Introduction
The perinatal period is a crucial stage for fetal growth and development, significantly influencing the long-term growth, development and functionality of fetal organs due to changes in maternal metabolic status (Brumby Reference Brumby1960; Reynolds et al. Reference Reynolds, Diniz and Crouse2022). Body condition score (BCS) serves as a key indicator of the metabolic status of dairy cows, reflecting their overall metabolic state (Roche et al. Reference Roche, Friggens and Kay2009; Vailati-Riboni et al. Reference Vailati-Riboni, Meier and Burke2016). Maintaining an appropriate BCS in perinatal dairy cows is essential for the development and productivity of their offspring (Poczynek et al. Reference Poczynek, de S. Nogueira and Carrari2023).
During the perinatal period, dairy cows undergo significant physiological changes, often resulting in a state of negative energy balance (NEB) due to higher energy demands than intake (Grummer Reference Grummer1995). To manage NEB, cows mobilize substantial body fat reserves (Janovick et al. Reference Janovick, Boisclair and Drackley2011). In comparison to cows with a normal BCS, obese cows exhibit greater fat mobilization and higher concentrations of non-esterified fatty acids (NEFAs) in their blood (Akbar et al. Reference Akbar, Grala and Vailati2015). Extensive fat mobilization is closely associated with reduced feed intake in obese cows, indicating a heightened metabolic challenge (Caldeira et al. Reference Caldeira, Belo and Santos2007; Schuh et al. Reference Schuh, Sadri and Häussler2019). Furthermore, BCS during the perinatal period influences serum levels of zinc (Zn), manganese (Mn) and chromium (Cr), with lower concentrations of these trace elements observed in obese cows (Dehghan Shahreza et al. Reference Dehghan Shahreza, Seifi and Mohri2020). In cows with elevated prepartum BCS, serum levels of NEFA, β-hydroxybutyrate (BHB) and glucose (GLU) are significantly higher than those in cows with normal BCS (Schuh et al. Reference Schuh, Sadri and Häussler2019). The developing fetus is affected by maternal nutrition, and Barker’s “developmental programming theory” posits that early maternal influences can lead to physiological and metabolic changes in the fetus, potentially impacting the offspring in both the short and long term (Barker Reference Barker1998).
Current research on ruminants has primarily concentrated on the phenotypic effects of maternal influences on offspring, encompassing aspects such as growth rate, ketone body characteristics, milk production and immune capacity (Alharthi et al. Reference Alharthi, Coleman and Alhidary2021; Lopes et al. Reference Lopes, Alharthi and Lopreiato2021; López Valiente et al. Reference López Valiente, Rodriguez and Long2021). However, investigations into the impact of maternal metabolic status during the perinatal period on the metabolic mechanisms of offspring remain limited. In both humans and mice, numerous epidemiological studies and experimental animal models have demonstrated that maternal metabolic disorders during pregnancy elevate the risk of metabolic diseases in offspring, resulting in long-term consequences (Bendor et al. Reference Bendor, Bardugo and Rotem2022; Damm et al. Reference Damm, Houshmand-Oeregaard and Kelstru2016; Jousse et al. Reference Jousse, Parry and Lambert-Langlais2011). We hypothesize that varying BCSs in perinatal dairy cows will influence the metabolism of their offspring.
The growth and development of calves prior to weaning are critical for their subsequent development and performance (Kertz et al. Reference Kertz, Hill and Quigley2017). The metabolic capacity of calves before weaning is a significant factor influencing their growth, with the liver serving as the central organ for metabolism. This study examined the impact of varying BCS in perinatal dairy cows on the metabolic status of their offspring by comparing differences in hepatic metabolites, gene expression and blood biochemical indicators in the calves.
