Associations between ultrasound measurements and hematochemical parameters for the assessment of liver metabolic status in Holstein-Friesian cows

Observational study on the associations between milk yield, composition, and coagulation properties with blood biomarkers of health in Holstein cows

The considerable increase in the production capacity of individual cows owing to both selective breeding and innovations in the dairy sector has posed challenges to management practices in terms of maintaining the nutritional and metabolic health status of dairy cows. In this observational study, we investigated the associations between milk yield, composition, and technological traits and a set of 21 blood biomarkers related to energy metabolism, liver function or hepatic damage, oxidative stress, and inflammation or innate immunity in a population of 1,369 high-yielding Holstein-Friesian dairy cows. The milk traits investigated in this study included 4 production traits (milk yield, fat yield, protein yield, daily milk energy output), 5 traits related to milk composition (fat, protein, casein, and lactose percentages and urea), 11 milk technological traits (5 milk coagulation properties and 6 curd-firming traits). All milk traits (i.e., production, composition, and technological traits) were analyzed according to a linear mixed model that included the days in milk, the parity order, and the blood metabolites (tested one at a time) as fixed effects and the herd and date of sampling as random effects. Our findings revealed that milk yield and daily milk energy output were positively and linearly associated with total cholesterol, nonesterified fatty acids, urea, aspartate aminotransferase, γ-glutamyl transferase, total bilirubin, albumin, and ferric-reducing antioxidant power, whereas they were negatively associated with glucose, creatinine, alkaline phosphatase, total reactive oxygen metabolites, and proinflammatory proteins (ceruloplasmin, haptoglobin, and myeloperoxidase). Regarding composition traits, the protein percentage was negatively associated with nonesterified fatty acids and β-hydroxybutyrate (BHB), while the fat percentage was positively associated with BHB, and negatively associated with paraoxonase. Moreover, we found that the lactose percentage increased with increasing cholesterol and albumin and decreased with increasing ceruloplasmin, haptoglobin, and myeloperoxidase. Milk urea increased with an increase in cholesterol, blood urea, nonesterified fatty acids, and BHB, and decreased with an increase in proinflammatory proteins. Finally, no association was found between the blood metabolites and milk coagulation properties and curd-firming traits. In conclusion, this study showed that variations in blood metabolites had strong associations with milk productivity traits, the lactose percentage, and milk urea, but no relationships with technological traits of milk. Specifically, increasing levels of proinflammatory and oxidative stress metabolites, such as ceruloplasmin, haptoglobin, myeloperoxidase, and total reactive oxygen metabolites, were shown to be associated with reductions in milk yield, daily milk energy output, lactose percentage, and milk urea. These results highlight the close connection between the metabolic and innate immunity status and production performance. This connection is not limited to specific clinical diseases or to the transition phase but manifests throughout the entire lactation. These outcomes emphasize the importance of identifying cows with subacute inflammatory and oxidative stress as a means of reducing metabolic impairments and avoiding milk fluctuations.

Novel insights into the associations between immune cell population distribution in mammary glands and milk minerals in Holstein cows

