Genomics: Insight

The societal construct of race is an inadequate method of human categorization, especially in the context of medicine

Background

The man-made concept of race is one of the most frequently used methods of classifying human populations today, and has for generations been the basis of many social injustices and conflicts [1]. But, race is almost impossible to soundly define; the ways in which societies have historically attempted to characterize race are:

1. Biologically, including morphology and skin color
2. Socio-culturally, including language, religion, and ethnicity
3. By geographic origin in the context of human migration

These criteria are open-ended and easily transcended by different groups, especially by interethnic admixed (ethnically mixed) populations [1]. Latin American populations serve as an example of how difficult race is to define because of its varying proportions of genetic admixture, which can be explained by the Iberian conquest of Latin America in the 16^th century. Because of the European colonization of the Americas and mixing with the indigenous peoples, in addition to the subsequent introduction of African slaves, the three races intermixed greatly. This racial admixture of Caucasian, indigenous, and African populations created what we today call the Latino populations. [1]

Race is an inadequate method of human categorization

Today, categorization depends solely on self-identification. Permitting individuals to identify themselves as a specific race instead of being labeled as such by others reinforces the idea that race is a societal construct, and allows people to maintain full ownership of that facet of their identity (as they should). However, it does raise the question of the validity of race as a reference point for medicine.

Countless studies have investigated the role of the racial genetic differences in disease susceptibility. In the world of preventive medicine, identifying dangerous genetic predispositions has the potential to improve early identification of those at high risk for disease and appropriately administer screenings and treatment.

What is Linkage Disequilibrium?

Linkage disequilibrium (LD) gauges the genetic diversity of a population by measuring how often two loci (the location of a specific gene on a chromosome) appear next to each other in the different organisms, because over generational time, chromosomal crossovers during meiosis will split up haplotypes (a group of alleles that are inherited as a group from a single parent) and weaken the linkage disequilibrium of a population. [2] One method of LD measurement is LOD score (logarithm of the odds), which estimates the probability of two genes being located near one another, and therefore being inherited together (or more linked). A higher LOD score indicates a higher linkage between genes, and hence a lower genetic diversity. [3]

What is Admixture Mapping?

Admixture mapping is a method that identifies the correlation between the expression of a certain trait, like a disease, and a certain ancestry.  To do this, scientists look at the genetic makeup of an ethnically admixed population . Within a population, looking at the frequency of a specific ancestry at a disease locus (a gene that causes the disease) can help to identify what ancestries can be associated with what variant of a trait. [4] If a certain ancestry appears to be correlated with a certain trait, this will show as a spiked percentage of this ancestry on a graph, which can be called an admixture peak. Admixture peaks indicate that this ancestry is more likely to carry a disease locus.

Comparing Genetic Diversity Within a Population

In 2007, scientists examined the genetic makeup of a group of self-identified African Americans (who are generally an ethnic mix of African and European populations) in order to identify how ancestry influences disease risk. They created models that investigated the correlation between ancestry and levels of the Interleukin 6 soluble receptor (IL-6 SR). IL-6 SR is a protein that plays an important role in disease progression for certain cancers, inflammatory diseases, neurological conditions, and pathogen infections. They measured the LOD score at the admixture peak in relation to the level of IL-6 in a given African American individual (arranged from highest levels to lowest levels on the x-axis). The scientists then ran different theoretical models in which the risk for certain ancestries were increased by a certain amount. It was observed that when risk for European ancestry was increased 2.5 fold, the LOD score peaked around 6 for the top 10%-30% of African Americans, while when risk for African ancestry was increased by 1.25 fold, the LOD score dropped to an average of -3 across the entire sample. This suggests that there is an allele with a strong positive influence on IL-6 SR levels that comes from predominately European ancestry that 10%-30% of African Americans carry. [5] In simpler terms, this data indicates that higher levels of European ancestry correlates with higher levels of IL-6 SR.

In a different study, scientists chose to construct haplotypes diagrams of the NAT2 gene. This gene codes for N-acetyltransferase type 2 (Nat2), which is an enzyme that influences how the body metabolizes certain drugs. Differences in this gene can influence disease susceptibility and have implications for the development of personalized drug therapies. In this study, haplotypes of NAT2 SNPs (a single-base variation in the DNA) are constructed in a population of northeastern Brazilians (typically an ethnic admixture of Afro-Brazilians, Caucasians, and Amerindians). From the parental populations, there are five different identifiable haplotypes between five significant SNPs (G191A, C481T, G590A, A803G, and G857A). Two of the haplotypes have Caucasian ancestry, suggesting a stronger LD for NAT2 in Caucasians; however, there are identifiable haplotypes from all three parental populations. [6] This prevalence of haplotypes across ancestries suggests that one’s ancestry does not have a real influence on their NAT2 gene, in contrast with the influence of ancestry on one’s IL-6 SR gene.

