The Pith: In this post I examine the relationship between racial ancestry and cancer mortality risks conditioned on particular courses of treatment. I review research which indicates that the amount of Native American ancestry can be a very important signal as to your response to treatment if you have leukemia, as measured by probability of relapse.
If you are an engaged patient who has been prescribed medication I assume you’ve done your due diligence and double-checked your doctor’s recommendations (no, unfortunately an M.D. does not mean that an individual is omniscient). Several times when I’ve been prescribed a medication I have seen a note about different recommended dosages by race when I did further research. Because of my own personal background I am curious when it says “Asian.” The problem with this term in medical literature is that “Asian” in the American context is derived from a Census category constructed in 1980 for bureaucratic and political purposes. It amalgamates populations which are genetically relatively close, East and Southeast Asians, with more distant ones, South Asians (when my siblings were born I remember that my parents listed their race as “Asian” when they filled out paper work for the hospital).
But at least the issues with an “Asian” category are clear. Consider the “Hispanic/Latino” category. In the the USA this term also became popular through government fiat around 1970, as a catchall for people whose ancestry derives from the Spanish speaking Americas, with Spaniards, Portuguese, and Brazilians, being border-line cases. Additionally, it has become relatively common in the general American culture to code Hispanic as non-white. This despite the fact that all Latin American populations have large self-identified white populations, with some, such as Argentina and Uruguay, being overwhelmingly white. In the USA between 54% and 92% of Hispanics identify as white in terms of their race. The discrepancy is that some surveys allow for the “Some other race” option, which is the second most popular choice. Surveys which force respondents into a few categories such as white, black, Native American or Asian, produce a result where Hispanics default to a white self-identification.
Implicitly we know it’s more complicated than this mishmash of bureaucratic convenience and opportunistic American identity politics. The HapMap has a Mexican American sample from Los Angeles. Above you see K = 3 in ADMIXTURE for Mexican Americans. Each thin “slice” is an individual, with the color proportions reflective of genomic contributions of one of three putative ancestral groups.The full plot had Europeans and Chinese as well. Blue seems to correspond with Native American, and red white European (the green residual is modal in East Asians). Los Angeles’ Mexican American community is obviously mixed-race. What in Latin American might be termed mestizo. And yet according to the survey data when forced to choose this community seems to affiliate with a white Spanish identity, blanco. Seeing as almost all of them are Spanish speaking and not indigenous (I am aware that the USA has a small and growing non-Spanish speaking Latino population of indigenous immigrants), this would make sense. But another facet of Mexican American identity surfaces in the concept of Aztlán, which is a nod to the Nahua roots of much of the Mexican population.
But whatever the the cultural nuance and subtly, which can be decomposed at length, it is also important to properly characterize the genetic structure of the Hispanic populations. Some Mexican Americans are predominantly white European in ancestry, and some are predominantly Amerindian. Many are mixed in roughly equal proportions. This is not just a minor detail. Going back to my first paragraph, a new letter to Nature Genetics reports on the differential response to treatment in children with leukemia proportional to Native American ancestry. Ancestry and pharmacogenomics of relapse in acute lymphoblastic leukemia:
Although five-year survival rates for childhood acute lymphoblastic leukemia (ALL) are now over 80% in most industrialized countries…not all children have benefited equally from this progress…Ethnic differences in survival after childhood ALL have been reported in many clinical studies…with poorer survival observed among African Americans or those with Hispanic ethnicity when compared with European Americans or Asians…The causes of ethnic differences remain uncertain, although both genetic and non-genetic factors are likely important…Interrogating genome-wide germline SNP genotypes in an unselected large cohort of children with ALL, we observed that the component of genomic variation that co-segregated with Native American ancestry was associated with risk of relapse (P = 0.0029) even after adjusting for known prognostic factors (P = 0.017). Ancestry-related differences in relapse risk were abrogated by the addition of a single extra phase of chemotherapy, indicating that modifications to therapy can mitigate the ancestry-related risk of relapse.
They inferred ancestry through two different methods. First, they used principal component analysis to extract the biggest independent dimensions of variation within the genetic data set. What happens when you do this is that you quickly recapitulate totally comprehensible patterns of population genetic clustering within your data set. To the left you see a PCA where the largest component of variance separates Africans from non-Africans (x axis) and the second largest separates Europeans from East Asians (y axis). The underlying data is from a merging of the HapMap and HGDP.
This pattern crops up over and over. Within this broader framework you see more specific trends. I have labelled the Mexican American populations on the two dimensional plot. Note its linear topology. This is a sign of possible admixture. Roughly, the position of any given individual along a line between two putative parental populations is proportional to their distance from those populations. In plain English, someone who is half-Chinese and half-Swedish will be placed equidistant from the Chinese and Swedish clusters on a PCA plot with those populations. The Mexican Americans span a region between Europeans and East Asians. This makes perfect sense in terms of their recent population history. It also means that just knowing that someone is “Mexican” in their heritage does not tell you as much about their ancestry as if you knew that someone was “Chinese.” There’s a lot of variance genetically in the Mexican population.