Udder health has a crucial role in sustainable milk production, and various reports have pointed out that changes in udder condition seem to affect milk mineral content. The somatic cell count (SCC) is the most recognized indicator for the determination of udder health status. Recently, a new parameter, the differential somatic cell count (DSCC), has been proposed for a more detailed evaluation of intramammary infection patterns. Specifically, the DSCC is the combined proportions of polymorphonuclear neutrophils and lymphocytes (PMN-LYM) on the total SCC, with macrophages (MAC) representing the remainder proportion. In this study, we evaluated the association between DSCC in combination with SCC on a detailed milk mineral profile in 1,013 Holstein-Friesian cows reared in 5 herds. An inductively coupled plasma-optical emission spectrometry was used to quantify 32 milk mineral elements. Two different linear mixed models were fitted to explore the associations between the milk mineral elements and first, the DSCC combined with SCC, and second, DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the proportion of PMN-LYM and MAC by SCC. We observed a significant positive association between SCC and milk Na, S, and Fe levels. Differential somatic cell count showed an opposite behavior to the one displayed by SCC, with a negative association with Na and positive association with K milk concentrations. When considering DSCC as count, Na and K showed contrasting behavior when associated with PMN-LYM or MAC counts, with decreasing of Na content and increasing K when associated with increasing PMN-LYM counts, and increasing Na and decreasing K when associated with increasing MAC count. These findings confirmed that an increase in SCC is associated with altered milk Na and K amounts. Moreover, MAC count seemed to mirror SCC patterns, with the worsening of inflammation. Differently, PMN-LYM count exhibited patterns of associations with milk Na and K contents attributable more to LYM than PMN, given the nonpathological condition of the majority of the investigated population. An interesting association was observed for milk S content, which increased with increasing of inflammatory conditions (i.e., increased SCC and MAC count) probably attributable to its relationship with milk proteins, especially whey proteins. Moreover, milk Fe content showed positive associations with the PMN-LYM population, highlighting its role in immune regulation during inflammation. Further studies including individuals with clinical condition are needed to achieve a comprehensive view of milk mineral behavior during udder health impairment.

Colour Doppler study of blood flow in the portal vein in relation to blood flow in the milk vein, milk yield and body condition of dairy cows during dry period and lactation

In dairy cows, the liver supports the increased nutrient demands of the udder for milk production. Blood flow is key for the transport of these nutrients. This study investigated portal vein blood flow volume (PVBFVol) in relation to daily milk yield (DMY), milk vein blood flow volume (MVBFVol) and body condition parameters of high-producing dairy cows, starting from late lactation, throughout dry period, and consecutive early lactation. Seventeen repeated examinations were performed on 19 Holstein cows and 313 measurement days were finally included. Vein morphology and blood flow were examined via B-mode and spectral Doppler (triplex) ultrasonography, respectively. Body condition parameters recorded were body condition score (BCS), backfat thickness (BFT) measurement with ultrasonography, heart girth circumference (HG) and withers height (WH). Longitudinal relationship of PVBFVol with MVBFVol, DMY, BCS, BFT, HG and WH was analyzed with linear mixed models, with random intercept effects, using restricted cubic splines. A significant increase of 8.28% (p < 0.01) in PVBFVol appeared for every 1 L/min increase in MVBFVol in the univariable model. PVBFVol presented a significant negative association with BCS (p < 0.01) and BFT (p = 0.02), while interaction with production stage was significant, too. PVBFVol significantly increased by 0.38% (p = 0.04) for every 1 kg increase in DMY in the multivariable model. In conclusion, the increased PVBFVol during lactation accompanies the escalation in metabolic activity of the liver and the increased blood circulation through the udder, coping with the udder's escalating nutrient demands for milk synthesis.

Associations between the detailed milk mineral profile, milk composition, and metabolic status in Holstein cows

The causes of variation in the milk mineral profile of dairy cattle during the first phase of lactation were studied under the hypothesis that the milk mineral profile partially reflects the animals' metabolic status. Correlations between the minerals and the main milk constituents (i.e., protein, fat, and lactose percentages), and their associations with the cows' metabolic status indicators were explored. The metabolic status indicators (MET) that we used were blood energy-protein metabolites [nonesterified fatty acids, β-hydroxybutyrate (BHB), glucose, cholesterol, creatinine, and urea], and liver ultrasound measurements (predicted triacylglycerol liver content, portal vein area, portal vein diameter and liver depth). Milk and blood samples, and ultrasound measurements were taken from 295 Holstein cows belonging to 2 herds and in the first 120 d in milk (DIM). Milk mineral contents were determined by ICP-OES; these were considered the response variable and analyzed through a mixed model which included DIM, parity, milk yield, and MET as fixed effects, and the herd/date as a random effect. The MET traits were divided in tertiles. The results showed that milk protein was positively associated with body condition score (BCS) and glucose, and negatively associated with BHB blood content; milk fat was positively associated with BHB content; milk lactose was positively associated with BCS; and Ca, P, K and S were the minerals with the greatest number of associations with the cows' energy indicators, particularly BCS, predicted triacylglycerol liver content, glucose, BHB and urea. We conclude that the protein, fat, lactose, and mineral contents of milk partially reflect the metabolic adaptation of cows during lactation and within 120 DIM. Variations in the milk mineral profile were consistent with changes in the major milk constituents and the metabolic status of cows.

