WO2014143080A1

WO2014143080A1 - Methods for generating personalized dietary guidance using fatty acids for purposes of reducing risk of pathology

Info

Publication number: WO2014143080A1
Application number: PCT/US2013/035788
Authority: WO
Inventors: Jeff S. Volek; Stephen D. PHINNEY; Douglas Bibus
Original assignee: Beyond Obesity Llc
Priority date: 2013-03-15
Filing date: 2013-04-09
Publication date: 2014-09-18

Abstract

The present invention relates to methods for managing the risk for pathologies and employing either absolute levels of, or changes over time, for the generation of individual- specific dietary guidance. The method comprises comparing one or more biomarker(s) against thresholds. This comparison provides a score for the individual's risk of developing a pathology, such as type-2 diabetes or weight gain. The biomarkers may be fatty acids, generally, and palmitoleic acid (POA) and/or di-homo gamma-linolenic acid (DGLA) in particular. Samples are collected from the individual and are used to analyze the levels of the biomarkers. The samples can be whole blood, serum, plasma, and buccal mucosa cells, for example. High or increasing levels of the biomarkers indicate that carbohydrate intake is above the individual's metabolic tolerance.

Description

METHODS FOR GENERATING PERSONALIZED DIETARY GUIDANCE USING

FATTY ACIDS FOR PURPOSES OF REDUCING RISK OF PATHOLOGY

BACKGROUND

[0001] The present invention relates to methods for generating individual specific dietary guidance to manage the risk of a pathology such as weight gain or diabetes. Such methods are particularly useful in the context of a weight loss regime or health driven lifestyle change. Such methods enable individuals to objectively tailor their dietary intake in response to physiological changes in order to effectuate healthy weight loss and disease prevention or resolution.

[0002] For a variety of reasons, including health, appearance, and body image, many people are concerned with achieving and maintaining a particular body weight or range of body weights. Most of these people are concerned about being overweight, and want to reduce their weight. In many locales, there are weight control clinics, in which large numbers of patients are checked, counseled, and prescribed for weight loss regiments. Typically these weight loss systems rely upon gross metrics in order to develop a diet suitable for the individual. These metrics often include gender, amount of weight that is desired to be lost, and age.

[0003] It should be noted that these weight loss regiments do not take into consideration the individual's unique physiology and reaction to differing dietary intakes. It has been shown that people respond very differently to the food they eat. Some people are far more prone to carbohydrate intolerance (aka insulin resistance) than others when appreciable dietary carbohydrates are ingested, for example. Most current weight loss and healthy diet systems provide generic guidance to people, but virtually none rely upon biological feedback in order to tailor the diet to the user's unique metabolism at any given point in their life.

[0004] One dieting system that has been popular since the 1970s, and has gained significant traction in recent years, is the Atkins Diet (Atkins Nutritionals, Inc.). The Atkins Diet, and other diets that emphasize restricting carbohydrate intake, have shown relatively good success for many people. The Atkins diet utilizes the principle that limiting dietary carbohydrate results in a greater reliance on fatty acids and ketones for energy. This shift in metabolic fuel use is associated with fat loss and a number of favorable health outcomes. Reduced intake of food due to feeling satiated is also a causal factor in weight loss, as is the improved fuel flow to the brain afforded by physiological levels of ketones developed as a result of carbohydrate restriction.

[0005] However, even these successful diets rely upon blunt force, one-size-fits-all approaches. In the Atkins diet, carbohydrate-containing foods are all but eliminated in the early stages of the regimen. Ketone levels may be measured in the urine in order to determine when a ketogenic state has been achieved. This crude and relatively inaccurate monitoring of urine ketone levels is sometimes employed to provide guidance to the user on how much carbohydrates may be allowed back into the diet.