Materials and methods
Experimental animals
The experiment was conducted from July 2023 to September 2023 at a dairy farm in Shandong Province. Thirty cows exhibiting significant differences in body condition were selected to participate in this experiment 14 days prior to the expected delivery date. The classification of the dairy cows in this study was relative, with a BCS of 3.56 ± 0.21 designated as the high body condition group (OHBCS) and a BCS of 3.09 ± 0.20 classified as the low body condition group (OLBCS). Specific BCS data can be found in Supplementary Table 1 All cows had similar parity (1.9 ± 0.5) and were in good health. Following natural calving, 10 healthy male calves with comparable birth dates were selected from each group. The calves were divided into two groups based on their mothers’ BCS: offspring of high-BCS cows (OHBCS) and offspring of low-BCS cows (OLBCS). Calves were required to receive qualified colostrum within 1 hour of birth, and all test calves were transferred to the calf island on the day they turned 1 day old. According to the farm’s feeding management protocol, calves were fed regular milk (the milk composition data for normal milk are presented in Supplementary Table 2) starting at 2 days of age, administered twice daily (at 7:00 and 15:00). From 2 to 15 days of age, each feeding consisted of 2.5 liters, while from 16 to 30 days of age, each feeding increased to 3.0 liters. The body weight, body height and body length of the 1-month-old calves are presented in Supplementary Table 3.
Sample collection
Blood sample collection and measurement
At 1 month of age, 10 mL of blood was collected from the jugular vein using a disposable syringe. The blood was collected in coagulation-promoting tubes, allowed to stand for 30 minutes, and then centrifuged for 5 minutes at 3000 r/min. The supernatant was aliquoted into 1.5 mL centrifuge tubes and immediately stored at −20°C. Blood biochemical indices, including total protein (TP), albumin (ALB), GLU, aspartate aminotransferase (AST), alanine aminotransferase (ALT), blood urea nitrogen (BUN), triglycerides (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL) and total cholesterol (TC), were measured using an automated biochemical analyzer (Beckman Coulter, USA). Levels of immunoglobulin G (IgG), interleukin-6 (IL-6), interleukin-2 (IL-2), tumor necrosis factor-α (TNF-α), bovine leptin (LEP), bovine adiponectin (ADP), bovine insulin, bovine resistin, NEFA and BHB were determined using enzyme-linked immunosorbent assay. Malondialdehyde (MDA) levels were measured using an MDA assay kit, superoxide dismutase (SOD) levels with an SOD assay kit, glutathione peroxidase (GSH-Px) using a GSH-Px assay kit and total antioxidant capacity (T-AOC) with a T-AOC assay kit.
Liver sample collection
The calves were slaughtered via exsanguination through the jugular vein. Immediately following slaughter, the abdomen was opened and the liver was extracted. The liver from each calf was divided into three cryogenic vials, which were rapidly placed in liquid nitrogen and subsequently stored at −80°C for further nontargeted metabolomic and transcriptomic analyses.
Liver tissue untargeted metabolomics
Untargeted metabolomic experiments were conducted on the OHBCS (n = 6) and OLBCS (n = 6). For each sample, 100 μL was mixed with 400 μL of precooled 80% methanol for resuspension in an Eppendorf Mic (EP) tube. The tube was incubated on ice for 5 minutes, followed by centrifugation at 15000 g and 4°C for 20 minutes. An appropriate volume of the supernatant was collected and diluted with mass spectrometry-grade water to reduce the methanol content to 53%. Centrifugation was performed as previously described. The final analysis was conducted using liquid chromatography-mass spectrometry at Wuhan Metware Biotechnology Co., Ltd.
Liver transcriptomics
RNA was extracted from the liver tissues of both groups (n = 3) using TRIzol reagent (Invitrogen). Library construction was performed by Wuhan Metware Biotechnology Co., Ltd. In brief, total RNA from the liver tissues was extracted using TRIzol reagent (TianGen, China), and its quality was assessed using a NanoDrop spectrophotometer (Thermo Scientific, U.S.A.). To generate sequencing libraries, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads, which were then utilized to synthesize the second strand of cDNA. Subsequently, DNA fragments were enriched through a PCR reaction, followed by purification and quantification using the Bioanalyzer 2100 system (Agilent Technologies Inc., U.S.A.). Finally, the constructed sequencing library was sequenced using the NovaSeq 6000 platform (Illumina, U.S.A.).
