu supplementation on-farm are unclear but could be multi-factorial [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. It may simply be that in the absence of clinical Cu toxicity, there is a perception that \u0026ldquo;more is better!\u0026rdquo; from those within the industry leading to excess levels of Cu supplementation on-farm [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, recent evidence would also suggest that other factors such as basal forage type (e.g. grass versus maize silage; [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]), rumen pH (e.g. high versus low; [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]), and copper source (e.g. oxide versus sulfate; [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]) can greatly alter dietary Cu absorption. There are various clinical signs which can present due to excessive Cu loading, including liver damage [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] impaired growth [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], and death due to haemolytic crisis [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], with the Animal and Plant Health Agency reporting 80 cases of clinical Cu toxicity in UK cattle between 2016 and 2023 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDetermining an elevated Cu status on-farm can be difficult, predominantly due to the allostatic control of blood Cu concentration by the liver, which results in plasma or serum concentrations that are a poor indicator of hepatic Cu status [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. For example, Dias et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] conducted a meta-analysis to determine if plasma Cu could be utilised as an indicator of animal status, concluding that it may only be useful when animals experience either exceptionally high or low hepatic Cu concentrations. Alternative indicators of an increased Cu status rely on blood enzymes, although not a direct indicator of hepatic Cu status, glutamate dehydrogenase (GLDH) has been shown to be a sensitive indicator of hepatotoxicity which could result from increased Cu levels [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, misdiagnosis may be problematic as other conditions can produce similar enzyme profiles [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. It is widely accepted that liver biopsies are the most accurate method for assessing Cu status, but sampling is an invasive procedure requiring veterinary training, with cost also being a limiting factor on farms [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. However, utilizing cull cattle for liver sampling may help mitigate these challenges by providing a less invasive and more cost-effective alternative [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Overall, the difficulty in assessing Cu status may serve to perpetuate the existence of chronic Cu poisoning as a silent epidemic within the dairy industry. Further to this, emerging studies are now raising concerns of harmful subclinical consequences associated with an elevated Cu status. For example, McCaughern et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] reported that Cu supplementation above requirements but below typical farm levels resulted in a 17.5 % reduction in the conception ate (73.7 % versus 91.2 %) of replacemen Holstein-Frisian heifers. Additionally, practicing vets have suggested anecdotal evidence of a link between increased dairy cow Cu status with a concurrent increase in disease incidence [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn conclusion, there is an oversupply of Cu within the dairy industry, which exceeds the nutritional requirements of cattle. When this environment is combined with recent evidence that liver copper concentrations below historic toxicity thresholds can negatively impact dairy cattle health and performance, there arises a need to reassess hepatic thresholds pertaining to optimal hepatic Cu concentrations within dairy cattle. The objectives of the current study were therefore to re-evaluate the associations between hepatic Cu concentration and the health and performance of replacement Holstein-Friesian heifers, with a view to determining critical thresholds at which these parameters are negatively affected.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eThis article is the second paper from a study conducted between September 2016 and September 2018 at the Harper Adams University Dairy Unit, Newport, Shropshire, UK. The initial study evaluated the effect of Cu supply during the rearing phase on the health, performance and fertility of replacement Holstein-Friesian heifers [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The aim of this paper was to utilise the secondary data generated to determine the hepatic Cu thresholds above which the fertility, performance and health of Holstein-Friesian dairy heifers is affected.\u003c/p\u003e \u003cp\u003eBriefly, the animal management undertaken by McCaughern et al.[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] can be summarised as follows. A longitudinal study was completed, where Eighty Holstein-Friesian heifers with a liveweight of 137\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 kg (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error) at 4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 months of age where fed either a recommended (16 mg/kg of DM; n\u0026thinsp;=\u0026thinsp;40) or a high dietary Cu concentration (32 mg/kg of DM; n\u0026thinsp;=\u0026thinsp;40) until six weeks before calving. The recommended level was provided to avoid deficiency and be marginally in excess of animal requirements [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], whilst the higher dietary concentration was selected to reflect the mean Cu concentration reported on UK farms by Sinclair and Atkins [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. All heifer rearing was performed to reflect typical commercial management conditions in the UK.