Protein biomarkers at the heart of multiomics strategies

Combining multiple omics technologies in a systems biology approach for a clear picture of real-time biology

Why multiomics?

Biomedical research is increasingly trending towards a big-picture approach to biological questions, and the terms “systems biology” and “multi-omics” are now frequently used to describe studies that look at multiple molecular and cellular aspects involved in the disease or process under investigation. Combining techniques such as genomics, transcriptomics, proteomics, or mass cytometry provide a much more detailed picture of what is happening, at a level that is simply not possible using single technologies. Many of the world’s leading research groups are now committed to this big-picture, multiomics approach to science, with leading institutes focused on this strategy, such as the Institute for Systems Biology in Seattle WA among others. Below, we will share some examples of how Olink has been used in system biology approaches by integrating proteomics with genomics, transcriptomics as well as other omic applications.

The past few decades saw a huge investment into the rapid development and application of genomics technologies, which led to significant steps forward in population genetics and understanding heritability, as well as progress in our understanding and treatment of disease, especially in the fields of monogenic diseases and oncology. A DNA sequence is only a blueprint that can define probable outcomes, however, and much more is required to really understand the dynamic changes that occur during normal biological processes and the transition to disease and its progression. This has led to the increased application of technologies that provide information on cellular changes, gene expression, proteins and metabolites, and proteomics is now set to take centre stage in the next era of biological research and the development of precision medicine.

Adding proteomics to the mix for actionable insights into real-time biology

In the central dogma, it is proteins that lie closest to biological outcomes, representing the individual phenotype and the impact from environmental and lifestyle factors. This is crucial for medical research, where the majority of diseases are complex and multi-factorial (and frequently heterogeneous), with contributions from genetics, environment and lifestyle choices. It has been a strong unmet need to move towards proteins, which represent real-time biology, as they are dynamic and actionable targets in both health and disease.

Profile and actionability for analysis at the DNA, RNA or protein level in precision medicine applications

Since changes in proteins are so closely linked to disease, proteomics data has the potential to enable better understanding of disease processes, supporting new and innovative drug discovery and development, and facilitating patient stratification opportunities. This is particularly pertinent given that the majority of drug targets are themselves proteins. Protein biomarkers are therefore valuable tools to guide effective and efficient drug development through enhancing the understanding of disease and by identifying patients who can benefit most from therapies.

Overcoming technical challenges for large-scale protein analysis

The unique value of protein analysis to better understand biology and drive therapeutic development has long been recognised, while implementation as been hampered by  limitations in available technologies. Olink’s PEA technology has addressed these challenges (specificity, sensitivity, reproducibility, sample volume requirements, scalability and throughput), providing a thoroughly validated, flexible proteomics solution covering a broad range of applications for academic and clinical research, as well as drug discovery and development.

Applications for Olink’s protein biomarker solutions

Systems biology – combining omics approaches

Proteins are an essential, core component in any attempt to really understand complex, dynamic human biology and to derive actionable outcomes from scientific studies. Challenges such as those posed by studying complex dynamic systems, questions of causality versus effect, or assessment of local versus systemic activity require a bigger picture strategy that combines proteomics with other approaches. This approach has led to several recent large-scale epidemiological studies that demonstrate the power of a broad, multi-omics approach:

• Zhong W, Gummesson A, Tebani A, et al.  Whole-genome sequence association analysis of blood proteins in a longitudinal wellness cohort. (2020) Genome Medicine, DOI: 10.1186/s13073-020-00755-0
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• Wainberg M, Magis A, Earls J et al. Multiomic blood correlates of genetic risk identify presymptomatic disease alterations. (2020) PNAS, DOI: 10.1073/pnas.2001429117
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Webinar recording – longitudinal ‘omics profiling for precision medicine

You may be interested to see a recording of a Science/AAAS webinar featuring Professor Mathias Uhlén (KTH Royal Institute of Technology, Stockholm, Sweden) and Olink’s Chief Scientific Officer, Dr. Ida Grundberg. Entitled “When proteins get personal: A new concept for highly sensitive, multiplexed plasma profiling“, the webinar describes a multiomic, longitudinal wellness study that supports an individual-based definition of health, and a central role for protein biomarker analysis in systems-level approaches to biological questions. You can view this outstanding webinar from one of the world’s leading researchers in this field using the link below:

Combinations of proteomics with other specific omics technologies can have particularly strong utility in certain key areas, as described below.

Proteogenomics with Mendelian Randomization to establish disease causality

Observational studies of protein levels cannot address the question of causality of a given protein in  a specific biological process or disease pathway, as the change observed could either be driving the process under study, or merely reflect an outcome of that process. This is particularly important for drug target identification, where causality is a prerequisite to take the protein into a drug discovery and development program. Combining proteomics with genomics (“proteogenomics”) can effectively address this problem by linking gene variants to protein expression levels to identify protein Quantative Trait Loci (pQTLs).  The associations of pQTLs with phenotypic outcomes can then be tested in a Mendelian Randomization analysis, and in cases where the genetic variant is located close to the gene encoding the protein of interest (“cis-pQTLs”), this strongly infers causality for the protein in the disease or biological process under investigation.