[0006] This uniformly severe degree of carbohydrate restriction is necessitated by the lack of accurate, personalized and physiologically derived indicators of the person's response to the diet. If it is unknown how someone will react to the diet, a large buffer must be used to ensure the diet works for as large a cohort as possible (in effect, punishing the many for the sins of the few). Unfortunately, such extreme measures tend to also discourage people from persisting with the diet. Additionally, without tangible and measurable indicators of metabolic function, users are left with weight tracking and subjective feedback as their only indicator of diet success.

[0007] Lastly, with most ketogenic diets, many physicians and patients are concerned that a high protein or fat intake may be unhealthy. Conventional wisdom suggests that a low fat diet is best for overall health, and particularly heart health. By tying the macronutrient composition of a weight loss regime to factors known to indicate risk of disease, an individual may justifiably feel reduced anxiety that a low carbohydrate diet is negatively impacting their health.

[0008] It is therefore apparent that an urgent need exists for objective methods for generating dietary guidance, and particularly guidance which is tailored to each individual via physiological data. Such methods would be able to provide individuals and physicians a powerful tool for weight loss, disease prevention and maintenance of a healthy diet.

SUMMARY

[0009] To achieve the foregoing and in accordance with the present invention, we propose methods for using specific levels of a person's fatty acids for generating dietary guidance. Such methods enable individuals to tailor their diets to their carbohydrate tolerance levels, and more effectively reach their goals. Moreover, the current methods of generation of dietary guidance may be employed by physicians to provide means to treat or prevent diseases such as type-2 diabetes.

[0010] In some embodiments, the method comprises comparing at least one biomarker for an individual against at least one threshold. This comparison provides a score for the individual's risk of developing a pathology, such as type-2 diabetes or weight gain. The biomarkers may be fatty acids, generally, and palmitoleic acid (POA) and/or di-homo gamma-linolenic acid (DGLA) in particular.

[0011] In some embodiments, samples are collected from the individual and are used to analyze the levels of the biomarkers. The samples can be any of whole blood, serum, plasma, and buccal mucosa cells, for example.

[0012] If the level of palmitoleic acid and/or di-homo gamma-linolenic acid are above the threshold, this indicates that carbohydrate intake is above the individual's metabolic tolerance. Additionally, if it is known that the individual is already on a low carbohydrate diet, elevated levels of these biomarkers may instead indicate that carbohydrate needs to be restricted further and/or the protein intake is above the individual's metabolic tolerance. Thus, dietary guidance may be developed by contrasting the biomarker levels and the dietary information of the individual.

[0013] Likewise, by repeatedly analyzing samples from the individual, trends for palmitoleic acid and/or di-homo gamma-linolenic acid may be identified. Increasing trends of these biomarkers may likewise be indicative of excess carbohydrate and/or protein intake.

[0014] Note that the various features of the present invention described above may be practiced alone or in combination. These and other features of the present invention will be described in more detail below in the detailed description of the invention and in conjunction with the following figures.

BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order that the present invention may be more clearly ascertained, some embodiments will now be described, by way of example, with reference to the accompanying drawings, in which: [0016] Figure 1 is the chemical structure of the first biomarker of interest, a fatty acid known as palmitoleic acid;

[0017] Figure 2 is the chemical structure of the second biomarker of interest, a fatty acid known as dihomo-y-linolenic acid;

[0018] Figure 3 is an example flow chart for the process of biomarker isolation from a blood sample, in accordance with some embodiments;

[0019] Figure 4 is an example flow chart for the process of biomarker isolation from a cheek cell sample, in accordance with some embodiments;

[0020] Figure 5 is an example functional block diagram illustrating users engaging a dietary guidance generator for producing physiologically tailored user guidance, in accordance with some embodiments;

[0021] Figure 6 is an example flow chart for the process of generating dietary guidance, in accordance with some embodiments;

[0022] Figure 7 is an example graph illustrating the biomarker response to

carbohydrate intake for multiple individuals, in accordance with some embodiments; and

[0023] Figure 8 is an example graph illustrating the biomarker response to protein intake under low carbohydrate conditions, in accordance with some embodiments.

