Inflammatory biomarkers are associated with ketosis ...

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Nov 12, 2014 - William E. Trout c, Lance H. Baumgard a,⁎ a Department of ..... Mullins, C.R., Mamedova, L.K., Brouk, M.J., Moore, C.E., Green, H.B., Perfield, K.L., Smith, J.F.,. Harner ... Rajala-Schultz, P.J., Grohn, Y.T., McCulloch, C.E., 1999.

Research in Veterinary Science 109 (2016) 81–85

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Inflammatory biomarkers are associated with ketosis in periparturient Holstein cows Mohannad Abuajamieh a, Sara K. Kvidera a, Maria V. Sanz Fernandez a, Amir Nayeri a, Nathan C. Upah a, Erin A. Nolan a, Sam M. Lei a, Jeffery M. DeFrain b, Howard B. Green c, Katie M. Schoenberg c, William E. Trout c, Lance H. Baumgard a,⁎ a b c

Department of Animal Science, Iowa State University, Ames 50011, USA Zinpro Corporation, Eden Prairie, MN, 55344, USA Elanco Animal Health, Greenfield, IN, 46140, USA

a r t i c l e

i n f o

Article history: Received 19 May 2016 Received in revised form 2 August 2016 Accepted 20 September 2016 Available online xxxx Keywords: Ketosis Inflammation Lipopolysaccharide Leaky gut

a b s t r a c t Ketosis is a prevalent periparturient metabolic disorder and we hypothesize that lipopolysaccharide (LPS) infiltration may play a key role in its etiology. Study objectives were to characterize biomarkers of inflammation during the transition period in healthy and clinically diagnosed ketotic cows. Cows were retrospectively categorized into one of two groups: healthy and clinically diagnosed ketotic. Two data sets were utilized; the first dataset (Study A) was obtained as a subset of cows (n = 16) enrolled in a larger experiment conducted at the Iowa State University Dairy utilizing Holstein cows (8 healthy; 8 ketotic), and the second dataset (Study B; 22 healthy; 22 ketotic) was obtained from a commercial farm. For both experiments, blood samples were collected prior to and following calving. Ketotic cows in both studies had reduced milk production compared to healthy cows (P b 0.01). Post-calving, ketotic cows had increased serum amyloid A (4.2 and 1.8 fold in studies A and B, respectively; P = 0.03 and P = 0.04), haptoglobin (N 6 fold and ~4 fold; P = 0.04 and P = 0.03), and lipopolysaccharide binding protein (66 and 45%; P b 0.01 and P = 0.02) compared with their healthy counterparts. Antepartum circulating LPS in ketotic cows was increased (2.3 fold; P = 0.01) compared to healthy cows in Study B. In summary, increased biomarkers of inflammation appear to be closely associated with ketosis in transition dairy cows. © 2016 Elsevier Ltd. All rights reserved.

1. Introduction The periparturient period is associated with substantial metabolic changes involving normal homeorhetic adaptations to support milk production. Alarmingly, a disproportionate amount of culling occurs in early lactation (NAHMS, 2008) and this is partially because some cows do not transition well into galactopoiesis. Metabolic maladaptation to lactation and subsequent ketosis is a significant issue that affects about 20% of dairy cows in its clinical version (Gillund et al., 2001), and over 40% of the cows as a subclinical disease (McArt et al., 2012). Apart from its obvious detrimental consequences on animal welfare, ketosis is a costly disorder limiting farm profitability (McArt et al., 2013). Ketosis is traditionally thought to result from excessive adipose tissue mobilization (Drackley, 1999; Grummer, 1993; Littledike et al., 1981). The liver takes up non-esterified fatty acids (NEFA) in proportion to blood concentrations (Herdt, 1988) however, ruminants' capacity to export hepatic lipids is limited (Kleppe et al., 1988; Drackley, 1999), which leads to excessive lipid accumulation and the subsequent development of fatty liver (hepatic steatosis; Grummer, 1993; Drackley, ⁎ Corresponding author at: 313 Kildee Hall, Ames, USA. E-mail address: [email protected] (L.H. Baumgard).

http://dx.doi.org/10.1016/j.rvsc.2016.09.015 0034-5288/© 2016 Elsevier Ltd. All rights reserved.

