Tag Archives: ancestry

50 whys to look for genes: 42. Depict human genealogical and genetic relationships

Using genome-wide variation it is possible to depict the variation among humans in ways that indicate the divergence from a common ancestral group. The following diagram comes from the work of Tishkoff and collaborators on genetic variation among humans in and out of Africa. Continue reading

50 whys to look for genes: 40. Determine one’s ancestry

Examining a male’s Y chromosome can expose genetic variants (or a pattern of variants) common in certain regions of the world and thus tell you that the root of his ancestry going through father-paternal grandfather-etc. probably originated in that place.  Similarly, examining a female’s X mitochondrial DNA, which are transmitted from the egg and not the sperm, can tell her the root of her ancestry going through mother-maternal grandmother-etc. probably originated in a given place. Continue reading

Gender, Race, and the Complexities of Science and Technology: A 2009 bibliography

In a 2009 graduate course on “Gender, Race, and the Complexities of Science and Technology,” students were asked to add an annotated reference or resource (=person, organization…) to an evolving bibliography each week.  Keywords are given in brackets are each reference. Annotations can be read by clicking on the links:

Armand Marie Leroi. 2005. A Family Tree in Every Gene. http://www.nytimes.com/2005/03/14/opinion/14leroi.html?pagewanted=1&_r=2&th.
[genetic technology_race_gender]

Aikenhead, Glen. “Integrating Western and Aboriginal Sciences: Cross-Cultural Science Teaching.” Research In Science Education 31, no. 3 (2001).
[elementary_science_education, aboriginals, curriculum_design]

Glen Aikenhead’s Webpage. http://www.usask.ca/education/people/aikenhead/

Anderson, Elizabeth (2009). “Feminist Epistemology and Philosophy of Science.” Stanford Encyclopedia of Philosophy. Retrieved 2/1/9 from http://plato.stanford.edu/entries/feminism-epistemology/

Anglin, Mary K. 1997. “Working from the Inside Out: Implications of Breast Cancer Activism for Biomedical Policies and Practices.” Social Science & Medicine 44:1403-1415.

Arditti, Rita (1980). “Feminism in Science” In: Science and Liberation. Boston MA: South End Press. pp 350-368.
[women_in_science, feminist_perspectives]

Armstrong, V. (2001). Theorizing gender and musical composition in the computerized classroom. Women: A Cultural Review 12(1),

Aronson, Debra (2009). “The Authenticy Filter: Lessons from Photoshop on Biological Engineering,” Science Progress. February 5th, 2009. Accessed on February 11, 2009 at: http://www.scienceprogress.org/2009/02/the-authenticity-filter/
[art_science, education, representation, biology]

Bandelt, Hans-Jurgen, Yao, Yong-Gang, Richards, Martin, and Antonio Salas (2008) “The brave new era of human genetic testing” BioEssays 30, 1246-1251
[ansestry, commodification, medical_industrial_complex, personal_genomics]

Barr, Jean and Birke, Lynda (1998). Common Science? Women, Science, and Knowledge. Bloomington IN: Indiana Press. 166pp.
[science-as-power, women_knowledge]

Benkov, Laura. (1994). Reinventing The Family: Lesbian and Gay Parents. New York : Crown Publishers

Best, S. & Kellner, D. (2001). The Post Modern Adventure. New York: Guilford Press.
[cultural_science, global_impacts_of_technology]

Bolnick, Deborah et al (2007) “The Science and Business of Genetic Ancestry Testing” Science 318 pp399-400 and follow-up letters in Science 319 pp1039-1040.
[race, personal_genomics, ansestry, commodification]

Bucchi, Massimiano and Federico Neresini (2008). “Science and Public Participation,” The Handbook of Science and Technology Studies. Cambridge, MA: MIT Press. pp. 449-472.
[public_participation, typologies, expert_knowledge, deficit_model]

Burow-Flak, Elizabeth (2000). Background Information on Cyborg Manifesto. http://faculty.valpo.edu/bflak/seminar/char_har.html
[cyborg feminism]

Butler, Judith. (1993). Bodies That Matter: On the Discursive Limits of “Sex”. New York: Routledge. [body_construction, heterosexuality, women]