Proteogenomics with Mendelian Randomization to establish disease causality

The unique power of this approach has led to its increasing adoption in recent studies, and has also resulted in a major international consortium dedicated to large-scale collaboration and data sharing. SCALLOP is a collaborative framework for the discovery and follow-up of genetic associations with proteins on the Olink Proteomics platform.  The aim of the SCALLOP consortium is to identify novel molecular connections and protein biomarkers that are causal in diseases, and date, 25 PIs from 20 research institutions have joined the effort, which now comprises summary level data on SNP to protein level associations from almost 65,000 patients or controls. A landmark publication from the consortium looking at pQTLs for 90 cardiovascular proteins in 30,000 individuals was recently published in Nature Metabolism – READ MORE

For more information about SCALLOP and to see a brief video interview with the consortium founder, Dr. Anders Mälarstig (Pfizer & Karolinska Institute), please use the link below:

Summary article

For a brief summary of three interesting proteogenomics articles citing the use of Olink that were published in 2020, READ HERE

Proteomics & cytometry

Biological systems typically involve an intricate interplay between different cell types, signalling molecules and other proteins. Approaches that combine cellular and molecular analyses can provide unique insights into complex biological questions, and nowhere is this more important than in studies involving the immune system. Advanced, high throughput technologies such as mass cytometry (e.g. CyTOF) enable detailed analysis of immune cell populations and how they change during health and disease. More recently, mass cytometry has been used in combination with Olink analysis to gain unique insights into immunological questions through this systems-level approach.

Olink & mass cytometry studies

In a landmark study from Dr. Petter Brodin’s group at Karolinska Institute, Stockholm, they used Olink and CyTOF to show for the first time that the immune systems of newborn children evolve in a stereotypic manner that is similar in diverse children, not predictable from cord blood measurements and driven by environmental factors such as the colonizing microbiome.

• Olin A,  Henckel E, Chen Y, et al. Stereotypic immune system development in newborn children. (2018) Cell, doi.org/10.1016/j.cell.2018.06.045.

Read more about this study HERE

This multiomics approach has also been important in COVID-19 studies that focused on immune system responses, providing vital insights into severe versus mild disease, recovery from severe disease, and in better understanding variants of the disease such as Multisystem Inflammatory Syndrome in Children. Some published examples of these studies are listed below:

• Consiglio et. al. (2020) The Immunology of Multisystem Inflammatory Syndrome in Children with COVID-19. Cell, DOI: 10.1016/j.cell.2020.09.016. – see the article here.
  • You can also read more about this study – HERE
• Arunachalam et. al. (2020) Systems biological assessment of immunity to mild versus severe COVID-19 infection in humans. Science, DOI: 10.1126/science.abc6261 – see the article here.
  • You can also read more about this study – HERE
•  Rodriguez et. al. (2020) Cell Reports Medicine, DOI: 10.1016/j.xcrm.2020.100078 – view the article
  • You can also read more about this study – HERE

Proteomics & transcriptomics

While proteins are chiefly responsible for most biological functions and can be seen as the ultimate executors of the information encoded in the genome, the transcription of genes as RNA plays an essential intermediate role. While post-transcriptional, translational and post-translational mechanisms all play key roles in the final concentration and biological activity of each protein, RNA measurements in the form of transcriptomics have long been used as a relevant proxy for biological output from the genome. While suitable proteomics technologies were lacking, powerful techniques such as RNAseq have enabled large scale studies of gene expression that have contributed to many systems biology studies. Since many factors other than gene transcription are involved in protein function, however, the availability of Olink’s powerful proteomics solution can now provide the key “missing link” from genetic information to real-time biological activity. An increasing number of studies are combining transcriptomics and Olink proteomics to gain a more complete picture, leveraging on the complementary potential of these approaches, for example to study localised changes at the tissue/cellular level by RNA analysis in relation to systemic changes at the proteomics level.

Case study:  A study in collaboration with Massachusetts General Hospital Cancer Center, performed deep proteomic profiling together with single-cell RNAseq in a metastatic melanoma cohort during treatment with checkpoint inhibitor immunotherapy. Around 1500 proteins were measured, resulting in plasma protein profiles associated with both predicted treatment response and overall survival. Single-cell RNAseq data  from individual immune cells within the tumors of melanoma patients showed that differentially expressed genes between responders and non-responders were primarily derived from myeloid cells, macrophages and dendritic cells, with an excellent correlation to the plasma proteomics data. This study demonstrates how circulatory proteins may provide a roadmap to inform biological insights about the localized tumor response to therapy. Please download the full case study report using the link below:

Selected publications

• Masoudzadeh N, Östensson M, Persson J, et al. Molecular signatures of anthroponotic cutaneous leishmaniasis in the lesions of patients infected with Leishmania tropica.. (2020) Scientific Reports, DOI: 10.1038/s41598-020-72671-7
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• Harden J, Shih Y-H, Xu J, et.al.  Paired Transcriptomic and Proteomic Analysis Implicates IL-1β in the Pathogenesis of Papulopustular Rosacea. (2020) Journal of Investigative Dermatology, DOI: 10.1016/j.jid.2020.08.013
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• Björk A, Da Silva Rodrigues R, Richardsdotter Andersson E. Interferon activation status underlies higher antibody response to viral antigens in patients with systemic lupus erythematosus receiving no or light treatment. (2020) Rheumatology, DOI: 10.1093/rheumatology/keaa611
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Questions?

If you have any questions or comments on how Olink could help to meet your needs in multi-omics research, please contact us via the form below: