Guests: Dr. Andres Contreras, Michigan State University; Dr. Bill Weiss, Ohio State University This journal club episode comes to you from the 2024 Tri-State Dairy Nutrition Conference. The paper is “Assessing Transition Cow Health: Integrating Traditional and Novel Biomarkers” from the conference proceedings with Dr. Andres Contreras of Michigan State University.
This journal club episode comes to you from the 2024 Tri-State Dairy Nutrition Conference. The paper is “Assessing Transition Cow Health: Integrating Traditional and Novel Biomarkers” from the conference proceedings with Dr. Andres Contreras of Michigan State University.
What is a biomarker, and what makes a good biomarker? Dr. Contreras defines anything that can help assess a physiological response or pathological state. Two examples would be BHBA (beta-hydroxybutyrate) and NEFA (non-esterified fatty acids), both fat mobilization measures. (2:56)
Dr. Contreras structured the paper in three sections of biomarkers: (3:54)
How many samples should be taken, and what cows should be sampled in a commercial dairy setting? Dairy size, pen size, and pocketbook size will all play a role in this decision. Experts usually recommend at least 10 head, and those 10 must represent the cows' population in your pen. If you have the ability to take more samples, Dr. Contreras recommends 10-12% of the cows in question. He then describes ideal times before and after calving to sample BHBA and NEFA for the most predictive value. (5:31)
Setting a target that integrates BHBA and NEFA the first week after calving with measures like body condition score and/or body weight is ideal. Cows will mobilize fat post-calving no matter what, so the goal is to moderate the degree and intensity of fat mobilization. (11:38)
Rumination and activity monitors are great for measuring biomarkers in real-time and are excellent tools for diagnosing problem cows early. Dr. Contreras has researched ultrasounds to measure fat mobilization, but this may not be practical in a commercial setting. Urine pH after calving might start to be a significant predictor of clinical ketosis. Healthy cows will have a higher urine pH than sick cows. (14:44)
A transition cow experiences several types of adaptations: lipid mobilization to address negative energy balance, skeletal muscle mobilization to address negative protein/amino acid balance, calcium mobilization to compensate for calcium loss, and oxidative stress due to generating energy. The goal is to target biomarkers that reflect the intensity of those adaptive mechanisms. Many of these require sending samples to a lab. A dairy’s nutritionist, veterinarian, and farm manager work together to create a targeted suite of biomarkers to assess their cows and reach their goals. (21:11)
Inflammation is often at the core of transition cow maladies. Measuring a panel of acute phase proteins the first week after calving and comparing the dynamics of how they occur through the year could help identify issues in closeup cows if those proteins are spiking. (26:03)
The group discusses the importance of using individual herds’ baseline data for prediction and assessment and focusing on closeup cows when fresh cow problems arise. They also discuss biomarkers for excessive protein catabolism and a liver functionality index. This leads to a discussion of whether creating an index might be a better overall measure than making decisions on just one diagnostic value. What if someday there might be one perfect predictive biomarker, and what might that look like? (27:50)
In summary, you should not rely on a single biomarker and start measuring early. Ideally, this would be in the dry period. If that’s too challenging, it would be at least a few days after cows go to the closeup pen. Cow-side biomarkers like BHBA, body condition score, and body weight can tell you a lot about transition cow health. Use all the biomarkers and herd records available to design your approach to transition cow health. (43:10)
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Scott (00:07):
Good evening everyone, and welcome to the Real Science Exchange, the pubcast where leading scientists and industry professionals meet over a few drinks to discuss the latest ideas and trends in animal nutrition. Hi, I'm Scott Sorrell, gonna be your host here tonight. Joining me is my co-host, Dr. Clay Zimmerman. As always, welcome Clay. Good to see you. Clay. What, what's in your glass tonight? This is a flying squirrel. Well, what's in yours, clay?
Clay
I'm enjoying a spotted cow today thanks to Carrie Lamont and it's quite enjoyable.
Scott
Also joining me is our resident professor Dr. Bill Weiss. Welcome Bill. And what might be in your glass.