Collins, P. H. (2005). Prisons for our bodies, closets for our minds: Racism, heterosexism, and black sexuality. Black Sexual Politics. New York: Routledge, 87-116.
[black_bodies_in_medical_experimentation, historical_examination_of_the_intersection_of_race_and_sexuality]

Council for Responsible Genetics (2009) GeneWatch – http://www.gene-watch.org/pages/genewatch.html
[personal_genomics, scientist_activist]

Critical Art Ensemble (2002). The Molecular Invasion. Brooklyn, NY: Autonomedia. 140pp. Anti-copyrighted; available for download at http://www.critical-art.net/books/molecular/index.html
[art_science, gmo_critique]

Croissant, JL and Smith-Doerr, L (2008). “Organizational Contexts of Science: Boundaries and Relationship between University and Industry,” in The Handbook of Science and Technology Studies(3rd Edition), EJ Hackett, O Amsterdamska, M Lynch, and J Wajcman (Eds). Cambridge, MA: MIT Press: 691-718.
[cultural_of_science, industrial_influences]

Chagnon, Napoleon A. (1995). The View From The President’s Window: The Academic Left and Threats to Scientific Anthropology. Human Behavior and Evolution Society Newsletter, 4(1). Retrieved 2002 August 31 from http://www.anth.ucsb.edu/faculty/chagnon/chagnon1995.html
[scientific anthropology]

Conrad, Peter. (1992). Medicalization and Social Control in Annual Review of Sociology, Vol. 18: 209-232 [medicine, social_control, medical_authority]

Donna M. Hughes. (2000). The Internet and Sex Industries: Partners in Global Sexual Exploitation. http://www.uri.edu/artsci/wms/hughes/siii.htm
[internet_sex industries]

Deloria, Vine Jr. (1999). “Perceptions and Maturity: Reflections on Feyerabend’s Point of View.” Spirit and Reason. Golden, CO: Fulcrum Publishing. pp.3-16.
[native_american_studies, philosophy_of_science, feyerabend, kuhn]

Dilworth, J. (1999). The cello: Origins and evolution. The Cambridge Companion to the Cello (R. Stowell, Ed.). Cambridge: Cambridge University Press.

Dreger, Alice. (1998). Hermaphrodites and the Medical Invention of Sex. Cambridge, Massachusetts: Harvard University Press [intersex, medical_ethics, medicine, identity]

Epstein, Steven. 2008. “The Rise of `Recruitmentology’: Clinical Research, Racial Knowledge, and the Politics of Inclusion and Difference.” Social Studies of Science 38:801-832. [race, STS]

Epstein, Steven. 2008. “Patient Groups and Health Movements.” Pp. 499-539 in The Handbook of Science and Technology Studies, edited by E. J. Hackett, O. Amsterdamska, M. Lynch and J. Wajcman. Cambridge: Massachusetts Institute of Technology.

First Nations University of Canada, Department of Sciencehttp://www.firstnationsuniversity.ca/default.aspx?page=30
[public_participation, expert knowledge, environmental contaminants]

Fausto-Sterling, Anne. 2003. “The Bare Bones of Race.” Social Studies of Science 38:658-694. [race, STS]

Ford, A & Peat, FD (1988). The Role of Language in Science. Foundations of Physics. Vol 18, 1233, Retrieved on February 1, 2009 from http://www.fdavidpeat.com/bibliography/essays/lang.htm.

Fox, M.F., Johnson, D. G., Rosser, S. V. (2006). Women, Gender, and Technology. Urbana-Champaign: University of Illinois Press. Preview Retrieved on February 25, 2009 from http://books.google.com/books?id=nf1E3EFqoXAC&printsec=frontcover&source=gbs_summary_r&cad=0#PPP1,M1
[feminist_perspectives, gendered_technology]

Garver, K. L. & Garver, B. (1994). The human genome project and eugenic concerns. The American Journal of Human Genetics 54(1), 148-158.
[bioethics, eugenics]

Gary C.Sieck(2001). Genome and hormones: an integrated approach to gender differences in physiology. http://jap.physiology.org/cgi/content/full/91/4/1485