Real-time PCR (RT-qPCR)
The gene expression of OHBCS (n = 3) and OLBCS (n = 3), along with the corresponding transcriptome samples, was analyzed using the QuantiTect SYBR Green PCR kit (Qiagen) on CFX96 thermal cyclers (Bio-Rad, Hercules, CA). The primers employed for quantitative reverse transcription polymerase chain reaction are listed in Table 1, with glyceraldehyde-3-phosphate dehydrogenase (GAPDH) serving as the internal control. Melt curve analysis was performed to confirm the specificity of the amplification reaction.
Table 1. RT-qPCR gene sequence
Data analysis and visualization
In the untargeted metabolomics analysis, raw data obtained from mass spectrometry were converted to mzXML format using ProteoWizard. Subsequently, peak extraction, alignment and retention time correction were conducted using XCMS software. Peaks with a missing rate exceeding 50% in each group were filtered out, and missing values were imputed utilizing the k-nearest neighbor (KNN) method. Peak areas were corrected using support vector regression. Metabolites were identified by searching an in-house database, integrating public databases and prediction libraries, and employing the Metabolite identification and Dysregulated Network Analysis (metDNA) method. Metabolites with a P-value 1 were deemed significantly different, whereas those with a P-value > 0.1 and a variable influence on projection (VIP) value >1 were considered to have a trend of significant difference. KEGG enrichment pathways with a P-value less than 0.05 relevant to this study were characterized using the MetaboAnalyst platform (MetaboAnalyst 6.0; https://www.metaboanalyst.ca).
For transcriptomics, reads were mapped to the reference genome using STAR software (version 2.5.3a), and gene expression levels were estimated using featureCounts (Subread-1.5.1; Bioconductor). Gene expression was quantified as RPKM (Reads Per Kilobase million Mapped Reads). Differentially expressed genes (DEGs) were defined as those with Padj 1.2 or<0.8. KEGG pathway enrichment analysis of DEGs was conducted using the OmicShare platform (p-value < 0.05) (https://www.omicshare.com/tools). Additionally, all statistical analyses were performed using GraphPad Prism 8 and SPSS 26 (IBM), with results presented as Mean ± SEM. Two-tailed, unpaired t-tests were employed to calculate p-values (* indicates p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001).
Results
Effect of different prepartum body conditions in dairy cows on blood metabolic parameters in offspring calves
OHBCS exhibited significantly higher insulin (INS) levels compared to OLBCS (p < 0.001). Furthermore, the concentrations of NEFA and BHB were also significantly elevated in the OHBCS group (p < 0.05) as shown in Table 2. However, variations in prepartum body condition among dairy cows did not significantly influence the concentrations of TP, ALB, ALT, AST, BUN, TC, TG, LEP, ADP, HDL cholesterol (HDL-C), or LDL cholesterol (LDL-C) in the blood of the offspring (p > 0.05).
Table 2. Effects of different body conditions of cows in early perinatal period on blood metabolic parameters of offspring calves
Note: TP: total protein ALB: albumin ALT: alanine aminotransferase; AST: aspartate transaminase; GLU: glucose; BUN: blood urea nitrogen; TG: triglycerides; TC: total cholesterol; LEP: leptin; ADP: adiponectin; INS: insulin; NEFA: non-esterified fatty acid; BHBA: β-hydroxybutyrate; HDL-C: high density lipoprotein cholesterol; LDL-C: low density lipoprotein cholesterol. Lowercase letters with the same data superscript in the table indicate no significant difference (P > 0.05), while different lowercase letters indicate significant difference (P < 0.05).
Effect of different prepartum body conditions in dairy cows on blood immune and antioxidant parameters in offspring calves
The blood levels of TNF-α in the OHBCS cows were significantly lower (p < 0.001) compared to those in the OLBCS cows. Additionally, IL-2 levels were significantly lower (p < 0.05), while IgG levels were significantly higher (p < 0.05) in the OHBCS group (Table 3). Serum levels of GSH-Px and SOD were also significantly higher (p < 0.001) in the OHBCS group than in the OLBCS group. However, no significant differences were observed in IL-6, T-AOC or MDA levels between the two groups (p > 0.05).
