Ketone bodies - causes and effects of their increased presence in cows' body fluids: A review

Diabetes and aortic dissection: unraveling the role of 3-hydroxybutyrate through mendelian randomization

BACKGROUND

In observational and experimental studies, diabetes has been reported as a protective factor for aortic dissection. 3-Hydroxybutyrate, a key constituent of ketone bodies, has been found to favor improvements in cardiovascular disease. However, whether the protective effect of diabetes on aortic dissection is mediated by 3-hydroxybutyrate is unclear. We aimed to investigate the causal effects of diabetes on the risk of aortic dissection and the mediating role of 3-hydroxybutyrate in them through two-step Mendelian randomization.

MATERIALS AND METHODS

We performed a two-step Mendelian randomization to investigate the causal connections between diabetes, 3-hydroxybutyrate, and aortic dissection and calculate the mediating effect of 3-hydroxybutyrate. Publicly accessible data for Type 1 diabetes, Type 2 diabetes, dissection of aorta and 3-hydroxybutyrate were obtained from genome-wide association studies. The association between Type 1 diabetes and dissection of aorta, the association between Type 2 diabetes and dissection of aorta, and mediation effect of 3-hydroxybutyrate were carried out separately.

RESULTS

The IVW method showed that Type 1 diabetes was negatively associated with the risk of aortic dissection (OR 0.912, 95% CI 0.836-0.995), The weighted median, simple mode and weighted mode method showed consistent results. The mediated proportion of 3-hydroxybutyrate on the relationship between Type 1 diabetes and dissection of aorta was 24.80% (95% CI 5.12-44.47%). The IVW method showed that Type 2 diabetes was negatively associated with the risk of aortic dissection (OR 0.763, 95% CI 0.607-0.960), The weighted median, simple mode and weighted mode method showed consistent results. 3-Hydroxybutyrate does not have causal mediation effect on the relationship between Type 2 diabetes and dissection of aorta.

CONCLUSION

Mendelian randomization study revealed diabetes as a protective factor for dissection of aorta. The protective effect of type 1 diabetes on aortic dissection was partially mediated by 3-hydroxybutyrate, but type 2 diabetes was not 3-hydroxybutyrate mediated.

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.

Multi-omics analyses reveal rumen microbes and secondary metabolites that are unique to livestock species

Ruminant livestock, including cattle, sheep, goats, and camels, possess a distinctive digestive system with complex microbiota communities critical for feed conversion and secondary metabolite production, including greenhouse gases. Yet, there is limited knowledge regarding the diversity of rumen microbes and metabolites benefiting livestock physiology, productivity, climate impact, and defense mechanisms across ruminant species. In this study, we utilized metataxonomics and metabolomics data from four evolutionarily distinct livestock species, which had fed on diverse plant materials like grass, shrubs, and acacia trees, to uncover the unique signature microbes and secondary metabolites. We established the presence of a distinctive anaerobic fungus called Oontomyces in camels, while cattle exhibited a higher prevalence of unique microbes like Psychrobacter, Anaeromyces, Cyllamyces, and Orpinomyces. Goats hosted Cleistothelebolus, and Liebetanzomyces was unique to sheep. Furthermore, we identified a set of conserved core microbes, including Prevotella, Rickenellaceae, Cladosporium, and Pecoramyces, present in all the ruminants, irrespective of host genetics and dietary composition. This underscores their indispensable role in maintaining crucial physiological functions. Regarding secondary metabolites, camel's rumen is rich in organic acids, goat's rumen is rich in alcohols and hydrocarbons, sheep's rumen is rich in indoles, and cattle's rumen is rich in sesquiterpenes. Additionally, linalool propionate and terpinolene were uniquely found in sheep rumen, while valencene was exclusive to cattle. This may suggest the existence of species-specific microbes and metabolites that require host rumen-microbes' environment balance. These results have implications for manipulating the rumen environment to target specific microbes and secondary metabolite networks, thereby enhancing livestock productivity, resilience, reducing susceptibility to vectors, and environmentally preferred livestock husbandry.IMPORTANCERumen fermentation, which depends on feed components and rumen microbes, plays a crucial role in feed conversion and the production of various metabolites important for the physiological functions, health, and environmental smartness of ruminant livestock, in addition to providing food for humans. However, given the complexity and variation of the rumen ecosystem and feed of these various livestock species, combined with inter-individual differences between gut microbial communities, how they influence the rumen secondary metabolites remains elusive. Using metagenomics and metabolomics approaches, we show that each livestock species has a signature microbe(s) and secondary metabolites. These findings may contribute toward understanding the rumen ecosystem, microbiome and metabolite networks, which may provide a gateway to manipulating rumen ecosystem pathways toward making livestock production efficient, sustainable, and environmentally friendly.

