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Have you ever wondered why you still survive and stay strong although often times, probably more often not getting 2,000 calories per day.

According to daily caloric recommendations by the USDA and FDA and other respected organizations, the average person should consume 2,000 and in some cases 2,500 calories per day.

The recommendation goes on the suggest a certain percentage of these calories should come from... Carbohydrates, some proteins, some fats...

Since everyone and I mean every person or individual is very different from the next person, there is no blanket, cookie cutter correct answer. If you were a twin or triplet still your DNA makeup will be different and require different degrees of calories and nutrients. You are you unique in every way. Although genes and the evidence of similar or the same genes are and can be convincing physiologically we are all very different.

Then we must take into account...

  • Our average daily needs

  • Our average daily expenditure

  • Subjective expenditure

  • Sedentary moments in our day

  • Dispositions

  • Predispositions

  • Contraindications

  • Special population relativity

You see where this is going? That's why my matrix is not just necessary or critical it is absolutely ESSENTIAL!

Apollos Genetics offers a variety of genetic tests, including

Metabolic Health, Nutritional Needs, Weight Management, Heart Health, Bone Health, and General Fitness Health.

Learn more about our Genetic testing by clicking the link below.

Definition of Genetic Fitness

The reproductive success of a genotype, usually measured as the number of offspring produced by an individual that survive to reproductive age relative to the average for the population.

Introduction To Genetic Testing Awareness

Basic Genetics

History of Genetic Testing

Specialty Genetics 


The p-value is a statistical measurement that describes the probability of occurrence of a specific outcome (Bush, 2012). Researchers and doctors use the p-value as the “significance threshold.” In general, the lower the p-value, the stronger the association and the risk of a false positive is low.

Most genomic researchers have agreed that a p-value of 10-8 is the “significance threshold” they believe is most likely to be true when associating a SNP with a specific disease (Panagiotou, 2011). Associations with a p-value of 10-6 and 10-7 are considered borderline, and those with a higher p-value > 10-5 are felt to have a high false discovery rate (FDR) (Panagiotou, 2011). 

Odds Ratio ​

An odds ratio (OR) is a measurement of effect size, or relative risk (Bush, 2012). In genetic terms this means how much a SNP will cause or prevent a disease or trait from occurring. An odds ratio of 1 is neutral, meaning the SNP does not impact the disease or trait. An odds ratio higher than 1 is related to an increased risk for disease. A lower odds ratio means the SNP has a protective effect (Bush, 2012).

Most SNPs for multi-factorial diseases have a modest effect and only increase risk slightly above the general population risk. This is important because it can help you decide if testing for a particular SNP has any value, even when there is a strong association.

For example, in a study by Nakajima and colleagues published in 2014, a variant called rs2423294 in the HAO1 gene was found to be associated with ossification (hardening) of the posterior longitudinal ligament of the spine. This disease is most common in Asians, and the study was across a large Asian population, replicated, and a p-value of 10-13 was identified. The odds ratio was 1.41, meaning a person with this variant was 1.41 times more likely to develop this type of spinal ligament ossification.

The lifetime risk for a person of Asian descent to develop this disorder is 2.4% (Knipe, 2015). If a person has this genetic variant, however, the lifetime risk becomes 3.5% (Nakajima, 2014). The lifetime risk for Caucasians is 0.2% (Knipe, 2015). Because the Nakajima, 2014 study did not include Caucasians, this data cannot be used to modify risks for Caucasians.

Another example is the genetic variants rs10757274 chromosome 9 (McPherson, 2007). In large studies that have been replicated, this have been found to be associated with coronary artery disease with a p-value of 10-45 (Hindorff 2015) and when found with another SNP, called rs2383206, the risk of coronary artery disease in Caucasians increases by 30-40%.

For the 25% of Caucasians that carry this SNP combination, their lifetime risk of coronary artery disease changes from 49% in men and 32% in women (Price, 2015), to as high as 67% and 45% respectively.

