Most lab tests and blood tests are designed to diagnose and treat illness and disease with medications or surgery. Strength and power athletes present a unique blood profile that most physicians will simply write off as "normal," even though performance is declining and the athlete is unsure why. Lab tests that come back as normal may still be problematic for a healthy athlete and may indicate some deficiencies that could be causing decreases in performance. The standard reference ranges for "normal" are compiled based on average of individuals ranging in age from 18-80 that had their lab tested by the organization that drew them. One lab panel from company A may have different reference ranges than company B, and this poses a problem for physicians and athletes alike.

In this series, we’ve covered some lab metrics that can be useful for an active exerciser looking to increase their performance or ensure they are not at risk for developing any nutritional, recovery, or health deficiencies. We’ve looked at Optimal Reference ranges as a way to interpret results, which can outline parameters of good health and performance. Since the body and its systems are interconnected, we have been looking at patterns and correlations between lab markers that show more of an overall look at how the body is responding to its environment currently (stress, sleep, nutrition, exercise, etc.) Using the optimal reference ranges, allows us to address some metrics before they become a big problem. We can start to see trends and see a composite of connected lab metrics that rise together, address them, and get everything working at peak capacity before any performance slow-down occurs. These labs can also help us determine if further testing is needed for certain conditions or problems.

Throughout this three-part series, we have covered labs that are commonly done as part of an annual checkup at the doctor's office and some other more specific labs done to get a larger picture of body functions. There are a multitude of available lab metrics to have tracked by your doctor, so we have covered some labs that you might have had done but never had explained before. We will also cover some labs that could be particularly useful for performance athletes. By going over these labs and giving you a little bit of background on what they are used for and what contributes to higher or lower levels, we hope to give you clues as to what diet or exercise changes to make to your programs to help you function at your best.

In the first part of this series we covered labs dealing with blood sugar regulation, blood cells and composition, electrolytes, male and female sex hormones, bone and muscle health, digestion and lipid levels. Last month’s installment covered oxygen deliverability, liver function, and kidney function. This is the third and final part of this series, where we cover the NMR lipoprofile test and an insulin resistance score. This last test goes more in depth as to cholesterol, lipid management and risk for insulin resistance and diabetes. It can also tell us more information about inflammation and give us clues as to what is driving inflammation in the body. These labs would normally be indicated on lab slips as a Complete Blood Count (CBC), Comprehensive Metabolic Panel (CMP), Male hormones, female hormones, and NMR Lipoprofile.

Liposcience NMR and LP-IR score

These tests are often used for individuals who may have a risk for cardiovascular disease or who have cholesterol levels on their standard lab tests come back a bit outside the reference ranges.

" The NMR LipoProfile® test is an FDA-cleared blood test that directly measures the amount of LDL circulating in the body. "LDL" is low-density lipoprotein and has long been recognized as a major causal factor in the development of heart disease. Although the relationship of increased LDL particle number and plaque buildup in the artery wall has been known since the 1950s, a diagnostic test did not exist to measure LDL particle number (LDL-P). Historically, LDL cholesterol, or LDL-C, has been used to estimate LDL levels to assess a patient's LDL-related cardiovascular risk and judge an individual's response to LDL-lowering therapy. Today, a more reliable measure of LDL exists that directly counts the number of LDL particles a patient has using NMR technology." - http://www.liposcience.com/nmr-lipoprofile-test/health-care-professionals

NMR Lipoprofile Test An NMR-lipoprofile test calculates the cholesterol carrying particles in blood. The cholesterol that is usually measured in a standard lipid profile is composed of triglycerides, HDL and a calculated LDL score. It's not unusual for a high particle score to correlate with a low calculated LDL score. Standard LDL-C levels are usually 0 - 100+ and particle count should correlate with LDL-C multiplied by 10. If your LDL-C level is 130, then your particle count should be around 1300, however there are many factors that can elevate particle number higher than 1300. If particle count for this hypothetical situation is over 1300, then it is considered "discordance"(1). It is because of this discordance that LDL-C does not capture that makes LDL-P a better risk predictor for cardiovascular events (2). The reasons for this "discordance" is numerous as LDL-P and cholesterol/triglycerides are variable based on inflammation status, insulin resistance, abdominal fatness, sleep quality/duration, stress/cortisol, etc. Higher particle numbers are usually most correlated with metabolic syndrome and individuals with more metabolic syndrome criteria tend to have higher particle score (3). I won't get into all of the details of particle elevation and why, but I will cover some action steps you can take to lower your particle count.

Optimal rest and recovery for hard-charging athletes should be a major priority, regardless of particle count. Particle count can be elevated because of lack of sleep and decreased recovery capacity. The standard recommendation for sleep is between seven and nine hours of sleep per night, and if you aren't getting this, my recommendation would be to fix this now. Lack of sleep can lead to a whole host of physical ailments that go far beyond particle counts, but will surely destroy your performance and gains in the gym. Get to bed earlier, create new bedtime rituals, start prepping for bed early, avoid caffeine in later parts of the day, relax and calm your mind before bed, and get your sleep.