Gene association analysis of an osteopontin polymorphism and ketosis resistance in dairy cattle

The aim of this study was to identify the c.495C > T polymorphism within exon 1 of the osteopontin gene (OPN), and to analyze its association with susceptibility to ketosis in Polish Holstein-Friesian (HF) cows. The study utilized blood samples from 977 HF cows, for the determination of β-hydroxybutyric acid (BHB) and for DNA isolation. The c.495C > T polymorphism of the bovine osteopontin gene was determined by PCR-RFLP. The CT genotype (0.50) was deemed the most common, while TT (0.08) was the rarest genotype. Cows with ketosis most often had the CC genotype, while cows with the TT genotype had the lowest incidence of ketosis. To confirm the relationship between the genotype and ketosis in cows, a weight of evidence (WoE) was generated. A very strong effect of the TT genotype on resistance to ketosis was demonstrated. The distribution of the ROC curve shows that the probability of resistance to ketosis is > 75% if cows have the TT genotype of the OPN gene (cutoff value is 0.758). Results suggest that TT genotype at the c.495C > T locus of the OPN gene might be effective way to detect the cows with risk of ketosis.

Lipolysis inhibition as a treatment of clinical ketosis in dairy cows: A randomized clinical trial

Excessive and protracted lipolysis in adipose tissues of dairy cows is a major risk factor for clinical ketosis (CK). This metabolic disease is common in postpartum cows when lipolysis provides fatty acids as an energy substrate to offset negative energy balance. Lipolysis in cows can be induced by the canonical (hormonally induced) and inflammatory pathways. Current treatments for CK focus on improving glucose in blood (i.e., oral propylene glycol [PG], or i.v. dextrose). However, these therapies do not inhibit the canonical and inflammatory lipolytic pathways. Niacin (NIA) can reduce activation of the canonical pathway. Blocking inflammatory responses with cyclooxygenase inhibitors such as flunixin meglumine (FM) can inhibit inflammatory lipolytic activity. The objective of this study was to determine the effects of including NIA and FM in the standard PG treatment for postpartum CK on circulating concentrations of ketone bodies. A 4-group, parallel, individually randomized trial was conducted in multiparous Jersey cows (n = 80) from a commercial dairy in Michigan during a 7-mo period. Eligible cows had CK symptoms (lethargy, depressed appetite, and milk yield) and hyperketonemia (blood β-hydroxybutyrate [BHB] ≥1.2 mmol/L). Cows with CK were randomly assigned to 1 of 3 groups where the first group received 310 g of oral PG once per day for 5 d; the second group received PG for 5 d + 24 g of oral NIA once per day for 3 d (PGNIA); and the third group received PG for 5 d + NIA for 3 d + 1.1 mg/kg i.v. FM once per day for 3 d (PGNIAFM). The control group consisted of cows that were clinically healthy (HC; untreated; BHB <1.2 mmol/L, n = 27) matching for parity and DIM with all 3 groups. Animals were sampled at enrollment (d 0), and d 3, 7, and 14 to evaluate ketone bodies and circulating metabolic and inflammatory biomarkers. Effects of treatment, sampling day, and their interactions were evaluated using mixed effects models. Logistic regression was used to calculate the odds ratio (OR) of returning to normoketonemia (BHB <1.2 mmol/L). Compared with HC, enrolled CK cows exhibited higher blood concentrations of dyslipidemia markers, including nonesterified fatty acids (NEFA) and BHB, and lower glucose and insulin levels. Cows with CK also had increased levels of biomarkers of pain (substance P), inflammation, including lipopolysaccharide-binding protein, haptoglobin, and serum amyloid A, and proinflammatory cytokines IL-4, MCP-1, MIP-1α, and TNFα. Importantly, 72.2% of CK cows presented endotoxemia and had higher circulating bacterial DNA compared with HC. By d 7, the percentage of cows with normoketonemia were higher in PGNIAFM = 87.5%, compared with PG = 58.33%, and PGNIA = 62.5%. At d 7 the OR for normoketonemia in PGNIAFM cows were 1.5 (95% CI, 1.03-2.17) and 1.4 (95% CI, 0.99-1.97) relative to PG and PGNIA, respectively. At d 3, 7, and 14, PGNIAFM cows presented the lowest values of BHB (PG = 1.36; PGNIA = 1.24; PGNIAFM = 0.89 ± 0.13 mmol/L), NEFA (PG = 0.58; PGNIA = 0.59; PGNIAFM = 0.45 ± 0.02 mmol/L), and acute phase proteins. Cows in PGNIAFM also presented the highest blood glucose increment across time points and insulin by d 7. These data provide evidence that bacteremia or endotoxemia, systemic inflammation, and pain may play a crucial role in CK pathogenesis. Additionally, targeting lipolysis and inflammation with NIA and FM during CK effectively reduces dyslipidemia biomarkers, improves glycemia, and improves overall clinical recovery.