Bill (00:47):
I have a Spotted Cow as well.
Scott (00:47):
A spotted cow as well. We're on a trend here. And our guest this afternoon is Dr. Andreas Contreras from Michigan State. And he did a presentation, or is going to give a presentation here at the Tri-State Nutrition Conference called Assessing Transition Cow Health, integrating Traditional and Novel Biomarkers. So I'm looking forward to that. Dr. Andreas welcome. Got some water in your glass?
Dr. Contreras
Yeah, fine water. Cheers.
Speaker 3 (01:25):
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Scott (02:28):
You know, this is your third trip to the pub. The first two times though was with a student. Yeah. So this is the first time by yourself, so yes, it's welcome back. Glad to have you. You're very welcome. Bill, would you mind walking us into the proceedings that we're gonna be discussing this afternoon? I
Bill (02:45):
I’d be happy to. I guess to, to start off with, what, what is a biomarker and what makes in, in general terms and what makes a good biomarker?
Scott (02:55):
Biomarker?
Andreas (02:56):
Well, biomarker, the broad definition is anything that can help us assess a physiological response or a pathology if, for example, the cows are sick. So good examples of biomarkers are broadly used. BHB, Petra hydroxybutyrate, it tells us the levels of beta hydroxybutyrate tells us the degree of fab mobilization in the cow, the same with the ne. So those are usually chemicals that we can measure in the blood and can help us identify any problems or any physiological responses in the calf. That's a broad definition.
Bill (03:39):
And they'd have to be, you know, applied. They'd have to be commercial. The assays have to be commercially available and at a reasonable cost as well. I mean, there's the research biomarkers, but then the, the, what we could eventually apply.
Andreas (03:54):
Yeah. I the way I actually structured this presentation, I, I divided the biomarkers in three broad areas. The ones that we can actually measure in the office, just looking at her records. Good examples are, you know, how many das do we have this month? How many hypocalcemia milk fevers we had this month? There are some other ones that I classified them as cow site so that we can measure right by the cow. For example, the beta hydroxybutyrate. Now we have those keto sticks. That we can measure the amount of block ketones in the urine. We also have the precision extra meter that uses the strips. So you can measure the BHP in the block, or there are some other ones that you can use in the milk. So those are cow site. And then we have the ones that we have to send to a lab and to be measured. So those ones are not cow side, obviously, because we have to submit it, and they usually take a little bit longer to get the results. So it's more difficult to actually use them to make decisions right away, for example, if you have a sick cow. But they might be able to help us to actually assess how well, how a transition count problem is going. Program is going. Okay.
Bill (05:13):
Yeah. Again, I know it would vary depending on, I'm talking more about blood or, or biological samples now, and I know it would vary, but how many cows, when do you sample this kind of stuff? A little bit on the practical on, on, again, not the research type markers, but commercial or practical ones.
Andreas (05:31):
Well, yeah, the, the question of how many and who to sample. So how many, usually what most experts recommend is at least 10 cows. Obviously, you have to take into account how big is your dairy, how big is your pan. So you might be, and if, how big is your pocket too? So how many you can actually sample, but ideally at least 10. And the important thing about those 10 is that they have to represent the population of cows that are in Japan. So if you have a pen that's composed of cows that are a third, first lactation, a third, second lactation, and a third, eh, fourth lactation or more, those cows that you select, they have to reflect the composition to make it actually a good picture of the entire cohort of the, or the entire pen that you have. So if you, if if you have, if you have the possibility of taking more samples, that would go for 10 to 12%. Mm-Hmm.
Bill (06:44):
And it would be the population of interest, not, you're looking at transition cows, obviously you don't sample dry off cattle.
Andreas (06:50):
Yeah, of course. So you would have, if you want to look at how your cows are starting off the dry period, you'll sample the dry pen, then how well the cows are responded to. For example, you DCA diets, you'll sample the closeups and probably wait a few days after they started with the DCA cells. And then for the fresh cows, it's the same, maybe wait, maybe two to three days, because right after coming, there's a lot of variation in the biomarkers. So you really want to wait maybe three or four days until you start collecting samples for biomarkers. Yeah.
