A blood test is an important step toward making almost any medical diagnosis. This is true whether there is concern that a patient may have diabetes, kidney disease, heart failure or many other conditions.
Most of the time, these blood tests deliver a single piece of information. They provide one clue about a potential health risk. Additional blood tests and specialized tests, such as ultrasound, X-rays or stress testing, are needed to get to the working diagnosis.
What if instead of needing different blood tests for each suspected health issue, health care providers could use one blood test to deliver a hundred or more different predictors for a large number of common diseases? In other words, what if a single blood test based on measuring thousands of proteins could provide an accurate, detailed portrait of a person’s current health and future disease risks?
That was the question that the authors of a recent Nature Medicine article1, co-led by Drs. Stephen Williams (SomaLogic, Inc.), Peter Ganz (University of California, San Francisco) and Nicholas Wareham (University of Cambridge) aimed to answer.
Why proteins are a special source of health information
The body’s proteins are particularly well suited to provide comprehensive health information. They are the instruments – the worker bees of the body – that carry out the functions of all cells.
Proteins circulating in blood reflect a person’s genetically inherited predisposition to diseases. It is encoded by the sequences of nucleotides that make up the genes in our DNA.
Proteins also reflect the effects of one’s environment (diet, lifestyle habits, the aging process and any drugs taken to ameliorate one’s health risks). This takes place by modification of gene expression rather than alteration of the genetic code itself.
DNA tests provide static information about our genes. By and large, that information does not change during one’s lifetime. And, it is only weakly associated with the risk of common diseases.2
On the other hand, protein levels change continuously as one’s health changes and disease risks emerge3, 4 And, the association of proteins with the risk of diseases can be strong.5
For these reasons, blood proteins have been hypothesized to provide a powerful snapshot of current health. They also offer a sneak preview of diseases not yet clinically apparent.
Technology to measure thousands of proteins in the blood
Until recently, the measurement of a large number of proteins in a complex mixture of cells and chemical substances such as blood was limited by a lack of suitable technology. The SomaLogic (Boulder, CO) technology overcomes this challenge.5, 6
It uses modified aptamers. These are chemically modified bits of single-stranded DNA that bind to proteins with high affinity (sub-nanomolar) and excellent specificity, similar to antibodies.7
The assay can currently measure nearly five thousand different proteins present in vastly different concentrations. And it can do it using just 0.15 milliliters of blood.
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The utility of proteomics: The proof-of-concept study
In the aforementioned proof-of-concept study, investigators measured the levels of 5,000 different proteins in archived blood samples from nearly 17,000 individuals participating in 5 different longitudinal health studies.1 This yielded a total of 85 million protein measurements making this the largest protein study to date.
Applying sophisticated machine learning computer approaches to this massive data set revealed protein expression patterns that correlated with 11 different measures of patients’ overall health. It also correlated with their risk of developing certain diseases in the years following the blood draw.
For example, the test could predict how much fat a person’s liver contained. Liver fat is a forerunner of liver cirrhosis, a risk factor for cardiovascular disease, and an indicator of insulin resistance.
The test also provided a measure of the overall level of physical fitness as well as a predictor of the likelihood of developing diabetes or cardiovascular disease within 5 years.
Eleven health indicators in a single blood test
The set of 11 results that this single blood test provided is listed here:
- the presence or absence of liver fat
- kidney function
- the percent body fat
- visceral fat
- lean body mass
- cardiopulmonary fitness
- average daily physical activity
- alcohol consumption
- cigarette smoking
- predicted diagnosis of diabetes in pre-diabetics within 10 years
- likelihood of heart attack, stroke, heart failure or cardiovascular death within 5 years in people without known heart disease
And since the paper was published, tests for cardiovascular risk in people with known heart disease, resting energy expenditure and glucose tolerance have been added to the list.
Protein patterns can pinpoint propensity for disease
This proof-of-concept study demonstrates a new paradigm. The measurement of blood proteins can accurately deliver health information that spans numerous medical specialties. This information should be actionable for patients and their health care providers.
From all the studies conducted to date, there is evidence that protein patterns can pinpoint propensity for the following diseases:
- coronary heart disease,
- heart failure,
- liver disease,
- kidney disease,
- dementia and
This is likely just the tip of the iceberg. Ultimately, our goal is to deliver a one-stop “Liquid Health Check” for personalized detection, prevention, and treatment of many diseases.
Implications of Liquid Health Check for patients and health care
A single blood test based on measuring proteins at scale has potentially important implications for transforming health care. They are as follows:
1. Patient convenience and reduction in health care cost
A patient would have to make several appointments with health care providers and undergo multiple tests costing thousands of dollars to get the equivalent amount of health information that the one blood sample provides by measuring thousands of proteins at once at a reasonable cost.
2. Provision of truly “personalized (precision) medicine”
Proteins are “downstream” from the traditional clinical risk factors. They can, therefore inform whether or not a person’s clinical risk factors have set in motion the machinery required to cause diseases.
