TRC #281: Race In Biomedical Research + Is Reality TV Real? + Skeptical Newlywed Game

ladiesnight2It’s ladies’ night at The Reality Check!   With Darren away, the rest of the crew is joined by Cristina Roach and Dina Tsirlin.   First Dina discusses the role of race in biomedical research.   Cristina then looks at whether reality TV is really real.  Lastly Adam challenges the two couples to a skeptical version of the Newlywed Game.

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Race In Biomedical Research

Akinniyi, D. C., & Payne, P. W. (2011). BIDIL LESSONS: CARDIOLOGISTS VIEWS OF A RACE-BASED PERSONALIZED MEDICINE. Journal of the American College of Cardiology, 57(14s1), E1926-E1926.

Taylor, A. L., Ziesche, S., Yancy, C., Carson, P., D’Agostino Jr, R., Ferdinand, K., … & Cohn, J. N. (2004). Combination of isosorbide dinitrate and hydralazine in blacks with heart failure. New England Journal of Medicine, 351(20), 2049-2057.

Doyle, J. M. (2006). What race and ethnicity measure in pharmacologic research. The Journal of Clinical Pharmacology, 46(4), 401-404.

Vaidyanathan G. Redefining clinical trials: the age of personalized medicine. Cell. 2012;148(6):1079-1080

Frueh, F. Personalized medicine: what is it? How will it affect health care? Paper presented at: 11th Annual FDA Science Forum; April 26, 2005; Washington, DC. . Accessed July 24, 2012

Bates, S. (2010). Progress towards personalized medicine. Drug discovery today, 15(3), 115-120.

Kahn, J. (2006). Genes, race, and population: avoiding a collision of categories. American Journal of Public Health, 96(11), 1965-1970.

Ross, C. J., Katzov-Eckert, H., Dubé, M. P., Brooks, B., Rassekh, S. R., Barhdadi, A., … & Hayden, M. R. (2009). Genetic variants in TPMT and COMT are associated with hearing loss in children receiving cisplatin chemotherapy. Nature genetics, 41(12), 1345-1349.

Mesko, B., Zahuczky, G., & Nagy, L. (2012). The triad of success in personalised medicine: pharmacogenomics, biotechnology and regulatory issues from a Central European perspective. New Biotechnology, 29(6), 741-750.

Salmela, E., et al. 2011. Swedish population substructure revealed by genome-wide single nucleotide polymorphism data. PLoS One 6: 2: e16747

Greenbaum, D. (2012). Regulation and the fate of personalized medicine.The virtual mentor: VM, 14(8), 645.

Bolnick, D. A., Fullwiley, D., Duster, T., Cooper, R. S., Fujimura, J. H., Kahn, J., … & TallBear, K. (2007). The science and business of genetic ancestry testing. SCIENCE-NEW YORK THEN WASHINGTON-, 318(5849), 399.

Hinton, C. F., Grant, A. M., & Grosse, S. D. (2011). Ethical implications and practical considerations of ethnically targeted screening for genetic disorders: the case of hemoglobinopathy screening. Ethnicity & Health,16(4-5), 377-388.

Ali-Khan, S. E., Krakowski, T., Tahir, R., & Daar, A. S. (2011). The use of race, ethnicity and ancestry in human genetic research. The HUGO journal,5(1-4), 47-63.

Kaplan, J. B., & Bennett, T. (2003). Use of race and ethnicity in biomedical publication. JAMA: the journal of the American Medical Association,289(20), 2709-2716.

Hunt, L. M., & Megyesi, M. S. (2008). The ambiguous meanings of the racial/ethnic categories routinely used in human genetics research. Social science & medicine, 66(2), 349-361.

HCD Research, Inc. (2005). Physicians Believe Drugs Targeted for Ethnic and Racial Groups May Provide Therapeutic Advantages. Retrieved from

Williams, M. J., & Eberhardt, J. L. (2008). Biological conceptions of race and the motivation to cross racial boundaries. Journal of Personality and Social Psychology, 94(6), 1033.

Lillquist, E., & Sullivan, C. A. (2006). Legal regulation of the use of race in medical research. The Journal of Law, Medicine & Ethics, 34(3), 535-551.