Table 3. Effects of different body conditions of cows in the early perinatal period on blood immunity and antioxidant indexes of their offspring calves
Note: IgG: immunoglobulin G; TNF-α: tumor necrosis factor-α; IL-2: interleukin-2; IL-6: interleukin-6; T-AOC: total antioxidant capacity; GSH-Px: glutathione peroxidase; MDA: malondialdehyde; SOD: superoxide dismutase. Lowercase letters with the same data superscript in the table indicate no significant difference (P > 0.05), while different lowercase letters indicate significant difference (P < 0.05).
Effect of different prepartum body conditions in dairy cows on liver metabolomics in offspring calves
In the Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA) model, the two groups exhibited a clear spatial separation (Fig. 1A). Based on the MS detection data, a total of 105 differential metabolites (p < 0.05) and 28 metabolites with differential trends (0.05 < p < 0.1) were identified. Among these, 54 metabolites were upregulated, and 51 were downregulated. Metabolites such as Suillin, Oxybutynin, Biphenyl-2,3-diol, Palmitic amide, Oxethazaine, [12]-Gingerdione, 16-Hydroxyhexadecanoic acid, 2-Decaprenyl-6-methoxy-3-methyl-1,4-benzoquinone, (8)-Gingerol, Sterculic acid, Imatinib, Ramiprilat, 6-Methoxy-3-methyl-2-all-trans-decaprenyl-1,4-benzoquinol, L-Tryptophan, Erythrose, Stachyose, Eicosapentaenoic acid, Erythritol and Geniposidic acid were significantly enriched in the livers of OHBCS calves (p < 0.05). Conversely, metabolites such as L-Homophenylalanine, Biocytin, 4,5-Chrysenedicarboxylate, L-Kynurenine, Malonic semialdehyde, 2,3-Diaminopropionic acid, Crotonic acid, N-Acetylvanilalanine, Aniline, 5-Hydroxyindoleacetic acid, (R)-2,3-Dihydroxy-isovalerate, Indole-3-glycerol phosphate, 3-Methylcrotonyl Glycine, Rasagiline, D-Kynurenine, Salmeterol, Ascorbic acid, Tetragastrin, N-Isovaleroylglycine and Palmitoyl Serinol were significantly enriched in the livers of OLBCS calves (p < 0.05). The top 50 differential metabolites between the two groups were further subjected to cluster analysis (Fig. 1B).
Figure 1. Analysis of different metabolites between perinatal high body condition dairy cow progeny (OHBCS) and perinatal low body condition dairy cow progeny (OLBCS).
To gain insights into the biological processes associated with the differential metabolites between the OHBCS and OLBCS groups, KEGG enrichment analysis was conducted. As shown in Fig. 2, significant differences were observed in pathways related to pyruvate, aspartate and glutamate metabolism; phenylalanine, tyrosine and tryptophan biosynthesis; the tricarboxylic acid (TCA) cycle; tryptophan metabolism; phenylalanine metabolism; pyruvate metabolism; biotin metabolism; glycine, serine and threonine metabolism; and d-amino acid metabolism (p < 0.05).
Figure 2. KEGG enrichment analysis of different differential metabolites. The progeny of perinatal cows with high body condition were represented by OHBCS and those of perinatal cows with low body condition were represented by OLBCS.
Effect of different prepartum body conditions in dairy cows on liver transcriptomics in offspring calves
Prepartum body conditions in dairy cows can influence the liver transcriptomes of their offspring. We analyzed the liver transcriptomes of calves from different groups using transcriptomic techniques. Figure 1 (A) demonstrates a clear spatial separation between the OHBCS and OLBCS, indicating significant differences between the samples. Differential gene selection criteria was based on |log2FC| ≥ 1 and false discovery rate (FDR) < 0.05, identifying 7177 DEGs, with 3871 upregulated and 3306 downregulated (Fig. 2B).
