Mixed Race Studies

In conclusion, based on a consecutive series of patients from an urban medical center in New York City we demonstrate that a spectrum of mixed ancestry is emerging in the largest US minority groups. While consistent with previous descriptive studies, when viewed from the clinical perspective this evidence invites a re-evaluation of the relevance of racial/ethnic labels. In combination with evidence of locus heterogeneity within and between populations, this picture of extensive gene flow lends credence to the argument that the transfer of historical population labels which reflect language and other social categories onto patient samples will in many cases be unwarranted.

Tayo BO, Teil M, Tong L, Qin H, Khitrov G, et al., “Genetic Background of Patients from a University Medical Center in Manhattan: Implications for Personalized Medicine,” PLoS ONE, Volume 6, Number 5 (2011-05-04): 8-10. http://dx.doi.org/10.1371/journal.pone.0019166.

Genetic Background of Patients from a University Medical Center in Manhattan: Implications for Personalized Medicine

PLoS ONE: A peer-reviewed, open access journal
Volume 6, Number 5 (2011-05-04)
11 pages
DOI: 10.1371/journal.pone.0019166

Bamidele O. Tayo
Department of Preventive Medicine and Epidemiology
Loyola University Chicago
Stritch School of Medicine, Maywood, Illinois

Marie Teil
Charles R. Bronfman Institute for Personalized Medicine
Mount Sinai School of Medicine, New York, New York

Liping Tong
Department of Preventive Medicine and Epidemiology
Loyola University Chicago
Stritch School of Medicine, Maywood, Illinois

Huaizhen Qin
Department of Biostatistics and Epidemiology
Case Western University, Cleveland, Ohio

Gregory Khitrov
Charles R. Bronfman Institute for Personalized Medicine
Mount Sinai School of Medicine, New York, New York

Weijia Zhang
Charles R. Bronfman Institute for Personalized Medicine
Mount Sinai School of Medicine, New York, New York

Quinbin Song
Charles R. Bronfman Institute for Personalized Medicine
Mount Sinai School of Medicine, New York, New York

Omri Gottesman
Charles R. Bronfman Institute for Personalized Medicine
Mount Sinai School of Medicine, New York, New York

Xiaofeng Zhu
Department of Biostatistics and Epidemiology
Case Western University, Cleveland, Ohio

Alexandre C. Pereira
University of Sao Paulo Medical School, Sao Paulo, Brazil

Richard S. Cooper
Department of Preventive Medicine and Epidemiology
Loyola University Chicago
Stritch School of Medicine, Maywood, Illinois

Erwin P. Bottinger
Charles R. Bronfman Institute for Personalized Medicine
Mount Sinai School of Medicine, New York, New York

Background

The rapid progress currently being made in genomic science has created interest in potential clinical applications; however, formal translational research has been limited thus far. Studies of population genetics have demonstrated substantial variation in allele frequencies and haplotype structure at loci of medical relevance and the genetic background of patient cohorts may often be complex.

Methods and Findings

To describe the heterogeneity in an unselected clinical sample we used the Affymetrix 6.0 gene array chip to genotype self-identified European Americans (N = 326), African Americans (N = 324) and Hispanics (N = 327) from the medical practice of Mount Sinai Medical Center in Manhattan, NY. Additional data from US minority groups and Brazil were used for external comparison. Substantial variation in ancestral origin was observed for both African Americans and Hispanics; data from the latter group overlapped with both Mexican Americans and Brazilians in the external data sets. A pooled analysis of the African Americans and Hispanics from NY demonstrated a broad continuum of ancestral origin making classification by race/ethnicity uninformative. Selected loci harboring variants associated with medical traits and drug response confirmed substantial within- and between-group heterogeneity.

Conclusion

As a consequence of these complementary levels of heterogeneity group labels offered no guidance at the individual level. These findings demonstrate the complexity involved in clinical translation of the results from genome-wide association studies and suggest that in the genomic era conventional racial/ethnic labels are of little value.

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