Prediction of detailed blood metabolic profile using milk infrared spectra and machine learning methods in dairy cattle

The adoption of preventive management decisions is crucial to dealing with metabolic impairments in dairy cattle. Various serum metabolites are known to be useful indicators of the health status of cows. In this study, we used milk Fourier-transform mid-infrared (FTIR) spectra and various machine learning (ML) algorithms to develop prediction equations for a panel of 29 blood metabolites, including those related to energy metabolism, liver function/hepatic damage, oxidative stress, inflammation/innate immunity, and minerals. For most traits, the data set comprised observations from 1,204 Holstein-Friesian dairy cows belonging to 5 herds. An exception was represented by β-hydroxybutyrate prediction, which contained observations from 2,701 multibreed cows pertaining to 33 herds. The best predictive model was developed using an automatic ML algorithm that tested various methods, including elastic net, distributed random forest, gradient boosting machine, artificial neural network, and stacking ensemble. These ML predictions were compared with partial least squares regression, the most commonly used method for FTIR prediction of blood traits. Performance of each model was evaluated using 2 cross-validation (CV) scenarios: 5-fold random (CV_r) and herd-out (CV_h). We also tested the best model's ability to classify values precisely in the 2 extreme tails, namely, the 25th (Q25) and 75th (Q75) percentiles (true-positive prediction scenario). Compared with partial least squares regression, ML algorithms achieved more accurate performance. Specifically, elastic net increased the R² value from 5% to 75% for CV_r and 2% to 139% for CV_h, whereas the stacking ensemble increased the R² value from 4% to 70% for CV_r and 4% to 150% for CV_h. Considering the best model, with the CV_r scenario, good prediction accuracies were obtained for glucose (R² = 0.81), urea (R² = 0.73), albumin (R² = 0.75), total reactive oxygen metabolites (R² = 0.79), total thiol groups (R² = 0.76), ceruloplasmin (R² = 0.74), total proteins (R² = 0.81), globulins (R² = 0.87), and Na (R² = 0.72). Good prediction accuracy in classifying extreme values was achieved for glucose (Q25 = 70.8%, Q75 = 69.9%), albumin (Q25 = 72.3%), total reactive oxygen metabolites (Q25 = 75.1%, Q75 = 74%), thiol groups (Q75 = 70.4%), total proteins (Q25 = 72.4%, Q75 = 77.2.%), globulins (Q25 = 74.8%, Q75 = 81.5%), and haptoglobin (Q75 = 74.4%). In conclusion, our study shows that FTIR spectra can be used to predict blood metabolites with relatively good accuracy, depending on trait, and are a promising tool for large-scale monitoring.

Metabolic and physiological adaptations to first and second lactation in Holstein dairy cows