DETAILED DESCRIPTION

[0024] The present invention will now be described in detail with reference to several embodiments thereof as illustrated in the accompanying drawings. In the following description, numerous specific details are set forth in order to provide a thorough

understanding of embodiments of the present invention. It will be apparent, however, to one skilled in the art, that embodiments may be practiced without some or all of these specific details. In other instances, well known process steps and/or structures have not been described in detail in order to not unnecessarily obscure the present invention. The features and advantages of embodiments may be better understood with reference to the drawings and discussions that follow.

[0025] Various dieting methods are known for the treatment of obesity, diabetes, high cholesterol and high triglycerides. It is well known in the medical community that the first step to follow for dieting is to reach the body normal weight. It is also well known that weight reduction into the normal range of body weight prevents the occurrence of most clinical complications of obesity. Furthermore, as clinical symptoms and the general condition of diabetic patients improves through dieting many diabetics become less reliant on diabetic medications.

[0026] The present invention relates to novel means and methods for generating dietary guidance for an individual, as well as managing the risk of diabetes and weight gain. These methods may be particularly useful in the context of a weight loss regime or health driven lifestyle change. The methods may also be useful for normal weight individuals with insulin resistance. Such methods enable patients and other users to objectively tailor their dietary intake in response to their personal physiological changes in order to effectuate healthy weight loss and disease prevention.

[0027] Note that while much of the discussion contained herein relates to weight loss guidance for the users, it is entirely possible that the methods disclosed herein are equally useful for disease screening, disease prevention regiments, physician information, and generation of a diet for maintaining or even determining a healthy means for gaining weight.

[0028] The following description of some embodiments will be provided in relation to numerous subsections. The use of subsections, with headings, is intended to provide greater clarity and structure to the present invention. In no way are the subsections intended to limit or constrain the disclosure contained therein. Thus, disclosures in any one section are intended to apply to all other sections, as is applicable.

I. BlOMARKERS

[0029] To facilitate the discussion, Figure 1 is the chemical structure of the first biomarker of interest, a fatty acid known as palmitoleic acid (POA). Palmitoleic acid, or (X)- 9-hexadecenoic acid, is an omega-7 monounsaturated fatty acid with the formula

CH₃(CH₂)₅CH=CH(CH₂)₇COOH that is a common constituent of the glycerides of human adipose tissue. It is biosynthesized in the liver from mainly carbohydrate substrates, with the last step being the production of POA from palmitic acid by the action of the enzyme delta-9 desaturase. It is present in all tissues, but generally found in higher concentrations in cheek cell membranes than in the serum or the liver.

[0030] POA is an indicator of the conversion of carbohydrates into fat. POA increases when the body cannot immediately burn as glucose or store as glycogen all of the carbohydrates being eaten. As such, POA is an early indicator that an individual's body is struggling to handle the dose of carbohydrate being consumed. In the past, elevated POA has been identified as an important indicator of obesity, and a risk factor for obesity related diseases, such as diabetes; however, until now, the levels of POA have not been analyzed to determine an individual's response to a dietary intake in a dynamic and prospective manner.

[0031] Many current leaders in the field of nutrition and metabolism claim that POA is a beneficial 'lipokine'. Based upon tissue culture and animal studies, they report that POA is associated with improved cardiac health, reduced inflammation and insulin resistance. While there are no published human studies showing that dietary POA supplementation reduces inflammation or insulin resistance, there is nonetheless a vigorous move to market serum POA testing and dietary POA supplements. The systems and methods disclosed herein challenge this conventional wisdom, and generate dietary guidance that is in complete opposition to the accepted conventional wisdom. As such, the methods of generating dietary guidance, as disclosed herein, are clearly unique and not readily evident.

