Metabolic changes in transition cows – opportunities for management
Thomas R. OvertonAssociate Professor of Animal Science
Director, PRO-DAIRYCornell University
The outcome challenge
• High milk production• Maintain/minimize loss of BCS• Low incidence of metabolic disorders• Minimize loss of immunocompetence• Control/decrease days to first ovulation
and maintain/enhance fertility• Make $$
Risk factors for resumption of estrous cycles by 65 days postpartum and pregnancy at 1st AI in lactating dairy cows
Variable Cyclic, % (n/n) Adjusted OR (95% CI) P value
BCS change from calving to 65 DIMLost 1 unit or more 58.7 (279/475) Referent -------Lost < 1 unit 74.6 (2,507/3,361) 1.96 (1.52, 2.52) < 0.001No change 80.9 (2,071/2,560) 2.39 (1.74, 3.28) < 0.001
Milk yield in the first 90 DIMQ1, 32.1 kg/d 72.7 (1,011/1,390) Referent ------Q2, 39.1 kg/d 77.6 (1,204/1,552) 1.34 (1.13, 1.60) < 0.01Q3, 43.6 kg/d 77.6 (1,350/1,739) 1.36 (1.15, 1.62) < 0.001Q4, 50.0 kg/d 75.3 (1,292/1,715) 1.21 (1.02, 1.43) 0.04
Variable Pregnant, % (n/n) Adjusted OR (95% CI) P value
BCS change from calving to 65 DIMLost 1 unit or more 28.9 (132/472) Referent ------Lost < 1 unit 37.3 (1204/3230) 1.42 (1.13, 1.79) < 0.01No change 41.6 (1008/2422) 1.69 (1.32, 2.17) < 0.001
Milk yield in the first 90 DIM
Q1, 32.1 kg/d 37.2 (496/1,334) Referent ------Q2, 39.1 kg/d 38.9 (576/1,481) 1.06 (0.91, 1.24) 0.42Q3, 43.6 kg/d 39.3 (652/1,661) 1.09 (0.93, 1.26) 0.26Q4, 50.0 kg/d 37.6 (620/1,648) 1.03 (0.88, 1.21) 0.65
Santos et al. (2009) Anim. Reprod. Sci. 110: 207–221
r2 = 0.57
Santos et al. (2010) Reprod. Dom. Rum. VII:387-404
r2 = 0.07
Energy intake and energy balance
Milk energy and energy balance
The metabolism challenge required to meet the outcome challenge
• Abrupt changes in demands for energy (and other nutrients)
• High gluconeogenic rates during postcalving period
• Minimize negative diet and management interactions with metabolism (esp. adipose)
• Maintain sufficient DMI during precalving period and facilitate acceleration during postcalving period
• Manage interactions of facility/nonnutritional management factors with metabolism?
Metabolic Adaptation (Schoenberg, 2010)
Impaired glucose disposal
Glucose sparing for gravid uterus and eventually the
mammary gland
Increased hepatic gluconeogenesis
Decreased uptake
of glucose by
peripheral tissues
Decreased insulin response of
adipose tissue
Increased mobilization of fatty acids
Changes in intake
Take homes • Coordination of metabolism to support late pregnancy and early
lactation is extensive and exquisite
• “Insulin resistance” to spare glucose for fetus and mammary gland is important for successful adaptation to lactation
• Some degree of fat mobilization (and elevated NEFA) is “normal”
• Excessive mobilization of fat (elevated NEFA) is associated with metabolic disorders, lower milk production, and poorer reproductive performance
• “Excessive” insulin resistance in body fat likely contributes to hypermobilization of NEFA and lower DMI (cows resemble Type II diabetics)– Fat cows– Cows overfed energy during either far-off or close-up period– Impact of environmental stressors?