Bill (07:23):
And again, for these blood, blood or urine based ones, do you look at averages or do you look at a cut up percent above a cutoff? Or how do you interpret once you get the data, what do you do with it?
Andreas (07:34):
That's a good point. So it's usually better to use cutoff points, and especially for BH, B and nifa, that those have been widely researched. And we have more information about what threshold we have to have the majority of the, of the cows within. So with those, I would usually use the threshold for others, for example, calcium, if you're able to measure calcium, I would be very careful if a cow has low calcium, I would treat for right away, for example. So it, it all depends on the type of biomarker. Okay.
Bill (08:08):
Yeah. I'd like before you guys check in here, but there's quite, I don't know how, how controversial, but there's quite two schools of thought on B HBAs. Yeah. What, what's your point of view or what's your opinion of, of the value of it and, and how does it differ from the other school
Andreas (08:27):
So with BHP, I think first of all, it's, they're only us usable after CABG. Okay. So the disease risk prediction value of BHP, it's very low Before CABG, after calving cows will start mobilizing fat, and you'll see increase of BHP within the first week after calving. And then by the second week after calving, you'll have cows that are have, that have high BHP, but they're good producers, usually best producers. So I think I would focus more on the first week after Calvin with the BHBs and kind of interpret depending on the cow for the second week or after. Yeah. What,
Bill (09:10):
What about, one more question you guys take. That's okay. What about NIFA's then?
Andreas (09:14):
Okay. Yeah.
Bill (09:15):
The same kind of controversy or valuable or not?
Andreas (09:17):
It, it is, but with the NIFA's, you have some predictive value before calving. And there are some thresholds, I think I included the values in the, in the proceedings but usually levels 0.7 before Calvin that they actually describe, or probably indicated that cows are starting to mobilize fat,
Bill (09:38):
But prepartum
Andreas (09:39):
And prepartum and then postpartum if they, yeah. And then you have to use both BHPA and NIFA for after CABG. So, but NIFA, you, you have to be careful on how you sample them and how you interpret them. Because during the day, the cows will have variation in the NIFA concentration depending on what time you feed them. So if you sample NIFA right before feeding them, they will be higher than after feeding. So you can always measure, but the most important thing is to do it always at the same time relative to feeding or relative to milking something that you know that it's gonna be always the same. So you can compare.
Bill (10:21):
And they, they also spike at calving or very clear.
Andreas (10:24):
Yes. What they cal very, yes, of course. Careful on that. So yeah, they do have to mobilize that because they have a long period of fasting right around having,
Clay (10:34):
I have a lot of questions. This is, I I love this. I love your talk. So maybe to pick up on the BHBA questions that, that bill had already had. So you were talking about looking at it the first week after calving. So, so when should you start checking how many days in milk?
Andreas (10:57):
I would probably say four days after calving. Because the first three days it can be all over the place. Especially, for example, with heifers that they might take longer to cap. So they might, they might pike after cabining cows might take longer. So it's better to be safe and measure them four days after if the cows are okay. Obviously, if the cows are sick, they're gonna have both B, H, B and NEFA pretty high. So it's, it's gonna be an obvious diagnosis that they are mobilizing fat because they're not eating at all.
Clay (11:31):
So what if the cows aren't sick? How aggressively should you respond?
Andreas (11:38):
That's a good question. And to tell you the truth, I don't know,
Clay (12:57):
So I think somewhat related to this, you you talked about fat protein ratio in the milk. Now, fundamentally we've increased the milk fat content in the us right? We average over 4% milk fat now. Mm-Hmm.