[0032] Secondly, Figure 2 is the chemical structure of the second biomarker of interest, a fatty acid known as dihomo-y-linolenic acid. Dihomo-y-linolenic acid (DGLA) is a 20-carbon ω^~6 fatty acid. DGLA is a carboxylic acid with a 20-carbon chain and three cis double bonds. The first double bond is located at the sixth carbon from the omega end. DGLA is the elongation product of γ-linolenic acid (GLA; 18:3, ω^~6). GLA, in turn, is a desaturation product of linoleic acid (18:2, ω^~6). DGLA is made in the body by the elongation of GLA.

[0033] Like POA, DGLA is an early indicator that the body is struggling to efficiently metabolized its current level of carbohydrate intake. Unlike POA, however, DGLA is not created as a byproduct of carbohydrate metabolism (i.e., the conversion of these excess carbohydrates into fats). Instead, DGLA is an intermediate product in the omega-6 anabolic pathway leading to arachidonic acid (AA, 20:4n-6). Arachidonic acid is an important regulator of genes controlling lipogenesis, but is also highly vulnerable to destruction by reactive oxygen species (ROS, aka oxygen free radicals). When dietary carbohydrates are consumed beyond an individual's tolerance, ROS production increases, AA is destroyed, and thus blood and tissue levels of DGLA increase as the omega-6 anabolic pathway accelerates AA production.

[0034] Thus, DGLA may also be utilized as a biomarker of the efficacy of a dietary regime. But because it reflects a different effect on fatty acid composition (i.e., stress on omega-6 essential fatty acid metabolism) than that of POA reflecting conversion of carbohydrate to fat, these two biomarkers are relatively independent indicators of

carbohydrate intolerance. As such, an assay using both biomarkers has the potential to be more powerful than either fatty acid alone.

[0035] What makes POA and DGLA such powerful tools as biomarkers is that two individuals, consuming the same diet, and generally having the same level of activity, may have very different responses to the same carbohydrate intake. Some individuals, through their unique physiology are more tolerant to carbohydrates, whereas others may be far more sensitive/intolerant. As such, simply going on a "low carb" diet may be unnecessarily strict for some, and insufficient for others to effectuate weight loss, disease prevention, or other desirable outcomes.

[0036] Turning briefly to Figure 7, the differing response to the biomarkers is provided in an example graph 700. In this example, three individuals' responses (biomarker concentration 710) to carbohydrate intake 720 are presented. The first individual, depicted as the plotted line 730, has a more sensitive reaction to carbohydrates than the others. As the carbohydrate intake increases, this first individual rapidly begins to show signs of

carbohydrate intolerance, thereby causing the biomarker concentration in that individual's body to increase rapidly. The second individual has a more muted response to increased carbohydrate intake, as depicted in plot line 740. The third individual is shown to be relatively tolerant to increased carbohydrate intake, as depicted in plot line 750.

[0037] Also illustrated in this example graph is a threshold 760 at which the biomarker concentration must stay below in order to ensure that the individual is maintaining the desired diet. This threshold may be determined as an absolute number or a previous value obtained from an individual. Thus, the first individual will require a far more carbohydrate restricted diet as compared to the second or third individual, in order to maintain the same efficacy of the diet. Likewise, the third individual may be able to have greater leniency in his carbohydrate intake to achieve similar results.

[0038] In some embodiments, the threshold used to compare against biomarker levels may be generated by taking a baseline of the biomarker from the individual, and subsequently attempting to reduce the baseline to a defined percentage of the steady state. Alternatively, the threshold may be developed by having the individual initially strictly restrict carbohydrate intake for a set period, and testing for biomarker levels. This measure of biomarkers may constitute a target level and the threshold may be set as being within a defined range about the target (i.e. within 120-140% of the target number). In yet other embodiments, the biomarker levels may be continuously monitored, and only sudden increases in biomarker levels are noted as exceeding the threshold. An in yet other embodiments, biomarker levels for a cohort of individuals may be utilized to provide a threshold level for the individual.