β-Hydroxybutyrate Effects on Bovine Caruncular Epithelial Cells: A Model for Investigating the Peri-Implantation Period Disruption in Ketotic Dairy Cows

Ketosis is a metabolic disorder arising from a negative energy balance (NEB). It is characterized by high β-Hydroxybutyrate (BHBA) blood levels and associated with reduced fertility in dairy cows. To investigate the impact of BHBA on bovine caruncular epithelial cells (BCEC) in vitro, these cells were stimulated with different concentrations of BHBA. Cell metabolism and motility were examined using an MTT assay and Live-cell imaging. RT-qPCR was used to examine mRNA expressions of TNF, IL6, RELA, prostaglandin E2 synthase (PTGES2) and receptor (PTGER2) as well as integrin subunits ITGAV, ITGA6, ITGB1 and ITGB3. Stimulation with 1.8 and 2.4 mM of BHBA negatively affected cell metabolism and motility. TNF showed increased mRNA expression related to rising BHBA concentrations. IL6, RELA, ITGAV, ITGA6, ITGB1 and ITGB3 as well as PTGER2 showed no changes in mRNA expression. Stimulation with 0.6 and 1.2 mM of BHBA significantly increased the mRNA expression of PTGES2. This does not indicate a negative effect on reproductive performance because low BHBA concentrations are found in steady-state conditions. However, the results of the study show negative effects of high BHBA concentrations on the function of BCECs as well as an inflammatory response. This could negatively affect the feto-maternal communication during the peri-implantation period in ketotic dairy cows.

Characteristics of Holstein cows predisposed to ketosis during the post-partum transition period

BACKGROUND

Ketosis is a common metabolic disorder during the post-partum transition period of dairy cattle. How the method of reproduction, parturition time, and calf birth weight affect the occurrence of ketosis on dairy herds remains elusive.

OBJECTIVES

This study investigated factors associated with the severity of ketosis.

METHODS

We divided 186 Holstein cows into three classifications based on the highest β-hydroxybutyrate (BHBA) concentration during the post-partum transition period, namely non-ketosis (<1.2 mmol/L, n = 94), subclinical ketosis (1.2-2.9 mmol/L, n = 58), and clinical ketosis (≥3.0 mmol/L, n = 34). We evaluated characteristics of cows associated with the severity of ketosis.

RESULTS

Ketosis was not associated with the method of reproduction, parturition time, pregnancy wastage, premature delivery, retained placenta, and type of calf. Cows calving in spring and especially summer were at higher risk of severe ketosis (p < 0.01). Cows with increased body condition score (BCS) at parturition, age, lactation number, and calving interval were more likely to develop severe ketosis (p < 0.05). Cows with clinical ketosis produced most milk (29.9 ± 1.0 kg) from days four to six, whereas cows without ketosis produced the least (21.3 ± 0.8 kg) (p < 0.001). Heavier calf birth weight resulted in high risk of severe ketosis (p < 0.01), due to increased milk yield during the early lactation.

CONCLUSIONS

The severity of ketosis is associated with the calving season, BCS at parturition, age, lactation number, calving interval, milk yield in the early lactation period, and calf birth weight. Nonetheless, it was not associated with the method of reproduction, parturition time, pregnancy wastage, premature delivery, retained placenta, and type of calf. This study is the first to investigate the associations between ketosis and calf birth weight. Our findings could help predict cows at risk of ketosis and take precautions.

