Exploring the complex relationship between race, genetics, and modern governance through scientific research and historical context.
In 2005, the U.S. Food and Drug Administration approved a heart failure drug called BiDil with an unusual specification—it was intended specifically for self-identified African Americans1 . This marked the first time the FDA had approved a race-specific drug, triggering a firestorm of controversy that would reverberate through medical and scientific communities for years to come1 .
The manufacturer's justification cited studies showing differential effectiveness in Black patients, but critics noted the research had significant methodological flaws and questioned whether we were witnessing the dawn of a new era of personalized medicine or the revival of scientific racism dressed in modern genetic clothing1 .
Two decades later, the debate over race, biology, and difference continues to evolve amid groundbreaking genetic research and shifting political landscapes. This article explores the complex intersection of race and science—how concepts of human difference have been used and misused throughout history, what modern genetics reveals about human variation, and why understanding these concepts matters for medicine, justice, and society.
The race categories we use today didn't emerge from sophisticated genetic analysis but from 18th-century naturalists like Carl Linnaeus, who created a hierarchical classification system with Europeans at the top4 .
In his foundational work Systemae Naturae, Linnaeus divided humans into four types by continental landmasses with not just physical descriptions but behavioral stereotypes—describing Africans as "crafty, lazy, and governed by caprice" while Europeans were "gentle, acute, inventive, governed by laws"4 .
These categories were socially constructed from the beginning, reflecting the biases and limited knowledge of their time rather than meaningful biological boundaries8 .
Modern scientists widely agree that race is a social construct, not a biological one3 8 . The socially-defined racial categories commonly in use do not map onto fixed biological categories in any meaningful way. Instead, race is better understood as a fluid, dynamic, and relational concept, both socially and biologically.
The completion of the Human Genome Project in 2003 confirmed what scientists had suspected: humans are 99.9% identical at the DNA level, and there is no genetic basis for race1 4 . The vast majority of genetic variation occurs within racial groups, not between them3 .
As geneticist David Reich has stated, "the long-held view about 'race' has just in the last years been proven wrong"3 .
| Aspect | Social Race Concept | Biological Ancestry Concept |
|---|---|---|
| Basis | Historical categories based on visible traits like skin color | Genetic similarities and differences measured through DNA analysis |
| Boundaries | Perceived as discrete categories | Continuous gradients without sharp boundaries |
| Variation | Emphasis on between-group differences | Most variation (≈85-90%) occurs within groups |
| Stability | Categories seen as fixed and essential | Understanding of variation evolves with new data |
| Utility | Useful for tracking social discrimination | Useful for understanding migration patterns and disease risks |
Human genetic diversity follows continuous gradients (clines) rather than discrete categories. The diagram below illustrates how genetic markers vary gradually across geographic space:
Continuous genetic variation across populations (simplified representation)
In June 2025, a massive NIH-funded study published in the American Journal of Human Genetics provided some of the most definitive evidence yet about the complex relationship between racial identity and genetic ancestry5 7 .
The research analyzed the DNA of more than 230,000 participants in the All of Us research program, a National Institutes of Health initiative designed to create a dataset that accurately represents the genetic diversity of the United States5 7 .
The researchers used a method called principal component analysis to identify genetic similarities and differences among participants7 . They compared the genetic data with people's self-reported racial and ethnic identities from the All of Us questionnaire, which included categories such as white, Black or African American, Asian American, and Hispanic/Latino7 .
The study revealed that self-reported race correlates poorly with genetic ancestry5 . Rather than sorting people into distinct clusters divided by racial and ethnic lines, the analyses found that people within different races and ethnicities show gradients of genetic variation7 .
The researchers also discovered significant genetic variation within the same racial groups across different U.S. states, likely reflecting the historical impacts of U.S. colonization, the transatlantic slave trade, and recent migrations7 .