Gorz, Andre (1980) “The Scientist as Worker.” In: Science and Liberation. Boston: South End Press. 398pp
[science-as-power, STS_History, culture_of_science, scientist_activist, social_change]

Haraway, Donna. 2004. “Teddy Bear Patriarchy: Taxidermy in the Garden of Eden, New York City, 1908-1936.” Pp. 151-197 in The Haraway Reader, edited by D. Haraway. New York: Routledge. [human_animal, STS_history, race, colonialism, feminist_perspectives]

Haraway, Donna. 2004. “A Manifesto for Cyborgs: Science, Technology, and Socialist Feminism in the 1980s.” Pp. 7-45 in The Haraway Reader, edited by D. Haraway. New York: Routledge. [feminist_perspectives]

Harding, S. (2005)From the woman quesion in science to the science question in feminism.

Harding, S (1991). Whose Science? Whose Knowledge?: Thinking from Women’s Lives. Ithaca, NY: Cornell University Press.
[science_feminism, feminist_perspectives, reflexivity_strong, objectivity_strong]

Harmon, A. (2007). Genetic testing + abortion =??? New York Times (New York, NY). Retrieved March 18, 2009 from http://www.nytimes.com/2007/05/13/weekinreview/13harm.html
[genetic_testing, abortion]

Hargittai, E. (2007). The social, political, economic, and cultural dimensions of search engines: An introduction. Journal of Computer-Mediated Communication, 12(3), article 1.

Hake, R.R. & J.V. Mallow. (2008). Gender Issues in Science/Math Education (GISME): Over 700 Annotated Reference & 1000 URL’s: Part 1 – All References in Alphabetical Order; Part 2 – Some References in Subject Order.

Hess, DJ (1995). Science and Technology in a Multicultural World: The Cultural Politics of Facts and Artifacts. New York, NY: Columbia University Press.
[culture_of_science, science-as-power, cultural_reconstruction, technototemism, multicultural_interpretations]

Ho , Mae-Wan (2007). The Importance of Being a Scientist-Activist. Institute of Science in Society Lecture on the occasion of the launch of Confessions of a Serial Womanizer by Zerbano Gifford, Nehru Center, London, October 1. Accessed 2/22/2009 at http://www.i-sis.org.uk/ScienceActivist.php
[scientist_activist, social_change]

Journal of American Medical Association (JAMA). Author in the Room Teleconference. Monthly discussions with authors of prominent JAMA articles. (Free). Accessed at: http://jama.ama-assn.org/cgi/content/full/299/1/70/DC1

Jungwirth, Bernhard and Bertram L. Bruce (F 2002). “Information Overload: Threat or Opportunity.” Journal of Adolescent and Adult Literacy. 45 no. 5
pp. 400-6.
[Information_Overload, Information_Anxiety, Technopoly]
Kahn, Johnathan. 2008. “Exploring Race in Drug Development.” Social Studies of Science 38. [race, STS]

Launius, R. D. (2007). The public history of science American memory, culture wars, and the challenge of presenting science and technology in a national museum. The Public Historian, 29(1), 13–30.

Lessons in Learning: The cultural divide in science education for Aboriginal learners.” Canadian Council on Learning. http://www.ccl-cca.ca/CCL/Reports/LessonsInLearning/LinL20070116_Ab_sci_edu.htm.
[cultural_worldviews, science_education, aboriginals]

Levine, Nancy E. (2008). Alternate Kinship, Marriage and Reproduction. Annual Review of Anthropology. Vol. 37, pp. 375-389

Mamo, Laura. (2007). Queering Reproduction: Achieving Pregnancy in the Age of Technoscience. Durham, N.C. : Duke University Press.