To further elucidate the biological functions of these DEGs, we conducted KEGG database annotations and hypergeometric test-based enrichment analyses. Seventeen modules exhibiting similar gene expression patterns were identified through weighted gene co-expression network analysis, with modules related to human diseases excluded (Fig. 3C). The majority of genes were found to be enriched in metabolic pathways. This suggests that the influence of various body conditions on the liver of offspring calves primarily affects metabolism, aligning with the objectives of our study.
Figure 3. Transcriptome differential analysis of perinatal high body condition dairy cow progeny (OHBCS) and perinatal low body condition dairy cow progeny (OLBCS). (A) PCA of liver transcriptome. (B) Transcriptome differential gene volcano map. (C) Gene co-expression network analysis. KO (KEGG ontology) enrichment circle diagram of cyan module (from the outside to the inside, the first circle represents enrichment pathways, and the number outside the circle is the coordinate ruler of the number of genes; the second circle represents the number and Q value of background genes in this pathway, and the more genes, the longer the bar; the third circle represents the number of the DEGs in this pathway; the fourth circle represents the value of rich factor in each pathway). (D) KEGG enrichment of differential genes in OLBCS and OHBCS groups (showing only the top 20 most significant pathways in metabolism).
Further analysis of the differential metabolic pathways in liver samples between the two groups revealed significant differences (p < 0.05) in several processes, including steroid hormone biosynthesis, bile secretion, pentose and glucuronate interconversions, drug metabolism via cytochrome P450, unsaturated fatty acid biosynthesis, porphyrin metabolism, protein processing in the endoplasmic reticulum, retinol metabolism, fatty acid metabolism, fatty acid elongation, niacin and nicotinamide metabolism, aldosterone synthesis and secretion, mineral absorption, sphingolipid metabolism, glycine, serine, and threonine metabolism, protein digestion and absorption, various forms of O-glycan biosynthesis, cortisol synthesis and secretion, and histidine metabolism (Fig. 3D). Quantitative PCR verification of the genes of interest confirmed consistency with transcriptomic results, thereby demonstrating the reliability of the transcriptomic data (Fig. 4).
Figure 4. q-PCR verification results of differential genes in OLBCS and OHBCS groups.
Discussion
Compared to OLBCS, OHBCS calves exhibited significantly higher levels of NEFAs and BHB in the blood (p < 0.05), which aligns with the findings of Alharthi et al. (Alharthi et al. Reference Alharthi, Coleman and Alhidary2021). In ruminants, NEFA and BHB are essential for maintaining energy balance. Offspring of obese cows often demonstrate compensatory growth during the first 2 months after birth (Poczynek et al. Reference Poczynek, de S. Nogueira and Carrari2023). The elevated levels of NEFA and BHB may provide an adequate energy supply for ruminants, potentially serving as a significant driving force behind the compensatory growth observed in calves from obese mothers (Long et al. Reference Long, Ford and Nathanielsz2011). The notable increase in blood BHB levels in calves with OHBCS may be associated with enhanced ketogenesis in the liver. However, elevated fat mobilization also increases the metabolic burden on the liver, with offspring of obese mammalian mothers being at a higher risk of developing fatty liver (Hagström et al. Reference Hagström, Simon and Roelstraete2021).
Leptin regulates feeding and energy expenditure through the hypothalamus, thereby maintaining body weight balance (Perucatti et al. Reference Perucatti, Di Meo and Vallinoto2006). In goats, leptin is associated with maternal BCS, offspring BCS and feed intake; notably, overweight ewes exhibit a deficiency in neonatal leptin (Long et al. Reference Long, Ford and Nathanielsz2011). Conversely, a recent study on dairy cows found no correlation between maternal BCS and offspring leptin levels (Brown et al. Reference Brown, Holdorf and Kendall2023). Our study similarly found no significant difference in leptin levels between the OHBCS and OLBCS groups. Although the TP content of the OHBCS group was higher than that of the OLBCS group, this difference was not statistically significant. Offspring calves from cows with a high body condition during the peripartum period experience greater nutritional restrictions in utero (Bernabucci et al. Reference Bernabucci, Ronchi and Lacetera2005a). Evidence suggests that intrauterine nutritional restriction during the peripartum period can enhance the permeability of the small intestine to macromolecular proteins, facilitating greater absorption of proteins from milk and subsequently increasing total blood protein levels (Sangild Reference Sangild2003). No significant differences in BUN levels were observed between the OHBCS and OLBCS groups; however, the elevated levels in the OLBCS group may indicate increased amino acid deamination activity, which provides a carbon skeleton for gluconeogenesis (Hammon et al. Reference Hammon, Steinhoff-Wagner and Flor2013).