Effect of Breed on the Fatty Acid Composition of Milk from Dairy Cows Milked Once and Twice a Day in Different Stages of Lactation

The objective of this study was to evaluate the effect of breed on the overall composition and fatty acid composition of milk from cows milked once a day (OAD) and twice a day (TAD) in different stages of lactation. Milk samples were taken from 39 Holstein-Friesian (F), 27 Jersey (J), and 34 Holstein-Friesian × Jersey (F × J) crossbred cows from a OAD milking herd and 104 F and 83 F × J cows from a TAD milking herd in early (49 ± 15 days in milk), mid (129 ± 12 days in milk), and late (229 ± 13 days in milk) lactation. Calibration equations to predict the concentrations of individual fatty acids were developed using mid-infrared (MIR) spectroscopy. There was a significant interaction between breed within the milking frequency and stage of lactation for the production traits and composition traits. Holstein-Friesian cows milked OAD produced milk with lower concentrations of C18:0 in early and mid lactations compared to F × J and J cows. Holstein-Friesian cows milked TAD produced lower concentrations of C18:0 in early lactation and lower concentrations of C16:0 and C18:0 in late lactation compared to F × J. Lower concentrations of these fatty acids would reduce the hardness of the butter when the milk is processed. In the OAD milking herd, F cows were superior for daily milk yield compared to J cows, but Jersey cows produced significantly (p < 0.05) higher percentages of fat and a higher concentration of C18:0 fatty acid. The relative concentrations of C18:0 and C18 cis-9 in F and J cows milked OAD imply there is no breed effect on the activity of delta-9-desaturase, whereas stages of lactation likely have an effect. These results can be used to assist with selecting breeds and cows that are suitable for either OAD or TAD milking, allowing closer alignment with milk processing needs.

The Use of Multilayer Perceptron Artificial Neural Networks to Detect Dairy Cows at Risk of Ketosis

Simple Summary

Ketosis is a serious metabolic disease in high-yield dairy cows, that affects productive herds throughout the world. Subclinical ketosis is one of the most dominant metabolic disorders in dairy herds during early lactation, so early detection and prevention are important for both economic and animal welfare reasons. Neural networks, which offer a high degree of accuracy in predicting various phenomena and processes where there is no clear causal correlation or there are no rules that allow the establishment of a logical cause-and-effect relationship, can be used to address problems related to prediction, classification, or control. A Multi-Layer perceptron (MLP) is a feedforward artificial neural network model that takes input data for a set of proper output. This study investigated the performance of four algorithms used to train MLP networks. The experimental results demonstrate that the MLP network model improved the accuracy of process recognition of subclinical ketosis in dairy cows. The received artificial model’s results were saved in the predictive model markup language (PMML) and can be used to describe the learning set, the algorithm used in the data mining application and related information.

Abstract

Subclinical ketosis is one of the most dominant metabolic disorders in dairy herds during lactation. Cows suffering from ketosis experience elevated ketone body levels in blood and milk, including β-hydroxybutyric acid (BHB), acetone (ACE) and acetoacetic acid. Ketosis causes serious financial losses to dairy cattle breeders and milk producers due to the costs of diagnosis and management as well as animal welfare reasons. Recent years have seen a growing interest in the use of artificial neural networks (ANNs) in various fields of science. ANNs offer a modeling method that enables the mapping of highly complex functional relationships. The purpose of this study was to determine the relationship between milk composition and blood BHB levels associated with subclinical ketosis in dairy cows, using feedforward multilayer perceptron (MLP) artificial neural networks. The results were verified based on the estimated sensitivity and specificity of selected network models, an optimum cut-off point was identified for the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC). The study demonstrated that BHB, ACE and lactose (LAC) levels, as well as the fat-to-protein ratio in milk, were important input variables in the network training process. For the identification of cows at risk of subclinical ketosis, variables such as BHB and ACE levels in milk were of particular relevance, with a sensitivity and specificity of 0.84 and 0.61, respectively. It was found that the back propagation algorithm offers opportunities to integrate artificial intelligence and dairy cattle welfare within a computerized decision support tool.