Andreas (13:27):
You know, I, I do not know now because now we have a lot of cross breads, for example, right? With the jersey. So you don't know. And the other thing is, I really discourage the use of milk fat milk fat protein ratio, because usually those results come too late right? And the other thing is that cows, if you have DHI, those cows within the first five day, first 4, 5, 4 to five days after Calvin, they don't get measured. So if you're gonna use it, it's because you can calculate and you can use, calculate the ratio right at the dairy. And that's not the case in many dairies. So I have it there because that data that I put there, the ratios, the limits that I proposed, those are for haling cows do not include jerseys, do not include cross breads. So I would use it carefully. And I think with the, for example, with the BHB, with the precision extra strips, we have a more sensitive and more specific type of biomarker. And that goes back to your question than using the Mel milk fat to protein ratio. So I really discourage the use because it's not practical and there might be a lot of variation.
Clay (14:40):
What about, so what about using the rumination and activity monitors?
Andreas (14:44):
Oh, yeah. Those are excellent. Obviously you have, and, and the good thing about those ones is that the cow eats her own control because she has a level of activity, a level of ruminations that she has sustained or not. And if there are changes, you're able to detect them before. They are great. If you use the data, obviously. So that, that would be my suggestion, use it. And you can set the alarms, adjust the alarms, depending on your cows, depending on the age, depending on number of lactations and so on. But if you have it, use it. And that is a type of biomarker. It's real time, you know, when the cow is going to change, start to exhibit changes and it's an excellent tool for diagnosis detecting cows early.
Clay (15:39):
And then another, there was another monitor here, I'm, I'm really not very familiar with. You talked about ultrasound. Ah,
Andreas (15:46):
Yeah.
Clay (15:47):
Can you explain that?
Andreas (15:48):
Yeah. So that, that comes back to some research that we've done the past decade. This, I think this from a couple of papers that we had in 2016. So we were trying to actually try to use the ultrasounds that we use for repro purposes. and we tested those probes and you're able to actually detect fat novelization if you measure the subcutaneous fat and the retroperitoneal fat. We, we, post a prob right RTA ahead of the ter cranial to theodor. Okay. And that's where we took our measurements. Eh, you know, for research it's good. I don't know if you can do it in, you know, in a commercial herd every day or set your cohort of cows and measure them because you have to use the same cow because you have to compare the first measurement before having to the two measurements, after having to see the fat mobilization intensity, because you're gonna detect the reductions in how thick the fat layer is.
Andreas (16:56):
So if you have the time, if you have a person that's very familiar with the use of the ultrasound, it is a good option. We report a good association between reductions in the fat death and levels of NIFA in plasma and BHP in plasma. So it is a good proxy. However, it requires a good training on the use of the instrument. And if you want to assess a muscle breakdown, the probes that you use for repro do not work because you really need depth, because you need to measure the whole math of the muscle that you want to select to monitor. So with the props that we use for repro, you can only measure the fat. You cannot go deeper. So you really need to buy those big expensive probes that are used in, in the beef industry to measure the rebuy and, and all the different muscles that they measure. Those are required for that part. But so you, you, you will not be able to use the simple linear probe that we use for repro purposes in there is.
Clay (18:10):
And then you, you mentioned urine pH, so, so obviously, you know, with a negative DA diet, I think we're all sort of familiar with that. Are there learnings? I'm curious, are there, are there learnings from urine pH? If you're not on a negative dec cat diet?
Andreas (18:28):
You know, it's very difficult to find a dairy that does not use decat. At least for us, we have not been able to, 'cause we need some controls and we cannot find them, so the thing is to try to save about 6.2, because below 6.2, the calcium mobilization starts to be reduced. And if you reach to five cows will not mobilize calcium. And actually you might be inducing metabolic acidosis, not the compensated metabolic acidosis that we want when we feed DCA diets, but the actual bad one. So what we are finding is that perhaps we need to start looking at the urine pH after calving. 'cause Everybody measures the PHB before calving, but after calving, we expect to see some changes, obviously. 'cause We are feeding a, a colonizing diets, so we expect the pH to go up. But the cows that are gonna be sick that are at higher risk, their pH will not increase as much.