DMI and NEFA
7
9
11
13
15
17
19
21
23
-21 -18 -15 -12 -9 -6 -3 0 3 6 9 12 15 18 21
Day relative to calving
DM
I (kg
/d)
50
150
250
350
450
550
650
NEF
A, m
Eq/L
DMINEFA
Adapted from Smith, 2004
Summary of metabolic regulation work focused on insulin resistance
• Glucose disposal slower and slope of NEFA decrease less following glucose challenge in prepartum cows compared to early lactation– Smith et al., 2004. J. Dairy Sci. 87(Suppl. 1):442.
• Strengthening adipose tissue responses to insulin using targeted approaches in prepartum cows– Decreased NEFA spike during immediate periparturient period
• Smith et al., 2007. J. Dairy Sci. 90:3660-3670; • Smith et al., 2009. J. Dairy Sci. 92: 3623-3633
– Increased DMI during immediate periparturient period• Smith et al., 2007. J. Dairy Sci. 90:3660-3670; • Smith et al., 2009. J. Dairy Sci. 92: 3623-3633
– Decreased BCS loss during early lactation and days to first ovulation
• Smith et al., 2009. J. Dairy Sci. 92: 3623-3633
Excessive prepartum energy intake and insulin resistance
• Mashek and Grummer (2003)– Large decreases in prepartum DMI → higher NEFA, liver TG postpartum
• Holtenius et al. (2003); Agenas et al. (2003)– Prepartum overfeeding (178%) → higher glucose and insulin prepartum,
higher insulin response to glucose challenge, higher postpartum NEFA, lower DMI postpartum
• Dann et al. (2006)– Far-off overfeeding (150%) → higher postpartum NEFA and BHBA,
lower postpartum DMI
• Douglas et al. (2006)– Lower glucose and insulin prepartum, lower NEFA and higher DMI
postpartum in cows fed 80% vs. 160% prepartum
• Schoenberg et al. (2010)– Decreased NEFA clearance following glucose challenge in cows overfed during
the dry period
Dry period energy formulation from herd to herd is a bit like walking a balance beam
• If cows consume insufficient energy, more metabolic problems postcalving
• If cows consume excessive energy, more metabolic problems postcalving
• MAJOR influence of nonnutritional factors on AMOUNT and UNIFORMITY of energy intake during both the far-off and close-up periods– Dictates different approaches on different farms to
achieve same goal
U.S. trends in last 5 to 7 years
• Largely abandoned “steam up” concept advocated by 2001 Dairy NRC
• Controlled energy strategies for dry cows during both far-off and close-up periods (Drackley, 2007)– 0.59 to 0.62 Mcal/lb of NEL– 12 to 16% starch– 40 to 50% forage NDF
• Appropriate for multiparous cows• Too low energy/too bulky for primiparous cows?• MP supply?? (RUP supplementation even more important)
Effects of far-off diet (Dann et al., 2006)
• Fed far off cows to achieve– Control (100% of predicted NRC energy requirement – actual 95%)– High energy density diet
• 80% of energy requirements• 150% (actual 160%) of energy requirements
• Close-up diet to achieve– 135% vs 80% of energy requirements
• Cows overfed far-off had– Lower subsequent DMI and calculated energy balance– Higher NEFA and BHB during first 10 d postpartum
• Close-up strategy did not affect periparturient metabolism or performance
Richards et al. (2009)
• Controlled energy (~ 0.60 Mcal/lb) during entire dry period• High energy (~0.73 Mcal/lb) during entire dry period• Controlled energy far off followed by high energy close up
• High energy for entire dry period– Gained more BCS during dry period– Lost more BCS during postpartum period
• Controlled energy for entire dry period– Lower postpartum NEFA, BHB, and liver fat compared to high
energy• Metabolic health for cows fed two-group more similar to
controlled energy than high energy
Common observations with prepartum overfeeding/excessive insulin resistance
• Large decreases in DMI as cows approach calving
• Low/sluggish increases in DMI in fresh cows
• Rapid BCS loss during postpartum period
• Higher incidence of subclinical and clinical ketosis and DA
• Sometimes lower colostrum yield