Clinical Utility

“Clinical utility,” as defined by the American College of Medical Genetics, is when a given intervention (in this case, genetic information) will lead to an improved health outcome, such as a diagnosis, treatment, management, or prevention of a disease. Genetic professionals and other health care providers are most interested in supporting testing where individuals, families or society obtain some benefit from the knowledge provided by a genetic test.

For example, a genetic test for the variant rs17822931 in the ABCC1 gene determines if your earwax is wet or dry. There is no specific clinical utility in knowing that information and is easily observable, so most healthcare professionals would not recommend this test to their patients, friends or family. Your earwax genotype could be a fun fact to know, though, and might be good lab exercise for students to do on their own DNA (Shah, 2013). Determining clinical utility isn’t always easy.

Another aspect of clinical utility is considering the risk/benefit ratio. The Food and Drug Administration (FDA) regulates genetic testing, and they have shut down testing that they deemed too risky. For example, in November of 2013 the FDA temporarily shut down a company that provided genetic information about breast cancer risk and blood thinning medication dosages until the company could establish the validity of their testing (Guiterrez, 2013). 

ACE: Deletion/Insertion

This variant is also represented as D or I. A person’s genotype can be DD, DI, or II. The ACE gene helps regulate blood pressure and cardio/respiratory efficiency. The I variant is common, and 11-25% of individuals are II. In a recent meta-analysis of over 360 studies that included the ACE variant, have II was strongly associated with performance in endurance athletes with an odds ratio of 1.35 (Ma, 2013).

It has been suggested that this information can be used to help athletes select a sport or to modify training to take into account if an individual is more likely to have a power or endurance muscle type (Kambouris, 2012).

This is an example where clear p-values were not provided, but the number and size of studies suggest the association is strong. The clinical utility will depend on the resources the athlete has to tailor training that favors power or endurance, or if is practical to use a genetic test to pick a sport.

AMPD1: rs17602729

The AMPD1 gene is important in processing ATP. People that have two copies of this variant are missing this enzyme which causes adenosine monophosphate deaminase deficiency. Most affected people don’t have symptoms, but some will have muscle pain and cramping after exercise, or prolonged fatigue and weakness after physical activity.

Symptoms begin in childhood or early adulthood. About 1 in 50 Caucasians and 1 in 40,000 Africans have adenosine monophosphate deaminase deficiency. It is very rare in Asians. Individuals with only one copy of the variant occasionally report symptoms.

The genetic research around this disorder pre-dates GWAS studies and has been verified through multiple methods. There is no specific approved treatment (Genetics Home Reference 2015).

In this example, there is no doubt that the genetic variant causes a specific muscle disorder, but it can’t be predicted who will express symptoms and there is no treatment available if you do have exercise intolerance and cramping.

Would knowing this information be a help or a hindrance to someone who tolerates exercise well? Would it be useful to someone who experiences extreme fatigue and muscle cramping after exercise and doesn’t know why? These are important clinical utility questions that have many facets to debate.

COL1A1: rs1800012

The COL1A1 gene makes a protein that contributes to the structure of collagen, bone, tendons, ligaments, skin, and the sclera (white part of the eye.) Disruptions or weaknesses to COL1A1 is associated with a number of disorders impacting these support structures (Genetics Home Reference, 2015). The rs1800012 variant contributes to a number of traits of interest to athletes and exercise enthusiasts. Here are two:


In a meta-analysis of 32 studies of >25,000 people, people with two copies of the rs1800012 variant called TT had lower bone mineral density, especially at the hip with a p-value of 10-6. The overall fracture risk for people with TT in this analysis was 1.3 times higher compared to people who did not have TT (Jin, 2011).

This example provides large studies, a good p-value, and at risk individuals can monitor their bone health by engaging in bone mineral density testing. They can also engage in exercise that builds muscle to stabilize bones, and maintain a healthy weight. The lifetime risk for men and women to have an osteoporotic fracture is 20% and 30% respectively.