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eLiver biopsies were performed at 12.4 months of age according to Davies and Jebbett [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], by insertion of a needle through the 11th intercostal space. Biopsy samples were immediately snap-frozen in liquid nitrogen and stored at -80\u0026deg;C. Liver Cu concentration was determined by inductively coupled plasma mass-spectrometry (ICP-MS) as described by McCaughern et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Blood samples were collected via jugular venipuncture using Becton Dickson vacutainers containing silica gel to determine serum GLDH and dipotassium EDTA to determine plasma minerals. Initial blood samples were collected in the week prior to commencing the study and continued at eight-week intervals throughout. After collection, all samples were centrifuged and stored at -20\u0026deg;C until analysis. Serum GLDH was measured using Randox Laboratories kits (GLDH: Catalogue No. GL441) and analyzed with a Cobas Miras Plus autoanalyzer (ABX Diagnostics). Plasma Cu concentrations were determined using ICP-MS, according to McCaughern et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHeifers were weighed and body condition scored (BCS; 1\u0026ndash;5 scale with 0.25 increments) fortnightly throughout the duration of the study. Oestrus detection commenced at five months of age as described by Van Erdenburg et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The breeding period began after 13 months of age, with insemination performed 12 hours after observed oestrus. Conception rate was calculated as the proportion of inseminated heifers confirmed pregnant by trans-rectal ultrasound. Heifers diagnosed as non-pregnant were returned to mating or excluded from the study if 260 days beyond the start of mating.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were carried out using R (version 4.4.1). Packages included: lme4[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], ROCit [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], mvnormtest [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], mgcv [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], OptimalCutpoints [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], Outliers [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], magrittr [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], EnvStats [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], and nlme [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRosner\u0026rsquo;s test was utilised to identify and remove outliers, while the Shapiro\u0026ndash;Wilk test was conducted to assess the data distribution for each variable. Variables that deviated from a Gaussian distribution were transformed using an inverse cubic root. Subsequently, a Mann\u0026ndash;Whitney U test was applied to compare hepatic Cu concentrations at 12.4 months of age with the values reported for the UK cattle population by Kendall et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Descriptive statistics were also performed to demonstrate the data spread for each continuous variable, consisting of a mean, standard deviation, range, and interquartile range. In contrast, percentages were presented for the dichotomous variables in addition to the underlying numerical counts.\u003c/p\u003e \u003cp\u003eGeneralised Additive Models (GAMs) were employed to examine the relationships between hepatic Cu concentrations at 12.4 months of age and dependant variables related to health or performance. The models calculated either the adjusted coefficient of determination (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{adj}^{2}\\)\u003c/span\u003e\u003c/span\u003e) for continuous variables, or McFadden\u0026rsquo;s coefficient of determination for dichotomous variables (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{McFadden}^{2}\\)\u003c/span\u003e\u003c/span\u003e). Following Gupta et al. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], an \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{adj}^{2}\\)\u003c/span\u003e\u003c/span\u003e \u0026gt; 0.5 was interpreted as indicative of a strong significant relationship, whilst, in line with McFadden [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] an \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{McFadden}^{2}\\)\u003c/span\u003e\u003c/span\u003e \u0026gt; 0.3 was considered significantly important.\u003c/p\u003e \u003cp\u003eDependent variables that demonstrated significant relationships with hepatic Cu concentrations were carried forward into receiver operator characteristic (ROC) curves to identify subclinical disease thresholds. These ROC curves evaluated the sensitivity and specificity of hepatic Cu concentrations in predicting disease outcomes as follows:\u003c/p\u003e \u003cp\u003eSensitivity=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{Number\\:of\\:true\\:positives}{Number\\:of\\:true\\:positives+number\\:of\\:false\\:negatives}\\times\\:100\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eSpecificity=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{Number\\:of\\:true\\:negatives\\:}{Number\\:of\\:true\\:negatives+number\\:of\\:false\\:positives\\:}\\times\\:100\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eFor the fertility ROC curves, heifers confirmed to be in calf were considered the \u0026lsquo;healthy\u0026rsquo; outcome. For serum GLDH activity\u0026thinsp;\u0026lt;\u0026thinsp;16.0 U/L defined the healthy population as reported by Hunter et al. [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. In contrast, for plasma Cu concentration two thresholds of \u0026gt;\u0026thinsp;25 or \u0026gt;\u0026thinsp;50 \u0026micro;mol/l were examined in accordance with current published thresholds [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Finally, Youden\u0026rsquo;s \u003cem\u003eJ\u003c/em\u003e statistic was calculated by finding the maximal vertical distance between the ROC curve and a 45\u0026deg; diagonal line passing through the origin using:\u003c/p\u003e \u003cp\u003eJ\u0026thinsp;=\u0026thinsp;Sensitivity\u0026thinsp;+\u0026thinsp;Specificity-1\u003c/p\u003e \u003cp\u003eThe hepatic Cu concentration yielding the maximum \u003cem\u003eJ\u003c/em\u003e was deemed the threshold at which disease breakdown occurred, thereby affecting the dependent variable.