Brewer, R. M. (2006). Thinking critically about race and genetics. The Journal of Law, Medicine & Ethics, 34(3), 513-519.

Díaz-Perera, G., Bacallao, J., & Alemañy, E. (2012). Subpopulations with particular epidemiologic profiles and risks in Havana, Cuba: diabetes, hypertension, and tobacco-related illnesses. Revista Panamericana de Salud Pública, 32(1), 9-14.

Collier, R. (2012). A race-based detour to personalized medicine. Canadian Medical Association Journal, 184(7), E351-E353.

Chang T. (2012) Personalizing Medicine: Beyond Race. Virtual Mentor. American Medical Association Journal of Ethics. 13(8), 628-634.

Chan, S. L., Suo, C., Lee, S. C., Goh, B. C., Chia, K. S., & Teo, Y. Y. (2011). Translational aspects of genetic factors in the prediction of drug response variability: a case study of warfarin pharmacogenomics in a multi-ethnic cohort from Asia. The pharmacogenomics journal, 12(4), 312-318.

Krimsky, S. (2012). The short life of a race drug. The Lancet, 379(9811), 114-115

Hamburg, M. A., & Collins, F. S. (2010). The path to personalized medicine. The New England Journal of Medicine, 363(4), 301-4.

Hunt, L. M., & Kreiner, M. J. (2013). Pharmacogenetics in Primary Care: The Promise of Personalized Medicine and the Reality of Racial Profiling.Culture, Medicine, and Psychiatry, 1-10.

Malandrino, N., & Smith, R. J. (2011). Personalized medicine in diabetes. Clinical Chemistry, 57(2), 231-40.

McGregor, J. (2010). Racial, ethnic, and tribal classifications in biomedical research with biological and group harm. The American Journal of Bioethics, 10(9), 23-24.

Chan, I. S., & Ginsburg, G. S. (2011). Personalized medicine: progress and promise. Annual review of genomics and human genetics, 12, 217-244.

Tayo, B. O., Teil, M., Tong, L., Qin, H., Khitrov, G., Zhang, W., … & Bottinger, E. P. (2011). Genetic background of patients from a university medical center in Manhattan: implications for personalized medicine. PloS one,6(5), e19166.

Burn, J. (2013). Should we sequence everyone’s genome? Yes. BMJ: British Medical Journal, 346.

McClellan KA, Avard D, Simard J, Knoppers BM. (2013). Personalized medicine and access to health care: potential for inequitable access? Eur J Hum Genet. 21(2), 143–147

Cornetta K, Brown G. (2013).Balancing personalized medicine and personalized care.  Acad Med. 88(3), 309–13.

McNearney TA, Hunnicutt SE, Fischbach M, et al. (2009). Perceived functioning has ethnic-specific associations in systemic sclerosis: another dimension of personalized medicine. J Rheumatol, 36(12), 2724-2732.

Lorusso, L. (2011). The justification of race in biological explanation.Journal of Medical Ethics, 37(9), 535-539.

Rajagopalan, R., & Fujimura, J. H. (2012). Will personalized medicine challenge or reify categories of race and ethnicity?. The virtual mentor: VM,14(8), 657.

Nevins, J. R., Huang, E. S., Dressman, H., Pittman, J., Huang, A. T., & West, M. (2003). Towards integrated clinico-genomic models for personalized medicine: combining gene expression signatures and clinical factors in breast cancer outcomes prediction. Human molecular genetics, 12(suppl 2), R153-R157

Mascarenhas-Melo, F., Sereno, J., Teixeira-Lemos, E., Ribeiro, S., Rocha-Pereira, P., Cotterill, E., … & Reis, F. (2013). Markers of increased cardiovascular risk in postmenopausal women: focus on oxidized-LDL and HDL subpopulations.Disease Markers, 35(2): 85–96

Cho, M. K. (2006). Racial and ethnic categories in biomedical research: there is no baby in the bathwater. The Journal of Law, Medicine & Ethics,34(3), 497-499.

Surbone, A. (2010). Cultural competence in oncology: where do we stand?.Annals of oncology, 21(1), 3-5.