Having this variant increases the risk to 26% and 43% respectively. Is that a large enough change to incur the costs and risks of regular bone mineral density testing? This change in risk does not change the recommendations to exercise regularly and maintain a healthy weight, but it might change a person’s motivation or exercise regimen.

Cruciate Ligament Ruptures:

In a review of 3 studies that examined the role of this variant with cruciate ligament ruptures that included a little more than 500 athletes, individuals who were TT were under-represented in the cruciate ligament tear and Achilles tendon rupture group, suggesting that TT is protective against these injuries.

The respective p-values and odds ratios were reported as p=.0002 and OR=10, and p=.0001 and OR 15. This means that individuals who do not have TT who are active have a higher risk of these injuries, related to their activity, than inactive or TT people (Collins, 2010).

This is an example of a low p-value with a small sample size. As more studies are conducted the meaning and implication of this result could change over time. The clinical utility is uncertain as it seems that the intervention would be based on a person’s activity, which is what you would do anyway without a test.

This also demonstrates that many variants impact a biological system and can be associated with more than one disease or trait. This puts a burden on the laboratory and practitioner to decide what to report, what not to report, and why.

FTO: rs17817449

The function of the FTO gene is unknown, but it has been clearly established to have a role in body mass. The rs17817449 variant has been strongly associated with obesity in a study of Caucasians with over 1,000 test subjects, replicated in another 2,500. The p-value reported is strong at 10-12 and the odds ratio reported for early onset extreme obesity is 1.67 (Wang, 2011).

Data for this variant is borderline. The study included Caucasians only, and the sample size is small for a common variant. However the p-value is excellent, and the odds ratio suggests a moderate increased risk. The clinical utility is unclear. This might be beneficial information for someone who has experienced obesity, or it may motivate behavior that focuses on maintaining a healthy lifestyle.

VDR: rs2282679

The VDR gene makes the vitamin D receptor. Vitamin D is important in bone mineralization. Low vitamin D levels have been associated with osteoporosis, rickets, and fractures. The variant rs2282679 is also called the Fok1 variant, and is found in about 30% of people.

A large study of over 16,000 Caucasians and replicated in a co-hort of >17,000 individuals found that rs228679 was significantly associated with vitamin D levels with a p value of 10-109. Individuals who had at least one copy of this variant had up to 2.5 times lower vitamin D than those that didn’t (Wang, 2010).

The genetic variants that cause low vitamin D have been studied extensively for links to bone fractures, lumbar disc degeneration, fatigue, autoimmunity, and a number of other disorders.

Results are inconsistent between researchers and studies are complicated by the many variables that impact vitamin D such as sun exposure and diet (Wang, 2010). Individuals that have this variant should have their vitamin D levels checked regularly by their doctor, who will discuss supplementation needs if needed (Kennel, 2010).

This final example provides the clearest data, although only for one ethnic group. The p-value is excellent, the right number of people was studied, and follow up is simple and clear with limited risk.

Genetic tests available on the market today fall into the following common categories:

Tests for DNA structural problems. Chromosomes can lose or gain pieces during cell division or rearrange their structure. If this happens at conception, a baby can be born with disorder like Down Syndrome, which is an extra chromosome. If this happens after conception in a tissue of the body, like the blood or digestive system, cancer can result.

Tests for specific DNA variants for a specific disease. This is the most common type of test available today. For example, cystic fibrosis is a lung disorder that impacts about 1 in 2,500 individuals. Carrier screening is offered prenatally to parents to determine their risk of having an affected child. This test focuses only on known mutations, in this case cystic fibrosis mutations.

SNP Array. Technology has advanced to allow laboratories to identify the nucleotide for over 1 million SNPs at one time. The purpose of this test is to identify small deletions on a chromosome that can’t be found any other way, and some groups are starting to filter this data for disease associated SNPs and create informational reports for patients on their predisposition to disease. In addition, interesting traits can be learned through such testing, such as if you have a variant that prevents you from tasting certain bitter substances.

