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Science Standard at MyHealthChecked

How MyHealthChecked collects and validates the science behind the DNA tests.

Our main goal at MyHealthChecked is to provide recommendations based on the most validated evidence to optimise health by analysing an individual’s genetic makeup. Our Science Advisory Board Team is dedicated to assessing scientific studies focused on personalised nutrition.

Each paper providing evidence for each polymorphism is assessed according to the Q-genie framework and only those polymorphisms with highest quality evidence shown across multiple studies are included in our report.

Q-genie

Q-genie

The Q-genie framework is a well validated tool used to assess the reliability of genetic association studies. This tool assesses 11 dimensions including the rationale of the study, establishment of comparison groups (i.e. controls groups), technical and non-technical classification of the genetic variant analysed, disclosure of source of bias, statistical power and sample size, statistical methods used, inclusion of Hardy-Weinberg Equilibrium, interpretation of the results including all assumptions and interferences.

Each question is marked on a 7-point Likert scale to give a final score: poor quality, moderate quality and good quality studies. At MyHealthCheked only studies with good or moderate quality are included in the analysis.

In assessing the quality of the evidence along with Q-genie we also use the following key tools and concepts

Hardy Weinberg Equilibrium
Study Power
Genotype errors and missing data
Haplotype variation

It is recommended that nutrigenomic research should match the distribution of genotype frequencies in study samples with those the population studied. The estimated number of homozygous and heterozygous variant carriers is assessed through Hardy-Weinberg Equilibrium (HWE). Research with significant deviation from HWE can result in false positive results and impair the quality of the study. At MyHealtChecked, we aim to include studies that utilise and are in line with HWE.

Study Power / Sample size

Study Power / Sample size

Appropriate sample size is a very important aspect of a research in order to ensure sufficient power to detect the desired outcome. Any research should provide details about the sample size calculation when publishing. Without a power calculation it is difficult to interpret and draw conclusions with the results obtained. Studies with underpowered sample size indicates absence of evidence. For these reasons, at MyHealthChecked only randomised studies with details of statistical power are considered for analysis.

Genotype errors and reporting data

Transparency in reporting of genotyping protocol along with error rates is important in the detection of associations or linkage. The criteria for nutrigenomic studies that indicate a good genotyping quality are those with call rates above 95%.

95%+ call rates

Nature of genetic variant and modelling haplotype variation

Nature of genetic variant and modelling haplotype variation

In order to draw the conclusion for the MyHealthChecked report, we consider all haplotypes or Linkage Disequilibrium (LD) for each genetic variant. A haplotype is a combination of certain alleles that are neighbour genes and may be inherited together. The consideration of haplotype aims to test different numbers of SNPs to check their effectiveness with the outcome than just one single variant. Further, it improves the understanding of possible effects of specific genetic variants as well as enabling comparison of results across several studies.

We love to talk about genetics and science!

We are always happy to discuss our approach and methodology with our customers.

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