1999). Further, because of the increased demand for gluconeogenesis associated with copious milk synthesis, there is insufficient oxaloacetate for citrate synthase to combine with acetyl-CoA (produced via NEFA βoxidation); excessive acetyl-CoA is then partitioned towards ketone synthesis (Berg et al., 2012). Circulating β-hydroxybutyrate (BHBA) concentrations are used to arbitrarily classify the severity of ketosis (McArt et al., 2012); however, increased plasma BHBA is only mildly associated with decreased milk yield, displaced abomasum, suboptimal reproduction, metritis, and mastitis (LeBlanc et al., 2005; Lucey et al., 1986; Rajala-Schultz et al., 1999; Seifi et al., 2007). Further, most cows have markedly increased plasma NEFA immediately post-calving, and recent evidence suggests that there is a poor relationship between circulating NEFA and BHBA (McCarthy et al., 2015), indicating that ketosis is not simply the result of excessive adipose mobilization. Consequently, the pathophysiology of ketosis remains unclear, and it is of particular interest to determine why some cows are ostensibly susceptible or predisposed to this metabolic disorder. Lipopolysaccharide (LPS), a cell wall component of Gram-negative bacteria, elicits an immune response when it breaches an epithelial barrier (Berczi et al., 1966). Acute phase proteins such as haptoglobin (Hp), serum amyloid A (SAA), and LPS binding protein (LBP), markers of bovine systemic inflammation (Ceciliani et al., 2012), are up-regulated

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during i.v or diet-induced endotoxemia in ruminants (Khafipour et al., 2009a; Plessers et al., 2015). Increased inflammatory markers following parturition have been reported in cows (Bertoni et al., 2008; Humblet et al., 2006; Mullins et al., 2012), but despite increased tissue expression of inflammatory signaling components the etiological origin of infection or inflammatory mediator(s) remains unknown (Vailati Riboni et al., 2015). Presumably, the inflammatory state following calving disrupts normal nutrient partitioning and is detrimental to productivity (Bertoni et al., 2008; Loor et al., 2005). Endotoxin-induced inflammation compromises productivity by redirecting nutrients away from anabolic processes that support milk and muscle synthesis (see review by Johnson, 1997) in order to supply the immune system with energy and biosynthetic intermediates. Inflammation's role in periparturient nutrient partitioning is not clear (Bertoni et al., 2004; Farney et al., 2013; Shwartz et al., 2009), and some suggest the source and extent of inflammation may determine whether it is beneficial or detrimental (Bradford et al., 2015). A possible reason for a portion of the aforementioned ambiguity could be the experimental comparison of cows undergoing a myriad of transition health disorders rather than direct comparisons between healthy and solely clinically ketotic cows. Therefore, experimental objectives were to retrospectively characterize biomarkers of inflammation during the transition period in healthy and clinically diagnosed ketotic cows. 2. Materials and Methods 2.1. Animals and Diets All live-phase aspects of the experiment were approved by the Iowa State University Institutional Animal Care and Use Committee. As an observational study, multiparous lactating Holstein cows from two different datasets were retrospectively categorized to 1 of 2 groups consisting of: 1) healthy cows not diagnosed for any illnesses or 2) clinically diagnosed ketotic cows with no other overt health disorder. The first dataset (Study A) consisted of a subset of cows (n = 16) milked 2 ×/d from a larger experiment (n = 184 cows) conducted at the Iowa State University Dairy as described by Nayeri et al. (2014). The procedures used to measure production and energetic variables presented herein were previously described (Nayeri et al., 2014). Ketotic transition cows (n = 8; parity = 2.4 ± 0.5; BCS = 3.1 ± 0.1; 305 ME = 14,164 ± 485 kg) were diagnosed by an Iowa State University faculty-veterinarian using a blood-based test (Precision Xtra® meter, Chicago, IL); cows N1.2 mmol/l BHBA were orally treated with 300 ml of propylene glycol until resolution of elevated BHBA (≤ 3 d). Healthy transition cows (n = 8; parity = 1.9 ± 0.8; BCS = 3.3 ± 0.1; 305 ME = 12,389 ± 800 kg) were devoid of a diagnosed health problem during the transition period. Cows in Study A calved between September 22nd, 2010 and February 21st, 2011 and had production variables collected from −21 to +14 days in milk (DIM). The second dataset (Study B) consisted of samples obtained from multiparous cows (n = 164) milked 3 ×/d housed on a commercial farm (N3000 lactating cows); 22 cows (parity = 3.5 ± 0.9) were diagnosed for ketosis using a urine-based test (Ketostix®, Bayer Health Care LLC, Mishawaka, IN) starting on the 5th DIM; cows N 15 mg/dl urine acetoacetate were treated with propylene glycol (300 ml for 3 d), and those cows were paired with 22 healthy cows (parity = 3.5 ± 1.0) that were devoid of overt health problems. Cows in Study B calved between October 7th and November 12th, 2014 and production data was collected until 14 DIM. For both studies, each ketotic cow in the data set was “paired” with a healthy cow calving at approximately the same time in order to account for other environmental effects (e.g. differences in feeds and ambient temperature). Each pair of cows in Study A calved 16.7 ± 4.2 d apart whereas each pair of cows in Study B calved 5.4 ± 1.0 d apart. In both studies a total mixed ration (TMR) consisting primarily of corn silage and a grain mix was provided ad libitum to meet or exceed