[0039] A table provided below presents example biomarker concentrations in cheek cells and serum, and potential mechanisms for calculating possible thresholds. Note that this table is purely illustrative in nature and is not intended to adversely limit the scope of this disclosure. For example, example thresholds are given for 40^th percentile of a cohort, and 125% of the restricted carbohydrate levels. These could just as easily be the 33^rd percentile of the cohort's biomarker levels and 110% or 150% of the restricted diet biomarker levels. The example table is provided below:

CE = cholesterol esters

[0040] In this manner the efficacy of a particular diet may be assessed using either of the two above identified biomarkers. Additionally, the diets may then be altered to ensure that it is effective in the long term, and can likewise be tailored to address differing goals. For example, an individual attempting to lose weight may have a lower biomarker threshold than someone who is at risk for diabetes, and who wishes to eat a diet that reduces the risk of that pathology, but still wishes to maintain a steady weight.

[0041] To make matters more complicated, POA and DGLA biomarkers are sensitive not only to carbohydrate intake, but may also be influenced by protein intake. Turning to Figure 8, an example graph of biomarker response to protein intake, when already on a restricted carbohydrate diet, is provided. As with the previous examples, each individual has unique physiology that causes the shape of their response curves to differ from that of another individual. In the context of a low carbohydrate ketogenic diet, increasing dietary protein increases serum insulin which is also a signal for increased lipogenesis. However, generally, the biomarkers are most heavily influenced by carbohydrate intake, and less so by protein intake.

[0042] In the example graph 800, two axis are provided: the level of protein intake

820, and the level of the biomarker 810. As with the previous graph, the biomarker may be either of POA or DGLA. The curve 840 indicates this individual's biomarker response to increasing protein consumption while restricting carbohydrate intake.

[0043] The biomarker level is lowest when the individual is consuming a low carbohydrate and low protein diet. As protein intake increases, the level of the biomarker increases, but at a more subdued pace than if carbohydrate intake were to increase. By delineating a biomarker threshold, as indicated previously, an individual may customize the diet by balancing out fat, protein and carbohydrate intake, in order to meet the biomarker requirements for efficacy.

II. MEANS OF SAMPLING

[0044] In order to screen for dietary efficacy, in near real time, it is important that the sample is taken from tissue that is representative of the recent fatty acid activity in a patient's body. While sampling fat tissue is possible, often these long lived tissues are not reflective of short term changes to metabolism (in addition to being more invasive to collect). The levels of fatty acids in blood, or other transient tissue is often more preferable for determining short term changes and responses to diet.

[0045] Figure 3 is an example flow chart 300 for the process of biomarker isolation from a blood sample, in accordance with some embodiments. In this example, the blood is collected from the individual (at 310) via finger prick or hypodermic needle. If by finger stick, a drop of blood adsorbed onto filter paper is extracted by the method of Bligh/Dyer, the lipid soluble compounds trans-methylated with sulfuric acid in methanol followed by analysis by gas chromatography. If by hypodermic phlebotomy, the plasma is separated (at 320) Extracted by the method of Bligh/Dyer and phospholipids, triglycerides, and cholesterol esters separated by thin-layer chromatography (at 330). These three fractions are then separately transesterified using sulfuric acid in methanol (at 340). The resulting fatty acid methyl esters may then be quantitated via gas chromatography (at 350) in order to determine levels of the particular biomarkers of interest.

[0046] Like blood, cheek cells are also well suited for sampling as they are readily collected without any discomfort, they can be collected by the individual at their home, and cheek cells replace themselves every few days which ensures that the cells reflect the individual's metabolism over a short time period. Lastly, cheek cells are highly

representative of serum fatty acid levels, and are well suited for determining biomarker levels accurately. Figure 4 is an example flow chart 400 for the process of biomarker isolation from a cheek cell sample, in accordance with some embodiments. In this method, the cheek cells are collected by a simple swabbing of the inside of the mouth (at 410). This may be performed by the individual in their own home, and the swab may be shipped to the laboratory for analysis. The cheek cells are extracted by the method of Bligh/Dyer, the lipid soluble compounds trans-methylated with sulfutic acid in methanol followed by analysis by gas chromatography (at 440) in order to determine levels of the particular biomarkers of interest, in the same manner as the blood sample.