Andreas (19:32):
And I'm gonna show some data tomorrow where we see the cows that are going to, or that are half key clinical ketosis. Their pH is already elevated above seven because they're not an ionizing diet, but it's not as high as the cows that are healthy. So it might be important to start measuring the urine pH after Calvin. And it might be another biomarker that we have right there. It's very cheap to measure. And it can give us a lot of information because when cows are mobilizing a lot of fat, they tend to decrease the PHB, cow, BHB, it will acidify it, it's an acid. The BHBs are acid. So they will try, they will tend to lower the pH h and the cows will start to compensate. And you'll see meta compensated metabolic acidosis in post cap postpartum cows that have clinical ketosis.
Clay (20:26):
So in a normal, normal lactating cow, the urine pH is, is is eight to eight and a quarter, right?
Andreas (20:32):
Yeah, it can, it can range right from 7.3 up to 8.2. It depends a lot of the diet, for example, if, if you're feeding so by carb, for example, to, to actually control the prevent, Sarah, you might see the pH to increase.
Scott (20:52):
Dr. Contreras, you outlined three different kinds of, of biomarkers. The third being where you actually send the samples away. Can you kind of maybe characterize what, what kind of samples and what you're measuring on the ones that you send away? And then does it ever make sense to bring that capability in-house?
Andreas (21:11):
Well, it all depends on what you're targeting. So if you have a transition cow, she's gonna experience several types of adaptations. One is lipid mobilization to address negative energy balance. She's gonna start mobilizing skeletal muscle to address negative protein or negative amino acid balance and some other nutrients. She's gonna start to mobilize calcium to actually compensate for the calcium loss. She's gonna experience some oxidative stress because she's generating more energy and generating energy actually generates reactive oxygen species that might induce oxidative stress. So you wanna target, eh, biomarkers that actually reflect the intensity of those adaptation mechanisms. So for example, with lipid mobilization, you usually measure nifa. 'cause Not all the bruises have a applied reader. So technically NIFA have to be submitted to a lab. If you want to measure anti an oxidative stress, you usually measure the antioxidant capacity and the reactive oxygen species.
Andreas (22:20):
If you want to measure amino acid movement, you can actually measure different biomarkers in the urine. Or if you want to measure, for example, inflammation, you can measure the acute phase proteins. So those are the major areas where you want to act, measure certain biomarkers to see the intensity of those adaptations. So there are some biomarkers that are more characterized for each type of adaptation. For example, with inflammation, acute phase proteins, proteins are very well characterized. We have good references for albumin, good reference limits for abog globin for oxidative stress, we have R os and we have antioxidants. We also have isop ants. I'm gonna touch upon a little bit tomorrow. I isop ants are the gold standard biomarker for oxidative stress. They are generated by the action of reacting native species on different poly fatty acids. And they state in the membrane so we can measure them afterwards and actually calculate the intensity of native stress.
Andreas (23:36):
So I cannot really give you a given set of biomarkers that must be measured. It depends on the nutritionist and the veterinarian on the farm manager to which one they, they want to target. If they have concerns about oxidative stress, they should measure biomarkers that are related to oxidative stress. If they're concerned about muscle breakdown or if they are feeding a specific amino acids, perhaps they should measure those amino acids or some biomarkers of muscle breakdown. The same with nifa and lipid mobilization, usually invi. Now we have one biomarker that we're starting to develop as called osteopontin. So osteopontin is a protein that's secreted by macrophages in the fat. And during extended lipolysis, extended periods of lipolysis that is negative energy balance. There's gonna be an influx of macrophages into a fat, and the more macrophages you have in the fat, the more osteopontin they secrete.
Andreas (24:41):
So we are starting to measure osteopontin to see if we can actually quantify the degree of inflammation in the fat chose by measuring osteopontin, which is easier than taking a fat sample and looking in section and looking into a microscope and see how many macrophages you have in there. So it would be proxy for lipid mobilization related inflammation in the fat. So those are just some examples. But the thing is that we have a lot of options, which is probably need to decide on which ones to use depending on, on our area of concern, or we are investing our money into certain interventions to actually help our cows transition. Well, so that, that was pro, that's probably the guidelines to select what type of biomarker you want to measure, the ones that you have to submit samples to a lap.