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eSeventy-five animals completed the study, with no signs of clinical hepatic Cu toxicity or deficiency observed throughout the duration of the study. The Mann\u0026ndash;Whitney U test determined that the mean hepatic Cu concentration of 298\u0026thinsp;\u0026plusmn;\u0026thinsp;124 mg/kg of DM at 12.4 months (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) was in line with UK values published by Kendall et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive characteristics of the replacement Holstein-Friesian dairy heifer population used to model potential relationships between liver copper status and animal health, performance, and fertility.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLower bound (minimum)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower quartile (Q1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUpper quartile (Q3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUpper bound (maximum)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHepatic copper (mg/kg of DM) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e298\u0026thinsp;\u0026plusmn;\u0026thinsp;124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e669\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLiver function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGlutamate dehydrogenase (U/L) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.5\u0026thinsp;\u0026plusmn;\u0026thinsp;22.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePlasma copper (\u0026micro;mol/L) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFertility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDays to first observed oestrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e327\u0026thinsp;\u0026plusmn;\u0026thinsp;64.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e549\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBCS at PSM \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLW at PSM (kg) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e532\u0026thinsp;\u0026plusmn;\u0026thinsp;44.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e650\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDays between PSM \u003csup\u003eb\u003c/sup\u003e and conception\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110\u0026thinsp;\u0026plusmn;\u0026thinsp;60.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e262\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConception rate to first service \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003e51.3% (38/74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConception rate to first and second service \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003e82.4% (61/74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eAbbreviations: BCS, body condition score; PSM, planned start of mating; LW, live weight.\u003c/p\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Data collected from the heifers at 12.4 months of age.\u003c/p\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Planned start of mating occurred at 13.0 months of age.\u003c/p\u003e \u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Presented as percentage of animals pregnant within the total population. Parentheses denote the number of animals who conceived out of the total number of animals served.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eLiver copper concentration and plasma glutamate dehydrogenase\u003c/h3\u003e\n\u003cp\u003eGeneralised additive modelling determined that hepatic Cu concentrations at 12.4 months of age explained 67.6% of the variation in serum GLDH activity during this period (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{adj}^{2}\\)\u003c/span\u003e\u003c/span\u003e= 0.649, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). An ROC curve analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) combined with Youden\u0026rsquo;s \u003cem\u003eJ\u003c/em\u003e statistic, identified a hepatic Cu threshold of 322 mg/kg of DM, above which serum GLDH activity exceeded 16 U/L.\u003c/p\u003e\n\u003ch3\u003eLiver copper concentration and plasma copper concentration\u003c/h3\u003e\n\u003cp\u003eA positive correlation was observed between hepatic Cu concentration and plasma Cu concentration at 12.4 months (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{adj}^{2}\\:\\)\u003c/span\u003e\u003c/span\u003e= 0.49, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02) of age. Two disease threshold values for plasma Cu concentrations were assessed: 25 \u0026micro;mol/l [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and 50 \u0026micro;mol/l [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], however, despite the positive correlation, the number of heifers which fitted into diseased categories was too small to meet statistical power requirements.