[0047] Exact methods of fatty acid extraction, separation, and gas chromatography analysis for determining fatty acid content are known and published by us, and it is within the scope of this disclosure to include any known deviations of sampling and fatty acid characterization protocols. For example, alkali treatment followed by HPLC may

alternatively be employed to isolate the fatty acids.

[0048] Further, it is considered that there are an number of other established methodologies for determining fatty acid levels within tissue samples, including but not limited to Methanol precipitation followed by gas chromatography, other HPLC techniques, and mass spectroscopy. It is considered that all such methods of sampling and analyzing fatty acids within the scope of this disclosure.

III. METHODS FOR GENERATING DIETARY GUIDANCE

[0049] Now that the biomarkers of interest have been discussed in sufficient detail, as well as techniques for sampling, attention may be turned to Figure 5 which provides an example functional block diagram 500 illustrating an individual 510 engaging a dietary guidance generator 550 for producing physiologically tailored user guidance 560, in accordance with some embodiments. Such a system requires that the user provides information regarding the diet 540, and one or more tissue samples in order to generate appropriate guidance. In addition, the guidance generator 550 may require user goal inputs in order to better tailor the guidance. For example, an individual 510 with a particular diet may receive different guidance if, for example, they are attempting to maintain a weight versus actively lose weight, or they engage in high volume of exercise. [0050] In this example diagram, the individual 510 supplies the tissue sample to the sample collector 520. Samples may include tissue biopsy, blood sample, or cheek cell swab, as previously discussed. The collector may be any vial, swab, biopsy needle, or appropriate container. The sample is then supplied to a sample analyzer 530 for characterization of the biomarkers.

[0051] As discussed above, the sample analyzer 530 may include several pieces of analytical equipment including a chromatography device, as well as chemical agents and other laboratory equipment. Sample analysis may employ technician input, or automated liquid handling, as is known in the art. The end result of the sample analysis is a reading of the biomarker of interest. As indicated above, POA and/or DGLA are both biomarkers of interest for the generation of dietary guidance.

[0052] After the biomarkers are characterized, the guidance generator 550 may compare the biomarker levels to the dietary data 540 in order to build appropriate dietary guidance 560.

[0053] Figure 6 is an example flow chart 600 for the process of generating dietary guidance, in accordance with some embodiments. In this example process the user sample is collected (at 610) as discussed previously. The sample is processed for the relevant biomarker(s) (at 620), and the levels of the biomarker(s) is compared to a target threshold (at 630). As discussed before, the threshold for the biomarker(s) may be dependent upon the individual's goals. Weight loss, weight gain, weight maintenance, disease treatment and disease prevention may each have differing thresholds for the biomarker(s).

[0054] If the biomarker is below the threshold, then the individual is meeting or exceeding their dietary goal and no further action is needed. However, if the POA and/or DGLA biomarker is above the desired threshold, then another inquiry is made as to the user's carbohydrate intake (at 640).

[0055] As discussed previously in relation to Figure 8, POA and DGLA are impacted not only by carbohydrate levels, but also the levels of protein consumed. A higher than desired POA or DGLA level typically indicates that too much carbohydrates are being ingested, and thus carbohydrate intake is reduced (at 650) to fix the high biomarker levels; however, if the individual's dietary data suggests that carbohydrates are already greatly restricted, the culprit may instead be protein. If this is the case, then protein intake is reduced (at 660). [0056] Since every individual has differing sensitivities to carbohydrates and to protein, the above guidance allows each individual to tailor their dietary intake of carbohydrates, proteins and fats in order to ensure maximal efficacy of their diet.