Martin, B (1993). “The Critique of Science Becomes Academic.” Published in Science, Technology, & Human Values, Vol. 18, No. 2, Spring 1993, pp. 247-259. – Accessed on February 22, 2009 at : http://www.uow.edu.au/arts/sts/bmartin/pubs/93sthv.html
[STS_History, action_research]

Martin, Emily. (1987) The Woman in the Body: A Cultural Analysis of Reproduction. Boston: Beacon Press. [reproduction, motherhood, vulture, medicine]

McNeal, A. (n.d.) How to Read a Scientific Research Paper–a four-step guide for students and for faculty. Retrieved on August 23, 2007 from http://helios.hampshire.edu/~apmNS/design/RESOURCES/HOW_READ.html

Mody, Cyrus C.and David Kaiser (2008). “Scientific Training and the Creation of Scientific Knowledge,” in: The Handbook of Science and Technology Studies. Cambridge, MA: MIT Press. pp 377-402.
[science_literacy, culture_of_science, education]

Myra Marx Ferree, Judith Lorber, Beth B. Hess. 1998. Revisioning Gender. http://books.google.com/books?id=edwE4L-yAhYC&dq=race++social+constructed&lr=&hl=zh-CN&source=gbs_summary_s&cad=0

Mark Nichols. 1998. Women’s Health: New Attitudes. http://www.thecanadianencyclopedia.com/index.cfm?PgNm=TCE&Params=M1SEC674909

Morning, Ann. 2008. “Reconstructing Race in Science and Society: Biology Textbooks, 1952-2002.” American Journal of Sociology 114:S106-S137. [race, STS]

Oldenziel, Ruth (2001). “Man the Maker, Woman the Consumer: The Consumption Junction Revisited” in: Feminism in Twentieth-Century Science, Technology, and Medicine. Chicago: University of Chicago Press, pp 128-148.[science_as_power, women_knowledge, STS_history]

Olson, Gary and Elizabeth Hirsch (1995). “Writing, Literacy, and Technology: Toward a Cyborg Writing.” Women Writing Culture. New York: Suny Press. Retrieved on 2/1/9 from http://www.stumptuous.com/comps/olsonhirsch.html

Okie, S. “Crack Babies: The Epidemic That Wasn’t.” New York Times. January 28, 2009.
[nature/nurture, black_women, science_and_morality, science_and_politics, “bad”_science, reproduction]

Ortner, Sherry B. (1974). Is Female to Male as Nature is to Culture? In M. Z. Rosaldo and L. Lamphere (eds) Woman, Culture and Society. Stanford, CA: Stanford University Press, pp. 68-87 [nature, culture, motherhood]

Parkinson, S. (2004). Corporate Influence on Science and Technology: Speech. Retrieved on February 2, 2009 from http://www.sgr.org.uk/SciencePolicy/SpeechGreenParty004.htm
[industrial_influences, scientific_ethics]

Packman, Carl. (2008). God(desses) and the Jouissance of Woman, or The (Cyborg) Future of Enjoyment. http://cyborg-enjoy.blogspot.com/
[cyborg feminism]

Preves, Sharon E. (2000). Intersex and Identity: The Contested Self. New Brunswick, New Jersey: Rutgers University Press [intersex, identity, construction, medical_ethics]

Reardon, Jennifer (2004) “Decoding Race and Human Difference in a Genomic Age” Differences 15:3 pp38-65.
[race, genome_phenome, scientific_debate]

Reardon, Jenny (2005) Race to the Finish. Princeton, NJ: Princeton University Press. 237 pp.

Roberts, D. (1997). Killing the black body: Race, reproduction and the meaning of liberty. New York: Vintage
[reproduction_politics, race_and_reproduction]

Roche, RA and Annas, GJ (2007). “New Genetic Privacy Concerns,” Genewatch, 20(1). Accessed on March 28, 2009 at http://www.gene-watch.org/genewatch/articles/20-1RocheAnnas.html
[personal_genomics, privacy]

Rose, H (1994). Love, Power and Knowledge: Towards a Feminist Transformation of the Science. Bloomington, IN: Indiana University Press.
[women_knowledge, women_in_science, feminist_perspectives]

Rose , Nikolas (2001). The Politics of Life Itself. Theory, Culture & Society 18:1. http://tcs.sagepub.com/cgi/content/abstract/18/6/1
[ancestry, genetic_testing, race, eugenics, personal_genomics, privacy, science_and_politics, scientific_racism]

