Race in biomedicine

From Wikipedia, the free encyclopedia

The role of race in biomedicine is actively debated among biomedical researchers.

Several questions are considered:

• can the concept of "race" be considered valid?
• When should race be taken into account when studying humans?
• What definition of race is appropriate for biomedical research?
• Do the biological differences between races justify the use of racial categories in research?
• Can genetic assignment to population groups be used in lieu of self-identified race?
• What are the ethical implications of using race in research?

The primary impetus for considering race in biomedical research is the possibility of improving the prevention and treatment of diseases. Many previous studies have observed that disease susceptibility and environmental responses vary by race. Thus, some researchers believe that race may be an informative category for biomedical research. Others fear using racial categories in research may cause social harm.

Contents 1 Racial, ethnic, and ancestral categories in genetics research 1.1 The effects of racial and ethnic identities on health 1.2 The allelic architecture of disease 1.3 Population substructure in genetics research 2 Disease association studies 3 Concept of race 4 Genetic differences among races 5 Genetic labelling 6 Research 7 References 8 See also 9 External link

[edit] Racial, ethnic, and ancestral categories in genetics research

[edit] The effects of racial and ethnic identities on health

Racial and ethnic groups can exhibit substantial average differences in disease incidence, disease severity, disease progression, and response to treatment (LaVeist 2002). In the United States, African Americans have higher rates of mortality than does any other racial or ethnic group for 8 of the top 10 causes of death (Hummer et al. 2004). U.S. Latinos have higher rates of death from diabetes, liver disease, and infectious diseases than do non-Latinos (Vega and Amaro 1994). Native Americans suffer from higher rates of diabetes, tuberculosis, pneumonia, influenza, and alcoholism than does the rest of the U.S. population (Mahoney and Michalek 1998). European Americans die more often from heart disease and cancer than do Native Americans, Asian Americans, or Hispanics (Hummer et al. 2004).

Considerable evidence indicates that the racial and ethnic health disparities observed in the United States arise mostly through the effects of discrimination, differences in treatment, poverty, lack of access to health care, health-related behaviors, racism, stress, and other socially mediated forces. The infant mortality rate for African Americans is approximately twice the rate for European Americans, but, in a study that looked at members of these two groups who belonged to the military and received care through the same medical system, their infant mortality rates were essentially equivalent (Rawlings and Weir 1992). Recent immigrants to the United States from Mexico have better indicators on some measures of health than do Mexican Americans who are more assimilated into American culture (Franzini et al. 2001). Diabetes and obesity are more common among Native Americans living on U.S. reservations than among those living outside reservations (Cooper et al. 1997). Rates of heart disease among African Americans are associated with the segregation patterns in the neighborhoods where they live (Fang et al. 1998). Furthermore, the risks for many diseases are elevated for socially, economically, and politically disadvantaged groups in the United States, suggesting that socioeconomic inequities are the root causes of most of the differences (Cooper et al. 2003; Cooper 2004).

However, differences in allele frequencies certainly contribute to group differences in the incidence of some monogenic diseases, and they may contribute to differences in the incidence of some common diseases (Risch et al. 2002; Burchard et al. 2003; Tate and Goldstein 2004). For the monogenic diseases, the frequency of causative alleles usually correlates best with ancestry, whether familial (for example, Ellis–van Creveld syndrome among the Pennsylvania Amish), ethnic (Tay-Sachs disease among Ashkenazi Jewish populations), or geographical (hemoglobinopathies among people with ancestors who lived in malarial regions). To the extent that ancestry corresponds with racial or ethnic groups or subgroups, the incidence of monogenic diseases can differ between groups categorized by race or ethnicity, and health-care professionals typically take these patterns into account in making diagnoses.

Even with common diseases involving numerous genetic variants and environmental factors, investigators point to evidence suggesting the involvement of differentially distributed alleles with small to moderate effects. Frequently cited examples include hypertension (Douglas et al. 1996), diabetes (Gower et al. 2003), obesity (Fernandez et al. 2003), and prostate cancer (Platz et al. 2000). However, in none of these cases has allelic variation in a susceptibility gene been shown to account for a significant fraction of the difference in disease prevalence among groups, and the role of genetic factors in generating these differences remains uncertain (Mountain and Risch 2004).