Gene Specific Sequencing. Many labs offer gene sequencing. In this test, only the genes known to cause a specific disease are sequenced, nucleotide by nucleotide, to find variants that can cause illness. BRCA1 and BRCA2 testing is conducted by gene sequencing.

Exome Test. An exome test sequences only the exons, the part of the gene that “expresses” protein. This represents about 1% of the all the DNA (genome) and is over 3 million pairs of nucleotides. The sequencing is actually the easy part - reassembling the DNA into a human readable format that can be analyzed for meaningful variation is the real challenge and time consuming aspect, not to mention the data storage required for the effort. Currently exome testing is primarily used to solve “mystery diagnoses” for rare childhood disease, but companies are starting to offer exome testing to healthy individuals to identify common variants that may pre-dispose them to disease in the future.

Scientist and laboratories are now offering genetic tests for athletes, fitness enthusiasts, and those seeking out weight management (Kambouris, 2012); which is where Apollos and the NEO GENE MATRIX options come into play. You may have seen some of these tests in the news. These test are often offered through physicians and wellness spas, and provides information on how the body processes carbohydrates, fats, and vitamins. It also provides information about muscle strength and performance type, identifying if individuals are endurance or power athletes. From these tests one get an answer based on their workout data, food consumption, and a variety of lab test results . GENETIC FITNESS MATRIX offers multiple options for practical purposes to the end of eating and exercise perfection.


Genetic testing is growing in popularity and I suspect that within 5-7 years the market will be flooded with testing options. Our The Genetic Fitness Matrix was born from many different secret algorithms derived from DNA / genetic testing results so that the practical side of using this data makes usable and applicable sense to the end user.

We are proud to be the very first globally to offer this product we call the Genetic Fitness Matrix. Join us now while its rather inexpensive.


Webborn N, Williams A, McNamee M, et al. Direct-to-consumer genetic testing for predicting sports performance and talent identification: Consensus statement Br J Sports Med 2015;49:1486–1491.

Mcmahan, I. (2015). The Genetics of Being Injury Prone The Atlantic Journal as accessed on November 6, 2015

Taylor, T. (2015) How far are athletes willing to go to gain an edge on the gridiron? Sports Illustrated as accessed on November 6, 2015

Genetics Home Reference: What is informed consent? (December 7, 2015) as retrieved from on December 14, 2015.

Consumer Access to Laboratory Testing and Information Classification: Position Paper (2012) as retrieved from on December 1, 2015

Ross, et al. Technical report: ethical and policy issues in genetic testing and screening of children Genet Med 2013:15(3):234–245

Partners in Laboratory Oversight (September, 2006) as retrieved from

on December 1, 2015

Clinical Laboratory Improvement Amendments (n.d.) as retrieved on December 1, 2015

Ahmetov II1, Fedotovskaya ON2 Current Progress in Sports Genomics Adv Clin Chem. 2015;70:247-314. 2015 Apr 11.

Kambouris, M., Ntalouka, F., Ziogas, G., & Maffulli, N. (2012). Predictive genomics DNA profiling for athletic performance. Recent Patents on DNA and Sequences, 6(3), 229-239.

Attar, A. et al. How Effective are F-MARC Injury Prevention Programs for Soccer Players? A Systematic Review and Meta-Analysis Sports Med. 2015 Sep 24. [Epub ahead of print]

Hindorff LA, MacArthur J (European Bioinformatics Institute), Morales J (European Bioinformatics Institute), Junkins HA, Hall PN, Klemm AK, and Manolio TA. A Catalog of Published Genome-Wide Association Studies. Available at: Accessed July 25, 2015

Seckington R, Powell L. HFE-Associated Hereditary Hemochromatosis. 2000 Apr 3 [Updated 2015 Sep 17]. In: Pagon RA, Adam MP, Ardinger HH, et al., editors. GeneReviews® [Internet]. Seattle (WA): University of Washington, Seattle; 1993-2015. Available from: 

