Cancer incidences in Europe related to mortalities, and ethnohistoric, genetic, and geographic distances.

We have previously shown that geographic differences in cancer mortalities in Europe are related to (in order of importance): geographic distances (reflecting environmental differences), ethnohistoric distances (encompassing cultural and genetic attributes), and genetic distances of the populations in the areas studied. In this study, we analyzed the relations of the same three factors to European incidences of 45 male and 47 female cancers. Differences in cancer incidences are correlated moderately, first with geographic distances, and then with genetic distances, but not at all with ethnohistoric distances. Comparing these findings to the earlier ones for cancer mortalities, we note the reversal in the importance of ethnohistory and genetics, and the generally lower correlations of incidence differences with the three putatively causal distance matrices. A path diagram combining both studies demonstrates the lack of cultural carcinogenic effects, but suggests cultural influences on procedures such as the registration of deaths in different political entities. Additionally, the relatively large correlation between ethnohistoric distances and mortality differences is caused by common factors behind the correlation of ethnohistoric and geographic distances. Geographic proximity results in similar ethnohistories. The direct effects of genetic distances are negligible and only their common effects with geographic distances play a role, accounting for the weak to negligible influence of genetics on incidence and mortality differences. Apparently, the genetic systems available to us do not substantially affect cancer incidence or mortality. We present indirect evidence that international differences in the quality of cancer rate data are greater in mortalities than in incidences.

Spatial autocorrelation of cancer in Western Europe.

We applied the techniques of spatial autocorrelation (SA) analysis to 40 cancer mortality distributions in Western Europe. One of the aims of these methods is to describe the scale over which spatial patterns of mortalities occur, which may provide suggestions concerning the agents bringing about the patterns. We analyzed 355 registration areas, applying one- and two-dimensional SA as well as local SA techniques. We find that cancer mortalities are unusually strongly spatially structured, implying similar spatial structuring of the responsible agents. The small number of spatial patterns (4 or 5) in the 40 cancer mortalities suggests there are fewer spatially patterned agents than the number of cancers studied. SA present in variables will bias the results of conventional statistical tests applied to them. After correcting for such bias, some pairwise correlations of cancer mortality distributions remain significant, suggesting inherent, epidemiologically meaningful correlations. Local SA is a useful technique for exploring epidemiological maps. It found homogeneous high overall cancer mortalities in Denmark and homogeneous low mortalities in southern Italy, as well as a very heterogeneous pattern for ovarian cancer in Ireland.

A problem with synthetic maps.

Synthetic maps of human gene frequencies, which are maps of principal component scores based on correlation of interpolated surfaces, have been popularized widely by L. Cavalli-Sforza, P. Menozzi, and A. Piazza. Such maps are used to make ethnohistorical inferences or to support various demographic or historical hypotheses. We show from first principles and by analyses of real and simulated data that synthetic maps are subject to large errors and that apparent geographic trends may be detected in spatially random data. We conclude that results featured as synthetic maps should be approached with considerable caution.

Sensitivity and specificity of a screening questionnaire for dry eye.

We developed a Dry Eye Screening Questionnaire for the Dry Eye Epidemiology Projects (DEEP), a proposed large epidemiologic study. All persons who screen positive and a small sample of those who screen negative are to be invited for a diagnostic examination. Containing 19 questions, of which only 14 were used in the analysis, the questionnaire takes only a few minutes to administer on the telephone. To construct a discriminator function and thus a ROC curve, we used stepwise multiple regression on screening responses from a clinic series of 77 cases and 79 controls. Stepwise regression may incorporate into the predictor equation variables whose relation to the predicted is only accidental. Further, misclassification rates are underestimated by the resubstitution method, in which the proportion misclassified is obtained from the same dataset in which the discriminator function was fitted. To counter these problems, we randomly divided the data in half. We chose as predictors only those variables (Dry and Irritated) selected by stepwise regression in both data halves. We estimated unbiased misclassification rates using the unbiased test set method, in which the discriminator is fitted in one data half, and misclassification rates are calculated in the other half. Comparison of ROC curves arising from resubstitution and test set estimates indicates that resubstitution bias in misclassification rate estimation is negligible in our data. A resubstitution estimate made on the entire data is thus preferred. The resulting sensitivity/specificity values are reasonably high (e.g., 60%/94%), suggesting that the questionnaire will be a useful screening tool in the DEEP study. A second discriminator using the sum of all 14 responses is similar in its misclassification characteristics to the first discriminator. A second potentially significant error, arising from applying results from a clinical series to a general population, will be investigated as survey results in DEEP become available.

Ethnohistory, genetics, and cancer mortality in Europeans.

