Welcome!
This is the Developmental Methylation Risk Atlas (DeMetRA), an interactive resource for finding MPSs that have been developed or applied to paediatric samples.
The atlas is originally based on this systematic literature review:
publications
unique MPSs
unique Phenotypes
Last update:
Paediatric methylation profile scores: a systematic review and open-source atlas, but is meant as a collaborative, live resource.
On this page, you can search the atlas, navigate to the other tabs to explore interactive visualizations of these data and to upload your MPS for others to find!
Notes
Rows are colored by the Category of the MPS:
◼ Biological markers — Molecular or cellular processes (e.g. immune function, biological ageing).
◼ Genetic syndromes — Conditions with a known genetic aetiology (e.g. Down syndrome, Fragile X).
◼ Lifestyle and environment — Prenatal or postnatal exposures such as smoking, diet, or socioeconomic adversity.
◼ Physical health indicators — Cardiometabolic, growth, or other somatic health outcomes.
◼ Neuro-psychiatric health indicators — Neurodevelopmental or psychiatric conditions (e.g. ADHD, ASD, depression).
◼ Cancer — Paediatric cancer or cancer risk.
Sample size refers to the internal validation sample; where studies used a train-test split, the total sample size across subsets is reported.
On this page, we collected different ways to visualize insights from the DeMetRA resource.
The interactive plots below are based on the entire atlas (i.e. latest systematic review (2025) + user uploads).
In the multilevel pie chart below, you can see the number of MPSs per Category | Pehnotype. Hover over the slices to get more information. Click on one of the inner macro-categories to zoom into its phenotypes.
Which phenotypes got the most publications? Hover over the bars to find out.
Take a look at some publication metadata. Explore the network of authors and publications.
The network graph below shows the connections between all authors and publications included in the review. Squares represent publications and they are colored by phenotype category. The light-blue dots represent individual authors. Hover over the nodes to get more info.
In the histogram below, you can see the number of MPSs calculated in each individual publication, colored by phenotype category. Hover over the bars to get more information (e.g publication title).
The histogram below shows the number of publications per author, when more than 1 publication was included in the review. These are colored by phenotype category. Hover over the bars to get more info.
Use the zoom and pan tools on the top-right corner of the plot to explore the data.
How is Developmental MPS research evolving over time?
Take a look at sample sizes over publication date.
The stacked histogram below shows the interest in different phenotype categories over the years.
43% of publications in this review use existing resources to compute their MPSs.
13% use published EWAS summary statistics, and 30% use a Pre-established MPS. Here we explore these publications further.
The Sankey diagram below shows how well the sample(s) used to develop the MPS match the sample in which the MPS was applied.
Fill in as many information as you can about the MPS(s) you have developed or applied to in a developmental context. The fields marked by * are compulsory.
Once you are done, hit the Submit for review button. We will process your submission as soon as possible and possibly get back to you. You can check the status of your submission here.
Note: something is wrong or missing? Please open an issue to let us know!
Age range (years) *Minimum and Maximum age of the sample. If this is a birth sample, use min: 0 max: 0.
Minimum and Maximum age of the sample. If this is a birth sample, use min: 0 max: 0.