the predicted requirements (NRC, 2001) of energy, protein, minerals and vitamins. Feed intake in Study A was monitored daily, but dry matter intake (DMI) was not measured in Study B due to the logistical constraints of a commercial farm. 2.2. Sample Collection In Study A, milk samples from each cow for composition analyses were obtained weekly from the a.m. milking. The samples were stored at 4 °C with a preservative (bronopol tablet; D and F Control System, San Ramon, CA) until analysis by Dairy Lab Services (Dubuque, IA) using AOAC approved infrared analysis equipment and procedures for milk components. For both experiments, blood samples were collected via coccygeal venipuncture into evacuated sodium heparin vacutainers (BD Vacutainer, Franklin Lakes, NJ) from the tail vein on d −7 ± 3, 3, 7, 10, and 14 ± 1 relative to calving. Additional blood samples were obtained at d − 21 ± 3 and 21 ± 1 relative to calving for LBP analysis in Study A. Blood samples were centrifuged at 1500 × g for 15 min at 4 °C. Plasma was aliquoted and subsequently frozen at − 20 °C until analysis. 2.3. Sample Analyses In both studies, plasma NEFA, glucose, BHBA, LBP, SAA, Hp, and plasma urea nitrogen (PUN) concentrations were determined using commercially available kits according to manufacturers' instructions (NEFA, Wako Chemicals USA, Richmond, VA; glucose, Wako Chemicals USA Inc., Richmond, VA; β-hydroxybutyrate, Pointe Scientific Inc., Canton, MI; LBP, Hycult Biotech, Uden, Netherlands; SAA, Tridelta Development Ltd., Kildare, Ireland; Hp, Immunology Consultants Laboratory Inc., Portland, OR; PUN, Teco Diagnostics Anaheim, CA). Lipopolysaccharide was measured in triplicate only in Study B using sterile procedures and a PyroGene® endotoxin detection assay (Lonza, Walkersville, MD). In Study A, LPS was not measured because blood samples were not obtained using pyrogen free techniques. 2.4. Statistical Analyses Studies were statistically analyzed separately. A repeated measures analysis with an autoregressive covariance structure and DIM as the repeated effect was used to determine effects of pair, group, DIM, and group by DIM interaction using PROC MIXED (SAS 9.4 Inst. Inc., Cary, NC). Ad-hoc statistical analysis was separately conducted on the precalving and the post-calving data sets, but data presented herein are from the post-calving period, unless otherwise noted. For each variable, the residuals' distribution was tested for normality and logarithmic transformation was performed when necessary. Results are reported as least squares means and means considered different when P ≤ 0.05 and tendency to differ if P b 0.10. 3. Results and Discussion 3.1. Production Parameters Milk yield was decreased in ketotic relative to healthy cows in Study A (28.3 vs. 38.6 kg/d; P b 0.01; Table 1) and Study B (32.8 vs.36.0 kg/d; P b 0.01; data not shown) and post-calving DMI was decreased (26%) for the ketotic cows in Study A (P = 0.01; Table 1). Milk total solids and fat content were increased (15 and 21%; P = 0.03 and P = 0.04 respectively; Study A; Table 1) for ketotic cows, likely due to the dilution effect of reduced milk yield. There were no group differences in fat corrected milk, protein content, lactose percentage, somatic cell count, and other milk solids (Table 1). Calculated energy balance was similar in both groups (P = 0.84).