Wang, T. J., Zhang, F., Richards, J. B., Kestenbaum, B., van Meurs, J. B., Berry, D., Spector, T. D. (2010). Common genetic determinants of vitamin D insufficiency: a genome-wide association study. Lancet, 376(9736), 180–188

Genetics Glossary (n.d) Retrieved July 25, 2015 from

Finegold, D. (2013) Genes and Chromosomes - Fundamentals. Retrieved October 2, 2015, from

Online Mendelian Inheritance in Man, (n.d.) Retrieved July 25, 2015 from:

Hindorff LA, MacArthur J, Morales J, Junkins HA, Hall PN, Klemm AK, and Manolio TA. (2015) A Catalog of Published Genome-Wide Association Studies. Retrieved July 25, 2015 from

Welter D, MacArthur J, Morales J, Burdett T, Hall P, Junkins H, Klemm A, Flicek P, Manolio T, Hindorff L, and Parkinson H. (2014) The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Research (Database issue): D1001-D1006. doi: 10.1093/nar/gkt1229. Epub 2013 Dec 6

Kambouris, M., Ntalouka, F., Ziogas, G., & Maffulli, N. (2012). Predictive genomics DNA profiling for athletic performance. Recent Patents on DNA and Sequences, 6(3), 229-239.

Abul-Husn, N. S. et al (2014) Implementation and Utilization of Genetic Testing in Personalized Medicine. Pharmacogenomics and Personalized Medicine 7: 227-40. doi 10.2147/PGPM.S48887

A Brief History of the Human Genome Project.(2012) Retrieved July 25, 2015 from

Genomic Medicine. (2012) Retrieved July 25, 2015 from

Genetics and Health Resources. (2015) Centers for Disease Control and Prevention. Retrieved July 25, 2105 from

Blumm KC (2015) Angelina Jolie Has Ovaries Removed After Doctor Detects Possible Sign of Early Cancer Retrieved July 25, 2015 from

Corcoran, M. (2013) Christina Applegate's Life After Breast Cancer Retrieved July 25, 2015 from

Hereditary Breast & Ovarian Cancer Program HBOC Fact Sheet (2013) Retrieved July 25, 2015 from

The Genetic Test Registry (n.d.) Retrieved July 25, 2015 from 

Proffitt, A. (2014) IBM Invests in Pathway Genomics' Watson-Powered Health App Retrieved July 25, 2015 from 

Loos RJ, et al. (2015).Advances in exercise, fitness, and performance genomics in 2014 Med Sci Sports Exer Jun;47(6):1105-12. doi: 10.1249/MSS.0000000000000645

Panagiotou, Orestis A., & John P A Ioannidis. "What Should the Genome-wide Significance Threshold Be? Empirical Replication of Borderline Genetic Associations." International Journal of Epidemiology 41.1 (2011): 273-86.

Bush, W. S., & Moore, J. H. (2012). Chapter 11: Genome-Wide Association Studies. PLoS Computational Biology, 8(12), e1002822.

Amoako, A. O., & Pujalte, G. G. A. (2014). Osteoarthritis in Young, Active, and Athletic Individuals. Clinical Medicine Insights. Arthritis and Musculoskeletal Disorders, 7, 27–32.

Castaño Betancourt, M. C., Cailotto, F., Kerkhof, H. J., Cornelis, F. M. F., Doherty, S. A., Hart, D. J., van Meurs, J. B. J. (2012). Genome-wide association and functional studies identify the DOT1L gene to be involved in cartilage thickness and hip osteoarthritis. Proceedings of the National Academy of Sciences of the United States of America, 109(21), 8218–8223.