Scott (25:36):
So I, I'm kind of thinking back or recalling a presentation that Dr. Lance Magar did. And, and I think in that presentation he'll tell you that many of the maladies that transition cal suffer is due to inflammation. So do you have a protocol or recommendation for measuring those acute phase proteins and, and, and should it be done regularly? And if so, then, then what, what might interventions might you prescribe?
Andreas (26:03):
That's an excellent question. And actually it's a pretty broad question. I would measure inflammation within the first week after cabg, after the part tuition events, eh, have passed. So I would not measure before four days, eh, I ha I provide some range or reference values for the different acute phase proteins. As I said, AOG globin is a good option for negative acute face proteins. For a positive acute face protein album is an excellent choice. As long as you have a good panel of those acute phase proteins, you can follow and compare the different cohorts of cows as they call. Depending on your definition of cohort, there are some herds that you might have a cohorts every week. If there's smaller herd, maybe the courts are every two weeks or every month. So if you can compare how the dynamics of those acute phase proteins occurred through throughout the year, you might be able to actually start to detect if you're having issues in the closeups because those proteins are starting to spike. Yeah, makes sense.
Bill (27:18):
You, one, one concern I have is do we have enough data to interpret these correctly? And I want to use calcium as an example. Years ago, if they were blood low, blood calciums 24 hours, we were really concerned. Now we know if they bounce back, they're fine. It's perfectly normal. So do we know enough so that we don't start interventions that we shouldn't be doing? In other words, ABHBA is high at two weeks, but it's fine. But we start changing things when we really shouldn't have.
Andreas (27:50):
I don't think we hardly any biomarker has good assessment of this, of the risk prediction value. We probably can count it with the hand as BHP, nifa and perhaps calcium, maybe ionized calcium. I think beyond those, we don't have enough data to actually be able to start making decisions without putting into context the here where you are and the region where you are. So that's why I really emphasize that if you want to actually have a management program for transition cows, you have to use your own data from your her or at least if you're a consultant, if you see many hertz, you have to kind of try to use values from the hertz that you are seeing. So that, that would be my advice. We, we cannot rely on, on actual threshold values for biomarkers other than NIFA's, BHPs or calcium. We just don't have the data.
Bill (29:01):
Do you think, again, let's stick with VHVA. Should this be a, a routine test or only if, if you're having problems or when would you recommend initiating a, a protocol where this becomes where you start testing is? 'cause There's, you know, there's a cost associated where there's time and a lot of things go into this.
Andreas (29:21):
Well, I'm, I'm very pragmatic. So if, if you're not having problems, eh, you should probably only do your, your cohort, your sub sample of the cohorts. Maybe do 10 to 12 cows every two weeks, every using, perhaps when you are having major changes in your diet, in your precal diet, maybe that's when you need to assess how those cows are doing through the close up and the, and the fresh. But if you have a, you know, a pretty steady management type with a pre steady flow of ingredients that are very similar in quality maybe you kind of start to balance it. It's very difficult because each, each herd, its, it's its own world. So if you really need to decide when is you need to intensify monitoring your, your cows Mm-Hmm,
Bill (30:22):
Do you have some like if you were, if a farmer called you up a nutritionist, do you have kind of a checklist where you'd say, okay, this is wrong, this is, this is wrong. You ought to initiate some blood sampling or something for BHB or any of these biomarkers?
Andreas (30:38):
Yeah, I would start with the, with the her records. If you see a spike in transition cow problems, let's say da eh, milk fevers, that's what you, what you don't, you don't need to look at your first cows, you need to look at your closeup cows. But that's what's coming. Okay. So, and then maybe you start to look at, you know, logs of, you know, what happened during the weekend, did the decant diet, everybody forgot to put it in. So those are us, the usual mistakes. And then I would start, but actually measuring before calving. Okay. That's really important. 'cause We tend to focus too much on the fresh cows. Really, we should focus all the time on the closeups. 'cause That's, those are the accidents waiting to happen in one or two weeks. Yeah. Okay.