Huge differences exist between cow yields and body sizes during their first and second lactations. The transition period is the most critical and investigated phase of the lactation cycle. We compared metabolic and endocrine responses between cows at different parities during the transition period and early lactation. Eight Holstein dairy cows were monitored at their first and second calving during which they were reared under the same conditions. Milk yield, dry matter intake (DMI), and body weight (BW) were regularly measured, and energy balance, efficiency, and lactation curves were calculated. Blood samples were collected on scheduled days from -21 d relative to calving (DRC) to 120 DRC for the assessment of metabolic and hormonal profiles (biomarkers of metabolism, mineral status, inflammation, and liver function). Large variations in the period in question for almost all variables investigated were observed. Compared with their first lactation, cows during their second lactation had higher DMI (+15%) and BW (+13%), their milk yield was greater (+26%), lactation peak was higher and earlier (36.6 kg/d at 48.8 DRC vs. 45.0 kg/d at 62.9 DRC), but persistency was reduced. Milk fat, protein, and lactose contents were higher during the first lactation and coagulation properties were better (higher titratable acidity, faster and firmer curd formation). Postpartum negative energy balance was more severe the during the second lactation (1.4-fold at 7 DRC) and plasma glucose was lower. Circulating insulin and insulin-like growth factor-1 were lower in second-calving cows during the transition period. At the same time, markers of body reserve mobilization (β-hydroxybutyrate and urea) increased. Moreover, albumin, cholesterol, and γ-glutamyl transferase were higher during second lactation, whereas bilirubin and alkaline phosphatase were lower. The inflammatory response after calving was not different, as suggested by the similar haptoglobin concentrations and only transient differences in ceruloplasmin. Blood growth hormone did not differ during the transition period but was lower during the second lactation at 90 DRC, whereas circulating glucagon was higher. These results agree with the differences in milk yield and confirmed the hypothesis of a different metabolic and hormonal status between the first and second lactation partly related to different degrees of maturity.

Relationships between Milk and Blood Biochemical Parameters and Metabolic Status in Dairy Cows during Lactation

This study aimed to determine blood and milk metabolic parameters and their correlations for the purpose of evaluating metabolic status in dairy cows. Blood and milk samples were collected from 100 Holstein dairy cows during morning milking. The cows were allocated to four groups according to the production period, including cows in early (n = 18), full (n = 26), mid (n = 25) and late (n = 31) lactation. The value of non-esterified fatty acids (NEFA), β-hydroxybutyrate (BHB), glucose, triglycerides (TG), total cholesterol (TChol), total protein (TP), albumin, globulin, urea, total bilirubin (TBil), aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), and lactate dexydrogenase (LDH) in the blood were determined. The following milk parameters were measured: fat, protein, lactose, urea, AST, ALT, ALP, GGT, LDH and BHB. Blood serum NEFA, BHB, TBil, AST, ALT, ALP and LDH were higher in early lactation cows, whereas glucose, TP, globulin and urea levels were significantly lower in early lactation cows. Milk fat and lactose levels were lower in early lactation cows, whereas milk protein and the activities of AST, ALT, ALP and LDH in milk were highly greater in early lactation cows. Milk fat was positively correlated with glucose, TP and TG, and negatively correlated with BHB, NEFA, TBil, ALT, LDH and ALP levels in the blood. Enzyme activities in milk were positively correlated with those in blood and with blood NEFA, BHB and TBil levels, and negatively correlated with blood glucose, TChol and TG. A significant positive correlation existed between blood and milk BHB values. Many correlations showed the same slope during all lactation periods. In conclusion, similar changes in blood and milk metabolite concentration during lactation and milk to blood correlations confirm that milk has great potential in predicting of blood metabolites and metabolic status of cows.

Maladaptation to the transition period and consequences on fertility of dairy cows

After parturition, dairy cows undergo a plethora of metabolic, inflammatory, and immunologic changes to adapt to the onset of lactation. These changes are mainly due to the homeorhetic shift to support milk production when nutrient demand exceeds dietary intake, resulting in a state of negative energy balance. Negative energy balance in postpartum dairy cows is characterized by upregulated adipose tissue modelling, insulin resistance, and systemic inflammation. However, half of the postpartum cows fail to adapt to these changes and develop one or more types of clinical and subclinical disease within 5 weeks after calving, and this is escorted by impaired reproductive performance in the same lactation. Maladaptation to the transition period exerts molecular and structural changes in the follicular and reproductive tract fluids, the microenvironment in which oocyte maturation, fertilization, and embryo development occur. Although the negative effects of transition diseases on fertility are well-known, the involved pathways are only partially understood. This review reconstructs the mechanism of maladaptation to lactation in the transition period, explores their key (patho)physiological effects on reproductive organs, and briefly describes potential carryover effects on fertility in the same lactation.