Rossiter , Margaret (1982). Women Scientists in America: Struggles and Strategies to 1940. Baltimore: Johns Hopkins Press. 439 pp
[women_in_science, feminist_perspectives]

Rossiter , Margaret (1995). Women Scientists in America: Before Affirmative Action 1940 – 1972. Baltimore: Johns Hopkins Press. 584pp
[women_in_science, feminist_perspectives]

Royte, E. (2008). The Caged Bird Speaks. Retrieved on February
4, 2009 from http://www.nytimes.com/2008/11/09/books/review/Royte-t.html?_r=1&scp=1&sq=%22The%20Caged%20Bird%20Speaks%22&st=cse
[linguistics, nonhuman_communication, scientific_objectivity_subjectivity]

R.E.Wyllys. (2003). Science as a social construct. http://www.ischool.utexas.edu/~l38613dw/website_spring_03/readings/ScienceSocialConstruct.html
[science_social construct]

Roger N. Lancaster(2006).Sex and Race in the Long Shadow of the Human Genome Project. http://raceandgenomics.ssrc.org/Lancaster/

Richard Marcus. (2005). The gene race. http://blogcritics.org/archives/2005/06/27/183347.php

Rubin, Gayle. (1975). The Traffic in Women: Notes on the “Political Economy” of Sex in Feminist Theory: A Reader, 2005 [Marxism, feminism, nature, culture]

Steven Weinberg. (1996). Sokal’s Hoax. http://www.physics.nyu.edu/faculty/sokal/weinberg.html

A Study on the Status of Women Faculty In Science at MIT (1999). Retrieved on February 9, 2009 from http://web.mit.edu/fnl/women/women.html#The%20Study

Feminist Epistemology and Philosophy of Science. (2000). http://plato.stanford.edu/entries/feminism-epistemology/
[science_epistemology_philosophy of science]

Shostak, Sara, Conrad, Peter, and Horowitz, Allan. 2008. “Sequencing and Its Consequences: Path Dependence and the Relationships between Genetics and Medicalization.” American Journal of Sociology 114: S287-S316. [STS, Medical_Sociology]

Teman, Emily. The Medicalization of “Nature” in the”Artificial Body”: Surrogate Motherhood in Israel. Medical Anthropology Quarterly, Volume 17, Issue 1

Tijssen, Robert J. W. (2004). Is the commercialisation of scientific research affecting the production of public knowledge?: Global trends in the output of corporate research articles.
[Corporate research, Research partnerships, Knowledge protection and dissemination, Semiconductors]

Thompson, Charis. (2005). Making Parents: The Ontological Choreography of Reproductive Technologies. Cambridge, MA: MIT Press

Valiverronen, Esa (2001). “Popularisers, Interpreters, Advocates, Managers, and Critics: Framing Science and Scientists in the Media.” pp 39-47 In: Nordicom Review 2/2001 (Ulla Carlsson, Ed.). 102pp Accessed 3/17/2009 at http://www.nordicom.gu.se/common/publ_pdf/17_021-030.pdf.
[ science_and_politics, scientific_objectivity_subjectivity, science-as-power, science_literacy, scientist_activist, social_change, scientists_in_media]

Varki, Ajit, Daniel Geschwind, and Evan Eichler (2008) Explaining human uniqueness: genome interactions with environment, behavior and culture. Nature Reviews Genetics 9, 749-763.
[genome_phenome, human_animal, nature_nurture]

Wailoo, Keith. 1997a. “‘Chlorosis’ remembered: Disease and the Moral Management of American Women.” in Drawing blood: technology and disease identity in twentieth-century America. Baltimore: Johns Hopkins University Press. [STS, Medicine, Gender]

Wailoo, Keith. 1997b. “Detecting ‘Negro Blood’: Black and White Identities and the Reconstruction of Sickle Cell Anemia.” Pp. 134-161 in Drawing Blood: Technology and Disease Identify in Twentieth-Century America. Baltimore: Johns Hopkins University Press. [race, STS, STS_history]

Wailoo, Keith. 2001. Dying in the City of the Blues: sickle cell anemia and the politics of race and health. Chapel Hill: University of North Carolina Press. [race, STS]

Washington, H. (2006). Medical Apartheid. New York: Harlem Moon.

