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Clinical implications of omics and systems medicine: focus on predictive and individualized treatment
1Centre for Individualized Medicine, Department of Pediatrics, Faculty of Health Sciences, Linköping University, Linköping, Sweden.
Abstract:
Many patients with common diseases do not respond to treatment. This is a key challenge to modern health care, which causes both suffering and enormous costs. One important reason for the lack of treatment response is that common diseases are associated with altered interactions between thousands of genes, in combinations that differ between subgroups of patients who do or do not respond to a given treatment. Such subgroups, or even distinct disease entities, have been described recently in asthma, diabetes, autoimmune diseases and cancer. High-throughput techniques (omics) allow identification and characterization of such subgroups or entities. This may have important clinical implications, such as identification of diagnostic markers for individualized medicine, as well as new therapeutic targets for patients who do not respond to existing drugs. For example, whole-genome sequencing may be applied to more accurately guide treatment of neurodevelopmental diseases, or to identify drugs specifically targeting mutated genes in cancer. A study published in 2015 showed that 28% of hepatocellular carcinomas contained mutated genes that potentially could be targeted by drugs already approved by the US Food and Drug Administration. A translational study, which is described in detail, showed how combined omics, computational, functional and clinical studies could identify and validate a novel diagnostic and therapeutic candidate gene in allergy. Another important clinical implication is the identification of potential diagnostic markers and therapeutic targets for predictive and preventative medicine. By combining computational and experimental methods, early disease regulators may be identified and potentially used to predict and treat disease before it becomes symptomatic. Systems medicine is an emerging discipline, which may contribute to such developments through combining omics with computational, functional and clinical studies. The aims of this review are to provide a brief introduction to systems medicine and discuss how it may contribute to the clinical implementation of individualized treatment, using clinically relevant examples.
Insights
Systems medicine uses omics and computational approaches to identify patient subgroups and discover new treatments for diseases with poor treatment response, enabling personalized and preventative healthcare.
Area of Science:
- Genomics and Systems Biology
- Translational Medicine
- Computational Biology
Background:
- Many patients do not respond to common disease treatments, leading to suffering and high healthcare costs.
- Disease heterogeneity and distinct patient subgroups contribute to variable treatment responses.
- High-throughput omics technologies enable the characterization of these subgroups.
Purpose of the Study:
- To introduce systems medicine and its role in clinical implementation.
- To discuss how systems medicine can advance individualized treatment strategies.
- To highlight the potential for predictive and preventative medicine.
Main Methods:
- Integration of multi-omics data (genomics, etc.)
- Computational analysis for identifying disease regulators and patient subgroups
- Functional studies and clinical validation
- Systems medicine approaches combining omics, computational, and clinical data
Main Results:
- Identification of distinct disease subgroups with unique genetic interactions.
- Discovery of novel diagnostic markers and therapeutic targets.
- Validation of a candidate gene for allergy diagnosis and therapy.
- Demonstration of potential for targeting mutated genes in cancer with existing drugs.
Conclusions:
- Systems medicine offers a framework for understanding disease complexity and improving treatment efficacy.
- Personalized medicine can be advanced through identifying patient subgroups and tailored therapies.
- Predictive and preventative strategies can be developed by targeting early disease regulators.
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