Associations between Milk Fatty Acid Profile and Body Condition Score, Ultrasound Hepatic Measurements and Blood Metabolites in Holstein Cows

Dairy cows have high incidences of metabolic disturbances, which often lead to disease, having a subsequent significant impact on productivity and reproductive performance. As the milk fatty acid (FA) profile represents a fingerprint of the cow’s nutritional and metabolic status, it could be a suitable indicator of metabolic status at the cow level. In this study, we obtained milk FA profile and a set of metabolic indicators (body condition score, ultrasound liver measurements, and 29 hematochemical parameters) from 297 Holstein–Friesian cows. First, we applied a multivariate factor analysis to detect latent structure among the milk FAs. We then explored the associations between these new synthetic variables and the morphometric, ultrasonographic and hematic indicators of immune and metabolic status. Significant associations were exhibited by the odd-chain FAs, which were inversely associated with β-hydroxybutyrate and ceruloplasmin, and positively associated with glucose, albumin, and γ-glutamyl transferase. Short-chain FAs were inversely related to predicted triacylglycerol liver content. Rumen biohydrogenation intermediates were associated with glucose, cholesterol, and albumin. These results offer new insights into the potential use of milk FAs as indicators of variations in energy and nutritional metabolism in early lactating dairy cows.

Early Warning for Ovarian Diseases Based on Plasma Non-esterified Fatty Acid and Calcium Concentrations in Dairy Cows

Inactive ovaries (IO) and ovarian (follicular or luteal) cysts (FC or LC) are two common ovarian diseases leading to infertility in dairy cattle. Both disorders are associated with altered metabolites and hormones. There are currently no known effective biomarkers that can be used for early diagnosis of ovarian diseases. The purpose of this study was to identify the plasma biomarkers of ovarian diseases in Holstein dairy cows that facilitate an early diagnosis of the diseases and control its progression. The experiment was performed from 3 weeks postpartum and last for 7 weeks. Seventy-six multiparous Holstein cows (mean age, 4.36 years; weight, 635.63 kg) were divided into healthy control group (HC, n = 22), FC group (n = 18), LC group (n = 18) and IO group (n = 18) by rectal palpation or ultrasonography during the last 2 weeks before trial end. Blood was collected via tail vein for measurement of plasma energy metabolites, liver function indicators, minerals, and hormones at 3 and 8 weeks postpartum. Data were analyzed by Mann-Whitney U, Kruskal-Wallis, Spearman correlation, binary logistic regression analysis and receiver operating characteristic analysis, where applicable. At 8 weeks postpartum, FC cows had a more severe body condition score loss and these had greater levels of non-esterified fatty acids (NEFA) and estradiol, and lesser levels of alanine aminotransferase (ALT), progesterone and insulin-like growth factor 1 (IGF-1) levels than HC cows (P < 0.05). LC cows had a lower milk yield, higher NEFA and progesterone levels, and lower calcium, phosphorus and magnesium levels than HC cows (P < 0.05). IO cows had a lower body condition score, higher NEFA levels, and lower ALT, calcium, phosphorus, magnesium, estradiol, progesterone and IGF-1 levels than HC cows (P < 0.05). At 3 weeks postpartum, cows with ovarian diseases had greater (P < 0.05) concentrations of NEFA, and lesser concentrations of ALT, calcium, phosphorus and IGF-1 than HC cows. Early warning values for ovarian diseases were plasma NEFA concentrations >0.50 mmol/L, or calcium concentrations <2.02 mmol/L. Therefore, plasma NEFA and calcium could be used as early-warning indicators for ovarian diseases in dairy cows.