World Health Organization. (2009) Gender and Genecitcs. http://www.who.int/genomics/gender/en/index.html

Welborn,V & Kanar, B (2000) Building Science Literacy. Accessed on February 4, 2008 at http://www.library.ucsb.edu/istl/00-winter/article2.html
[literacy, education]

Wertheim, Margaret. “The Way of Logic.” New Scientist 148 (December 2, 1995) 38-41.
[Helen_Verran, Epistemology, Indigenous_Logic]

Winner, L. (1986). Do artifacts have politics? The whale and the reactor: A search for limits in an age of high technology. Chicago: University of Chicago Press, 19-39. Retrieved February 20, 2009 from

Zimmerman, B. (2005). Technology is culture: two paradigms. Leonardo Music Journal, 15, 53-57.
[musical_technology, technology_and_culture]

Improving the use of “race” in clinical decisions: Learn more about racism or ancestry?

Suppose you are a doctor seeing a patient with hypertension.  The patient is a 54 year-old black man.  What should you do?  What more do you want to know before deciding what to do?

Perhaps you already know more along the following lines:

Regardless of region, blacks were less likely than whites to achieve treatment success with atenolol (P = .02) or prazosin (P = .03) and more likely with diltiazem (P = .05).  ( Cushman et al., 2000)

(Atenolol is a beta blocker; prazosin lowers blood pressure by relaxing blood vessels ; diltiazem is a calcium channel blocker).

You might say to yourself, “I know that not all black men with hypertension do better with calcium channel blocker and worse with beta blockers, but on average they do.  So I’ll prescribe diltiazem and see what happens.  If it doesn’t work well, I’ll change the medication.”

But you might also say, “I want to know more about this black man and learn to make decisions not simply based on averages.”  If so, let me trace two paths of learning more that you might follow, first around racism and second around ancestry.

“This is a 54 y.o. black man, or, at least, that is how he appears to me…”  You may know that not every man that looks black identifies as African-American, so you might first ask that.  Even if he doesn’t self-identify that way, you might think, “Given his skin color, he may have experienced racial discrimination.  Let me ask him whether he has.”  You may know that self-reports of experience of racism are conditioned by class, so you might look for a survey that is better at probing beyond self-reports.  You might, however, think, “Having someone answer questions on a survey and then interpreting the results takes time and the insurance company doesn’t reimburse me for that time.  What would I do with what I learn, anyway?”  Yet, if enough doctors collected the survey data—or even the self-reports of experiences of discrimination—then researchers could assess whether there was an association with that and the responses to the alternative hypertension medications.  After all, it’s implausible that experiences of discrimination have no physical effect on our bodies and it’s plausible that these effects might add up over time to produce differences in ways that bodies are hypertensive.  “OK,” you might say, “I’m interested in this line of inquiry, but I won’t start asking my patients about experiences of racial discrimination until researchers have shown clear associations with what anti-hypertension medicine works best.”  Understandable, but you might do some reading after hours about the positive effects of acknowledging the topic of discrimination and, conversely, of pride in one’s identity.

Now to the ancestry line of inquiry: “This is a 54 y.o. black man, or, at least, that is how he appears to me…”  You may know that not every man that looks black identifies as African-American, so you might first ask that.  You might discover that he is an immigrant from Africa, not a descendant of slaves in the United States.  Either way, you might know that genomic studies are starting to identify some genetic variants of biomedical significance that are more common in people of specific areas of Africa (e.g., Genovese etal. 2010).   You might ask, “Does your ancestry trace back to region X?”  There is a good chance that African-Americans won’t know this, or won’t know their places of ancestry with enough precision to be helpful, or will have multiple places of origin in Africa.  Moreover, if he is a descendant of slaves, you know he has probably has a lot of European ancestry.  “OK, we need to do a genetic test to see if he has the genetic variant in question.  But, on second thoughts, doing the test is expensive and the insurance company doesn’t reimburse me for that.  In any case, what would I do with what I learn?  Has any genetic variant been associated with what anti-hypertensive medication is appropriate, or is it simply telling us that the population of African-American men as a whole (meaning the population on average) has higher risk when they possess that variant?”  Yet, if researchers collected more data about ancestry (which would probably require genetic markers given people’s imperfect knowledge of their ancestors) then researchers could assess whether there was an association between ancestry and responses to the alternative hypertension medications.  But you might ask, “how plausible is it that such associations will be useful for clinical decisions, or even for further research?” You might ask this because you know that Genome-Wide Association studies “have not found common genes with a big impact on heart health” (Couzin-Frankel 2010).  There is heated debate about whether to “hope that the low-effect genes they are finding will help identify pathways and drug targets.”  (“Low effect” here means much smaller relative risk than between modifiable aspects of diet and behavior.)  “OK,” you might say, “I wonder if I should be interested in this line of inquiry?  Let me see if anyone can show me what considerations I’m overlooking.”

