Proteins generally determine whether people are healthy or sick regardless of their genomic background. Thus, comprehensively mapping the precise makeup and distribution of proteins in the body, the “proteome,” will greatly advance researchers’ and physicians’ knowledge of health and disease. With an improved understanding of the proteome, researchers will be better able to design novel treatments that target diseases at their mechanistic roots in proteins and monitor treatment effectiveness through protein fluctuations.
Next generation proteomics technologies, like the Nautilus Proteome Analysis Platform, aim to give researchers the ability to quickly and comprehensively analyze the proteome. These technologies will hopefully help us achieve a healthier future. But a critical question is, for whom? To ensure the benefits of proteomics reach all people, we need to make the data and applications derived from these technologies available to everyone regardless of background, ethnicity, geographic location, or any other factors.
In the past, biological research efforts have been marred by fundamental biases that limit the scope of their findings as well as their utility. To combat these biases, many, including the American Association for Cancer Research and the National Academies of Sciences Engineering and Medicine, have called for concerted efforts to improve representation in biological and clinical research. As proteomics begins to mature, we and others have the opportunity to avoid the biases of the past and create a more equitable healthcare future for all.
This post describes the ways biases have historically led to inequities in genomics research and highlights ways researchers can rectify those inequalities with more and better data. In part 2 of this series, we will discuss how novel proteomics technologies may enable a more equitable future.
To understand how research biases have undermined health equity in the past, it is informative to look to genomics. It is an understatement to say that much good has come from sequencing the human genome. With a first (and quite rough) draft of the human genome completed in the early 2000s, researchers gained access to information and technologies that created a scaffold upon which they could build hypotheses about the causes of a wide variety of diseases. They began to quickly associate many specific genetic variants with diseases. Unfortunately, this scaffolding was built off of genome sequences that came almost exclusively from people of European descent. There was very limited representation of people from other ancestries and, even today 87% of people in large scale genomic studies are of European descent. This limits the benefits to people from other ancestries in a number of ways:
(For a more thorough look at these and other issues of equity in genomics see Sirugo et al 2019.)
These issues lead to cascading inequities in healthcare. With biased genomics data, researchers create tests that only diagnose patients from particular subpopulations and treatments that are only effective in these subpopulations. For example, most screens for cystic fibrosis only identify genetic variants commonly found in people of European descent (Lim et al 2016), and many people with uncommon variants are ineligible for recently approved treatments (McGarry and McColley 2021). These inequities lead to mistrust in the biomedical system and deter minority participation in health research (George et al 2014).
With the proteomics revolution, we have the chance to avoid the biases of the past and engender trust in an improved healthcare system. We’ll discuss how in the next post in this series.
|cookielawinfo-checkbox-analytics||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".|
|cookielawinfo-checkbox-functional||11 months||The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".|
|cookielawinfo-checkbox-necessary||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".|
|cookielawinfo-checkbox-others||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.|
|cookielawinfo-checkbox-performance||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".|