[0057] In sum, the present invention provides methods for providing dietary guidance. Such methods enable individuals to tailor their diets to their carbohydrate tolerance levels, and more effectively reach and to sustain their dietary goals. Moreover, the current methods of generation of dietary guidance may be employed by physicians to provide means to treat or prevent diseases such as type-2 diabetes.

[0058] While this invention has been described in terms of several embodiments, there are alterations, modifications, permutations, and substitute equivalents, which fall within the scope of this invention. Hence, it should also be noted that there are many alternative ways of implementing the methods and apparatuses of the present invention. It is therefore intended that the following appended claims be interpreted as including all such alterations, modifications, permutations, and substitute equivalents as fall within the true spirit and scope of the present invention.

Claims

CLAIMS What is claimed is:

1. A method for generating dietary guidance comprising:

comparing at least one biomarker for an individual against at least one threshold; and scoring the individual's risk for developing a pathology.

2. The method of claim 1, wherein the pathology is type-2 diabetes or other insulin resistant condition.

3. The method of claim 1, wherein the pathology is weight gain.

4. The method of claim 1, wherein at least one biomarker is at least one fatty acid.

5. The method of claim 4, wherein at least one biomarker is the combination of palmitoleic acid plus di-homo gamma-linolenic acid.

6. The method of claim 4, wherein at least one biomarker is di-homo gamma-linolenic acid.

7. The method of claim 5, further comprising:

collecting a sample from the individual; and

analyzing the sample for the at least one biomarker.

8. The method of claim 7, wherein the sample is whole blood.

9. The method of claim 7, wherein the sample is at least one of serum and plasma.

10. The method of claim 7, wherein the sample is buccal mucosa cells.

11. The method of claim 6, further comprising:

collecting a sample from the individual; and

analyzing the sample for the at least one biomarker.

12. The method of claim 11, wherein the sample is whole blood.

13. The method of claim 11, wherein the sample is at least one of serum and plasma.

14. The method of claim 11, wherein the sample is buccal mucosa cells.

15. The method of claim 5, further comprising generating dietary guidance based upon if the level of the palmitoleic acid plus di-homo gamma-linolenic acid is above the threshold, wherein the palmitoleic acid and di-homo gamma-linolenic acid above the threshold indicates that carbohydrate intake is above the individual's metabolic tolerance.

16. The method of claim 6, further comprising generating dietary guidance based upon if the level of the di-homo gamma-linolenic acid is above the threshold, wherein the di-homo gamma-linolenic acid above the threshold indicates that carbohydrate intake is above the individual's metabolic tolerance.

17. The method of claim 5, further comprising:

receiving dietary data for the individual, wherein the dietary data indicates the individual is on a low dietary carbohydrate intake; and

generating dietary guidance based upon if the level of the palmitoleic acid plus di- homo gamma-linolenic acid is above the threshold, wherein the palmitoleic acid and di- homo gamma-linolenic acid above the threshold indicates that protein intake is above the individual's metabolic tolerance.

18. The method of claim 6, further comprising:

generating dietary guidance based upon if the level of the di-homo gamma-linolenic acid is above the threshold, wherein the di-homo gamma-linolenic acid above the threshold indicates that protein intake is above the individual's metabolic tolerance.

19. The method of claim 7, further comprising:

repeatedly analyzing samples from the individual; and

generating dietary guidance based upon if the level of the palmitoleic acid plus di- homo gamma-linolenic acid increases over the repeated analysis, wherein the increase in palmitoleic acid plus di-homo gamma-linolenic acid indicates that carbohydrate intake is above the individual's metabolic tolerance.

20. The method of claim 11, further comprising:

repeatedly analyzing samples from the individual; and

generating dietary guidance based upon if the level of the di-homo gamma-linolenic acid increases over the repeated analysis, wherein the increase in di-homo gamma- linolenic acid indicates that carbohydrate intake is above the individual's metabolic tolerance.