We studied human population structure using genotypes at 377 autosomal microsatellite loci in 1056 individuals from 52 populations. Within-population differences among individuals account for 93 to 95% of genetic variation; differences among major groups constitute only 3 to 5%. Nevertheless, without using prior information about the origins of individuals, we identified six main genetic clusters, five of which correspond to major geographic regions, and subclusters that often correspond to individual populations. General agreement of genetic and predefined populations suggests that self-reported ancestry can facilitate assessments of epidemiological risks but does not obviate the need to use genetic information in genetic association studies.

African Origins The modern human originated in Africa and subsequently spread across the globe. However, the genetic relationships among the diverse populations on the African continent have been unclear. Tishkoff et al. (p. 1035; see the cover, published online 30 April) provide a detailed genetic analysis of most major groups of African populations. The findings suggest that Africans represent 14 ancestral populations. Populations tend to be of mixed ancestry which documents historical migrations. The data mainly support but sometimes challenge proposed relationships between groups of self-identified ethnicity previously hypothesized on the basis of linguistic studies. The authors also examined populations of African Americans and individuals of mixed ancestry from Cape Town, documenting the variation and origins of admixture within these groups.

A total of 20,000 parent-offspring transfers of alleles were examined through the genotyping within 40 CEPH reference families of 28 short tandem repeat polymorphisms (STRPs) located on chromosome 19. Forty-seven initial mutation events were detected in the STRPs using DNA from transformed lymphoblastoid cell lines, but less than half (39%) could be verified using DNA from untransformed cells. None of the cases where three alleles were observed in a single individual could be verified using DNA from untransformed cells. The average mutation rate for the chromosome 19 STRPs after correction for events which would not be detectable as Mendelian errors was 1.2 x 10(-3) per locus per gamete per generation. This rate may have been inflated by somatic as opposed to germline events. Observed mutation rates for individual STRPs ranged from 0 to 8 x 10(-3). The average mutation rate for tetranucleotide STRPs was nearly four times higher than the average rate for dinucleotide STRPs. For determination of the mode of mutation, events involving STRPs on other chromosomes were also examined. Of the events which were verified using DNA from untransformed lymphocytes or which were likely among those for which DNA from untransformed cells was not available: none were located at the sites of meiotic recombination, 91% involved the gain or loss of a single repeat unit, and 15 occurred in the male germline compared to 4 in the female germline (p = 0.01).

Comprehensive human genetic maps were constructed on the basis of nearly 1 million genotypes from eight CEPH families; they incorporated >8,000 short tandem-repeat polymorphisms (STRPs), primarily from Généthon, the Cooperative Human Linkage Center, the Utah Marker Development Group, and the Marshfield Medical Research Foundation. As part of the map building process, 0.08% of the genotypes that resulted in tight double recombinants and that largely, if not entirely, represent genotyping errors, mutations, or gene-conversion events were removed. The total female, male, and sex-averaged lengths of the final maps were 44, 27, and 35 morgans, respectively. Numerous (267) sets of STRPs were identified that represented the exact same loci yet were developed independently and had different primer pairs. The distributions of the total number of recombination events per gamete, among the eight mothers of the CEPH families, were significantly different, and this variation was not due to maternal age. The female:male ratio of genetic distance varied across individual chromosomes in a remarkably consistent fashion, with peaks at the centromeres of all metacentric chromosomes. The new linkage maps plus much additional information, including a query system for use in the construction of reliably ordered maps for selected subsets of markers, are available from the Marshfield Website.

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Recent research has emphasized the importance of the metabolic cluster, which includes glucose intolerance, dyslipidemia, and high blood pressure, as a strong predictor of the obesity-related morbidities and premature mortality. Fundamental to this association, commonly referred to as the metabolic syndrome, is the close interaction between abdominal fat patterning, total body adiposity, and insulin resistance. As the initial step in identifying major genetic loci influencing these phenotypes, we performed a genomewide scan by using a 10-centiMorgan map in 2,209 individuals distributed over 507 nuclear Caucasian families. Pedigreebased analysis using a variance components linkage model demonstrated a quantitative trait locus (QTL) on chromosome 3 (3q27) strongly linked to six traits representing these fundamental phenotypes [logarithm of odds (lod) scores ranged from 2.4 to 3.5]. This QTL exhibited possible epistatic interaction with a second QTL on chromosome 17 (17p12) strongly linked to plasma leptin levels (lod ‫؍‬ 5.0). Situated at these epistatic QTLs are candidate genes likely to influence two biologic precursor pathways of the metabolic syndrome. O besity is a common and chronic disorder associated with decreased longevity and increased morbidity from a variety of diseases, including type 2 diabetes mellitus, hypertension, stroke, and coronary heart disease (1). Fat distribution, specifically the pattern known as upper-body, abdominal, or visceral obesity, is a major predictor of the adverse metabolic profile predisposing to these health risks (2). Thus, abdominal-visceral fat size has emerged as a significant precursor of glucose intolerance, hyperinsulinemia, elevated plasma triglycerides, decreased high density lipoprotein-cholesterol, and increased blood pressure (3). Fundamental to this metabolic milieu are close interactions between total body adiposity, abdominalvisceral fat size, and insulin resistance. Reaven (4) provided evidence to suggest that resistance to insulin-stimulated glucose uptake is associated with a series of related metabolic variables, termed ''syndrome X,'' which cluster in the same individual and include glucose intolerance, disturbed plasma lipids, and high blood pressure (4). Because of close similarities of these features with those associated with abdominal obesity, the more collective term metabolic syndrome was introduced (5).The etiology of the abdominal obesity-metabolic syndrome is complex and is thought to involve metabolic, neuroendocrine, and genetic interactions. A metabolic-neuroendocrine cascade has been proposed in which increased free fatty acid flux from the highly lipolytic visceral adipocytes, together with imbalances in sex hormones, could cause the insulin resistance and hyperinsulinemia, with their metabolic consequences (6). Weight gain with preferential deposition of adipocytes in the abdominal-visceral region is considered secondary to adoption of Westernized diet, activity lifestyle, and reactivity to emotional, intellectual, and physical stresses (5...

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