Optimal carbohydrate intake is the next step because from clinical experience, too few carbohydrates based on training volume and exercise capacity can lead to a higher particle count. The challenge with this is that this varies based on training, insulin resistance, sleep, blood sugar regulation, and food intolerances. Exercises that consistently deplete muscle glycogen stores can lead to a greater need for carbohydrates to fuel exercise and muscle mass gain. Insulin resistance, sleep issues, poor blood sugar regulation, and certain food intolerances can lower the number for optimal carbohydrates in grams to eat per day. It is a unique balancing act to get the optimal amount of carbs per day, but try to have a goal in mind when trying to nail this one down. The best number of carbs to eat per day for training may not be the best number of carbs to eat per day to lower particle count. It would be best to look at a few other lab markers to determine relative risk and talk with your doctor about prioritizing health goals.
Particles are measured from 0 - 3000+ in nmol/L, with most particle measurements falling between 1000 - 2000 nmol/L. According to Liposcience data, particle counts less than 1000 are low risk, 1000 - 1299 nmol/L are moderate risk, 1300-1599 nmol/L are borderline-high risk, 1600 - 1999 nmol/L are high risk and over 2,000 nmol/L is very high risk.

LipoScience - LP-IR Score This is a measurement used to assess Insulin Resistance (IR) and is scored based on VDL, LDL and HDL particle measures from an NMR lipoprofile test. It has been compared to a number of other tests for assessing insulin sensitivity and seems to be the most useful in clinical settings (4, 5, 6). It is a predictive score for assessing someone's risk for developing diabetes and decreased glucose tolerance. AN LP-IR score can assess hypoglycemic tendencies years ahead of pre-diabetes and provide a good push to help individuals to lead healthier lives. The score is graded on a level of 0-100 with numbers on the lower end of the spectrum being most insulin sensitive and numbers on the higher end being most insulin resistant. From clinical experience, an LP-IR score is variable and there are many things that affect this score. Similar to an NMR lipoprofile test, sleep, recovery, training, food intolerance, and carbohydrate content of the diet are all factors that affect the LP-IR score. The majority of the things we would do to improve a particle count would be the same things we do to improve IR. More specifically, heavy weight training and activities that deplete muscle glycogen stores would be one of the best ways to address IR with exercise. Addressing IR with diet would mean fewer total carbohydrates, a decrease in refined food products, more fiber from fruits and vegetables, ample protein and a good balance of dietary fats to name a few. Sleep and stress management are generally the biggest issues we see in dealing with IR score. Diet and exercise are much easier to control for an individual than their sleep and their responses to stress. From personal experience, if someone sleeps good and is relatively cool, calm and collected, their LDL-P and LP-IR score are on the lower end despite their diet and exercise program. As someone starts to sleep better and respond to stress better, their scores tend to improve even if their diet and exercise don't. I speak the praises of diet and exercise for a living, but can't ignore the usefulness of having fun, sleeping well, and being in control of stress. An LP-IR score of less than 45 is good, but an IR score less than 25 is optimal.

Summary

When we look at biomarkers for performance, there are a lot of metrics that can be useful for helping us to maximize performance when looked at from "optimal" reference ranges compared to standard reference ranges. There are many lab tests that are used specifically to identify, diagnose and treat conditions, but these labs shouldn't be the only thing someone takes into consideration when assessing someone's health or illness. Signs and symptoms should be a driver for some lab testing and assigning appropriate diagnoses. I use lab testing in practice to guide me to ask certain questions to see if there is an issue or the lab numbers are an anomaly. Since I am not a medical doctor, I don't diagnose or treat any conditions, I merely use the labs as a way to try and help someone improve their diet, exercise, and lifestyle habits and then refer them out to a medical doctor as needed. I like to use lab testing because it can help pinpoint some issues and decrease time spent in trial and error working with someone not seeing results despite their best efforts. We can use lab testing to predict an individual's success with a low-carb diet, weight training, high-carb diet, decrease in training volume, as well as see what supplements they should stop or start taking to help them improve.

My recommendation for getting lab testing is to start with some basic tests and dive deeper if some levels are not within range. Having too many lab tests and numbers may confuse some individuals or turn them into hypochondriacs because a few unrelated numbers might be off, possibly due to dehydration or a faulty test. All lab testing should be taken in context and compared to an individual's dietary, exercise, sleep, recovery, medical history, and supplementation habits. Hopefully these series of articles have helped to identify some potential areas of improvement in your labs and the steps you can take to optimize your performance.

References
1. Otvos, James D. et al. “Clinical Implications of Discordance Between LDL Cholesterol and LDL Particle Number.” Journal of clinical lipidology 5.2 (2011): 105–113. PMC. Web. 24 May 2015.
2. Cromwell, William C., et al. "LDL particle number and risk of future cardiovascular disease in the Framingham Offspring Study—implications for LDL management." Journal of clinical lipidology 1.6 (2007): 583-592.
3. Wallenfeldt, Karin, et al. "Apolipoprotein B/apolipoprotein AI in relation to the metabolic syndrome and change in carotid artery intima-media thickness during 3 years in middle-aged men." Stroke 35.10 (2004): 2248-2252.
4. Garvey WT, Kwon S, Zheng D, Shaughnessy S, Wallace P, Hutto A, Pugh K, Jenkins AJ, Klein RL, Liao Y. Effects of insulin resistance and type 2 diabetes on lipoprotein subclass particle size and concentration determined by nuclear magnetic resonance. Diabetes. 2003;52:453-462
5. Goff DC, Jr., D'Agostino RB, Jr., Haffner SM, Otvos JD. Insulin resistance and adiposity influence lipoprotein size and subclass concentrations. Results from the insulin resistance atherosclerosis study. Metabolism. 2005;54:264-270
6. Mackey RH, Mora S, Bertoni AG, Wassel CL, Carnethon MR, Sibley CT, Goff DC, Jr. Lipoprotein particles and incident type 2 diabetes in the multi-ethnic study of atherosclerosis. Diabetes care. 2015;38:628-636