I introduced the preamble about PCA plots because the figure where they use PCA to elucidate the ancestry of the HapMap and their sample population of leukemia effected children can be somewhat confusing. What you see is that panel A, B, and C, are PC 1, 2, and 3, respectively. That means that the top panel explains the most variation, and the third panel the least. I’ve added some extra labels because of the small font. You see in the top panel immediately what was evident in the two dimensional plot above: Africans separate out from non-Africans.The boxes represent the 25-75 percent intervals within the populations. Contrast the very tight distributions of the “pure” reference populations, and the more varied distribution of the children in their data set. It seems that some self-identified white children have a rather high load of African ancestry, while the black Americans naturally vary a great deal more than Yoruba in Nigeria. The distribution of the Mexican Americans reflects the African ancestry which has been absorbed within the Mexican population more broadly.
Panel B illustrates the second PC, which separates non-Africans on a rough west-east axis. So what’s going on with the Asians? Again, the 1980 Census strikes again! A substantial fraction of the “Asians” are “South Asian,” who have somewhat more “European” than “Asian” ancestry. Again, a small minority of “white” children seem to have substantial Asian ancestry. The Hispanic pattern is rather easy to explain, probably simply Amerindian-European admixture variation.
The last PC seems to separate Native Americans from other populations. So why are white and Asian children also exhibiting variance here? First, a non-trivial proportion of white Americans have substantial Native American ancestry. Brett Favre has a grandparent who was a member of the Choctow tribe, for example. Second, I suspect much of the variance is due to a common ancestry between Amerindians and some Eurasian groups which isn’t showing up in the white Utah sample, which is sampled from the far west of Eurasia, or the Chinese sample.
Another way to visualize ancestry is of course to posit K number of ancestral groups, and assign given quanta of ancestry to each individual from a given K. To the right you see a STRUCTURE bar plot where 2,500+ individuals are displayed vertically, with shading proportional to ancestry. I’ve placed tentative labels. Most of the children in the sample are white, and so exhibit mostly European (red) ancestry. From what I know about the black American community it seems that on this visualization they’ve been separated into two clusters (see the supplements for the algorithm). About 10% of black Americans are more than 50% white, while the median black American has 20-25% white ancestry. The Asian cluster is strange because it amalgamates East and South Asians. South Asians are 65-90% “European,” depending on their ancestral region. Finally, you have the Mexican Americans, who span the range of admixture between Europeans and Amerindians, with some African element as well.
STRUCTURE produces the averages to the left for self-identified populations. The proportions for African Americans is just about right. For the Hispanic category it seems more European than the Los Angeles Mexican Americans, but there are historical reasons to suspect that Mexican Americans in Texas have more Spanish ancestry, while Cubans in the USA are overwhelmingly white (and Puerto Ricans have more white ancestry than black or Amerindian). The very low percentages for non-European ancestry for whites makes me skeptical of the means; I assume there are some mixed-race individuals who identify as white, but I wonder if most white Americans with ~1% “Native American” just have deep common ancestry dating back to the Ice Age, or whether it’s an artifact of the method.
But what’s the point of all this? Ancestry analysis is fun, interesting, and has some relevance to broader socio-political debates and conflicts, but this is a story with some medical relevance (which is why it’s in Nature Genetics). In short, the authors found that Native American ancestry was a very high risk factor for relapse, conditional on the extent of chemotherapy. I merged table 3 and some panels from figure 2 to show what’s going on:
On the right are a list of risk (or mitigating) factors. I’ve underlined the effect of the proportion of Native American ancestry, treated as a continuous variable. To the left, you see the probability of cancer relapse as a function of Native American ancestry. The red line are those with less than 10% Native American ancestry, and the blue line more than 10%. In the top panel you see the impact on self-identified whites. The bottom panel shows the outcome for those who did not receive “delayed intensification” treatment. Panel E, which I did not show, illustrates clearly that the two lines converge when delayed intensification treatment is provided. If there is something in the Native American genetic background causing this problem, then it seems one can model it as a “gene-environment interaction.” That is, the genetically mediated outcome is conditional on particular environmental conditions (in this case, lack of the treatment).
But ancestry isn’t magic. The authors managed to track down candidates SNPs associated with Native American ancestry on the genomic level. In particular, the risk allele at rs6683977 at PDE4B was significantly more common among those with more than 10% Native American ancestry than less than 10%. Native American ancestry in that genomic region was also associated with particular relapse risk.
This seems a relatively straightforward application of using genetic data in a cost-benefit program. In the United States there is a major issue with growing health care costs. Many with a technocratic “evidence based” bent are curious as to efficacies of particular treatments, and their relationship to the costs incurred. It may be that for particular genetic backgrounds the cost-benefit calculus will be different than for the general population. While further rounds of chemotherapy may not be justified in terms of return-on-investment (i.e., probability of survival 10 years out) for a white child, it may be for a Native American one. Weighing costs and probabilities like this may seem bloodless, but we do it implicitly every day. This is just another tool in that thankless enterprise.
Citation: Yang JJ, Cheng C, Devidas M, Cao X, Fan Y, Campana D, Yang W, Neale G, Cox NJ, Scheet P, Borowitz MJ, Winick NJ, Martin PL, Willman CL, Bowman WP, Camitta BM, Carroll A, Reaman GH, Carroll WL, Loh M, Hunger SP, Pui CH, Evans WE, & Relling MV (2011). Ancestry and pharmacogenomics of relapse in acute lymphoblastic leukemia. Nature genetics PMID: 21297632