[edit] The allelic architecture of disease

The genetic architecture of common diseases is an important factor in determining the extent to which patterns of genetic variation influence group differences in health outcomes (Reich and Lander 2001; Pritchard and Cox 2002; Smith and Lusis 2002). According to the common disease/common variant hypothesis, common variants present in the ancestral population before the dispersal of modern humans from Africa play an important role in human diseases (Goldstein and Chikhi 2002). Genetic variants associated with Alzheimer disease, deep venous thrombosis, Crohn disease, and type 2 diabetes appear to adhere to this model (Lohmueller et al. 2003). However, the generality of the model has not yet been established and, in some cases, is in doubt (Weiss and Terwilliger 2000; Pritchard and Cox 2002; Cardon and Abecasis 2003). Some diseases, such as many common cancers, appear not to be well described by the common disease/common variant model (Kittles and Weiss 2003; Wiencke 2004).

Another possibility is that common diseases arise in part through the action of combinations of variants that are individually rare (Pritchard 2001; Cohen et al. 2004). Most of the disease-associated alleles discovered to date have been rare, and rare variants are more likely than common variants to be differentially distributed among groups distinguished by ancestry (Risch et al. 2002; Kittles and Weiss 2003). However, groups could harbor different, though perhaps overlapping, sets of rare variants, which would reduce contrasts between groups in the incidence of the disease.

The number of variants contributing to a disease and the interactions among those variants also could influence the distribution of diseases among groups. The difficulty that has been encountered in finding contributory alleles for complex diseases and in replicating positive associations suggests that many complex diseases involve numerous variants rather than a moderate number of alleles, and the influence of any given variant may depend in critical ways on the genetic and environmental background (Risch 2000; Weiss and Terwilliger 2000; Altmüller et al. 2001; Hirschhorn et al. 2002). If many alleles are required to increase susceptibility to a disease, the odds are low that the necessary combination of alleles would become concentrated in a particular group purely through drift (Cooper 2004).

[edit] Population substructure in genetics research

One area in which racial and ethnic categories can be important considerations in genetics research is in controlling for confounding between population substructure, environmental exposures, and health outcomes. Association studies can produce spurious results if cases and controls have differing allele frequencies for genes that are not related to the disease being studied (Cardon and Palmer 2003; Marchini et al. 2004), although the magnitude of this problem in genetic association studies is subject to debate (Thomas and Witte 2002; Wacholder et al. 2002). Various methods have been developed to detect and account for population substructure (Morton and Collins 1998; Hoggart et al. 2003), but these methods can be difficult to apply in practice (Freedman et al. 2004).

Population substructure also can be used to advantage in genetic association studies. For example, populations that represent recent mixtures of geographically separated ancestral groups can exhibit longer-range linkage disequilibrium between susceptibility alleles and genetic markers than is the case for other populations (Hoggart et al. 2004; Patterson et al. 2004; Smith et al. 2004; McKeigue 2005). Genetic studies can use this admixture linkage disequilibrium to search for disease alleles with fewer markers than would be needed otherwise. Association studies also can take advantage of the contrasting experiences of racial or ethnic groups, including migrant groups, to search for interactions between particular alleles and environmental factors that might influence health (Chaturvedi 2001; Collins et al. 2003).

[edit] Disease association studies

Race is associated with differential disease susceptibility and environmental responses. Many highly penetrant Mendelian diseases that are caused by mutations in a single gene are known to be found at higher frequencies in certain races. The HbS allele that causes haemochromatosis is found at higher frequencies in sub-Saharan Africans and Southern Europeans. Similarly, the ΔF508 allele of CFTR that causes cystic fibrosis is found in higher frequencies in Northern Europeans. It is believed that many of these mutations first occurred in the population that is most affected.

Race has also been found to be associated with susceptibility to complex, multifactorial and multigenic diseases. The incidence and death rate of prostate and breast cancers are significantly higher in African-Americans than European-Americans. Higher proportions of individual African ancestry is associated with increased susceptibility to both obesity and abnormal levels of insulin secretion. Likewise, Hispanic, American Indian, African American, Pacific Island, and South Asian ancestry is considered a risk factor for diabetes. Also, the incidence of heart disease and high blood pressure is higher in African-Americans than European-Americans.