Hamilton, J. A. (2008). Revitalizing difference in the HapMap: race and contemporary human genetic variation research. The Journal of Law, Medicine & Ethics, 36(3), 471-477

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8 Responses to TRC #281: Race In Biomedical Research + Is Reality TV Real? + Skeptical Newlywed Game

  1. Darren says:

    Hi all (I thought I would post publicly in case other listeners had the same thought)

    Great job, Dina! I think you presented well on the complexity and complications associated with “race-based” medicine. It is really hard to disentangle the confounding variables in various populations. Race has been such a nebulous and misused concept for so long it is important to explore such things.
    I also think you have the most references/citations of any segment we’ve ever had! 🙂

    That said, I hope you don’t mind but I’m not entirely convinced. My several thoughts follow:
    I really wish someone had brought up the sickle-cell thing again because I was curious about that.
    Also, I understand there is great variability within a population so it can make it hard to have any useful comparison, but the little I have read about BiDil indicates it does work and it was tried in the first place because of differential reaction in a previous study. The problem could be I don’t really have access to all those wonderful articles you linked so if there is one in particular I should read let me know.

    The wikipedia link says “Cohn re-analyzed the data and found a signal that the drug combination appeared to work better in self-identified African-Americans in the V-HeFT trial, and published a paper on that work, and filed a new patent on the use of BiDil in “black” patients.[2][4][5] It had already been known that African-Americans with congestive heart failure (CHF) respond less effectively to conventional CHF treatments (particularly ACE inhibitors) than caucasians.[6]”

    First, is that second part not true? It seems hard to believe there aren’t any useful categorizations, although I do acknowledge you said the genome analysis said this was basically the case.

    Also, is it another myth that ‘asians’ typically lack a genetic disposition to an enzyme?

    I realize there are differences in populations, but if I think the age of personalized medicine will eventually be here, it seems so plausible to me that inbetween generic drug for all (what we mostly have now) and this pill only for Darren, there will be pills for people similar to Darren. Sex will be a huge differentiator, so is age, but I could also see some loose (or retrospectively determined) notion of ‘race’ being useful.

    Basically, I know that environment plays a large role, but are the non-environmental problems on this chart not relevant? (or is it really true Europeans spend more time in the sun than African Americans, thus why they get skin cancer more?)

    Isn’t Tay–Sachs disease a clear example of genetic differences?

    Happy to be more fully convinced 🙂

    • Jim V says:

      I have given myself a few months to ponder Dina’s research and I’m still not convinced. Yes, there are more than 40 highly technical references (though the order of presentation is a bit baffling — neither alphabetical, date or subject).

      Michael Specter, in his 2009 book “Denialism,” gives a very different view while recognizing that the concept of race is fraught with problems of every kind. He quotes the prominent yet controversial geneticist Neil Risch from U of California, SF (referring to the 99% identicality among any two humans picked at random from anywhere in the world): “What we are going to find is precisely that the other percent plays a role in determining why one person gets schizophrenia or diabetes while another doesn’t, why one person responds well to a drug while another can’t tolerate it.” Why are Crohn’s disease and hemochromatosis more prevalent among Europeans whereas the “Delta 32 mutation on the CCR5 receptor” has never been found in Africans or Asians? (of significance in AIDS research).

  2. Fredrik says:

    Great episode! As always!
    What’s the name of the music played in the Newlywed game?

  3. PatG says:

    A great episode as always. Thanks for bringing up those questions Darren – I had much the same thoughts.

  4. Dina says:

    Alrighty, finally got some time to sit down and articulate a response. Here we go 🙂