GSH-Px directly interacts with free radicals and lipid peroxides, thereby safeguarding the body from oxidative damage. Consequently, glutathione serves as a vital indicator of antioxidant activity (Forman et al. Reference Forman, Zhang and Rinna2009). Similarly, SOD functions as an antioxidant enzyme that constitutes the primary intracellular antioxidant pathway. In this study, the levels of GSH-Px and SOD in the OHBCS group were significantly higher than those in the OLBCS group (p < 0.001). This difference may be attributed to the elevated levels of NEFA and BHB in the bloodstream of the OHBCS group (p < 0.05). Elevated concentrations of GSH-Px and SOD are essential for protecting the body from oxidative damage and for maintaining a normal physiological state. Previous studies have demonstrated that plasma GSH-Px levels correlate with plasma lipid levels (Tüzün et al. Reference Tüzün, Erdil and İnal2002), and that increased concentrations of NEFA and BHB in dairy cows are associated with heightened oxidative stress (Bernabucci et al. Reference Bernabucci, Ronchi and Lacetera2005b).
IgG is the predominant immunoglobulin in the body, facilitating the phagocytosis of pathogens by immune cells and neutralizing bacterial toxins (Shi et al. Reference Shi, Xu and Mao2020). Elevated IgG levels can enhance immune function in dairy cows (Xu et al. Reference Xu, Huang and Hou2017). The concentration of IgG in the OHBCS serum was significantly higher than that in the OLBCS serum, possibly due to the greater nutritional restrictions experienced by the maternal OHBCS during the peripartum period. Recent studies indicate that offspring of nutritionally restricted cows exhibit higher passive immunity coefficients for IgG (Wichman et al. Reference Wichman, Redifer and Meyer2023). A limitation of this study is the absence of measurements for other immunoglobulins, such as immunoglobulin A and immunoglobulin M.
The liver serves as a central hub for metabolic pathways in the body. To further investigate the mechanisms by which various body conditions in cows during the peripartum period affect their offspring, we employed untargeted metabolomics and transcriptomics to assess liver metabolites and differential gene expression, with a particular emphasis on liver-involved metabolic pathways. Succinate, α-ketoglutaric acid and malate are critical intermediates of the TCA cycle. Notably, pyruvate, succinate and malate levels were lower in the OHBCS group compared to the OLBCS group. Furthermore, the genes IDH1 and SUCLA2, which are part of the TCA pathway, exhibited significant inhibition in the OHBCS group (p < 0.001). Additionally, pyruvate, an essential substrate of the TCA pathway, was also significantly decreased in the OHBCS group. The genes encoding the pyruvate dehydrogenase complex, such as PDHA1 and DLD, were significantly downregulated in the OHBCS group, indicating that the conversion of pyruvate to acetyl-CoA was inhibited in this group. These findings suggest that the TCA pathway was inhibited in the OHBCS group (as illustrated in Fig. 5). Glycolysis is the primary pathway for pyruvate production, which is subsequently linked to other biochemical pathways. In this study, two key genes in the glycolysis pathway, G6PC1 and PDHA1, were significantly inhibited, indicating a marked downregulation of the glycolysis pathway in the OHBCS group. This downregulation may represent another significant factor contributing to the decreased levels of pyruvate.
Figure 5. Hypothesized mechanisms of different body conditions of perinatal cows on liver metabolism of offspring calves. Genes rather than metabolites are shown in italics, green and blue for declines in the OHBCS group, and red and orange-yellow for increases.