Clay (31:25):
So I really, I really like the table that you put in there, the reference table. You listed hemoglobin. So if hemoglobin is out of the, that range, what is that telling you?
Andreas (31:41):
We, we listed hemoglobin because we are recently in the lab, we started to use blood analyzer. Her blood analyzer. I don't know if you're familiar with the point of care product by vo, sorry, I shouldn't did was I allowed to say that brand here or not? Anyways, they're broadly using hospitals. They're broadly using animal hospital to and those ones usually come in cartridges and the cartridges you can load an amount of plot. It, it varies depending on the cartridge, and it gives you a readout of different biomarkers, all the blood gases. So it's a good option when you're assessing how well your dcas are doing beyond your pH It's more exact actually measures ionized calcium, glucose so, and it gives you a readout of hemoglobin. So that's why we included the reference values. Again, those have not been validated as a risk predictors.
Andreas (32:43):
So I cannot give you a range of when to be considered or not, because it probably wouldn't be useful, eh, but it's more important to look on the ones that we already have information, and those include the blood pH, the calcium ionized calcium levels, glucose levels, especially if you have cows post calving. And I compliment that with the BHB measurements. So that, that would be an ideal, an ideal set of calcium biomarkers that you can measure one week after calving would include the BHP using the precision extra. If you have the point of care handheld device, you could use some of those cartridges or some outputs that include calcium and blood pH and acid based status. And that you, in pH HI think we're trying to build something that we can use that's very affordable Right. At the farms before you need to submit any samples to a lab or a diagnostic lab or a, a nutritional lab.
Clay (33:49):
Are there, are there biomarkers we can measure that would that would indicate we're having excessive protein catabolism?
Andreas (34:04):
Yeah, you can measure those creatinine and there are other markers in the urine that you can measure. Yeah. Yeah. Actually there's a nice review by JA, Jackie Berman Mm-hmm.
Clay (34:47):
So I think the last, the last item you listed in, in that table was liver functionality index. Can you speak to that for a minute? Yeah.
Andreas (34:57):
Well, obviously the liver is the metabolic machine. And there are some studies from the Italian group and they actually develop the liver index. So they have different metabolites, and I describe them in the proceedings, and they, they have an equation that develop, and actually that gives you liver index function and you can adjust. But again, you need to send those to a lab. They're usually very expensive. Each test is about $30. So it adds up. And to help you diagnose, maybe you don't need to go that far to actually measure all the ASDLT and all the different hepatic enzymes if your problem maybe is in the closeups and you want to measure it before it happens. So it's more, those ones are usually more used for research purposes. But I think for practical purposes, maybe we could limit those a little bit more to the cow side and very specific, eh, for example, the acute phase proteins that are well characterized and they're usually easier to run when you submit those samples to a diagnostic lab.
Bill (36:10):
Do you know of from studies, we, I I did sometimes on acute phase proteins, one would go up, one wouldn't, or you get different results. And so do you know, are people working on developing indexes where they start like body condition change? Ne is all this stuff kind of going into something and say, this cow's at risk rather than relying on a single measurement?
Andreas (36:34):
Yeah. There are different groups that are developing indexes, and I can't, I cannot speak to the actual risk prediction value of those indexes, eh, because not everybody is using them. So the applicability of those indexes to a herd that's located in a different region to where those were developed, you know, that that might change the predictive risk. But those are, and as we have more information coming, for example, I talk a little bit about the milk BHP, that now it's available in some robotic milkers to actually measure BHP in line. So those ones are, those are gonna fit the her management software. And actually you might be, the different manufacturers might be able to develop an index based on, on, on the data they have available to, for example, including the, you know, the, the ruminal colors of the activity loggers. Yeah. And then they can develop their, their index. So I think the producers have now have those alternatives. And I think those alternatives, those alternatives would increase as we're able to measure more, more data Yeah. And feed more data into the different algorithms that those machines use.
Bill (37:59):
I just would think these integrated indexes or something like that would be more always a little leery of making big decisions on a number.