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLiver copper concentration and fertility parameters\u003c/h2\u003e \u003cp\u003eThere was no association between hepatic Cu concentration at 12.4 months and the number of days to first observed oestrus (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{adj}^{2}\\:\\)\u003c/span\u003e\u003c/span\u003e= 0.001, p\u0026thinsp;=\u0026thinsp;0.33). However, conception rates to either first service, or first and second service were both lowered by higher hepatic Cu concentrations at 12.4 months of age with \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{McFadden\\:}^{2}\\)\u003c/span\u003e\u003c/span\u003evalues of 0.35 and 0.31, respectively. This led to the production of ROC curves with conception rates and hepatic Cu values which in turn allowed Youden\u0026rsquo;s \u003cem\u003eJ\u003c/em\u003e statistics of 167 mg/kg of DM and 260 mg/kg of DM to be generated for first, or first and second services respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCopper toxicity, hepatic copper concentrations and glutamate dehydrogenase\u003c/h2\u003e \u003cp\u003eDespite multiple historic case reports of Cu poisoning in dairy cattle [\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], and a decline in annual UK cases from a mean of 34 between 2000 and 2004 [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] to 10 between 2020 and 2024, the disorder is still the most commonly diagnosed mineral toxicity within cattle [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The liver plays a critical role in this discourse, not only is it the primary organ responsible for Cu storage, but it also maintains Cu homeostasis within the animal [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Sites of Cu storage within each hepatocyte include the nucleus, cytosol, and the large granule fraction which accounts for the greatest proportion of the element [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The development of Cu toxicity within the animal is generally considered to be a two-stage process [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The initial pre-haemolytic stage consists of Cu accumulating sub-clinically in the liver, accompanied by an increase in blood enzymes indicative of liver breakdown, as exemplified by GLDH [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Literature to date has not attempted to determine the precise liver Cu concentration above which an increase in GLDH can be expected. However, Suttle [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] reported that biochemical changes could be observed within a marginal hepatic toxicity range with a lower limit of 350 mg/kg of DM, which would broadly agree with the current study\u0026rsquo;s threshold hepatic Cu value of 322 mg/kg of DM, above which serum GLDH activity becomes abnormal. Indeed, a linear relationship is hypothesised to exist between the pattern of Cu storage within the hepatocyte and overall hepatic Cu concentration throughout both the healthy and pre-haemolytic phases, respectively [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe second stage of Cu toxicity involves a haemolytic crisis characterised by extensive liver damage and the mass release of Cu into circulation leading to increased kidney Cu levels [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Much debate surrounds the chain of events associated with this haemolytic phase. Lopez-Alonso et al.[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] associated its occurrence with an increase in hepatic Cu storage within the lysosomal fraction at approximately 1500 mg/kg of DM. Suttle[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] appears to broadly agree with this by capping the marginal toxicity band at a threshold of 1500 mg/kg of DM. However, Hunter et al.[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] observed cases of fatal Cu toxicity without haemolytic crisis, suggesting that alternative biochemical pathways may be involved. Livesey et al.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] defined chronic Cu poisoning as the occurrence of liver and kidney degeneration upon histopathological examination, in addition to a hepatic Cu concentration above a threshold value of 508 mg/kg of DM, and a kidney Cu concentration above 41.3 mg/kg of DM. The reasons for this varying case presentation surrounding Cu induced fatality are unclear but may result from differences in breed type and/or stage of production [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. It is well understood for example, that Jersey cattle have a greater susceptibility to Cu toxicity than other dairy breeds [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Additionally, lactating cattle may have a reduced hepatic Cu tolerance due to the stress associated with milk production [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], negative energy balance[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] and greater liver triglyceride levels [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. However, it should be noted that the maximum threshold values of 167 and 260 mg/kg of DM identified for optimal conception rates in the present study, are well below those associated with the various defined stages of Cu toxicity within the literature [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePlasma copper concentration as a biomarker for hepatic Cu concentration\u003c/h2\u003e \u003cp\u003ePlasma Cu concentrations for all heifers in the current study population were well above the 9 \u0026micro;mol/L considered to denote an adequate Cu status [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Much debate surrounds the plasma Cu toxicity threshold, with Suttle[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] associating toxicity with a plasma Cu