Through KEGG enrichment analysis of the transcriptome and metabolome, we identified significant differences in metabolic pathways related to lipid metabolism. However, there were no differences in the gene expression of CD36, FABP3, LPL and SLC27A1, which are involved in fatty acid transport. Notably, ACSL1 and CPT2 were significantly upregulated in OHBCS (p < 0.0001). ACSL1 encodes enzymes from the long-chain acyl-CoA synthetase family that catalyze the initial step of intracellular fatty acid activation, while CPT2 plays a crucial role in the fatty acid oxidation pathway, indicating a reduced capacity for fatty acid β-oxidation. Furthermore, DGAT1, which is involved in triglyceride structural formation by catalyzing the acylation of glycerol with fatty acids (Ali et al. Reference Ali, Li and Li2021), was significantly upregulated in OHBCS compared to OLBCS (p < 0.0001). This suggests that the triglyceride synthesis pathway is upregulated in the OHBCS group compared to the OLBCS group, potentially leading to increased lipid accumulation in the liver of OHBCS. Evidence indicates that lipid accumulation is associated with TCA cycle capacity (Koves et al. Reference Koves, Ussher and Nolan2008). Additionally, DPP4 was significantly downregulated in OHBCS (p < 0.001). DPP4 plays a crucial role in liver GLU metabolism and homeostasis, affecting INS sensitivity and hepatic fat deposition (Aroor et al. Reference Aroor, Habibi and Ford2015; Baumeier et al., Reference Baumeier, Saussenthaler, Baumeier, Schlüter, Saussenthaler, Laeger, Rödiger, Alaze, Fritsche, Häring, Stefan, Fritsche and Schwenk2017; Miyazaki et al. Reference Miyazaki, Kato and Tanak2012). In calves subjected to peripartum nutritional restriction, the expression of DPP4 is also limited (Muroya et al. Reference Muroya, Zhang and Otomaru2022). The expression of angiopoietin-like protein 8 (ANGPTL8) is closely related to GLU and lipid metabolism (Ye. et al. Reference Ye., Zong and Zou2023). Although the role of ANGPTL8 in GLU and lipid metabolism remains controversial, its upregulation in the liver may be associated with disorders of GLU and lipid metabolism (Fenzl et al. Reference Fenzl, Itariu and Kosi2014; Hu et al. Reference Hu, Sun and Yu2014; Zhang et al. Reference Zhang, Wu and Dai2020). In our study, ANGPTL8 expression was significantly elevated in offspring of cows with high BCSs OHBCS (p < 0.001), indicating a heightened risk of hepatic GLU and lipid metabolism disorders in these calves during the peripartum period. However, further long-term follow-up studies are warranted. Additionally, ACACA, the rate-limiting enzyme in de novo fatty acid synthesis, converts acetyl-CoA to fatty acids and plays a crucial role in this process (Wang et al. Reference Wang, Hu and Diao2022). In OHBCS, ACACA expression was significantly decreased (p < 0.001), suggesting a diminished hepatic capacity for fatty acid synthesis, which is accompanied by reduced acetyl-CoA flux into the fatty acid synthesis pathway. This reduction implies that acetyl-CoA is more involved in the ketogenic pathway, as illustrated in Fig. 5. A study examining the hepatic metabolic mechanisms in dairy cows during the perinatal period also found that acetyl-CoA generated from fatty acid β-oxidation is utilized in ketogenesis (Ghaffari et al. Reference Ghaffari, Alaedin and Sadri2021). This finding explains why blood BHB levels were significantly higher in the OHBCS group compared to the OLBCS group.
