You receive a phone call: the results from routine blood tests show a \u201clow white cell count\u201d. Your doctor explains that more investigations are necessary, perhaps a referral to the haematologists. This might represent something concerning.<\/p>\n
But what if this \u201clow white cell count\u201d were completely normal for you, because of a harmless genetic variant shared with millions of people worldwide?<\/p>\n
This scenario describes the Duffy null variant<\/a>: a genetic variation that leads to fewer neutrophils \u2013 a type of white blood cell \u2013 circulating in the blood. Even though neutrophils fight infections, people with the variant aren\u2019t at higher risk of illness<\/a>. <\/p>\n The Duffy null variant protects against Plasmodium vivax malaria, a form of the disease that relies on the Duffy antigen to enter red blood cells. In regions of Africa and the Middle East<\/a> where P. vivax once circulated widely, this variant became common precisely because it blocked the parasite\u2019s entry.<\/p>\n However, when a doctor receives a blood test result, none of this context is present. All they see is a number \u2013 often in red \u2013 and a reference range which explains what \u201cnormal\u201d should be. It is this reference range that guides interpretation of an individual blood test result.<\/p>\n<\/p>\n The miscategorisation of neutrophil counts as \u201clow\u201d in people with the Duffy null variant can lead to real-world harms. These include anxiety<\/a>, as a flagged \u201clow\u201d white cell count can sound like an early warning sign of serious illness.<\/p>\n It also drives avoidable bone marrow biopsies<\/a>, because clinicians may worry about bone marrow failure or blood cancer and order invasive tests that aren\u2019t actually needed.<\/p>\n People with the variant may be excluded from clinical trials<\/a> because their neutrophil count appears to fall below strict eligibility cut-offs, despite being completely healthy. And it can even lead to reduced chemotherapy doses<\/a>, as treatment algorithms automatically lower doses in response to neutrophil numbers, potentially compromising care.<\/p>\n In the past, this pattern was labelled \u201cethnic neutropenia\u201d, but that term creates its own problems<\/a>. Race and ethnicity are socially constructed categories, not biological determinants. They\u2019re based on social histories, cultural identities and the ways societies classify people, rather than on precise genetic differences.<\/p>\n Medical practices and technologies can contribute to how socially constructed categories are made and reproduced. People grouped together under the same racial or ethnic label can have very different ancestries and health profiles, so these categories don\u2019t reliably map onto people\u2019s blood counts.<\/p>\n Using them to judge whether a neutrophil level is \u201cnormal\u201d risks reinforcing crude groupings and misdiagnosis. What matters is a person\u2019s Duffy status \u2013 the genetic factor that actually drives the difference in neutrophil numbers \u2013 and blood tests need to be interpreted accordingly.<\/p>\n New research<\/a> led by Lauren Merz at the University of Michigan and Stephen Hibbs at Queen Mary University of London shows that more than 20% of people with the Duffy null variant are miscategorised as \u201cabnormal\u201d by current reference ranges. <\/p>\n This study created new blood count reference ranges, specific for healthy people with the Duffy null variant. These new Duffy null ranges were consistent for varied participants living in Namibia, Saudi Arabia, the UK and the US, and can be incorporated into clinical practice to support better interpretation and decision making.<\/p>\n<\/p>\n What is a reference range?<\/p>\n This isn\u2019t the first time that a reference range \u2013 the range of values doctors use to decide whether a test result is \u201cnormal\u201d \u2013 has worked for some people but not others. Research shows that the HbA1c test, commonly used to diagnose and monitor type 2 diabetes, gives falsely low results<\/a> in people with a genetic variant widespread among South Asian groups.<\/p>\n These miscategorisations raise a key question: what sort of technology is a reference range? When reference ranges appear in textbooks or on blood test reports, they look like they reveal fixed biological \u201ctruths\u201d.<\/p>\n But approaches from science<\/a> and technology studies<\/a> encourage us to think differently about what biomedical practices and technologies do. They show how everyday medical practices produce and operationalise racial differences<\/a>.<\/p>\n To understand this properly, we need to look at what happens in practice. Creating a reference range follows a set process<\/a>. A laboratory identifies around 120 healthy people from the local population and measures their blood.<\/p>\n The third lowest result (the 2.5th percentile) becomes the \u201clower limit of normal\u201d, and the third highest (the 97.5th percentile) becomes the \u201cupper limit of normal\u201d. Once a reference range is published, other hospitals can adopt it after checking it against as few as 20 people.<\/p>\n The problem is that these ranges are often built from samples taken mostly from majority groups in a particular region. As a result, they can miss important variation present in minoritised groups and those gaps can translate into mislabelling, misinterpretation and unnecessary worry for patients whose biology simply falls outside the narrow sample used to define \u201cnormal\u201d.<\/p>\n