The common disease-common variant (often abbreviated CD-CV) hypothesis predicts common disease causing alleles will be found in all populations. An often cited example is an allele of apolipoprotein E, APOE ε4, which is associated in a dose-dependent manner with susceptibility to Alzheimer's disease. This allele is found in Africans, Asians and Europeans. However, many disease causing alleles are found to have different (technically called epistatic) effects in different populations. For example, the increased risk of Alzheimer's disease that is associated with the APOE ε4 allele is 5-fold higher in individuals with Asian rather than African ancestry.

Polymorphisms in the regulatory region of the CCR5 gene affect the rate of progression to AIDS and death in HIV infected patients. While some CCR5 haplotypes are beneficial in multiple populations, other haplotypes have population-specific effects. For example, the HHE haplotype of CCR5 is associated with delayed disease progression in European-Americans, but accelerated disease progression in African-Americans. Similarly, alleles of the CARD15 (also called NOD2) gene are associated with Crohn's disease, an inflammatory bowel disorder, in European-Americans. However, none of these or any other alleles of CARD15 have been associated with Crohn's disease in African-Americans or Asians.

Diseases that differ in frequency by race or ethnicity (Halder & Shriver, 2003).

Disease	High-risk groups	Low-risk groups	Reference(s)
Obesity	African women, Native Americans South Asians, Pacific Islanders, Aboriginal Australians	Europeans	McKeigue, et al. (1991); Hodge & Zimmet (1994)
Non-insulin dependent diabetes	South Asians, West Africans, Peninsular Arabs, Pacific Islanders and Native Americans	Europeans	Songer & Zimmet (1995); Martinez (1993)
Hypertension	African Americans, West Africans	Europeans	Douglas et al. (1996); Gaines & Burke (1995)
Coronary heart disease	South Asians	West African men	McKeigue, et al. (1989); Zoratti (1998)
End-stage renal disease	Native Americans and African populations	Europeans	Ferguson & Morrissey (1993)
Dementia	Europeans	African Americans, Hispanic Americans	Hargrave, et al. (2000)
Systemic lupus erythematosus	West Africans, Native Americans	Europeans	Molokhia & McKeigue (2000)
Skin cancer	Europeans		Boni, et al. (2002)
Lung cancer	Africans, European Americans(Caucasians)	Chinese, Japanese	Schwartz & Swanson (1997); Shimizu, et al. (1985)
Prostate cancer	Africans and African Americans		Hoffman, et al. (2001)
Multiple sclerosis	Europeans	Chinese, Japanese, African Americans, Turkmens, Uzbeks, Native Siberians, New Zealand Maoris	Rosati (2001)
Osteoporosis	European Americans	African Americans	Bohannon (1999)
Atrial fibrillation	European-Americans	African-Americans	[1]
Carotid artery disease	European-Americans	African-Americans	[2]
Coronary artery disease	European-Americans	African-Americans	[3]
Dementia	African-Americans	European-Americans	[4]
End-stage renal disease	African-Americans	European-Americans	[5]
Focal segmental glomerulosclerosis	African-Americans	European-Americans	[6]
Hepatitis C clearance	European-Americans	African-Americans	[7]
HIV progression	African-Americans	European-Americans	[8]
HIV vertical transmission	European-Americans	African-Americans	[9]
Hypertensive heart disease	African-Americans	European-Americans	[10]
Hypertensive retinopathy	African-Americans	European-Americans	[11]
Intracranial haemorrhage	African-Americans	European-Americans	[12]
Lupus nephritis with systemic lupus erythematosus	African-Americans	European-Americans	[13]
Myeloma	African-Americans	European-Americans	[14]
Non-insulin dependent diabetes	African-Americans	European-Americans	[15]
Obesity/BMI	African-Americans	European-Americans	[16]
Pregnancy-related death	African-Americans	European-Americans	[17]
Stroke	African-Americans	European-Americans	[18]
Systemic lupus erythematosus	African-Americans	European-Americans	[19]
Systemic sclerosis	African-Americans	European-Americans	[20]

[edit] Concept of race

Main article: Race.

In biomedical research conducted in the U.S., the 2000 US census definition of race is often applied. This grouping recognizes five races: black or African American, white, Asian, native Hawaiian or other Pacific Islander, and American Indian or Alaska native. However, this definition is inconsistently applied across the range of studies that address race as a medical factor, making assessment of the utility of racial categorization in medicine more difficult.

