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From genetic data to a formula: how a genotype shifts a dose
Genes show how a body processes nutrients – for life. At Novogenia, about 50 genes with three possible genotypes each feed into a formula, along with age, sex, body weight, a questionnaire on diet and lifestyle and, where available, blood values, which take precedence. An impaired gene shifts the calculated requirement within a fixed window, for example for folate or vitamin D. Each gene is backed by at least three independent studies; the doses derived from them are logical conclusions.
Folic acid needs a switch
The folic acid in food supplements is a precursor. Before cells can use it, the body converts it – all the way to methylfolate, the form that mainly circulates in the blood. One of the decisive steps is carried out by a tool whose blueprint sits in the MTHFR gene. Think of it as a light switch: folic acid is the lamp, and MTHFR turns it on.
In 1995, researchers described a common change in this gene: about 38% of the gene copies they examined carried it. The variant came with lower activity of the tool, and people with two impaired copies had significantly elevated homocysteine levels in their blood – homocysteine is a substance the body processes further with the help of active folate (Frosst et al., Nature Genetics, 1995).
Twenty years later, a meta-analysis showed the effect directly in folate status: in healthy women with two impaired copies of the MTHFR 677C>T variant, folate levels were 13% lower in serum or plasma and 16% lower in red blood cells than in women with two functioning copies – measured with the recommended microbiological method (Tsang et al., American Journal of Clinical Nutrition, 2015).
That is the bridge from genes to a formula: a genotype shifts nutrient status measurably. The logical conclusion: anyone carrying two impaired MTHFR copies has good reason to pay attention to a good folate supply. In the calculation, this enters as a higher requirement – how much higher depends on the overall picture from all the data.
Three ways genes shift requirements
Novogenia reports deliberately call genes simply “functioning” or “impaired.” That is a simplification; the technical terms are genetic variants or polymorphisms. An impaired gene can act in three ways:
| Effect | What happens in the body | Examples |
|---|---|---|
| Conversion slowed | The body turns a nutrient into its active form more slowly. | Folate, coenzyme Q10 |
| Benefit reversed | An otherwise beneficial substance becomes unfavorable for this person. | Iron, omega-3 |
| Higher requirement | More is needed for a nutrient to take full effect. | Selenium, vitamin D3 |
The second way shows why personalization works in both directions: sometimes the best response to a gene is less, not more. The third way can be observed particularly well in the blood – using vitamin D as the example.
Same dose, different effect: vitamin D
In a randomized controlled trial with 1,787 healthy adults in the United States, some participants received 1,000 IU of vitamin D3 per day for one year. With vitamin D3, vitamin D levels rose by 6.1 ng/mL on average. But there was genetics behind the average: how much levels rose depended on variants near the genes CYP2R1, CYP24A1 and VDR (Barry et al., Journal of Clinical Endocrinology & Metabolism, 2014).
These three genes sit at decisive points: CYP2R1 helps convert vitamin D into its storage form, CYP24A1 breaks it down again, and VDR is the docking site in the cells – vitamin D is the key, the receptor is the lock. If one of these tools works differently, it can take more vitamin D to reach the same level.
The logical conclusion: the same dose does not take everyone equally far. Genes that raise requirements therefore enter the calculation as a higher requirement. And this is where genes and blood values work well together: genes set the direction, a measured value shows where someone stands today – and takes precedence for its nutrient. How that works in detail is covered in From blood values to a formula.
About 50 genes, three genotypes, one questionnaire
At Novogenia, about 50 genes feed into a formula, each with three possible genotypes: two functioning copies, one functioning and one impaired copy, or two impaired copies. Mathematically, that yields 700 sextillion possible genetic profiles.
A gene is only included in the analysis if at least three independent studies support its effect. Each variant is weighted based on the scientific literature and Novogenia’s own PubMed-based literature reviews; markers with weaker evidence are weighted more conservatively.
But genes are only part of the picture. Sex, age and body weight are added, along with a questionnaire covering, among other things, fruit and vegetable intake, dairy, a vegan or vegetarian diet, smoking, alcohol, sun exposure and training. The questionnaire is the part that moves with life: anyone who goes vegan or trains more updates it – the genes stay the same.