M. Abuajamieh et al. / Research in Veterinary Science 109 (2016) 81–85 Table 1 Effect of health status on production variables in transition dairy cows in Study A.a Gb

Parameter

Pre-calving DMId, kg Post-calving DMIe, kg EBALf, Mcal/d Milk yield, kg/d Milk composition Fat % kg/d Protein % kg/d Lactose % kg/d SCC, 1000/ml Other solids, % Total solids, % 3.5% FCM, kg/d

SEM

P-value G

DIMc

GxDIM

0.4 0.8 3.0 1.4

0.54 0.01 0.84 b0.01

0.06 b0.01 0.97 b0.01

0.43 0.93 0.64 0.16

6.2 1.8

0.3 0.2

0.04 0.50

0.02 0.05

0.95 0.78

3.3 1.3

3.3 1.0

0.1 0.1

0.75 0.03

b0.01 b0.01

0.45 0.92

4.7 1.9 84 5.6 13.0 51.4

4.7 1.4 86 5.6 15.0 43.8

0.1 0.1 17 0.1 0.3 3.1

0.96 b0.01 0.77 0.93 0.03 0.12

b0.01 b0.01 0.02 b0.01 0.02 0.01

0.17 0.07 0.94 0.17 0.42 0.89

Healthy

Ketotic

9.8 13.3 −16.4 38.6

9.5 9.8 −17.3 28.3

5.1 1.9

a Data collection, calculations and analysis have been previously described (Nayeri et al., 2014). b Group. c DIM = Days in milk. d Dry matter intake during 21 d before calving in Study A. e Dry matter intake and other production data collected for 14 d after calving. f Energy balance = NEintake − NEoutput.

3.2. Blood Metabolites Circulating glucose did not differ between ketotic and healthy cows (P N 0.10; Table 2) but exhibited the typical pattern of post-partum hypoglycemia observed during the transition period. The lack of glucose differences between health statuses agrees with others (Asl et al., 2011; Gröhn et al., 1983) and illustrates how tightly glucose concentrations are homeostatically controlled. In Study A, despite following the expected temporal patterns associated with parturition (Drackley, 1999), there were no overall differences in either pre or post-calving BHBA and NEFA between health status groups. In contrast, although there were no pre-calving differences (data not shown), ketotic cows in Study B had increased post-calving circulating NEFA (~ 50%; P b 0.01; Table 2) and BHBA (16%; P = 0.01; Table 2) compared with healthy cows. Interpreting blood energetic metabolites in both experiments is complicated by the fact ketotic cows were diagnosed and treated with propylene glycol between 7 and 10 DIM of Study A and between 5 and 10 DIM of Study B, and this has obvious implications to bioenergetic variables in samples obtained following treatment. Specifically,