Let me note one thing that has been put aside in this exposition of the two paths.  The Cushman study showing differential response to medication between blacks and whites was actually a study of differential responses to medication inside versus outside the “stroke belt,”  that is, the “12 states with stroke mortality rates more than 10% above the mean rate for the rest of the United States: 10 of these states are in the south- eastern region.”  The authors conclude:

Hypertension in patients residing inside the Stroke Belt responded less to the use of several antihypertensive medications [even after controlling for race] and important differences were shown in a number of characteristics that may affect the control of blood pressure, compared with patients residing outside the Stroke belt.

Perhaps the first questions a doctor might ask is “Do you come from the Stroke belt? Do your parents?”  In their spare time the doctor might learn about the competing theories for the existence of this belt (e.g., Howard et al. 2010, Kuzawa and Sweet 2009).

Couzin-Frankel , J.: 2010, Major Heart Disease Genes Prove Elusive. Science 328(5983),1220-1221.

Cushman, W; D.J. Reda; H. M. Perry; D. Williams; M. Abdellatif; B. J. Materson, Regional and Racial Differences in Response to Antihypertensive Medication Use in a Randomized Controlled Trial of Men With Hypertension in the United States, Arch Intern Med. 2000;160:825-831.

Genovese, G. et al. (2010), Association of Trypanolytic ApoL1 Variants with Kidney Disease in African Americans, Science 13 August 2010: 329 (5993), 841-845.

Howard, V. et al. (2010) Prevalence of hypertension by duration and age at exposure to the stroke belt, J Am Soc Hypertens. 2010 Jan–Feb; 4(1): 32–41.

Kuzawa C. and E. Sweet (2009), Epigenetics and the Embodiment of Race: Developmental Origins of US Racial Disparities in Cardiovascular Health. AMERICAN JOURNAL OF HUMAN BIOLOGY, 21(1); 2-15.

Depictions of human genetic relationships: Exploration 8

Exploration 8: Deeper messages in the conventional ancestral tree of human groups

The original Tishkoff diagram of human ancestry is certainly easier to read than the reticulating web of exploration 6, let alone the web overlaid with aprons in exploration 7.  We could try to remedy this by helping audiences to become familiar with the graphic conventions and by using technology like the slide show to display the branching and replacement of ancestral aprons with those of their descendants.  In this concluding post of the series I argue that it is important for all to work on being able to read reticulating webs because of an undesirable message built into the simpler branching diagram.

To expose this message, consider the horizontal links in the Tishkoff diagram, which represent gene flow between branches, that is, admixture.  The branching pattern can be extracted from the genetic data only because these flows are not so large as to obscure the genetic mutations or other differences that arose over time after each branching.  Indeed, to ensure that this is the case, some studies of human genetic variation involve data from the special subset of people who live in the same place as, say, all their great-grandparents.  The reticulating web with aprons likewise relies on a branching pattern that can be discerned despite the potentially confounding effects of gene flow.  Still, the aprons remind us of variation around the mid-point of each group—variation that may well have been enlarged by gene flow.

Now, there are some branching patterns that are subject to minimal or no gene flow, namely branching of species or higher taxa (taxonomic groups) from ancestral taxa.   We are all familiar with such evolutionary trees.  The first example is for the classes of vertebrates; the second is for liverwort species.