One of the study's authors, Luisa Borrell of the CUNY School of Public Health, summarized the clear message: "These are two distinct constructs, they mean different things, and they should not be used interchangeably"5 .
| Finding | Description | Implication |
|---|---|---|
| Within-Group Variance | Most genetic differences exist within racial/ethnic groups rather than between them | Racial categories poorly capture actual genetic variation |
| Geographic Patterns | Genetic variation found within same racial groups across different states | Migration patterns and local histories shape genetic ancestry |
| Hispanic/Latino Diversity | Those in California, Texas, Arizona had high Native American ancestry; those in New York had highest African ancestry | "Hispanic" encompasses tremendous genetic diversity |
| African Ancestry Complexity | Those with West African ancestry had different BMI predispositions than those with East African ancestry | Broad "African" category masks important health-related differences |
Visual representation of the proportion of genetic variation occurring within versus between traditionally defined racial groups
| Method/Tool | Function | Application in Race/Ancestry Research |
|---|---|---|
| Principal Component Analysis (PCA) | Statistical technique that identifies patterns in genetic data | Reveals gradients of genetic variation that may not align with social race categories |
| Genome-Wide Association Studies (GWAS) | Scans genomes for markers associated with specific traits | Can reveal genetic factors in health disparities while controlling for environmental factors |
| Genetic Ancestry Estimation | Uses reference panels to estimate biogeographic ancestry | Provides more precise understanding of ancestral origins than racial categories |
| Admixture Mapping | Identifies genes associated with traits in recently mixed populations | Helps disentangle genetic and environmental contributions to health differences |
| Geographic Ancestry Modeling | Maps genetic variation across geographic space | Demonstrates continuous nature of human genetic diversity (clinal variation) |
Visualizes genetic similarities and differences as points in multidimensional space, revealing continuous variation rather than discrete clusters.
Identifies specific genetic variants associated with traits or diseases, helping distinguish genetic from environmental influences.
Uses reference populations to estimate geographical origins, providing more nuanced understanding than broad racial categories.
The use of race in medicine presents both promises and perils. On one hand, documenting health outcomes by race can reveal significant disparities—as seen during the COVID-19 pandemic when Black, South Asian, and Hispanic people were disproportionately affected4 .
Tracking health outcomes by race reveals important patterns of inequality that need addressing.
Immediately searching for biological explanations while ignoring social factors risks misdiagnosing the causes of disparities4 .
Frontline workers during the pandemic were more likely to be from ethnic minorities—a social factor explaining differential exposure risk4 .
The fundamental problem, as articulated in the book "What's the Use of Race?", is that when racial categories are embedded in medical research and practice, they can reinforce the false idea that race itself is a biological determinant of health rather than a social one.
In forensic science, DNA analysis is sometimes used to predict a suspect's perceived race through forensic DNA phenotyping. While this may seem like a practical application of genetics, it raises serious concerns about reinforcing racial stereotypes and potentially leading law enforcement down incorrect paths.
As Pamela Sankar, a bioethics professor at the University of Pennsylvania, notes, inferring a person's physical characteristics from genetic ancestry information is not straightforward and can lead to false assumptions.
The science of race and genetics exists within a political context, and research findings can be weaponized for ideological purposes4 5 .
The Trump administration specifically targeted a Smithsonian exhibition for promoting the idea that "race is not a biological reality but a social construct," calling it "divisive" and "anti-American ideology"4 .
This politicization creates challenges for scientists. As Jonathan Kahn, a legal and historical scholar at Northeastern Law School, observed about the recent All of Us study: "The paper is very open to interpretation. It doesn't settle anything"5 .
The journey to understand human variation has been marked by missteps, from Linnaeus's hierarchical classifications to the era of eugenics and the continued misuse of race as a biological category. Modern genetics has provided us with powerful tools to see what previous generations could not—that the old racial categories don't align with genetic reality, and that human genetic variation is far more complex, continuous, and fascinating than those simplistic boxes would suggest.
While race may not be biological, racism and racial disparities have very real effects on health and society4 .
The challenge moving forward is to acknowledge this paradox. As Ann Morning, a sociologist at New York University, notes, "When scientists use racial categories, for example, in genetic research, it sends a message to the wider society that races are actually biological groupings as opposed to social constructs"8 .
This doesn't mean we should abandon tracking health outcomes by race—quite the opposite. We need this data to document and address disparities, while being clear that the causes are primarily social, not genetic.
The most promising path forward may lie in recognizing what genetics can and cannot tell us about ourselves. As Charles Rotimi, senior author of the All of Us study, aptly stated: "Trying to use genetics to define race or to use genetics to support our racial classification is like slicing soup. You can cut all you want—that soup is going to stay mixed"5 .
In recognizing both the power and limitations of genetics, we can develop a more accurate, ethical, and useful understanding of human difference—one that serves all of humanity.
Future research should focus on: