SCORacle Newsletter - April 2024 Edition
Personalised diagnostics is an area of science that is based on the idea that a person’s own clinical, genetic, genomic and environmental information can identify patient-specific diseases and target individual medical treatments to maximise response and help reduce adverse effects.
The conventional trial-and-error method of treatment, where two individuals with the same medical condition may exhibit vastly different responses to identical drugs, could soon be obsolete. Recent research indicates that by leveraging a patient’s unique genetic profile, clinicians have the potential to proactively address premature organ aging—a condition newly associated with organ-specific diseases and mortality—within a 15-year timeframe.
Using a simple and minimally invasive blood test, researchers have demonstrated that organ-specific plasma proteins circulating in blood can identify biological organ age. With the use of a Python package modelled to predict organ age, clinicians can forecast mortality, organ specific functional decline, disease risk and progression; and predict future disease. This allows for planning of preventative treatments and targeting of lifestyle modifications and drug therapy to the individual.1
Practical uses of personalised medicine
Personalised medicines such as IVF for fertility issues, have been around for many years but there were just 13 examples of this in 2006. By 2011, there were 72 examples, the most successful being in cancer treatments but also type 1 diabetes:
- Herceptin which treats the 30% of breast cancers with an over-expression of HER2 protein.
- Those identified with the V600E defect in the DNA in malignant melanoma (60% of those diagnosed), now have increased life expectancy where previously late-stage prognosis was poor.2
- A new biochip developed in the UK is the first in the world to use genetics to quickly identify who is at high risk of developing type 1 diabetes before a diagnosis is made using a genetics risk score. The research could help develop new screening programmes worldwide for type 1 diabetes, starting at newborns. The test, publicly available since February 2024 via the developer, distinguishes between type 1 and type 2 diabetes and allows and supports FDA approved disease modifying drugs that can only be administered pre-diagnosis.3
Research into Genome and RNA sequencing, Epigenetics, ageotyping is developing rapidly and the belief is that this research will lead to a simple blood test that guides prognostics and allows intervention before illnesses develops with the goal of reversing or slowing down disease development.
Why is this being done?
Scientists know little about how human organs change with age but with a better understanding, research in this area could help address the financial burden of aging, while revolutionising patient care and preventative drug development.
Studies on mice show that molecular changes across organs occur with age and researchers have identified unique molecular aging trajectories and timings. Without relying on invasive measures such as tissue sampling or costly methods of investigation such as MRI, researchers were able to identify similar findings in humans using minimally invasively techniques. Organ-specific proteins in blood plasma can enable assessment and monitoring of overall health, detect organ aging, and predict disease with a view to identifying changes to prevent organ-related disease.
Background to study
Blood testing has been used for nearly 100 years and can identify illness if readings exceed or fall short of the specified threshold for certain markers. However, there is also a wide range of proteins that make their way into blood plasma as it circulates, including a vast amount of potential protein biomarkers—such as growth factors, antibodies, and proteins that hold a substantial amount of information indicative of normal function or disease and in doing so, blood plasma can be as effective in monitoring overall health.
Protein biomarkers are now more sensitive than ever, and clinicians can now detect abnormalities before there is any demonstrable clinical manifestations. Knowing this, researchers have painstakingly analysed blood from 1400 healthy participants aged 20-90 and identified around 900 organ specific proteins.
How was this achieved?
Using data from a previous RNA sequencing project, researchers identified 900 organ-enriched proteins in blood and used data collected from various larger studies on aging, ongoing since 2008, to train a machine learning algorithm to produce models to identify the difference between chronological age and biological age. By asking the algorithm to guess the chronological age of the plasma protein, researchers calculated the organ age gap.
The study looked specifically at the following 11 organs, organ systems and tissue:
- heart
- fat
- lung
- immune system
- kidney
- liver
- muscle
- pancreas
- brain
- vasculature
- intestine
The algorithm then gave a score for each organ and found that organs age at different rates within individuals. If the age of an organ is more advanced than others in that age group, there is a 20–50% higher mortality risk of them developing disease affecting that organ in the next 15 years, and death.
Those with accelerated aging in multiple organs were associated with major age-related disease but notably, diseases like heart attacks and Alzheimer’s disease exhibit associations with accelerated aging across nearly all organs.
Specifically, the study revealed that individuals with accelerated heart aging face a 250% increased risk of heart failure. An aging heart also serves as a robust predictor for myocardial infarction (MI) and atrial fibrillation.
Fast aging in the kidneys was a strong predictor of metabolic disorders such as obesity, hypercholesterolaemia, hypertension (a 1-year age gap) and diabetes (a 1.3-year age gap). Accelerated aging in the muscles was associated with gait impairment. The only organ found not to be associated with early death in 15 years was the intestines.
Meanwhile, those experiencing accelerated brain aging are more susceptible to cognitive decline, and vascular aging independently predicts Alzheimer’s disease (AD) progression—matching the strength of the current best blood-based biomarker, plasma pTau-181. Additionally, the Cognition-Brain age gap identified unique molecular insights into brain aging that other studies have not captured.For example, certain growth protein levels in the blood may reflect reduced protein processing, leading to the shedding of growth-related proteins in the brain which suggests that researchers may have identified the protein responsible for cognitive decline in aging.
The belief is that this research will lead to a simple blood test that guides prognostic work – to allow intervention before illness develops and reverse or slows down accelerated aging. If detected early, this blood test can guide treatment before symptoms start.
Implications for underwriting and claims
At present the study has a very limited demographic. Whilst the study showed that men and women had similar age prediction, most of the participants in the cohorts were over 50 and white. The findings are not proven in younger lives and cannot be generalised to the wider population. Also, a single organ doesn’t tell the whole story of aging because deterioration processes are interconnected. And a good amount of the factors that drive age-related organ dysfunction are environmental, lifestyle, pollution, diet, and gut microbes. However, this is a growing area of research, and this approach will become more sophisticated.
In terms of underwriting, we know that disease processes become more prevalent as people age. Genetic predisposition, lifestyle and environmental conditions e.g. alcohol, family history, diet, weight etc are relevant underwriting factors.
Underwriters already look to determine if a disease process is normal for age, i.e. if someone has coronary artery disease they consider if this is normal or abnormal for age and use predictive modelling/values to determine where the person sits in the general population. Given that underwriters already underwrite for risk factors for certain conditions, they will need to be aware of the potential future application of this test to consider if it should be taken into account.
As far as claims is concerned, applicants for cover may have even greater insight to their risks of developing disease if this area of personalised medicine develops, so anti-selection may be a risk. The test is silent on cancer which is the most common cause of claim but those with access to testing or that can afford personalised diagnostics to predict future disease will have greater insight to their own health and risks of disease which may lead to further concerns over anti-selection.
Conclusion
This test when developed, could address the massive global disease burden of aging, and revolutionalise patient care, preventative medicine and drug development. We need to keep an eye on developments as we can’t tell how many people will take up the test or if it will be widely available, but this is certainly an exciting area of development in personalised medicine.
For further information about this article, please contact
Footnotes:
1 Organ aging signatures in the plasma proteome track health and disease | Nature
2 BRAF is one of the most frequently mutated oncogenes recognised in melanoma. The most frequent oncogenic BRAF mutations consist of a single point mutation at codon 600 (mostly V600E) that leads to constitutive activation of the BRAF/MEK/ERK (MAPK) signalling pathway. Source: National Library of Medicine – BRAF Mutations in Melanoma: Biological Aspects, Therapeutic Implications, and Circulating Biomarkers