Source: http://www.biology.duke.edu/bryology/LiToL/LeafyII.html

Our familiarity with these trees invites us to think—even if subconsciously—about human genetic ancestry as if the branches are like separate species.  There is a long history of scientific arguments that human races are separate species, or that the branches of the human tree achieved human status at different rates.  As Desmond and Moore (2009) have shown in Darwin’s sacred cause: How a hatred of slavery shaped Darwin’s views on human evolution, the debate was especially heated during Darwin’s adult life.  Darwin’s view of descent from a single common ancestor was a minority view, discredited to some extent by its association with literal interpretation of the bible’s account of Adam and Eve, but more so by its association with anti-slavery movements.  Yet, the debate did not disappear with the 19th century.  Carleton Coon, a physical anthropologist who died in 1981 after a long career as a professor at Harvard and University of Pennsylvania, wrote in 1962 that Homo erectus evolved into Homo sapiens five separate times “as each subspecies, living in its own territory, passed a critical threshold from a more brutal to a more sapient state”.  (http://en.wikipedia.org/wiki/Carleton_S._Coon#Polygenism)  The multiregional hypothesis is a more recent variant.

Ideas about multiple origins for humans are not the only way that biology can be invoked to explain or even justify a hierarchy of human races.  However, to the extent that we want to distance ourselves from such views, it can only help to do the work to depict genetic relationships among humans in ways that allow simultaneously for similarity, diversity, and admixture at the same time as we depict ancestry.

Depictions of human genetic relationships: Exploration 7

Exploration 7: Superimposing genetic variation on the ancestry diagram from a simulation

The following picture comes from the same random simulation used in the previous post to generate directions of branching and the distances of each branch from its most recent common ancestor.  The two dimensions stand for the genetic variation of the whole set of populations.  This time aprons are drawn around the midpoints of the groups A to R at the bottom of the ancestry tree (but not around their ancestors).  This shows that the variation of the original population (which would extend about 20% past the largest circle) is reduced after the branchings that have brought us to the present, but there is still great overlap between most groups.  In particular, the descendants A and B of the group AB, which branched off early, shows variation that subsumes that in the the rest of the groups.

A careful viewer might notice, however, that there are some circles that do not overlap at all, as if to say these groups share no genetic variation.  This is an artifact of my deciding to reduce the variation at each branching enough so that not all the circles would extend beyond the web.  In doing so, I realized that I was increasing the ratio of between groups to average within-group variation well beyond what we find in the actual human world.

Depictions of human genetic relationships: Exploration 6

Exploration 6: Superimposing changes in genetic location on an ancestry diagram, a simulation

In the previous post, the depiction of a 2-D ancestry “fan” plus “aprons” allowed us to represent within group variation as well as branching.  Whereas in a branching diagram we sought to minimize the crossing over of branches because “they suggest that the two branches at a fork are further away from each other than to one of the earlier branches, which goes against the information contained in the sequence of branches” (see earlier post), with the inclusion of aprons that overlap we can embrace branches that cross over.  Consider the following simulation, which also allows for evolution along branches to happen at different rates.

In a branching process, each group breaks into two.  Imagine that the new groups are small so that by genetic drift, that is, by chance, all members end up with the same variant a some genetic locus (position on the genome), that is, this locus does not contribute genetic variation.  (See an analogy given in the wikipedia entry on genetic drift.)  The population eventually grows larger and genetic drift ceases to be significant.  Each of the new groups then represents a subset of the variation existing in their common ancestor group.  If we discount new mutations for now, none of the branched-off groups can have more genetic variation than groups from which they are descended.

The following diagram uses a random simulation to generate directions of branching and the distances of each branch from its most recent common ancestor.  The two dimensions stand for the genetic variation of the whole set of populations.  No aprons are drawn around the midpoints of the groups, but it should be noted that the variation of the original population spans a space five times as wide as the area shown in the diagram.

The following slide show builds up the messy web branching from one group (AR) to two (AB and NR), and so on, step by step.

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Of course, this is only a simulation.  The actual genetic data might yield a 2-D web that is quite different.  Nevertheless, in the next post, we add aprons to the simulation to complete a picture of similarity, diversity, and ancestry.