SYNOMICS LABSSpecimen · Pinus stem, transverse section
Five orbits · five biological layers
Links · relationships measured together
Chronic illness, measured as one system.
We design studies that measure several biological layers in the same people, at rest and under load, to find the subgroups that averages hide. The aim: diagnostic tools and treatment evidence for conditions that sit between specialties.
Conditions that cross systems have often been studied one system, one marker and one moment at a time. We study them the way they present: together, under various circumstances, and person by person.
Medicine that looks ahead.
Many chronic conditions are recognised only once they are established and can be diagnosed. Predictive, preventive and personalised medicine, known as PPPM or 3P medicine, asks what can be seen earlier, in the space between health and disease, and for whom. It is the framework Synomics Labs works within.
- 02.0
Reactive
The usual starting point. Care begins when symptoms cross the threshold for a diagnosis. Many people live with symptoms that persist even when standard tests find nothing to explain them. For conditions that fluctuate and cross specialties, that threshold can be reached late, or not at all, and the years before it go largely unmeasured.
- 02.1
Predictive
Reading signals that may point to risk before an illness is established. 3P medicine describes this stage as sub-optimal health: no diagnosis yet, but change that can be measured. For us, those signals come from several biological layers measured together, rather than from a single marker.
- 02.2
Preventive
Using those signals to act earlier, and in a more targeted way. Whether acting earlier changes the course of a chronic, multi-system illness is itself a research question, so it is something we set out to test, not something we assume.
- 02.3
Personalised
People who share a diagnosis can follow very different courses. 3P medicine reads results against the individual and the subgroup they belong to, rather than against an average that may describe no one in particular.
- 02.4
Measured, then connected
Each of these steps depends on measurement. The five biological layers that follow are how those signals are gathered, and how the relationships between them are studied.
Schematic · illustrative, not study data
Five layers. One dataset.
Each layer answers a different question about the same person. Measured together, the relationships between them can be studied.
- 03.1
Genomics
The DNA sequence and its variation. Largely fixed from birth, it is the code the other layers read from.
Measured withWhole-genome sequencing · exome sequencing · genotyping arrays
Why it matters hereVariation in genes such as those for connective tissue and immune signalling may shape susceptibility. On its own, the genome shows what is possible, not what is happening now.
- 03.2
Transcriptomics
The transcriptome: the complete set of RNA transcripts in a cell or tissue. Where the genome is static, the transcriptome is dynamic, showing which genes are being expressed at that moment.
Measured withRNA sequencing · single-cell RNA sequencing · spatial transcriptomics · microarrays
Why it matters hereExpression can shift within hours, so sampling before and after a challenge such as exertion can reveal responses that a resting sample would miss. Single-cell and spatial methods show which cells are responding, and where.
- 03.3
Proteomics
The proteins present in blood or tissue: enzymes, signalling molecules, structural proteins and inflammatory mediators.
Measured withMass spectrometry · affinity-based protein panels
Why it matters hereProteins carry out most of the work the genome encodes. Many immune and inflammatory signals are measured here, and some change over short timescales.
- 03.4
Metabolomics
The small molecules produced by metabolism: sugars, lipids, amino acids and the intermediates of energy production.
Measured withMass spectrometry · NMR spectroscopy
Why it matters hereIt is the layer closest to function, and so to the questions of energy, exertion and recovery that many chronic, multi-system conditions raise.
- 03.5
Microbiome and metagenomics
All the genetic material in a sample, sequenced directly. This captures bacteria, viruses and fungi (the mycobiome) in the gut, mouth and skin, without needing to culture them first.
Measured withShotgun metagenomics · 16S and ITS amplicon sequencing · metatranscriptomics
Why it matters hereMicrobial communities interact with immune function and metabolism. The same methods can sample a person’s surroundings, such as indoor air and dust, so that exposures like damp and mould can be measured directly rather than assumed. The role of such exposures in chronic multi-system illness is still debated, and measurement is how that question can be tested.
- 03.6
Connecting the layers
Multi-omics integration combines the layers to follow biological information from code to function: from genome, to transcript, to protein, to metabolite, with the microbes read in tandem.
Measured withNetwork, factor and machine-learning integration methods
Why it matters hereThe same people are measured at the same time points, so relationships between layers can be analysed rather than inferred. Integration methods are also used to separate one diagnosis into subtypes, which is how the subgroups that averages hide can be found. Which layers are measured is set out for each study.
Designed for conditions that fluctuate.
How each study is put together: when samples are taken, what is measured, how the results are analysed, and over how long.
In a provoked state
Where possible, samples are taken before and after a challenge such as exertion, as well as at rest, because many symptoms appear only under load.
Many people with chronic, multi-system conditions can look well on a resting test, yet feel worse after exertion, sometimes not until a day or more later. Measuring the response to a defined, carefully limited challenge, and the recovery from it over the following days, can show what a resting sample misses. Part of the development work is designing challenges that are small, optional and safe to stop, with safety measures agreed before any study begins.
Across layers
Each study measures several biological layers in the same people, so that the relationships between them can be seen.
Samples for every layer are taken at the same visits, so a change in one layer can be set against the others at the same moment, rather than compared across different studies and different people. A shift in one layer often only makes sense when read against the others. Measuring them together is what lets connections between layers be tested, rather than assumed.
Looking for subgroups
Where one name covers several presentations, we analyse for subgroups rather than averaging them together. A treatment that helps some people and not others can look ineffective when everyone is counted together.
Subgroups found in one set of data are checked in another before they are relied on, so that a pattern is not mistaken for chance.
A subgroup is defined by a pattern across several layers rather than by a single marker, so that it can be recognised again in new data, and so that later studies can ask whether it responds differently to treatment.
Followed over time
Fluctuating conditions change from week to week. Studies follow the same people across repeated visits, and between visits where possible, so that a lasting pattern can be told apart from a good or a bad day.
Three lines of work.
Each line of work starts from the same idea: what one measure, one average or one appointment can miss.
- 05.1
Diagnostic tools
A result within the normal range, in tandem with symptoms that persist, is not the end of an enquiry but the beginning of a better question. We aim to develop tests for the questions standard panels were never designed to ask, built on patterns across layers rather than single markers.
Schematic · one person’s profile across the layers, against a reference average - 05.2
Treatment testing
Structured testing of treatment options for chronic conditions, designed from the outset so that subgroups who respond differently can be told apart.
Schematic · each dot one person; an average near zero hides three different responses - 05.3
Tracking and monitoring
Tools and continuous monitors that record how symptoms, wearable measures and lab markers change together over time in everyday life, not only during a clinic appointment. Built for fluctuating illness, and for people with limited energy to spare.
Schematic · symptoms, wearable and lab measures after exertion, followed over 14 days
Build the evidence with us.
Synomics Labs is at an early stage. We are looking for partners and funders to help shape its first study.
- Partners
Clinical, academic and industry
Teams who share an interest in multi-system conditions and in study designs that cross specialties.
- Funders
Philanthropists and grant-makers
Those who would like to support research that starts from the questions single-specialty studies leave open.
Or write to us directly at [email protected].