Can you go too low?• Janovick and Drackley (2010)
– Cows fed low energy dry cow diets (1.21 vs. 1.63 Mcal NEL/kg) had higher postpartum DMI, lower NEFA, better energy balance, but also yielded less milk (33.3 vs 38.9 kg/d for wk 1-8)
• Silva del Rio et al. (2010)– Cows fed higher energy diet for entire dry period (1.54 Mcal/kg
for 8 wk vs. 1.32 Mcal/kg for far-off and then 1.54 Mcal/kg diet for last 3 wk) had lower energy balance because of increased milk yield and higher postpartum NEFA
Overall goals for energy intake of both far-off and close-up cows
• Far off cows (dry off until ~ 3 weeks precalving)– ~ 15 - 17 Mcal of NEL per day– 110 to 120% of ME requirements (CNCPS 6.1)
• Close-up cows (last 3 weeks before calving)– ~16 - 18 Mcal of NEL per day– 110 to 120% of ME requirements (CNCPS 6.1)
• Vary energy density of diets based upon group DMI– Which means have to know DMI to know how much to “bulk up” the
diet– Almost want to achieve the above in the largest DMI package that
cows will consume consistently
You HAVE to chop the %(*(#*@&# straw/hay
3.5 lbs straw in 26 lb DM package 6 lbs straw in 27 lb DM package
Potential management/facility related stressors for transition cows
• Overcrowding (increased stocking density)
• Commingling of cows and heifers
• Excessive number of pen moves (group changes)
• Heat stress
• Overall cow comfort/hygiene
Physiological measures of stress and inflammation?
Environmental stressors can also induce an acute phase response in cattle.
Plasma cortisol Non-invasive measures of stress?
• Fecal Cortisol Metabolites (Möstl and Palme)
Changes in the activity and functioning of the hypothalamic-pituitary-adrenal (HPA) axis are often used to quantify an animal’s response to a potential stressor.
Haptoglobin
Prepartum haptoglobin is not associated with postpartum disease
Prepartum Haptoglobin
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
wk-3 wk-2 wk-1Week from Calving
g/L
Healthy
One Event
> One Event or Death
No differences in prepartum Haptoglobin between health categories.
Haptoglobin is a non-specific marker of inflammation, infection or injury
(Huzzey et al., Submitted for review 2010)
Fecal cortisol during wk -2 and -1 were higher in cows that developed more than one health disorder
or died by 30 DIM
Prepartum Fecal Cortisol Metabolites
100
120
140
160
180
200
220
240
260
280
wk-3 wk-2 wk-1Week from Calving
ng/g
feca
l DM
HealthyOne Event> One Event or Death
(Huzzey et al., Submitted for review 2010)
-2500
-2000
-1500
-1000
-500
0
primiparousmultiparous
Haptoglobin
Cutpoint: >1.1 g/L
****
**
wk -3 wk -2 wk-1 wk+1
∆ 30
5ME
(kg
milk
)
††
% Cows Above Cutpoint: wk -3 wk -2 wk-1 wk+1
MultiparousPrimiparous 4.9 7.7 6.0 39.0
3.0 4.8 3.0 27.4
Haptoglobin and milk production (Huzzey et al., 2010)
Fecal cortisol and milk production (Huzzey et al., 2010)
-1500
-1000
-500
0
500
1000 primiparousmultiparous
Fecal Cortisol
Cutpoint: 250 ng/g fecal DM 70 ng/g fecal DM
**** **
wk -3 wk -2 wk-1 wk+1
% Cows Above Cutpoint: wk -3 wk -2 wk-1 wk+1
8.2 17.0 25.3 20.36.1 13.0 27.0 35.2Multiparous
Primiparous
∆ 30
5ME
(kg
milk
)
Overstocking affects behavior
Increased aggression Reduced feeding times Increased feeding rate Increased inactive standing time Reduced lying time
Little work has evaluated how these behavioral changes influence subsequent health
Overstocking and metabolism
Control: Full access to feed bunk (~2 ft/cow) and lying stalls (10stalls/10cow)
Overcrowded: 50% less feed bunk space (~1 ft/cow) and lying stalls (5 stalls /10 cows)
Treatments (6 cows and 4 springers per group)
Huzzey, Nydam, Grant, and Overton, 2010 Cornell Nutrition Conference
Competition for feed
Standard Overstocked
Huzzey, Nydam, Grant, and Overton, 2010 Cornell Nutrition Conference
There is a positive correlation between the time it takes to approach the bunk following FD and daily NEFA (r=0.30) and glucose (r=0.24) concentration (P≤0.02).