From the perspective of genetics, human population structure is the result of patterns of mating. Historically, the greatest influence on mating patterns is geography. Genetic research has shown that the greatest genetic differentiation among humans corresponds with continental groupings. To the extent that racial labels correspond to continental groups, some argue that they are informative for biomedical research. Migration between continents in the last two centuries, with consequent racial admixture has caused some to question the significance of this notion of race to medicine.

In multiracial societies such as that of the United States, racial groups also differ by social and cultural correlates such as economic status and access to healthcare. These factors are believed to explain some of the differential health care outcomes among races. An open area of investigation is whether racial differences persist in studies where social and cultural correlates are taken into account.

[edit] Genetic differences among races

The existence of genetic differences among races is well accepted. In general, genetic clusters exist that correspond tightly to the census definition of race and to self-identified ancestry. One large exception to this correspondence is that South, Central, and West Asians (e.g. Asian Indians) cluster with Europeans and are separate from East Asians. The association between race and genetics also breaks down for groups, such as Hispanics, that exhibit a pattern of geographical stratification of ancestry. The biomedical relevance of genetic differences among races is a matter of debate. Some researchers argue that the available evidence supports the notion that some of the genetic differences between races have biomedical significance, and thus should be studied.

[edit] Genetic labelling

An alternative view argues that the underlying genetic-cluster categories can be used in lieu of racial labels for biomedical purposes. Proponents of this view argue that by directly examining the genotype, the problem of using racial labels can be avoided. Moreover, they argue that genotyping is more reliable than using self-identified race as a proxy for ancestry. Some fear that the use of racial labels in biomedical research runs the risk of unintentionally exasperating health disparities.

Proponents of using race in biomedical research argue that ignoring race will be detrimental to the health of minority groups. They argue that disease risk factors differ substantially between racial groups, that relying only on genotypical classes ignores non-genetic racial factors that impact health, and, furthermore, that minorities would be poorly represented in clinical trials if race were ignored.

[edit] Research

The Human Genome Diversity Project (HGDP) has attempted to map the DNA that varies between humans. In the future, HGDP could possibly reveal new data in disease surveillance, human development and anthropology. HGDP could unlock secrets behind and create new strategies for managing the vulnerability of ethnic groups to certain diseases. It could also show how human populations have adapted to these vulnerabilities. To date, HGDP research has resulted in a representative world distribution of 52 distinct genetic markers.

