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N L Oden

Publications and source records attributed to N L Oden.

7 recordsLinked to original sources

Origins of the Indo-Europeans: genetic evidence.

Two theories of the origins of the Indo-Europeans currently compete. M. Gimbutas believes that early Indo-Europeans entered southeastern Europe from the Pontic Steppes starting ca. 4500 B.C. and spread from there. C. Renfrew equates early Indo-Europeans with early farmers who entered southeastern Europe from Asia Minor ca. 7000 BC and spread through the continent. We tested genetic distance matrices for each of 25 systems in numerous Indo-European-speaking samples from Europe. To match each of these matrices, we created other distance matrices representing geography, language, time since origin of agriculture, Gimbutas' model, and Renfrew's model. The correlation between genetics and language is significant. Geography, when held constant, produces a markedly lower, yet still highly significant partial correlation between genetics and language, showing that more remains to be explained. However, none of the remaining three distances--time since origin of agriculture, Gimbutas' model, or Renfrew's model--reduces the partial correlation further. Thus, neither of the two theories appears able to explain the origin of the Indo-Europeans as gauged by the genetics-language correlation.

Blood Group Antigens

Genetic evidence for the spread of agriculture in Europe by demic diffusion.

European agriculture originated in the Near East about 9,000 years ago. The Neolithic reached almost all areas suitable for agriculture by 5,000 yr BP (before present). The routes and times of the spread of agriculture through Europe are relatively well established, but not its manner of spreading. This could have been by cultural diffusion with few genetic consequences. By contrast, Ammerman and Cavalli-Sforza proposed that the spread of farming increased local population densities, causing demic expansion into new territory and diffusive gene flow between the neolithic farmers and mesolithic groups. We have now tested observed genetic patterns against expectations derived from the demic expansion hypothesis. We found significant partial correlations of genetic distances with a distance matrix especially designed to represent the spread of agriculture on that continent, when geographic distances are held constant. These findings support the hypothesis of Ammerman and Cavalli-Sforza and invite further investigation into Renfrew's hypothesis on the origin of the Indo-European languages.

Agriculture

Estimating kappa from binocular data.

A common error in statistical analysis of ophthalmic data is the lack of accounting for the positive correlation generally present between observations made in fellow eyes. The alternative of data analysis from only one eye in each patient may lead to loss of power and unrealistically large confidence intervals. This paper discusses a method to estimate kappa, a measure of agreement between two graders, when both graders rate the same set of pairs of eyes. The method assumes that the true left-eye and right-eye kappa values are equal and makes use of the correlated binocular data to estimate confidence intervals for the common kappa. Simulations show that the new estimators are better than the estimator based on only one eye; new confidence intervals had the correct coverage probability, but were usually only about 70 per cent as wide as single-eye intervals. The general methodology described here applies to analysis of grader agreement in rating other paired body structures.

Atrophy

Genetic differences among language families in Europe.

We investigated whether 59 allele frequencies and 10 cranial variables differed among speakers of the 12 modern language families in Europe. Although this is a classical analysis of variance design, special techniques had to be developed for the analysis because of spatial autocorrelation of both biological and language data. The method examines pooled sums of squares within language families. These are compared with the same quantities obtained by randomly partitioning the available data points in Europe into internally cohesive subsets representing the same sample sizes for each language family as in the originally observed data. Our results suggest that for numerous genetic systems, population samples differ more among language families than they do within families. These findings are considered in relation to two contrasting models: a model of random spatial differentiation of gene frequencies unrelated to language and a model of aboriginal genetic differences among speakers of different language groups. Our observed findings suggest partial validity of both models.

Alleles

Spatial patterns of human gene frequencies in Europe.

The aims of this study of spatial patterns of human gene frequencies in Europe are twofold. One is to present new methodology developed for the analysis of such data. The other is to report on the diversity of spatial patterns observed in Europe and their interpretation as evidence of population processes. Spatial variation in 59 allele and haplotype frequencies (26 genetic systems) for polymorphisms in blood antigens, enzymes, and proteins is analyzed for an aggregate of 3,384 localities, using homogeneity tests, one-dimensional and directional spatial correlograms, and SYMAP interpolated surfaces. The data matrices are reduced to reveal the principal patterns by clustering techniques. The findings of this study can be summarized as follows: 1) There is significant heterogeneity in allele frequencies among the localities for all but one genetic system. 2) There are significant spatial patterns for most allele frequencies. 3) There is a substantial minority of clinal patterns in these populations. Clinal trends are found more frequently in HLA alleles than for other variables. North-south and northwest-southwest gradients predominate. 4) There is a strong decline in overall genetic similarity with geographic distance for most variables. 5) There are few, if any, appreciable correlations in pairs of allele frequencies over the continent, and there is little interesting correlation structure in the resulting correlation matrix. 6) Few spatial correlograms are markedly similar to each other, yet they form well-defined clusters. Spatial variation patterns, therefore, differ among allele frequencies. Patterns of human gene frequencies in modern Europe are diverse and complex. No single model suffices for interpretation of the observed genetic structure. Some clinal patterns reported here support the Neolithic demic-expansion hypothesis, others suggest latitudinal selection. Most of the clinal patterns are in HLA alleles, but there is also evidence from ABO for east-west migration diffusion. The majority of patterns are patchy, consistent with hypotheses of isolation by distance or of settlement of genetically differing, subsequently expanding ethnic groups. While undoubtedly there has been an ongoing stochastic process of differentiation consistent with the isolation-by-distance model, this has not obscured the directional patterns caused by migration (demic diffusion), and has perhaps only reinforced the contribution from settlement of ethnic units to patterns of genetic variation. However, the impact of the latter is most difficult to discern and requires further methodological developments.

ABO Blood-Group System

Genetic changes across language boundaries in Europe.

By means of three different methods we investigated whether 59 allele frequencies and ten cranial variables show increased change at 29 language-family boundaries in Europe. The quadrat-variance method compares variances of map quadrats crossed by language-family boundaries to variances of quadrats that are not crossed. The rate-of-change method examines the directional derivative of surfaces of the variables perpendicular to a language-family boundary and compares these derivatives to the same quantities obtained by randomly placing the language boundaries on the map of Europe. The difference method tests whether these variables differ more across language-family boundaries than across randomly placed boundaries. These special data-analytic techniques had to be developed to avoid the problem of spatial autocorrelation of both language and biological data. All three methods indicate increased genetic change at language-family boundaries. Clearer and more pronounced results are obtained by the first two methods than by the difference method. Thirteen language-family boundaries show significant gene frequency change by at least one of the methods. Changes are more marked in gene frequencies than in cranial variables. Different allele frequencies mark the increased change at different language boundaries. A model, based on the known history of each language-family boundary, was constructed to predict whether given boundaries should exhibit increased genetic change. The model is in good agreement with the observed results.

Alleles