% o
f cow
s at
the
feed
bun
k
Hour of the Day
Pattern of feeding activity
In the overstocked group fewer cows were at the feed bunk following fresh feed delivery while more cows were at the bunk at night
0
10
20
30
40
Control
Feed Delivery
Huzzey, Nydam, Grant, and Overton, 2010 Cornell Nutrition Conference
Feeding time was not different between overstocked and control groups (242 vs. 241 min/cow/d)
Feeding rate was greater in overstocked cows
DMI & feeding time
Cows in the overstocked group had a greater DMI (33 vs 31 lb/d)
DM
I (kg
/cow
)
Treatment Day
1 2 3 4 5 6 7 8 9 10 11 12 13 1410
11
12
13
14
15
16
17
ControlOverstocked
daytrt
day*trt(d13,14 not included)
P = 0.99P < 0.001P = 0.51
Huzzey, Nydam, Grant, and Overton, 2010 Cornell Nutrition Conference
Daily metabolite concentrations
1 3 5 7 9 110
5
10
15
20
25
30
35
40
P = 0.18P = 0.21P = 0.88
daytrt
day*trt
0 1 2 3 4 5 6 7 8 9 10 110
20
40
60
80
100
120
140
ControlOverstocked
P = 0.28P = 0.001P = 0.82
daytrt
day*trt
0 1 2 3 4 5 6 7 8 9 10 1158
60
62
64
66
68
P = 0.69P = 0.05P = 0.70
daytrt
day*trt
0 1 2 3 4 5 6 7 8 9 10 110
5
10
15
20
25
P = 0.16P = 0.11P = 0.68
daytrt
day*trt
NEFA
Insulin
Glucose
Fecal Cortisol Met.trt day
uEQ
/L
mg/
dLuI
U/m
L
ng/g
feca
l DM
Huzzey, Nydam, Grant, and Overton, 2010 Cornell Nutrition Conference
Challenges with assessing energy metabolism and inflammation-related opportunities in transition cows
• Most of dairy industry works on averages
• Challenges related to energy/grouping mgt/nonnutritional factors cause increases in variation in DMI/performance– Almost impossible to detect some of these on farms
• Potential tools for use in monitoring variation in transition cow management– NEFA (best marker for negative energy balance)– BHB (“gold standard” blood ketone)– Haptoglobin and/or fecal cortisol? (not ready for prime time)– Variation in early lactation milk yield
Question: Which of the following do you think are the most important effects/associations of elevated NEFA and/or BHB in transition cows?
A) Increased incidence of health disorders
B) Poorer reproductive performance
C) Decreased milk production
Herd-level impacts of elevated NEFA/BHB
Metabolite level Herd Alarm
Associated with:
PRE-PartumNEFA > 0.3 mEq/L
15% +3.6% Disease incidence-1.2% Pregnancy rate- 529 lbs ME305 milk (both heifers and cows)
POST-PartumNEFA > 0.6a - 0.7b mEq/L
15% +1.7% Disease incidenceb
- 0.9% Pregnancy ratea
Heifers: -640 lbs, Cows: - 1,272 lbs
BHB > 10a-12b* mg/dL 15%
*20%
+1.8% Disease incidenceb
-0.8% Pregnancy rateb
Heifers: -1,179 lbs*, Cows: - 732 lbsa
*15% of 15 = 2-3 animals Ospina et al., 2010
Approach for monitoring energy-related blood analytes in transition cows
• Sample size:– >12 cows
• Cows to sample– Pre-partum: 14 to 2 days before calving– Post-partum: 3 to 14 DIM
• Sample to take– Serum (red top tubes)– Don’t shake, keep cool
• What to do with sample?– BHB: Lab or Precision Extra Meter– NEFA: Lab
• What to do with results– Interpret % above cut-point– More than 15% above cut-point indicates herd-level problem
Interpretation of metabolites to assess herd-level opportunities
• Scenario 1 – High prepartum NEFA, High postpartum NEFA and/or BHB– Likely starting with low DMI in close-up cows– Too low energy in prefresh diet, facility and/or management issues (grouping,
stocking, heat stress)?
