How proteomics helped diabetic kidney disease research advance
- Clinical research , Proteomics
- Read time: 7 minutes
Dr. Krolewski and his team at the Harvard Medical School found 56 proteins to be significant in diabetic kidney disease patients. Potentially, these could serve as prognostic biomarkers for disease progression and treatment response. This is how adding proteomics to the methodologies elevated their research.
Dr. Andrzej Krolewski, the head of the Genetics and Epidemiology section of the Harvard Medical School, has been working on the genetics of type 1 and type 2 diabetes. For the last 30 years, he has been actively investigating diabetic kidney disease in patient cohorts from the Joslin diabetes center, where he is also a researcher.
Read more about Dr. Krolewski, Professor of Medicine at Harvard Medical School, and Joslin Diabetes Center on their website.
Before proteomics, genomics was the answer
Having started one of the first biobanks of its kind in the late 1990s, Dr. Krolewski collected data on 5000 patients over the past 10 to 20 years to understand the disease progression of diabetic kidney disease. This was the time where human genetics as a field was making huge advances, with the human genome project being just one of them. The promise of genetics as the solution to all our biological questions and conundrums captivated even Dr. Krolewski, who began genetic studies in earnest to make progress in his research.
However, despite his efforts, the results of this research were underwhelming, and he needed to utilize a different approach, using a different form of -omics.
Moving to proteomics
Having had no luck in exploring the human genome for answers to his research questions, Dr. Krolewski turned to the human proteome instead. His initial work was backbreaking; he and his team had to perform countless ELISAs and used up invaluable sample specimens to make any scientific progress. Their application of proteomics analysis to a high-quality longitudinal study cohort led to many discoveries, although these were hard-won.
He then became aware of Olink and ran a pilot study on over 1000 proteins for a subset of his samples.
Proteomics methodologies improved as time passed and Dr. Krolewski became aware of SomaScan. This technology uses SOMAmers, a modified form of nucleotide aptamer, to simultaneously analyze thousands of proteins at once, compared to one at a time with ELISA. He then became aware of Olink and ran a pilot study on over 1000 proteins for a subset of his samples.
Olink technology delivers on accuracy and sensitivity
Comparing this data to that of SomaScan, Dr. Krolewski found that Olink was hard to beat on accuracy and specificity. Olink also offered him the flexibility and scalability that SomaScan could not, enabling the progression from protein biomarker discovery to more targeted studies focusing solely on the proteins found to be most interesting after screening. In this way, he was able to scale down analyses from 11 Olink panels, down to just 5, saving on costs and precious sample.
Dr. Krolewski and his team used these 5 panels to run a study on 500 individuals from the Joslin longitudinal study cohort, for which their first paper has now been published (DOI: 10.1016/j.kint.2020.07.007). Overall, 56 proteins were found to be significant in diabetic kidney disease patients, and these could potentially serve as prognostic biomarkers for disease progression and treatment response.
Watch an interview with Dr. Krolewski to learn more about him and his work with Olink.
Dr Krolewski and his team are now working with Olink to develop 21 of these proteins into a customized panel to determine which of them may be used to predict kidney disease development in diabetic patients. He also plans to use the panel to conduct further studies on patient response to treatment, as well as make further advances in treatment for this disease, which are currently very limited.
Ihara K et al.,2021, A profile of multiple circulating tumor necrosis factor receptors associated with early progressive kidney decline in Type 1 Diabetes is similar to profiles in autoimmune disorders. Kidney Int. DOI: 10.1016/j.kint.2020.07.00
How the proteome behaves in healthy individuals
Clinical research, Multiomics
To achieve the goal of precision medicine, not only do different molecular profiles need to be understood in disease populations, but they must also be understood in the context of healthy populations.
Key proteomics publications from 2020
Proteomics
Welcome to the first post of the all-new weekly Olink to Science! Our customer survey revealed that you would like to know more about the many publications, research, and other science happening at Olink, therefore this blog aims to do just that: keep you informed on the exciting science taking place with our technology.
Protein biomarkers are crucial in early detection of cancer
Clinical research, Oncology, Protein biomarkers
A central premise of precision medicine is to identify biomarkers indicative of disease transitions early on. This is especially important in cancer where early treatment intervention could increase a patient’s chance of survival and reduce the probability of cancer recurrence.
Using PEA and RNA-Seq to study disease pathology
Clinical research, Proteomics
The following study illustrates how transcriptomics and proteomics complement one another to clarify the pathology of a complex, and little understood disease. Atopic dermatitis (AD) is the most common chronic skin condition affecting up to 20% of children and 7-10% of adults, depending on the population.
Olink protein biomarker panel indicates fermented foods fight inflammation
Inflammation, Proteomics
Could food be used to fight chronic disease?
Study identifies proteins involved in immunotherapy response
Oncology, Proteomics
'Ultimately, it is all about understanding and treating patients better in the future.'
Proteins diagnostic of lung cancer up to 5 years before disease onset
Oncology
An earlier Olink to Science blog post covered some amazing research that found that certain blood protein biomarkers have the potential to predict cancer up to 3 years before diagnosis. This may also be the case for lung cancer, as detailed in a recent study by Dagnino and her colleagues, where elevated levels of CDCP1 were detected in participants of a cohort who later developed the disease.
Utilizing proteogenomics technology for novel drug target discovery
Drug discovery & development
High-throughput multiplexed proteomic technology is leading the way to the latest developments in pre-clinical disease analysis in drug discovery. The pharmaceutical industry is now increasing its efforts in the discovery of novel drug targets by using protein quantitative trait loci (pQTLs), which allows for a more confident inference of disease causality and associated protein regulation.
Developing a high-performance biomarker panel for Alzheimer’s disease
Clinical research, Neurology, Protein biomarkers
A simple search of the term ‘scourge of Alzheimer’s Disease’ brings up over half a million website hits. A major disease, about 15% of us that reach the age of 67 to 74, and 44% of those 75 to 84 will develop AD.
How proteomics helped diabetic kidney disease research advance
Clinical research, Proteomics
Dr. Krolewski and his team at the Harvard Medical School found 56 proteins to be significant in diabetic kidney disease patients. Potentially, these could serve as prognostic biomarkers for disease progression and treatment response. This is how adding proteomics to the methodologies elevated their research.
2947
Biomarker assays
~881 million
Protein data points generated
1182
Publications listed on website