The metabolism of amino acids in offspring is influenced by maternal nutritional status during pregnancy (Gruppuso. et al. Reference Gruppuso., Boylan and Anand2005). Research on epigenetic modifications has demonstrated that maternal nutrition during pregnancy affects the promoter methylation levels of enzymes involved in the urea cycle and tyrosine aminotransferase in the liver of offspring (Muroya et al., Reference S., Otomaru and Oshima2023). In this study, KEGG enrichment analysis of differential metabolites revealed significant differences in multiple amino acid metabolism pathways between OHBCS and OLBCS (Figures 3-4). Metabolomic KEGG enrichment analysis indicated significant reductions in the glycine, cysteine and serine metabolic pathways in OHBCS (p < 0.05). These amino acids are all glycogenic; therefore, the reduction in their metabolic levels also diminishes the supply of raw materials for the GLU metabolic pathway to some extent, which correspondingly reduces the GLU metabolism level, including TCA, in the OHBCS group. In the phenylalanine, tyrosine and tryptophan synthesis pathways, phenylalanine and tyrosine levels were significantly higher in OHBCS than in OLBCS. Studies have indicated that tyrosine is elevated in the offspring of obese and type 2 diabetes patients compared to those of normal offspring (Villarreal-Pérez et al. Reference Villarreal-Pérez, Villarreal-Martínez and Lavalle-González2014). Phenylalanine and tyrosine function as both ketogenic and glucogenic amino acids, generating acetoacetic acid in the ketogenic pathway and fumarate in the glucogenic pathway. Although acetoacetic acid and fumarate were not directly detected in the metabolomic data, we speculate that the reduced requirement for fumarate in the TCA cycle in OHBCS, combined with the significant elevation of β-hydroxybutyrate in the blood, suggests that phenylalanine, tyrosine and tryptophan primarily contribute to the ketogenic pathway. Furthermore, amino acid metabolism generates substantial amounts of ammonia, which is converted to urea and excreted via the ornithine cycle. The ornithine cycle is an energy-consuming process; consequently, the levels of the TCA cycle and the capacity for fatty acid β-oxidation in the OHBCS group are lower than those in the OLBCS group. This reduction results in the liver lacking sufficient energy for the urea cycle. Additionally, the decreased levels of carbamoyl phosphate synthetase-1 (CSP-1) (p < 0.001) in the arginine cycle pathway indicate a diminished urea cycle pathway in the OHBCS group. Furthermore, the BUN content in the OHBCS group was lower than that in the OLBCS group. Based on this evidence, we speculate that the OHBCS group experiences a greater cumulative ammonia pressure.
Conclusion
This study selected two groups of cows that exhibited a significant difference in BCS during the pre-perinatal period, aiming to examine the impact of BCS on the metabolic mechanisms of offspring calves. It was observed that liver glycolysis and TCA cycle levels, along with fatty acid β-oxidation and arginine cycle were inhibited, while triglyceride synthesis and the ketogenic pathway were increased. Consequently, the concentrations of NEFA and BHB in systemic circulation were significantly elevated, suggesting that the liver’s energy supply in the OHBCS group was lower than that in the OLBCS group. Additionally, the OHBCS group required more ketone bodies to meet energy demands, which may lead to adverse effects associated with elevated ketone bodies and liver triglyceride deposition; these negative effects warrant long-term investigation. Furthermore, we found that the antioxidant stress capacity of offspring calves with high body condition during the perinatal period was superior to that of calves with a low body condition. The next phase of this study will focus on the metabolism of muscle and adipose tissue in calves.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/anr.2025.2.
Acknowledgements
The authors would like to express their gratitude to the staff of Shandong Gaosu Bioengineering Co., Ltd. (Jinan, China) for their assistance with animal husbandry and sampling.
Author contributions
ZH and YW designed the study; YZ, YW and YG conducted the trial; YG analyzed the blood sample data, YW analyzed the liver sample data, YW completed the writing of the paper, ZH provided the project funding and revised the manuscript, and all authors read and approved the final manuscript.
Funding statement
This research was supported by grants from the National Natural Science Foundation of China (Grant Number: 32172760) and was also funded by the Modern Agro-industry Technology Research System of China (Grant Number: CARS-36).
Conflict(s) of interest
The authors declare no competing interests.
Ethical Standards
All tests involving animals are conducted in accordance with the principles of the Animal Protection and Utilization Committee of Shandong Agricultural University (Shandong, China).
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