Maternal depression, antidepressant prescriptions, and congenital anomaly risk in offspring: a population-based cohort study.

OBJECTIVE: To estimate risks of major congenital anomaly (MCA) among children of mothers prescribed antidepressants during early pregnancy or diagnosed with depression but without antidepressant prescriptions. DESIGN: Population-based cohort study. SETTING: Linked UK maternal-child primary care records. POPULATION: A total of 349,127 singletons liveborn between 1990 and 2009. METHODS: Odds ratios adjusted for maternal sociodemographics and comorbidities (aORs) were calculated for MCAs, comparing women with first-trimester selective serotonin reuptake inhibitors (SSRIs) or tricyclic antidepressants (TCAs) and women with diagnosed but unmedicated depression, or women without diagnosed depression. MAIN OUTCOME MEASURES: Fourteen system-specific MCA groups classified according to the European Surveillance of Congenital Anomalies and five specific heart anomaly groups. RESULTS: Absolute risks of MCA were 2.7% (95% confidence interval, 95% CI, 2.6-2.8%) in children of mothers without diagnosed depression, 2.8% (95% CI 2.5-3.2%) in children of mothers with unmedicated depression, and 2.7% (95% CI 2.2-3.2%) and 3.1% (95% CI 2.2-4.1%) in children of mothers with SSRIs or TCAs, respectively. Compared with women without depression, MCA overall was not associated with unmedicated depression (aOR 1.07, 95% CI 0.96-1.18), SSRIs (aOR 1.01, 95% CI 0.88-1.17), or TCAs (aOR 1.09, 95% CI 0.87-1.38). Paroxetine was associated with increased heart anomalies (absolute risk 1.4% in the exposed group compared with 0.8% in women without depression; aOR 1.78, 95% CI 1.09-2.88), which decreased marginally when compared with women with diagnosed but unmedicated depression (aOR 1.67, 95% CI 1.00-2.80). CONCLUSIONS: Overall MCA risk did not increase with maternal depression or with antidepressant prescriptions. Paroxetine was associated with increases of heart anomalies, although this could represent a chance finding from a large number of comparisons undertaken.

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.

Factors affecting population variation in eastern Adriatic isolates (Croatia).

Inhabitants of the Croatian islands of Brac, Hvar, Korcula, and the Peljesac Peninsula have been the subject of extensive previous studies of local population differentiation. Most of these studies used biological and ecological variables, but some also considered historical and sociological factors. In this study we use genetic, morphological, kinship, and language distance data, collected for individuals from 26 rural communities on the islands of Brac, Hvar, Korcula, and the Peljesac Peninsula in the Adriatic, to further explore the interaction of historical, sociological, and biological factors in small populations and to test the significance of some of these proposed causes. First, we use matrix correlation methods to evaluate the relationships among different types of distance measures. The specific measures of genetic distance used here do not correlate well with other measures of population distance, and it appears that for the studied genetic systems the populations are not strongly differentiated. As expected, kinship and language distances have a high degree of association. Morphological differences among populations seem to be more closely tied to kinship distances than to genetic distances. This may result from modification of some morphological features by environmental rather than genetic factors, or it may be attributed to extensive, selective, nonrandom emigration of the population during the first decade of the twentieth century. In the second part of our analysis we use matrix correlation methods to evaluate and possibly identify the external factors that have contributed to the population differences. Specifically, we use design matrices to test hypotheses that population differences can be explained by one of the following factors: geographic isolation on the islands and peninsula, distance from the mainland, geographic barriers within the islands and peninsula, and the historical factors that differentially affected the three islands and the peninsula. Most of these design matrices reflect geographic distances; although correlations between morphological variables and simple geographic distance between localities were not significant, correlations between these localities and a design matrix incorporating geographic distance along with geographic barriers, such as bodies of water and mountain ranges, are particularly important for explaining distances among kin. Design matrices provide an important tool for quantifying the relationship between historical and geographic factors, and measures of population distance.

Spatial genetic structure of human populations in Japan.

We studied spatial patterns for 24 allele frequencies representing 15 systems (blood antigens, enzymes, serum proteins, color blindness, and cerumen) in Japan. The total number of samples over all systems and localities is 1125. We investigated patterns of genetic variation graphically as interpolated allele frequency surfaces, as one-dimensional and directional correlograms, and by testing for the direction of maximal genetic autocorrelation. We examined the allele frequency surfaces by various techniques of spatial autocorrelation analysis and found 13 allele frequency surfaces from 9 genetic systems exhibiting significant spatial patterns. Several surfaces have clinal patterns along the major axis of the Japanese archipelago; others tend toward a maximum or minimum in south-central Honshu. Yet other allele frequencies show long-distance differentiation or patchiness. We discovered seven areas of rapid genetic change by using the wombling method. These areas largely reflect maritime and montane barriers, and some are associated with dialectal boundaries in these populations. The observed patterns support the hybridization or dual structure hypothesis for the peopling of Japan.