[edit] References

• Bohannon, A.D. (1999), ‘Osteoporosis and African American women’, J. Women's Health Gend. Based Med. Vol. 8, pp. 609-615.
• Boni, R., Schuster, C., Nehrhoff, B. and Burg, G. (2002), ‘Epidemiology of skin cancer’, Neuroendocrinol. Lett. Vol. 23(Suppl. 2), pp. 48-51.
• Douglas, J.G., Thibonnier, M. and Wright, Jr., J.T. (1996), ‘Essential hypertension: Racial/ethnic differences in pathophysiology’, J. Assoc. Acad. Minor. Phys. Vol. 7, pp. 16-21.
• Editorial. Genes, drugs and race. Nature Genetics 29, 239 - 240 (2001).
• Farrer, L. A. et al. Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA 278, 1349-1356 (1997).
• Ferguson, R. and Morrissey, E. (1993), ‘Risk factors for end-stage renal disease among minorities’, Transplant. Proc. Vol. 25, pp. 2415-2420.
• Fernandez, J. R. et al. Association of African genetic admixture with resting metabolic rate and obesity among women. Obes. Res. 11, 904-911 (2003).
• Gaines, K. and Burke, G. (1995), ‘Ethnic differences in stroke: Black-white differences in the United States population. SECORDS Investigators. Southeastern Consortium on Racial Differences in Stroke’, Neuroepidemiology Vol. 14, pp. 209-239.
• Gonzalez, E. et al. Race-specific HIV-1 disease-modifying effects associated with CCR5 haplotypes. Proc. Natl Acad. Sci. USA. 96, 12004-12009 (1999).
• Gower, B. A. et al. Using genetic admixture to explain racial differences in insulin-related phenotypes. Diabetes 52, 1047-1051 (2003).
• Halder I, Shriver MD. (2003). Measuring and using admixture to study the genetics of complex diseases. Hum Genomics 1, 52-62.
• Hardy, J., Singleton, A. & Gwinn-Hardy, K. Ethnic differences and disease phenotypes. Science 300, 739-740 (2003).
• Hargrave, R., Stoeklin, M., Haan, M. and Reed, B. (2000), ‘Clinical aspects of dementia in African-American, Hispanic, and white patients’, J. Nat. Med. Assoc. Vol. 92, pp. 15-21.
• Hodge, A.M. and Zimmet, P.Z. (1994), ‘The epidemiology of obesity’, Baillieres Clin. Endocrinol. Metab. Vol. 8, pp. 577-599.
• Hoffman, R.M., Gilliland, F.D., Eley, J.W. et al. (2001), ‘Racial and ethnic differences in advanced-stage prostate cancer: The Prostate Cancer Outcomes Study’, J. Nat. Cancer Inst. Vol. 93, pp. 388-395.
• Holden, C. Race and medicine. Science 302, 594-596 (2003).
• Hugot, J. P. et al. Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn's disease. Nature 411, 599-603 (2001).
• Inoue, N. Lack of common NOD2 variants in Japanese patients with Crohn's disease. Gastroenterology 123, 86-91 (2002).
• Martin, M. P. et al. Genetic acceleration of AIDS progression by a promoter variant of CCR5. Science 282, 1907-1911 (1998).
• Martinez, N.C. (1993), ‘Diabetes and minority populations. Focus on Mexican Americans’, Nurs. Clin. North Am. Vol. 28, pp. 87-95.
• Martinson, J. J., Chapman, N. H., Rees, D. C., Liu, Y. T. & Clegg, J. B. Global distribution of the CCR5 gene 32-basepair deletion. Nature Genet. 16, 100-103 (1997).
• McKeigue, P.M., Miller, G.J. and Marmot, M.G. (1989), ‘Coronary heart disease in south Asians overseas: A review’, J. Clin. Epidemiol. Vol. 42, pp. 597-609.
• McKeigue, P.M., Shah, B. and Marmot, M.G. (1991), ‘Relation of central obesity and insulin resistance with high diabetes prevalence and cardiovascular risk in South Asians’, Lancet Vol. 337, pp. 382-386.
• Molokhia, M. and McKeigue, P.M. (2000), ‘Risk for rheumatic disease in relation to ethnicity and admixture’, Arthritis Res. Vol. 2, pp. 115-125.
• Ogura, Y. et al. A frameshift mutation in NOD2 associated with susceptibility to Crohn's disease. Nature 411, 603-606 (2001).
• Risch, N.; Burchard, E.; Ziv, E. & Tang, H. (2002). Categorization of humans in biomedical research: genes, race and disease. Genome Biol. 3, comment2007. [1]
• Rosati, G. (2001), ‘The prevalence of multiple sclerosis in the world: An update’, Neurol. Sci. Vol. 22, pp. 117-139.
• Schwartz, A.G. and Swanson, G.M. (1997), ‘Lung carcinoma in African Americans and whites. A population-based study in metropolitan Detroit, Michigan’, Cancer Vol. 79, pp. 45-52.
• Shimizu, H., Wu, A.H., Koo, L.C. et al. (1985), ‘Lung cancer in women living in the Pacific Basin area’, Nat. Cancer Inst. Monogr. Vol. 69, pp. 197-201.
• Songer, T.J. and Zimmet, P.Z. (1995), ‘Epidemiology of type II diabetes: An international perspective’, Pharmacoeconomics Vol. 8 (Suppl. 1), pp. 1-11.
• Wiencke, J. K. Impact of race/ethnicity on molecular pathways in human cancer. Nature Rev. Cancer 4, 79-84 (2003).
• Yancy, C. D. Does race matter in heart failure. Am. Heart J. 146, 203-206 (2003).
• Zoratti, R. (1998), ‘A review on ethnic differences in plasma triglycerides and high-density-lipoprotein cholesterol: Is the lipid pattern the key factor for the low coronary heart disease rate in people of African origin?’, Eur. J. Epidemiol. Vol. 14, pp. 9-21.

[edit] See also

• Pharmacogenomics

[edit] External link

• News-Medical.net