    I too wish we got back to the sickle-cell issue because it really was an important point.
    At some point we realized that we’ve been talking for a while and it was only the first segment so we had to carry on. I’m really happy that there’s this forum where we can continue to discuss these issues since that’s what the podcast is all about! ]
    So, regarding sickle cell anemia, the idea is that, yes, sickle cell anemia is common in Africa, but it is much more frequent in specific areas, such as Sub-Saharan Africa as well as in other parts of the world, such as: South America, Cuba, Central America, Saudi Arabia, India, and Mediterranean countries such as Turkey, Greece, and Italy. So, as you can see, we can’t say that this disease is attributed to a certain “race”, but rather that in response to environmental pressures where malaria was common, a gene mutation arose that made individuals more resistant to malaria if they had one copy of the mutated gene. If they had two copies of the gene, they got afflicted with SCA. So, the idea is, that rather than making generalizations like “Individuals from an African descent are much more likely to have SCA”, we can say, individuals who were born/have ancestors from these specific geographic areas are more likely to have SCA. This is a great paper that’s free and also provides a nice visual representation of the spread of the gene:
    Tay Sachs is another good example of this but a bit different. So first, I think you’d agree that “Eastern European Jews” is not a race on its own and this disease also afflicts other populations like French-Canadians. The idea is that individuals whose ancestors lived close by and interbred among themselves for long periods of time were likely to have a more similar genetic makeup and as a result accumulate some bad mutations over time, since the mating was not random etc.

    So, this is a specific answer that’s making a more global point which is this: If we had a good marker that could tell us very specifically where individuals originated from geographically (which is actually very hard to do since there are many instances of intermingling between populations, migration etc), or even better, if we could cheaply just read everyone’s whole genome, life would be easy and we wouldn’t need those labels like “race” to help us group individuals. We will probably be able to sequence everyone’s genome in maybe 10-15 years and then we can just group individuals by their genetic make-up. However, to group individuals based on some sloppy characteristics like skin color is not a very good way to do science. Yes, sometimes individuals that look similar will have a similar genetic makeup, but sometimes they won’t. In fact, like I mentioned in the podcast, the genetic variability between Africans is larger than the variability between Eurasians and Africans, which even further stresses the idea that you can’t just lump all “African Americans” in one racial group. Here’s a free article

    Regarding BiDil, yes, it is true that researchers found some differential responses between blacks and whites but there’s still a lot of uncertainty as to why this is happening and what the mechanism is behind it. I think it is entirely possible that a lot of environmental socioeconomic differences can potentially account for the differences in response to this drug, or maybe not. Researchers are not sure yet and obviously if this drug works, I’m not saying we should take it off the market. Although, an interesting anecdote about it is that some self-identified African Americans actually don’t want to take this drug exactly because of this negative labelling. In any case, I think it’s important not to blow it out of proportion and conclude that because one drug seems to work better in blacks we should now target different treatments depending on an individual’s race. I personally think that’s a slippery slope and that research can be better targeted towards specific genotypic variations rather than towards specific races which are poor proxies for these variations.

    I’m not saying I have all the answers and I’m happy to debate this further.

  5. Fredrik says:

    An interesting article in The Scientist argues that as we still are several steps away from truly personalized medicine, the inclusion of race in clinical trials inches us closer to the ideal system; just like age, gender and other characterstics used in the research.

    It can also be noted that many countries require evaluation of the effect of race and/or ethnicity in new drug applications. Thus, the decision to include these variables in clinical trials does not so much dependent on the interest of the researchers as on global regulatory requirements for new drugs.

  6. Dina says:

    Hi Fredrik,

    Thanks for sharing this great article! It addresses a lot of the issues I have covered and I generally agree with what it says. To clarify, the main thesis of my segment was that race is not the best way to distinguish between individuals since it has no biological foundation and its use is questionable. I’m not saying it should absolutely not be used especially since at times that’s the only variable we may have available. What I am saying is that we should look for other ways to investigate the differences between individuals. For example, researchers can collect a variety of other more objectively measured variables instead of race such as social deprivation index, education level, measures of pollution etc. This is potentially more complex, more expensive etc. I think that race can potentially be dropped if all the variety of “host factors” for which race seems to be a proxy of can be accounted for.

    On a related note, I don’t think it inches us closer to the ideal system. It’s more of a ‘place holder’ until we can sequence everyone’s genome cheaply at which point we should drop this concept altogether from biomedical research (not -all- research, however) as we will have a much more reliable way to group individuals.

    In terms of the inclusion of the variable, you’re absolutely right, it’s definitely not only up to the researchers to decide whether ‘race’ should be included. The government plays an important role and should not take this responsibility lightly because in a way it shapes our discourse around the topic.

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