Geographic variation in cancer rates is thought to be the result of two major factors: environmental agents varying spatially and the attributes, genetic or cultural, of the populations inhabiting the areas studied. These attributes in turn result from the history of the populations in question. We had previously constructed an ethnohistorical database for Europe since 2200 B.C., permitting estimates of the ethnic composition of modern European populations. We were able to show that these estimates correlate with genetic distances. In this study, we wanted to see whether they also correlate with cancer rates. We employed two data sets of cancer mortalities from 42 types of cancer for the European Economic Community and for Central Europe. We subjected spatial differences in cancer mortalities, genetic, ethnohistorical, and geographic distances to matrix permutation tests to determine the magnitude and significance of their association. Our findings are that distances in cancer mortalities are correlated more with ethnohistorical distances than with genetic distances. Possibly the cancer rates may be affected by loci other than the genetic systems available to us, and/or by cultural factors mediated by the ethnohistorical differences. We find it remarkable that patterns of frequently ancient ethnic admixture are still reflected in modern cancer mortalities. Partial correlations with geography suggest that local environmental factors affect the mortalities as well.

Using distance matrices to choose between competing theories and an application to the origin of modern humans.

This paper examines competing theories for cases in which both the data and the hypotheses can be represented as distance matrices. A test due to Dow & Cheverud has been used for such comparisons in anthropology, but when data are spatially, temporally, or phylogenetically autocorrelated, this test may be far too liberal. We examine a classification procedure based on ratios of probabilities obtained from Mantel tests of the competing hypotheses and find that design matrices describing only lag-one connections and those eliminating common connections of competing hypotheses are the most informative. We apply this method to simulated gene-frequency data in a 7 x 7 chessboard representing a stepping-stone model and discriminate between alternative theories with a 7% misclassification rate. We also apply these techniques to the current controversy concerning the origin of anatomically modern humans by testing design matrices representing regional continuity and single African origins. The outcome for lag-one matrices and those showing only unique lag-one differences indicate that the single African origin of anatomically modern humans fits the distance matrix based on 165 characters of 83 fossil crania better than the competing theory. However, we also tested a design matrix describing single origin out of southwest Asia. This design matrix was clearly most similar to the data in all tested cases. These results make the regional-continuity theory a less likely explanation for the observed cranial differences than the two single-origin theories. Of these, single southwest Asian origins seems the more likely interpretation of the data.

Historical population movements in Europe influence genetic relationships in modern samples.

We have newly constructed an ethnohistorical database consisting of 3460 records of ethnic locations and movements in Europe since 2200 B.C. Using this database, we computed vectors of proportions that peoples speaking various language families contributed to the gene pools of 2216 1 degree x 1 degree land-based quadrats of Europe. From these vectors we computed ethnohistorical distances as arc distances between all pairs of quadrats. We used these distances as predictors of genetic distances, which we calculated independently from 26 genetic systems. We find significant partial correlations between ethnohistorical and genetic distances when geographic distance, a common causative factor, is held constant. Ethnohistorical distances explain a significant amount of the genetic variation observed in modern populations. These results are highly robust to simulated errors in and omissions from the ethnohistorical database. Randomization tests show that the historical sequence of the movements does not affect estimates of the ethnohistory-genetics correlation, but the geographic locations of movements do. We track the development of the ethnohistory-genetics correlation through time and show it to be gradual and cumulative over the past 4200 years.

Realistic power simulations compare point- and area-based disease cluster tests.

One can roughly divide disease cluster tests into area-based (using regional data) and point-based (using exact locations). We have compared the power of two area-based methods (Moran's I and I* (pop), a new method) to that of two point-based methods (the Cuzick-Edwards test and Grimson's test), using three realistic simulations of disease (fox rabies in England, childhood leukaemia in North Humberside, England, and Lyme disease in Georgia). The naive belief that point-based methods should be better is not supported: for the complex data simulated here, I* (pop) and the Cuzick-Edwards test had higher power than Grimson's method or Moran's I. I* (pop) capitalizes on high inter-region variability, while Moran's I cannot.

Disease clusters in structured environments.

This paper discusses the distributions of several cluster statistics and illustrates their utility in the analysis of disease incidence or prevalence data arising in organized or structured environments. Such environments involve primary inhabitant locations in office buildings, manufacturing plants, apartment complexes and communities of homes, for example. The methods, which include some generalizations of some existing methods as well as some new ones, will be used to test for household clustering of Trypanosoma cruzi seropositivity data.

Indo-European origins: a computer-simulation test of five hypotheses.