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propylene glycol treatment would immediately decrease circulating NEFA and BHBA concentrations. This explains why cows clinically diagnosed with ketosis using the urine based test (Study B) had an overall (1–14 DIM) concentration of BHBA in plasma considerably less than even the arbitrary definition of subclinical ketosis since some of the blood samples (7, 10 and 14 DIM) were obtained after treatment. 3.3. Blood Inflammatory Markers In Study B, circulating LPS concentrations were increased twofold in ketotic cows pre-calving (−7 DIM) in comparison with healthy cows (P = 0.01; Fig. 1A), but no LPS differences were detected post-partum. There was no pre-partum difference in LBP in either study, but LBP was increased (66 and 45%; P b 0.01 and P = 0.02; Study A and B respectively; Fig. 1B and C) in ketotic compared to healthy cows. In fact, ketotic cows in Study A had a twofold increase (P = 0.05) in LBP at 3 DIM compared to healthy cows (4 d prior to ketosis diagnosis). There were differences in LBP concentrations (and in SAA and Hp regardless of health status) between studies (Fig. 1), and it is not clear whether this is biologically relevant or the result of sample handling or assay drift. However, similar intra-laboratory differences have been reported by others (Khafipour et al., 2009a, 2009b). Regardless of absolute content, the magnitude and temporal pattern of the differences in LBP between ketotic and healthy cows was consistent in both studies. It is unclear why there are temporal dissimilarities in health status effects between LPS and LBP (i.e. differences in LPS pre-partum and LBP post-partum), but the difference in pre-partum LPS likely explains the post-calving difference in LBP as LPS exposure up-regulates the expression and secretion of LBP (Fang et al., 2003; Mani et al., 2012). Serum amyloid A was increased 4.2 and 1.8 fold for ketotic cows when compared with their healthy counterparts (P = 0.03 and P = 0.04; Table 2), in Study A and B, respectively. In addition, Hp similarly increased for the ketotic cows compared with their healthy counterparts (N6 and ~4 fold; P = 0.04 and P = 0.03; Study A and B respectively; Table 2). Both SAA and Hp are acute phase proteins up-regulated during immune system activation (Ceciliani et al., 2012) and the temporal increase (data not shown) in both SAA and Hp in ketotic cows is similar to the postpartum temporal differences in LBP between healthy and ketotic cows. 3.4. Proposed Mechanistic Relationship Between Inflammation and Ketosis Ketotic cows had increased circulating markers of inflammation both pre-calving (LPS) and post-calving (SAA, LBP, Hp) and these data suggest the development of ketosis may be intimately tied to inflammation. Admittedly, we cannot pinpoint the origin of the LPS and like

Table 2 Effect of health status on bioenergetics and inflammatory variables in transition dairy cows. Study Aa

Parameter G

Glucose, mg/dl NEFAe, μEq/l BHBA, mmol/l PUN, mg/dl SAAf, μg/ml Hpg, μg/ml a b c d e f g h

c

Study Bb

SEM

Healthy

Ketotic

65 741 0.86 12.1 17.2 139

65 694 1.20 10.6 72.7 841

3 90 0.21 1.0 15.8 230

P-value

G

SEM

G

DIMd

GxDIM

Healthy

Ketotic

0.90 0.77 0.16 0.29 0.03 0.04

b0.01 0.01 0.18 0.83 0.09 0.02

0.26 0.48 0.16 0.93 0.51 0.05

58 592 0.50 9.3 58.1h 47h

56 882 0.58 9.2 101.5h 176h

Study conducted at Iowa State University Dairy Farm (−21 to 14 DIM; n = 16; 8 healthy and 8 ketotic). Study conducted at commercial dairy farm (−21 to 14 DIM; n = 44; 22 healthy and 22 ketotic). Group. Days in milk. NEFA. Serum amyloid A. Haptoglobin. Data were back transformed after making the log-transformation.