Andreas (38:07):
Oh, yes, yes. I I, I hear you. Yeah. And that's why, for example, you, I don't, I don't think you should base your decisions on only one single biomarker or one of those indexes, because there is more to that. And you, that's why I emphasize, hey, look at the, at the her records, look at the cal side biomarkers, if you have some available, and then look at some of those eh, biomarkers that you have to send to AL lab, for example, the nifa. So it, it, you have to make a comprehensive evaluation of the data you have before you take any decisions.
Scott (38:43):
Yeah. Dr. Contreras, I'm kind of curious you know, if you had a magic wand what kind of a diagnostic biomarker diagnostic would you create that you don't have today that you wish you had? And maybe it's not just one, right? Maybe it's an index as we were just talking. But what would that be? Any thoughts?
Andreas (39:03):
Well, the idea one would be one that you measure one week after you dry off your cows, that will give you, with high sensitivity and specificity a good risk value for your group of cows. So, for example, cows that were dry off on the 1st of September, on the 7th of September, you measure this magic biomarker and it tells you that with higher specificity and high sensitivity, that maybe 20 to 25% of your cows are gonna ha at a higher risk of having an issue during the transition period. With that in mind, you can really follow that cohort and be very careful with any changes that you make with the diets that you formulate, with how you treat those cows. So if, if you're aware that the risk is coming, you have more tools to prevent that risk. So that would be the ideal. The earlier, the better. Yeah. And the ideal thing is right after you dry off the cows, right? So,
Scott (40:16):
So is that pure fantasy or do you think there's some things that you perhaps could measure that would give you that indication? Yeah, we,
Andreas (40:23):
We are gonna, I'm gonna present some data on a couple of biomarkers that you can measure within the first week after dry off that, at least in this very small sample size that we had, it was only 18 cows total. We saw that two ants, so, so oxidates fatty acids that increase in cows that were, that had actually a healthy event after Calvin. And those were linoleic acid derived OSI lipids. So, and I'm gonna talk about those tomorrow. And we had a paper out in 2022 by one of our students, Ashley Putin, and there we in the Journal of Data Science, and then we described those, those linoleic acid derive oxy lipids as possible candidates, but again, it was only one herz. So we, we need more work on this. Yeah,
Scott (41:22):
Makes sense.
Speaker 6 (41:23):
You gotta start someplace. So
Scott (41:25):
Anything else, gentlemen? All right. Well then as we wind down clay, what I'd like you to do is, is you know, are, is there any key learnings for yourself today from today's conversation?
Speaker 3 (41:39):
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Clay (42:03):
I think there will be a lot of interest in this talk tomorrow. Yeah, I think they, you're probably last on the whole program for that reason. I, I, I think there will be a lot of interest in this whole topic. So I am, I am intrigued by what you said at the end about, you know, is, is there something we could test in the early dry period that could be become a good biomarker for issues?
Scott (42:29):
Yeah. Yeah, for sure. Bill, any key takeaways for practicing nutritionists that you would wanna share from this talk?
Bill (42:36):
One, there's a, a lot of more biomarkers than what I would consider a biomarker. So I've learned the definition is a lot broader than I thought. A lot of these are very applicable to a farm. They can measure 'em easily, some less so, and I think the integration of of, of multiple bio, at least two, but multiple biomarkers to make, help make decisions, I think is, is in this paper quite
Scott (42:59):
Well. Yeah. Excellent. And Andreas you're gonna give a presentation tomorrow, and I'm sure at the end you're gonna have some take hold messages. What might those be for the audience?
Andreas (43:10):
Actually, you summarizing those very well. Right,
Scott (44:28):
Yeah. No, great guidance. Gentlemen, this has been a good one. I appreciate your participation. Dr. Contreras, thank you for joining us once again for your third time. Have to have you back for a fourth to our loyal audience. Just thank you so much for joining us once again. We hope you learn something. We, we hope you had some fun and we hope to see you next time here at Real Science Exchange, where it's always happy hour and you're always among friends.
Speaker 3 (44:54):
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