• Scenario 2 – High prepartum NEFA, low postpartum NEFA and/or BHB– Likely low DMI in close-up cows– Are you sampling the survivors in the fresh pen? – Is the herd outmanaging or putting band-aids on fresh cow issues?
• Scenario 3 – Low prepartum NEFA, high postpartum NEFA and/or BHB– Is herd overfeeding energy either far-off or close-up? – Diet or facility/management issues specific to maternity/fresh cow group
Ways to evaluate variation in early lactation performance
• Milk yield/ME projection and index of variability at test days following calving• Standard deviation
• +/- 1 SD accounts for 67% of observations• Coefficient of variation (CV)
• SD divided by mean
• 1st Test day milk yield (n=48)• Mean SD = 25.2 lb (range 10.5 to 30.4)• Mean CV = 0.35 (range 0.25 to 0.62)
• 1st ME projected milk yield (n=48)• Mean SD = 5166 lbs (range 4192 to 6822)• Mean CV = 0.20 (range 0.16 to 0.24)
Herd-level pregnancy rate vs. CV (index of variation) of ME milk yield projected at the first test day after calving
Fresh cow cull/dead first 60 DIM – 6.9%
Date Drawn ID# NEFA BHB10/6/2006 334 0.32 10/6/2006 346 0.39 10/6/2006 1712 0.43 10/6/2006 2012 0.62 10/6/2006 2292 0.51 10/6/2006 2327 0.37 10/6/2006 2394 0.82 10/6/2006 2456 0.34 10/6/2006 2582 0.77 10/6/2006 2589 0.53 10/6/2006 2647 0.29 10/6/2006 2651 0.29 10/6/2006 2776 0.48 10/6/2006 3094 0.58 10/6/2006 3095 0.45 10/6/2006 3102 0.59 10/6/2006 3106 0.44 10/6/2006 3113 0.49 10/6/2006 3116 0.85 10/6/2006 303 0.35 2310/6/2006 313 0.27 610/6/2006 330 0.2 610/6/2006 347 0.35 510/6/2006 2385 0.55 510/6/2006 2408 0.33 610/6/2006 2491 2.07 2210/6/2006 2619 0.38 510/6/2006 2659 0.22 510/6/2006 2681 0.42 810/6/2006 2730 0.13 510/6/2006 2836 0.6 1010/6/2006 3076 0.77 610/6/2006 3080 0.27 410/6/2006 3085 1.11 3010/6/2006 3089 1.4 1510/6/2006 3093 0.82 5710/6/2006 3099 0.3 510/6/2006 3105 0.52 1010/6/2006 3110 0.36 4
17/20 prepartum animals > 0.3 mEq/L NEFA!!
5/20 postpartum animals > 0.7 mEq/L NEFA
5/20 postpartum animals > 12 mg/dL BHBA
60
80
100
120
40
Monthly snapshot of herd milk production at test day
Days in milk at test day
The outcome challenge
• High milk production• Maintain/minimize loss of BCS• Low incidence of metabolic disorders• Minimize loss of immunocompetence• Control/decrease days to first ovulation
and maintain/enhance fertility• Make $$
The transition management challenge
• Putting systems into place (nutritional strategies, facilities, grouping strategies) that decrease individual variability or counter inherent animal to animal variation
• Remember, it’s about milk and reproductive performance; disorders/disease should not drive the transition opportunity discussion