1 48 0.02 0.3 15.3h 48h

P-value G

DIM

0.33 b0.01 0.01 0.83 0.04 0.03

0.07 b0.01 0.01 0.03 b0.01 b0.01

GxDIM 0.41 0.41 0.40 0.31 0.38 0.28

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4000

A

LPS (EU/ml)

* 3000 2000 1000 0

-7

3

7

10

14

Days relative to calving

LBP (ng/ml)

50000

B *

40000

**

30000

4. Conclusions

20000 10000 0

-21

3

10

21

Days relative to calving

LBP (ng/ml)

8000

C

**

*

systemic inflammation, and increases circulating acute phase proteins. Therefore, we believe compromised intestinal integrity in the transition cow may be caused by either rapid changes in diet (i.e. increased fermentable carbohydrates following calving), suboptimal feed intake (Stoakes et al., 2015) or inflammatory cytokines derived from distally damaged tissue (i.e. the uterus), which have been shown to increase intestinal permeability in laboratory models (Paibomesai et al., 2013). Additionally, we and others have previously demonstrated that leaky gut causes inflammation and an acute phase response in monogastric models (Lambert et al., 2002; Pearce et al., 2013; Sanz-Fernandez et al., 2014). Thus our experimental design and selection criteria enables us to suggest intestinal permeability may play a pivotal role in the development of ketosis. However, further experimentation is needed to clarify the relationship between leaky gut and metabolic maladaptation to lactation.

Ketotic cows had increased circulating markers of inflammation pre and post-calving and, importantly, prior to the clinical signs of ketosis. We are unable to definitively identify the origin of inflammation, but our selection criteria rules out the obvious sources of mastitis and metritis. We believe increased intestinal permeability may play a role in the development of ketosis. Conflict of Interest

*

6000

*

4000

None. Acknowledgements

2000 0

-7

3

7

10

14

Days relative to calving

Healthy

Ketotic

Fig. 1. Effects of health status (healthy vs. ketotic) on (A) circulating lipopolysaccharide (LPS) in Study B, (B) LPS binding protein (LBP) in Study A, and (C) LBP in Study B. Ketosis was diagnosed between 5 and 10 DIM. Healthy cows were not diagnosed with a health disorder. The data are shown as least squares mean ± SEM. *Represents differences (P b 0.05) and ** represents difference tendencies (0.05 b P ≤ 0.10).

others who have observed increased expression of inflammatory networks in the liver, adipose, and mammary tissue following calving, a source of overt infection or inflammatory mediator(s) is unclear (Vailati Riboni et al., 2015). However, our selection criteria (lack of clinical signs of metritis or mastitis) suggest that neither the uterus nor mammary gland was the etiological origin of inflammation. We have recently demonstrated that moderate feed restriction increases intestinal permeability in both pigs (Pearce et al., 2013) and ruminants (Stoakes et al., 2015), and dairy cows experience a well-described decrease in feed intake prior to calving (Drackley, 1999). Thus, we believe compromised intestinal integrity (so called “leaky gut”) is a likely source of LPS infiltration and cause of systemic inflammation. Rationale for our hypothesis originates from data derived from a variety of experimental models indicating that LPS and associated inflammation contributes to fatty liver via interfering with normal hepatic lipid metabolism (Ametaj et al., 2005; Bradford et al., 2009; Ilan, 2012). It is noteworthy in intestinal disease models (i.e. Crohn's) that LPS-induced fatty liver occurs without the coinciding increased circulating NEFA. If intestinal LPS infiltration is increased at or around parturition, it may affect liver lipid metabolism and consequently create a situation where the cow is more prone to develop ketosis. Khafipour et al. (2009a) demonstrated that grain-induced rumen acidosis causes

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