concentration of 25 \u0026micro;mol/L or higher, whereas Laven and Livesey[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] suggested a diagnosis of Cu poisoning in live animals above 50 \u0026micro;mol/L with appropriate associated clinical signs including increased kidney and blood plasma Cu concentration. Indeed, a positive relationship between plasma Cu and hepatic Cu concentration was observed in the current study. However, due to insufficient numbers of heifers meeting toxicity thresholds, this study was unable to generate a suitable ROC curve which associated hepatic Cu accumulation with toxicity risk. These findings align with those of others who question the reliability of plasma Cu as a biomarker for an elevated hepatic Cu status [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Instead, plasma Cu concentration may only become diagnostically relevant in animals with a low Cu status[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] or advanced stages of Cu accumulation, such as when hepatic Cu levels exceed 1500 mg/kg of DM at which point haemolysis occurs, thereby releasing Cu into the bloodstream immediately prior to death [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLiver Cu status and fertility\u003c/h2\u003e \u003cp\u003eFertility is critically important for dairy cattle, as cows must produce a calf to initiate each lactation throughout the production cycle [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. A key component of optimal fertility and long-term productivity is ensuring that heifers calve at an age which optimises that animals' lifetime production [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Calving early at 18 to 22 months has been shown to decrease milk yield by 593 kg per lactation, similarly, increasing age at first calving beyond 26 months has been reported to decrease the total number of lactations and associated productive days [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Several studies have explored the impact of Cu intake on fertility parameters in dairy cattle, yielding mixed results. Hamali et al. [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] reported improved fertility as identified by a reduced interval between calving and observed oestrus, when multiparous Holstein dairy cows were supplemented with 2.5 gram slow-release Cu capsules. In contrast, Hawkins [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] observed a decrease in 21-day submission and conception rates when 200 mg of Cu as Ca-Cu-EDTA was injected 10 days before the PSM in seven New-Zealand dairy herds. It should, however, be taken into consideration that indicators of animal Cu status and basal dietary Cu concentration were not monitored in either study [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. In contrast, McCaughern et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] was the first to report a 17.5% reduction in the conception rate of replacement Holstein-Friesian heifers fed above their Cu requirements, with mean hepatic Cu concentrations that would be considered normal, with no clinical signs of Cu toxicity [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFindings from the present study further support the potential of animal Cu status to impact fertility, with conception rate to first service declining at hepatic Cu concentrations above 167 mg/kg of DM, whilst conception rates to first and second service declined above 260 mg/kg of DM. This is particularly pertinent, as extrapolation from Kendall et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] in relation to the latter threshold would place 96.7% of UK Holstein-Friesian cull cows at a hepatic Cu status that has the potential to alter their fertility [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] although, it is important to note that Kendall et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] did not include replacement Holstein-Friesian heifers in their survey. With the exact mechanisms by which Cu could influence fertility remaining unclear, requiring further research.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eRelationships exist between hepatic Cu concentrations, blood GLDH activity, and measures of fertility in replacement Holstein-Friesian dairy heifers. Alterations in liver function as indicated by a diseased level of GLDH occurs at hepatic Cu concentrations above 322 mg/kg of DM. A hepatic Cu concentration above 167 mg/kg of DM lowers the probability of conception to first service in Holstein-Friesian heifers, whilst hepatic Cu concentrations above 260 mg/kg of DM lowers conception probability to first and second service. It should be considered that all liver Cu thresholds pertaining to fertility in this study, are well below current published values relating to Cu toxicity and would indicate that performance can be altered at concentrations considered to be normal. Indeed, these findings may warrant a discussion of the definitions surrounding Cu toxicity, as the thresholds identified in this study may be better associated with Cu status optimization for maximal animal performance, as opposed to toxicity. The reasons for these relationships between liver Cu concentrations and measures of fertility are unclear and warrant further investigation, but findings highlight the need to consider dietary Cu supply for optimal animal performance.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe financial support for the original study was provided by the Agricultural and Horticultural Development Board (Warwickshire, UK). The further analysis presented in this paper was funded by the Harper Adams University Deputy Vice-Chancellor Early Career Researcher PhD fund.