Unlike genetic risk factors that do not change during an individual’s lifetime, protein risk scores are responsive to modifications in their environment (e.g., diet, lifestyle behaviors, drugs and so forth).
We thus envision that protein-based risk scores (unlike genetic risk scores) would be regularly tracked over one’s lifetime to inform the following:
- changes in health risk
- the need for any treatments
- the necessity to make lifestyle changes
We believe it is important to commercialize this test so it can help patients broadly. To this end, SomaLogic has already launched the first ten SomaSignal™ tests based on the findings described in the Nature Medicine article. Discovery and development efforts are ongoing and there are already more than one hundred tests in the pipeline.
Liquid Health Check: academic and industry collaboration
Liquid Health Check represents an important collaboration between academic centers and industry. An important aspect of this collaboration is a focus on openness and transparency from which patients will ultimately benefit.
Study results are published in peer-reviewed journals, typically with detailed supplemental information.1, 5, 8 We do this so that health care professionals and pharma to be able to scrutinize and use the data and information for their own research studies.
The bottom line
Advanced technology and data analytics have made it possible to create a single blood test, the Liquid Health Check, that provides personalized, actionable information about an individual’s health and health risks. We believe that this will transform healthcare.
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- Williams SA, Kivimaki M, Langenberg C, Hingorani AD, Casas JP, Bouchard C, Jonasson C, Sarzynski MA, Shipley MJ, Alexander L, Ash J, Bauer T, Chadwick J, Datta G, DeLisle RK, Hagar Y, Hinterberg M, Ostroff R, Weiss S, Ganz P and Wareham NJ. Plasma protein patterns as comprehensive indicators of health. Nat Med. 2019;25:1851-1857.
- Mosley JD, Gupta DK, Tan J, Yao J, Wells QS, Shaffer CM, Kundu S, Robinson-Cohen C, Psaty BM, Rich SS, Post WS, Guo X, Rotter JI, Roden DM, Gerszten RE and Wang TJ. Predictive Accuracy of a Polygenic Risk Score Compared With a Clinical Risk Score for Incident Coronary Heart Disease. JAMA. 2020;323:627-635.
- Lehallier B, Gate D, Schaum N, Nanasi T, Lee SE, Yousef H, Moran Losada P, Berdnik D, Keller A, Verghese J, Sathyan S, Franceschi C, Milman S, Barzilai N and Wyss-Coray T. Undulating changes in human plasma proteome profiles across the lifespan. Nat Med. 2019;25:1843-1850.
- Emilsson V, Gudnason V and Jennings LL. Predicting health and life span with the deep plasma proteome. Nat Med. 2019;25:1815-1816.
- Ganz P, Heidecker B, Hveem K, Jonasson C, Kato S, Segal MR, Sterling DG and Williams SA. Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients With Stable Coronary Heart Disease. JAMA. 2016;315:2532-41.
- Gold L, Ayers D, Bertino J, Bock C, Bock A, Brody EN, Carter J, Dalby AB, Eaton BE, Fitzwater T, Flather D, Forbes A, Foreman T, Fowler C, Gawande B, Goss M, Gunn M, Gupta S, Halladay D, Heil J, Heilig J, Hicke B, Husar G, Janjic N, Jarvis T, Jennings S, Katilius E, Keeney TR, Kim N, Koch TH, Kraemer S, Kroiss L, Le N, Levine D, Lindsey W, Lollo B, Mayfield W, Mehan M, Mehler R, Nelson SK, Nelson M, Nieuwlandt D, Nikrad M, Ochsner U, Ostroff RM, Otis M, Parker T, Pietrasiewicz S, Resnicow DI, Rohloff J, Sanders G, Sattin S, Schneider D, Singer B, Stanton M, Sterkel A, Stewart A, Stratford S, Vaught JD, Vrkljan M, Walker JJ, Watrobka M, Waugh S, Weiss A, Wilcox SK, Wolfson A, Wolk SK, Zhang C and Zichi D. Aptamer-based multiplexed proteomic technology for biomarker discovery. PLoS One. 2010;5:e15004.
- Rohloff JC, Gelinas AD, Jarvis TC, Ochsner UA, Schneider DJ, Gold L and Janjic N. Nucleic Acid Ligands With Protein-like Side Chains: Modified Aptamers and Their Use as Diagnostic and Therapeutic Agents. Mol Ther Nucleic Acids. 2014;3:e201.
- Williams SA, Murthy AC, DeLisle RK, Hyde C, Malarstig A, Ostroff R, Weiss SJ, Segal MR and Ganz P. Improving Assessment of Drug Safety Through Proteomics: Early Detection and Mechanistic Characterization of the Unforeseen Harmful Effects of Torcetrapib. Circulation. 2018;137:999-1010.
Financial Disclosures: Dr. Ganz is a member of the SomaLogic Medical Advisory board, for which he receives no remuneration of any kind. Dr. Williams is an employee of SomaLogic.
Editors note: I invited Drs. Ganz and Williams to submit this post after hearing their excellent presentation at the always excellent Precision Medicine World Conference 2020. We received no remuneration for publishing this post.