Allele frequency distributions were generated by computer simulation of five models of microevolution in European populations. Genetic distances calculated from these distributions were compared with observed genetic distances among Indo-European speakers. The simulated models differ in complexity, but all incorporate random genetic drift and short-range gene flow (isolation by distance). The best correlations between observed and simulated data were obtained for two models where dispersal of Neolithic farmers from the Near East depends only on population growth. More complex models, where the timing of the farmers' expansion is constrained by archaeological time data, fail to account for a larger fraction of the observed genetic variation; this is also the case for a model including late Neolithic migrations from the Pontic steppes. The genetic structure of current populations speaking Indo-European languages seems therefore to largely reflect a Neolithic expansion. This is consistent with the hypothesis of a parallel spread of farming technologies and a proto-Indo-European language in the Neolithic. Allele-frequency gradients among Indo-European speakers may be due either to incomplete admixture between dispersing farmers, who presumably spoke proto-Indo-European, and pre-existing hunters and gatherers (as in the traditional demic diffusion hypothesis), or to founder effects during the farmers' dispersal. By contrast, successive migrational waves from the East, if any, do not seem to have had genetic consequences detectable by the present comparison of observed and simulated allele frequencies.

Adjusting Moran's I for population density.

I derive two new statistics, Ipop and Ipop*, that adjust Moran's I to study clustering of disease cases in areas (for example, counties) with different, known population densities. A simulation of Lyme disease in Georgia suggests that these new statistics can be more powerful than those currently in use. This is because they consider both spatial pattern and non-binomial variance in rates as evidence supporting disease clusters.

Assessing directional effects in spatial data.

A variable is measured at two locations separated by a given distance. Are the values more similar to each other if the locations are oriented in one direction than another? This question has application to studies of human genetics, epidemics, and acid rain. One obvious analytic approach, regression on latitude and longitude, fails when data are non-directional (isotropic) but spatially autocorrelated. Moreover, although non-zero slope implies similarity between neighbours, the converse is not true. IDIFF, a statistic derived from Moran's coefficient of spatial autocorrelation, is developed to detect general directional effects that apply to the collection of data points. Simulations suggest that, when data have isotropic spatial autocorrelation but are incorrectly assumed to be independent, IDIFF will at worst reject too little. IDIFF has good power to distinguish epidemics that spread non-directionally from those that spread in a favoured direction.

Genetic relationships of European populations reflect their ethnohistorical affinities.

From 420 records of ethnic locations and movements since 2000 B.C., we computed vectors describing the proportions which peoples of the various European language families contributed to the gene pools within 85 land-based 5 x 5-degree quadrats in Europe. Using these language family vectors, we computed ethnohistorical affinities as arc distances between all pairs of the 85 quadrats. These affinities are significantly correlated with genetic distances based on 26 genetic systems, even when geographic distances, a common causative factor, are held constant. Thus, the ethnohistorical distances explain a significant amount of the genetic variation observed in modern populations. Randomizations of the records by chronology result in loss of significance for the observed partial correlation between genetics and ethnohistory, when geography is held constant. However, a randomization of records by location only results in reduced significance. Thus, while the historical sequence of the movements does not seem to matter in Europe, their geographic locations do. We discuss the implications of these findings.

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.

Morphology of the normal visual field in a population-based random sample: principal components analysis.

I applied principal components analysis to Humphrey central 24-2 threshold values from both eyes of 304 clinically normal persons selected by simple random sample from Barbados, WI. The first component, accounting for 62 per cent of the variation, is equivalent to the average threshold value within persons. The first eigenvector, when represented by grey scale maps depicting a pair of eyes, reveals that, as average threshold increases, the visual field rises and flattens, like an umbrella that, initially closed, is simultaneously opened and thrust upwards. I verify three numerical predictions based upon this umbrella description. Much less important sources of variation involve disparity between fellow eyes, and hemimeridional and other symmetric differences within eyes. I discuss briefly possible physiologic explanatory mechanisms.

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.

Familial thyroid disease and delayed language development in first admission patients with schizophrenia.

One hundred consecutive first admission patients with a DSM-III-R diagnosis of schizophrenia, schizoaffective disorder, or schizophreniform disorder were compared with 100 randomly selected community controls. Childhood histories of physical, medical, and perinatal trauma, as well as physical and cognitive development, were examined by structured interviews with all available mothers of patients and controls. The prevalence of specific psychiatric disorders and several medical illnesses among first degree and more distant relatives was determined by family history questionnaires. The patient group did not have an excess of childhood head injuries, serious infections, or perinatal/birth complications compared with controls. With social class level taken into account, it was found that the acquisition of reading skills occurred significantly later in patients than controls. Family histories of schizophrenia and thyroid disorders were significantly more frequent among patients than controls. These data fail to indicate any childhood physical or medical environmental trauma that could lead to an increased risk for schizophrenia, although patients were substance abusers to a greater extent than controls. This study also confirms the already known contribution of familial factors and suggests an association of the inheritance of thyroid disorders with schizophrenia. Delayed development of reading skills suggests that precursers of illness may appear early in life before psychosis is evident.