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy conception, design, and planning were undertaken by Amy Marsh, James McCaughern, Liam Sinclair and Alexander Mackenzie. Analysis of the data was performed by Amy Marsh and Joe Roberts, with all authors contributing to the interpretation of research findings. All authors also participated in drafting and approval of the submitted manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that supports the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis of this secondary data is in keeping with the principles of replacement, reduction and refinement as defined under the UK Animals (Scientific Procedures) Act 1986 (amended 2012). All further data analyses presented in this manuscript received local ethical approval from the Harper Adams University Research Ethics Committee (18101200PHD-P0583).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDavies IJ (2013 Oct) The clinical significance of the essential biological metals. 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N Z Vet J 62(5):244\u0026ndash;249\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":"biological-trace-element-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bter","sideBox":"Learn more about [Biological Trace Element Research](https://www.springer.com/journal/12011)","snPcode":"12011","submissionUrl":"https://submission.nature.com/new-submission/12011/3","title":"Biological Trace Element Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Dairy cattle, Fertility, Liver, Glutamate dehydrogenase, Plasma copper.","lastPublishedDoi":"10.21203/rs.3.rs-6360858/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6360858/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eExcessive copper (Cu) supplementation is common on dairy farms worldwide, despite a growing body of research highlighting the risks of over-supplementation, including liver damage, impaired growth, and reduced fertility. However, diagnosing Cu toxicity remains challenging due to the liver\u0026rsquo;s allostatic regulation of blood Cu levels and debate surrounding toxicity thresholds. This study utilised secondary data from a longitudinal study conducted between September 2016 and September 2018 involving eighty replacement Holstein-Friesian heifers. Data was utilised to generate receiver operating characteristic curves which established liver Cu thresholds associated with suboptimal liver function and fertility. Results indicated that hepatic Cu concentrations exceeding 167 mg/kg of dry matter (DM) were associated with reduced conception rates to first service, while concentrations above 260 mg/kg of DM reduced conception probability to first and second services. Hepatic Cu concentrations exceeding 322 mg/kg of DM were linked to impaired liver function, as evidenced by elevated serum glutamate dehydrogenase activity. In contrast, a toxicity threshold value could not be generated for plasma Cu, underscoring its inadequacy as a biomarker. The fertility thresholds identified in this study may be more closely related to optimizing Cu levels for animal performance rather than indicative of liver Cu toxicity, suggesting the need for further research.\u003c/p\u003e","manuscriptTitle":"A re-evaluation of the optimal liver copper concentrations for health, performance and fertility of replacement Holstein-Friesian heifers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-24 17:50:32","doi":"10.21203/rs.3.rs-6360858/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-26T01:32:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-25T16:30:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-25T15:36:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-23T10:38:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"131681163563862362263136865966304382838","date":"2025-04-22T05:07:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"321401924135049345484781314778553835126","date":"2025-04-19T11:20:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-08T20:30:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"318543178257069897835732703532280495907","date":"2025-04-04T16:59:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"237122125683029498813433518570597419175","date":"2025-04-04T13:50:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"56824482483488318440452516279448121903","date":"2025-04-04T08:46:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-04T01:39:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-03T02:10:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-03T01:48:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biological Trace Element Research","date":"2025-04-02T11:30:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biological-trace-element-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bter","sideBox":"Learn more about [Biological Trace Element Research](https://www.springer.com/journal/12011)","snPcode":"12011","submissionUrl":"https://submission.nature.com/new-submission/12011/3","title":"Biological Trace Element Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5e994647-4cd3-4193-a109-686d17d87b49","owner":[],"postedDate":"April 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-09T15:59:54+00:00","versionOfRecord":{"articleIdentity":"rs-6360858","link":"https://doi.org/10.1007/s12011-025-04668-0","journal":{"identity":"biological-trace-element-research","isVorOnly":false,"title":"Biological Trace Element Research"},"publishedOn":"2025-06-04 15:56:51","publishedOnDateReadable":"June 4th, 2025"},"versionCreatedAt":"2025-04-24 17:50:32","video":"","vorDoi":"10.1007/s12011-025-04668-0","vorDoiUrl":"https://doi.org/10.1007/s12011-025-04668-0","workflowStages":[]},"version":"v1","identity":"rs-6360858","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6360858","identity":"rs-6360858","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}