However, there are identifiable haplotypes from all three parental populations

Data: Comparing Genetic Diversity Between Populations

Due to the prevalence of asthma, especially amongst American children, scientists have tried to establish a genetic risk profile for the disease many times. One team organized a table of admixture peaks (within certain admixed populations) with genes that have been proven to impact asthma susceptibility in select admixed populations, although there is no clear pattern in ethnic-based susceptibility. There are a considerable number of admixture peaks for genes of African Ancestry; in fact, all identified admixture peaks in African American populations are from the African parental populations. However, there is still a significant variety in ancestry of admixture peaks across populations: Native American ancestry plays a large role in asthma susceptibility in Puerto Rican populations especially, and although people of European ancestry are notably less susceptible to the disease, there are still European admixture peaks in Mexican and Latino populations. [7] Looking at ancestry would not be an effective way to predict asthma susceptibility.

Overall, human populations have proven to be ancestrally extremely diverse, especially in Latin America. For example, scientists categorized different AIMs (ancestry-informative markers, which are certain genes that are typically specific to certain ethnic groups) in Central American populations (excluding Mexico) in order to identify the differing genetic influences of the parental populations. The variety was made extremely clear: St. Vincent and Grenada, for instance, have an 81% African ancestry, while East Guatemala has only 7%. East Guatemala also has the highest Amerindian genetic makeup at 53%, while the remaining populations range from 0%-19%. This demonstrates that there is little consistency in the genetic makeup of admixed populations, so there is not much opportunity to use generalizations about ethnicity and race for medical reasons within these groups.[1]

Conclusion

Despite the presence of some disease-related patterns along ethnic lines, the variety of haplotypes and SNPs for different genes renders the concept of race inept as a categorization of people in the context of preventive medicine. This is especially true given the increasing presence of ethnically admixed populations worldwide. When trying to identify genetic predispositions towards certain diseases, identifying specific AIMs would serve as a more precise categorization of people, although the categories would still have to be extremely dynamic and varying in order to encompass the many genetic nuances of human populations.

It is important to keep in mind that genetics is only one of many factors in the identification of disease susceptibility. Asthma risk, for instance, is also impacted by socioeconomic status  because environmental factors are important in development of the disease. As scientists Olden and White put it, “genetics loads the gun, but the environment pulls the trigger.” Individuals in impoverished areas within a more highly developed region risk greater exposure to risk factors such as traffic, mold, detrimental dietary options, and cigarette smoke, while potentially not being able to access adequate healthcare; thus, there is an uneven distribution of life-threatening asthmatic cases along socioeconomic lines. [7]

Genetics is only one of many factors in… disease susceptibility

Taking all of this into consideration when evaluating disease susceptibility individualized disease treatment is important.

There is also a further societal implication in the flaws of race as a construct. Race, especially in the US, serves as the basis for countless prejudices and conflicts; when this basis is rendered invalid, where does it leave us?

Related Links

1. Salzano, Francisco, and Mónica Sans. “Interethnic Admixture and the Evolution of Latin American Populations.” Genetics and Molecular Biology, 2013, www.ncbi.nlm.nih.gov/pmc/articles/PMC3983580/#b13-gmb-37-151.
2. Robinson, Mary Ann. “Linkage Disequilibrium - an Overview | ScienceDirect Topics.” Encyclopedia of Immunology (Second Edition), 1998, www.sciencedirect.com/topics/neuroscience/linkage-disequilibrium.
3. Brody, Lawrence. “LOD Score.” Genome.Gov, www.genome.gov/genetics-glossary/LOD-Score.
4. Shriner, Daniel. “Overview of Admixture Mapping.” Current Protocols in Human Genetics, 2013, currentprotocols.onlinelibrary.wiley.com/doi/abs/10.1002/0471142905.hg0123s76.
5. Reich, David, et al. “Admixture Mapping of an Allele Affecting Interleukin 6 Soluble Receptor and Interleukin 6 Levels.” The American Journal of Human Genetics, 2007, www.cell.com/ajhg/fulltext/S0002-9297(07)61112-4.
6. Talbot, Jhimmy, et al. “Interethnic Diversity of NAT2 Polymorphisms in Brazilian Admixed Populations.” BMC Genetics, 2010, link.springer.com/article/10.1186/1471-2156-11-87.
7. Mersha, Tesfaye. “Mapping Asthma-Associated Variants in Admixed Populations.” Frontiers Genetics, 2015, www.frontiersin.org/articles/10.3389/fgene.2015.00292/full#B128.