Nakajima M. et al A genome-wide association study identifies susceptibility loci for ossification of the posterior longitudinal ligament of the spine. Nat Genet. 2014 Sep;46(9):

Knipe, H., & Gaillard, F. (2015, October). Ossification of the posterior longitudinal ligament | Radiology Reference Article | Retrieved October 29, 2015, from

McPherson, et al. A Common Allele on Chromosome 9 Associated with Coronary Heart Disease (2007) Science 8: Vol. 316 no. 5830 pp. 1488-1491

Hindorff LA, MacArthur J, Morales J, Junkins HA, Hall PN, Klemm AK, and Manolio TA. (2015). A Catalog of Published Genome-Wide Association Studies. Retrieved July 25, 2015 from: // 

DNA Microarray Technology (August 27,2015) as retrieved from on November, 8, 2015.

Price, P. Estimation of cardiovascular risk in an individual patient without known cardiovascular disease (2015) UptoDate Retrieved Oct. 29, 2015 from

ACMG Board of Directors Clinical utility of genetic and genomic services: a position statement of the American College of Medical Genetics and Genomics Genetics in Medicine (2015) 17, 505–507

Goldman, et al. Genetic counseling and testing for Alzheimer disease: Joint practice guidelines of the American College of Medical Genetics and the National Society of Genetic CounselorsGenetics in Medicine Volume 13, Number 6, June 2011

Shah, K. et al. Affordable hands-on DNA sequencing and genotyping: an exercise for teaching DNA analysis to undergraduates. Biochem Mol Biol Educ. 2013 Nov-Dec; 41(6):388-95.

Loos RJ, et al. (2015). Advances in exercise, fitness, and performance genomics in 2014 Med Sci Sports Exer Jun;47(6):1105-12

Kambouris, M., Ntalouka, F., Ziogas, G., & Maffulli, N. (2012). Predictive genomics DNA profiling for athletic performance. Recent Patents on DNA and Sequences, 6(3), 229-239.

Wang K1, Li WD, Zhang CK, Wang Z, Glessner JT, Grant SF, Zhao H, Hakonarson H, Price RA. A genome-wide association study on obesity and obesity-related traits. PLoS One. 2011 Apr 28;6(4):e18939.

Guiterrez, A. Letter to 23andMe. (2013). Food and Drug Administration retrieved on Oct. 30, 2015.

Ma, F., Yang, Y., Li, X., Zhou, F., Gao, C., Li, M., & Gao, L. (2013). The Association of Sport Performance with ACE and ACTN3 Genetic Polymorphisms: A Systematic Review and Meta-Analysis. PLoS ONE, 8(1), e54685.

Genetics Home Reference: (Nov. 2, 2015) Adenosine monophosphate deaminase deficiency. Retrieved November 8, 2015

Genetics Home Reference: (Nov. 2, 2015) COL1A1. Retrieved November 8, 2015

Jin H1, Evangelou E, Ioannidis JP, Ralston SH. Polymorphisms in the 5' flank of COL1A1 gene and osteoporosis: meta-analysis of published studies. Osteoporos Int. 2011 Mar; 22(3):911-21.

Osteoporosis Statistics (n.d.) as retrieved from November 7, 2015

Collins M1, Posthumus M, Schwellnus MP. The COL1A1 gene and acute soft tissue ruptures. Br J Sports Med. 2010 Nov; 44(14):1063-4.

Wang, K., Li, W.-D., Zhang, C. K., Wang, Z., Glessner, J. T., Grant, S. F. A., … Price, R. A. (2011). A Genome-Wide Association Study on Obesity and Obesity-Related Traits. PLoS ONE, 6(4), e18939.

Wang, T. J., Zhang, F., Richards, J. B., Kestenbaum, B., van Meurs, J. B., Berry, D., … Spector, T. D. (2010). Common genetic determinants of vitamin D insufficiency: a genome-wide association study. Lancet, 376(9736), 180–188.

Kennel, K. A., Drake, M. T., & Hurley, D. L. (2010). Vitamin D Deficiency in Adults: When to Test and How to Treat. Mayo Clinic Proceedings, 85(8), 752–758. 

(“Genetics Glossary” Retrieved from Finegold, 2013 (“The Genetic Test Registry” (n.d.) Retrieved from


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