The Nexus Gene Chip contains a very large number of probes that link with specific genetic variants throughout the entire genome, including single-nucleotide polymorphism (SNP), deletion-insertion polymorphisms (DIPs or InDels), repeats, and copy number variants (CNV), as well as the mitochondrial chromosome. This allows Existence to detect a wide breadth of variants throughout the human genome and to analyze the risk for hundreds of rare and common diseases with a single test. As a result, we are able to determine with an extremely high degree of accuracy whether or not one or more specific gene sequences known to be associated with disease are present. Our gene chip provides information only on those variants known to be the most important for your health and has built-in cross-checks to improve accuracy and reliability beyond the typical gene chip results.

From the very beginning, the Nexus Gene Chip was created with a single purpose: to empower people over disease. The result is a first-of-its-kind gene chip that allows Existence to efficiently test for more genes and analyze the risk for more diseases and traits than ever before possible.

For monogenic phenotypes, no algorithm is utilized and instead an individual may have one of three possible outcomes: non-carrier, carrier, or most likely affected. Existence does take into consideration penetrance and expressivity on a variant-by-variant basis, and when this information is available, our reports will specifically note whether a phenotype is likely to be observable. Degree of severity may also be available for some variants that cause monogenic phenotypes. This determination may be based on information about the specific variant(s) or may be ascertained by using Existence’s Reflex analysis to analyze other genes and their variants shown to influence phenotype severity for the original genetic variant-phenotype association.

For multifactorial phenotypes, Existence does not use an algorithm when published studies provide specific information on a set of variants that are associated with a specific phenotype. For example, in the evaluation of prostate cancer, studies may have evaluated a set of variants for risk, indicating specific risk according to the number of alleles present for each of the variants in the set. For other multifactorial phenotypes, an industry standard multiplicative algorithm is used when two or more variants associated with the same phenotype that are not in linkage disequilibrium are detected.

When known, non-genetic factors may also be included in the analysis process. For example, a genotype may be associated with different levels of risk for a phenotype based on one or more non-genetic factors, such as whether there is a family history of the disease, whether the person is a cigarette smoker, or based on the person’s BMI. Existence integrates these non-genetic factors into our analysis whenever possible in order to provide health care professionals with a comprehensive analysis of risk.

Existence takes into account some non-genetic factors when conducting our analysis of disease. As discussed in the Algorithm Information section above, when research has shown that the risk associated with a specific allele, genotype, and/or haplotype is dependent upon a definable non-genetic factor, such as family history of a disease, cigarette smoking status, BMI, age, etc., this non-genetic information is included when calculating risk. At times, non-genetic factors may also be taken into consideration by our Disease Matrix and Reflex analysis technology. For example, if a person is a smoker, that might activate a part of the Disease Matrix and ensuing Reflex analysis for a phenotype that would otherwise remain quiescent. This allows for genetically tailored prevention also to be based on certain non-genetic factors.