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Many researchers are currently studying the distribution of genetic variations among diverse groups, with particular interest in explaining racial/ethnic health disparities. However, the use of racial/ethnic categories as variables in biological research is controversial. Just how racial/ethnic categories are conceptualized, operationalized, and interpreted is a key consideration in determining the legitimacy of their use, but has received little attention. We conducted semi-structured, open-ended interviews with 30 human genetics scientists from the US and Canada who use racial/ethnic variables in their research. They discussed the types of classifications they use, the criteria upon which they are based, and their methods for classifying individual samples and subjects. We found definitions of racial/ethnic variables were often lacking or unclear, the specific categories they used were inconsistent and context specific, and classification practices were often implicit and unexamined. We conclude that such conceptual and practical problems are inherent to routinely used racial/ethnic categories themselves, and that they lack sufficient rigor to be used as key variables in biological research. It is our position that it is unacceptable to persist in the constructing of scientific arguments based on these highly ambiguous variables. Keywords: Race; Ethnic groups: Human genetics: Health disparities: Bioethics; USA: Canada

The relationship between human placental alkaline phosphatase (PLAP) genotype and birth weight is investigated in a sample of white, black and Puerto-Rican new-born infants from New Haven, Connecticut (total 710 subjects). Black and Puerto-Rican infants show a higher incidence of growth retardation and a higher frequency of ALPp*1/*1 genotype as compared to whites. The proportion of newborns with a low birth weight (below the 10th percentile) is lower in infants with ALPp*1/*1 genotype than in those with other PLAP genotypes, especially among non-whites. It is argued that the higher frequency of ALPp*1 allele among non-whites might be, at least in part, a consequence of their adaptation in the past to environmental conditions adverse to optimal intrauterine development. KEY WORDS Birth weight, Genetic background, Interethnic variability, Placental alkaline phosphatase

While the history of Africans in the Americas predates institutional slavery, it is notably marked by the brutal period of kidnapping and mass transport of millions of indigenous Africans during the transatlantic slave trade from ~1619 to 1850. Thus, the vast majority of contemporary African Americans are descendants of enslaved Africans. The voluntary immigration of Africans to the Americas before and after the enslavement period contributed significantly less to the African American gene pool. Human identity is usually shaped in relation to ancestry. However the vast majority of African Americans know little about their specific African ancestry. This is why it has been extremely important to African Americans to get a better understanding of potential contributors to their ancestry. Historical shipping and trade documents provide some insight on the ethnic and geographic origin of enslaved Africans. The sources of enslaved Africans encompassed a wide geographic range consisting of eight coastal regions from Senegal south through the Cape of Good Hope and north along eastern Africa to Cape Delgado. The accumulation of genetic data namely, nonrecombining, lineage-defining markers such as mtDNA, Y-chromosome, and autosomal haplotypes from indigenous African populations has sparked major interest in the possibilities of DNA tests for African ancestry. A recent web-based poll of African Americans revealed that 80% view it important enough to determine their African ancestral heritage through DNA testing. Until recently, large geographic gaps existed in genetic samples from Africa, leading to poorly defined areas (i.e., Angola, Gabon, Congo, and Zaire) where limited sampling of indigenous African populations occurred. Currently our laboratory has amassed genetic data from over 52 indigenous populations representing 21 contemporary African countries. Here we discuss the ethical and social issues related to the construction of the African ancestry genetic database and the broad range of responses from the African American community to the possibilities of DNA testing for ancestry.

Over the past few years our lab has assembled a collection of cell lines on over 30 populations including at least three populations from each of the major geographic regions of the world. To date we have a complete set of allele frequency data on 14 haplotyped loci (46 sites total, two to six sites per locus) and 9 single-site loci on 30 distinct populations with an average sample size n@50. This complete dataset of 23 independent loci on 30 distinct populations has now been analyzed for genetic distances, etc. The Fst values for the 55 individual sites across the 30 populations range from 0.04 to 0.41, with a mean of 0.16. The smallest value occurred at one site at the D4S 10 locus but the haplotypes for D4S 10 had an Fst =0.17. The largest value occurred for a single SNP in the ADH gene cluster. PCA analyses give four main clusters of populations corresponding to Africa, Europe and Southwest Asia, East Asia, and the Americas. In tree analyses, the Africa-Europe pair is separated by a long branch from the East Asia-Americas pair. Three populations do not fall clearly in any of these clusters: Nasioi Melanesians, Micronesians, and Yakut Siberians. The overall pattern is consistent with an out-of-Africa model; indeed, some of the haplotypes included-CD4, DRD2, DM, PAH-have been used on subsets of these populations to argue strongly for that model. The additional data at those and the other haplotyped loci continue to be consistent with the existence of a significant founder effect associated with the expansion out of Africa and accumulating drift and loss of variation from West to East across Eurasia and then from North to South in the Americas. Supported by NIH grants GM57672, AA09379, and NSF grant BCS-9912028.