'Digital twins,' an aid to give individual patients the right treatment
at the right time
Date:
May 6, 2022
Source:
Linko"ping University
Summary:
An international team of researchers have developed advanced
computer models, or 'digital twins', of diseases, with the goal
of improving diagnosis and treatment. They used one such model
to identify the most important disease protein in hay fever. The
study underlines the complexity of disease and the necessity of
using the right treatment at the right time.
FULL STORY ==========================================================================
An international team of researchers have developed advanced computer
models, or "digital twins," of diseases, with the goal of improving
diagnosis and treatment. They used one such model to identify the most important disease protein in hay fever. The study, which has just been published in the open access journal Genome Medicine, underlines the
complexity of disease and the necessity of using the right treatment at
the right time.
==========================================================================
Why is a drug effective against a certain illness in some individuals,
but not in others? With common diseases, medication is ineffective in
40-70 percent of the patients. One reason for this is that diseases are
seldom caused by a single "fault" that can be easily treated. Instead,
in most diseases the symptoms are the result of altered interactions
between thousands of genes in many different cell types. The timing is
also important. Disease processes often evolve over long periods. We
are often not aware of disease development until symptoms appear, and
diagnosis and treatment are thus often delayed, which may contribute to insufficient medical efficacy.
In a recent study, an international research team aimed to bridge the
gap between this complexity and modern health care by constructing computational disease models of the altered gene interactions across
many cell types at different time points. The researchers' long-term
goal is to develop such computational models into "digital twins" of
individual patients' diseases.
Such medical digital twins might be used to tailor medication so that each patient could be treated with the right drug at the right time. Ideally,
each twin could be matched with and treated with thousands of drugs in
the computer, before actual treatment on the patient begins.
The researchers started by developing methods to construct digital
twins of patients with hay fever. They used a technique, single-cell
RNA sequencing, to determine all gene activity in each of thousands of individual immune cells - - more specifically white blood cells. Since
these interactions between genes and cell types may differ between
different time points in the same patient, the researchers measured gene activity at different time points before and after stimulating white
blood cells with pollen.
In order to construct computer models of all the data, the researchers
used network analyses. Networks can be used to describe and analyse
complex systems.
For example, a football team could be analysed as a network based on the
passes between the players. The player that passes most to other players
during the whole match may be most important in that network. Similar principles were applied to construct the computer models, or "twins,"
as well as to identify the most important disease protein.
In the current study, the researchers found that multiple proteins and signalling cascades were important in seasonal allergies, and that these
varied greatly across cell types and at different stages of the disease.
"We can see that these are extremely complicated changes that occur in different phases of a disease. The variation between different times
points means that you have to treat the patient with the right medicine
at the right time," says Dr Mikael Benson, professor at Linko"ping
University, who led the study.
Finally, the researchers identified the most important protein in the
twin model of hay fever. They show that inhibiting this protein, called PDGF-BB, in experiments with cells was more effective than using a known allergy drug directed against another protein, called IL-4.
The study also demonstrated that the methods could potentially be applied
to give the right treatment at the right time in other immunological
diseases, like rheumatism or inflammatory bowel diseases. Clinical implementation will require international collaborations between
universities, hospitals and companies.
The study is based on an interdisciplinary collaboration between
15 researchers in Sweden, the US, Korea and China. The research has
received financial support from the EU, NIH, the Swedish and Nordic
Research Councils, and the Swedish Cancer Society.
========================================================================== Story Source: Materials provided by Linko"ping_University. Original
written by Karin So"derlund Leifler. Note: Content may be edited for
style and length.
========================================================================== Journal Reference:
1. Xinxiu Li, Eun Jung Lee, Sandra Lilja, Joseph Loscalzo, Samuel
Scha"fer,
Martin Smelik, Maria Regina Strobl, Oleg Sysoev, Hui Wang, Huan
Zhang, Yelin Zhao, Danuta R. Gawel, Barbara Bohle, Mikael Benson. A
dynamic single cell-based framework for digital twins to prioritize
disease genes and drug targets. Genome Medicine, 2022; 14 (1) DOI:
10.1186/s13073-022- 01048-4 ==========================================================================
Link to news story:
https://www.sciencedaily.com/releases/2022/05/220506102620.htm
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