How a genotype shifts the dose
Genetic weighting follows clear rules. This is how genes and the other data interlock:
| Situation | What the algorithm does |
|---|---|
| maximum genetic risk for a nutrient | leads to the maximum dose of that nutrient |
| below-average genetic problem | leads to a below-average dose |
| marker with weaker evidence | is weighted more conservatively |
| several areas of the analysis affect the same nutrient | the highest requirement counts |
| a blood value exists | the measured value takes precedence for that nutrient |
| calculated requirement outside the window | is set to the minimum or maximum |
This leads to a rule you should also explain to your customers: a dose can never be traced back to a single gene. A statement of the form “gene X gives nutrient Y at dose Z” would be incorrect – which is why we do not publish such statements. So MTHFR alone never sets a folate dose; it is one voice among many. The full calculation in seven steps is shown in How a personalized nutrient recipe is calculated.
Your data: raw data or a fresh saliva sample
As a DNA testing company, genetic lab or platform with genotype data, you have two routes:
- Use existing data: Raw genotype data, an SNP panel, genetic test results or an entire database can be interpreted. Whether your panel covers the genes needed is checked in the project.
- Run a fresh analysis: If data are missing, we supply saliva kits in your design, and genotyping runs in our own lab in Eugendorf. The analysis takes 4 days.
Two points are best settled right at the start. First, the purpose: the formula uses genetic traits related to nutrition and nutrients. Medical analyses belong in a physician’s hands wherever national law requires it. Second, the country: in Switzerland, genetic tests on particularly sensitive characteristics such as nutrition may only be ordered by certain health professionals, and the sample must be taken in their presence (Art. 34 Federal Act on Human Genetic Testing, GUMG). In Germany and Austria, by contrast, almost everything hinges on whether an analysis is medical; the country comparison is in Who may offer genetic tests?.
How raw data are handed over technically is covered in Data integration: raw data, interfaces, formats. And because genetic data are specially protected under the GDPR, consent for the new purpose is part of the setup – more in Data protection and roles between lab and manufacturer.
What the research supports
The building blocks of the calculation are scientifically grounded: the established reference values (D-A-CH, EFSA), the scientific literature on each genetic variant and EFSA’s safety assessments. The folate and vitamin D examples show how concretely genes shape nutrient status and the response to intake.
That gene-based recommendations can make a real difference in everyday life is also shown by an internal study on diet: in an internal Novogenia study with 302 people, participants on a gene-based diet lost around 2.4 times more weight than on a standard diet (Understanding scientific approaches). The study concerns a diet, not a food supplement – but it supports the core idea: a recommendation that matches a person’s genes can achieve more than a recommendation for the average.
For the finished, fully personalized combination product, there are no large randomized trials yet; research is evolving. That is why the rule is: the genetic traits are well documented, and the doses derived from them are logical conclusions, not scientifically proven.
How to explain it to your customers
- Personalization, not promises: Offer a transparently calculated, individually dosed formula – not a health promise.
- Authorized claims only: Health claims only in their official wording, such as “Folate contributes to normal homocysteine metabolism” (Regulation (EU) No 432/2012), and only if the conditions of use are met. More in Health claims: what you may advertise.
- Genes are not destiny: An impaired gene is not a verdict but a pointer to what is worth paying attention to.
- Explain change: The formula changes with age, with new questionnaire answers or blood values and with new scientific findings – the genes themselves stay the same.
How the dose is ultimately capped – with EFSA’s upper levels, national maximum amounts and the specifics of Switzerland – is covered in Dosing and safety: limits and rules.
Frequently asked questions
How many genes feed into a personalized formula?
Can we use the genetic data we already hold?
Does a single gene determine the dose of a nutrient?
How solid are gene-based doses?
What applies to nutrition-related genetic tests in Switzerland?
Related: From blood values to a formula · From SNP data to formula · From genetic profile to personalized supplements
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Request a project →Offer for labsNote: This guide is general information for businesses and professionals and does not replace medical or legal advice. The genetic traits determined in a genetic analysis are well documented (each gene included is backed by at least three independent studies); recommendations derived from them are logical conclusions, not scientifically proven. Regulations can change; errors and changes excepted.