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.

Dermatoglyphic variation in Europe.

We describe the geographic variation patterns of 236 dermatoglyphic variables (118 for each sex) for 74 samples in Europe. Using principal components analysis and rotating to simple structure, we simplified these patterns to the first 20 axes, representing 74.2% of covariation. We then used heterogeneity tests, interpolated surfaces, one-dimensional and directional correlograms, and distances between correlograms to analyze the factor scores of these 20 axes. We also ordinated the 74 localities. The data are remarkable for showing little spatial autocorrelation, despite significant heterogeneity among localities. Only three factor axes exhibit consistently significant correlograms, indicating that there are few spatial patterns in the original variables in Europe. Almost all correlations between pairs of variables occur within serially homologous character sets and are thus developmentally determined. There is some support for demic diffusion from the southeast in finger patterns and ridge counts. We compare these results to those of previous studies and note that Lapps and Icelanders are outliers with respect to both genetics and finger tip variables, whereas Tatars are outliers with respect to craniometrics and dermatoglyphics.

Worldwide analysis of genetic and linguistic relationships of human populations.

In this study we relate language differences on a global scale with genetic distances for the same populations. The analysis is carried out on more populations (130) but fewer genetic systems (11) than earlier studies. We constructed an overall genetic distance matrix that allowed for missing values. A separate genetic distance matrix was also computed for each genetic system, and matching matrices of linguistic and geographic distances were associated with each genetic distance matrix, because the number of populations used differed among the genetic systems studied. Significant matrix correlations between language and genetics were found for both overall genetic distances and a substantial number of genetic systems, even when the effects of geographic distances were held constant. This demonstrates a significant correspondence between genetics and language on a global scale. Genetic matrices were correlated with two different linguistic distance matrices: one with higher (supraphyletic) taxonomic structure, in which among other features sub-Saharan Africans separate from non-Africans in the basal split and the Eurasiatic superphylum is postulated; and one without such structure. The correlations yield no genetic evidence to support the proposed higher linguistic structure. UPGMA and neighbor-joining trees were constructed for linguistic and genetic data. The proposed African split pattern is not supported by these data. Both types of trees indicate a pattern of grouping of east Asians, Arctic populations, and Australian natives separating from Caucasoid and African populations.

Origins of Indo-Europeans and the spread of agriculture in Europe: comparison of lexicostatistical and genetic evidence.

A series of tests was undertaken to relate lexicostatistical dissimilarities (LAN) among 48 Indo-European languages to distances representing various causal hypotheses. The comparison is limited to languages currently spoken in Europe. The putative causal distance matrices include (1) geographic (GEO) distances between the languages, (2) distances representing the origin of agriculture (OOA), (3) distances representing a model postulated by C. Renfrew (REN) concerning transformations that gave rise to the major Indo-European language families in Europe, and (4) distances representing a competing hypothesis by M. Gimbutas (GIM) concerning the origin and spread of Indo-European languages in Europe. Pairwise Mantel tests of the matrices show that OOA correlates better with LAN than does REN, supporting Renfrew's basic hypothesis of the dispersal of the Indo-European languages with the spread of agriculture but showing less effect for his postulated transformations. Partial correlation of LAN with OOA when GEO is held constant is significant at p = 0.004, whereas REN is no longer correlated with LAN when GEO is held constant. When repeated for only seven languages chosen to represent the seven major families of Indo-European languages currently spoken in Europe, the results differed appreciably, yielding a negative, albeit nonsignificant, partial correlation between OOA and LAN when GEO is held constant. This apparent contradiction led us to develop some new statistical approaches to examine, confirm, and explain the patterns. Decomposing the Mantel correlation coefficients for the 48 Indo-European languages into several additive correlation components showed that much of the positive component of the correlation coefficient was contributed by LAN, OOA correlation within language families, particularly within the Germanic family, covering up the negative contributions between language families. The differentiation of the seven major Indo-European language branches in Europe seems unrelated to the times of the origin of agriculture. This finding fails to support the fundamental assumption of Renfrew's hypothesis. There are also no significant correlations between LAN and REN or GIM. A series of Monte Carlo experiments confirmed these findings. Consideration of the accumulated evidence from genetics supports the model of demic diffusion during the origin of agriculture. However, published genetic studies and the present study lend no support to the notion that the early farmers were indeed the Indo-Europeans.

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.

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.

Genetic structure of human populations in the British Isles.

Spatial patterns were studied for 36 allele frequencies representing 14 genetic systems (blood antigens, enzymes and serum proteins) in the United Kingdom and Irish Republic. The total number of data points over all systems and localities is 331. Patterns of genetic variation in space are graphically represented by one-dimensional and directional correlograms, and by interpolated allele-frequency surfaces. The data surfaces were examined by the various techniques of spatial autocorrelation analysis. Zones of rapid change across allele surfaces were discovered by the wombling method. Six allele frequency surfaces from four genetic systems exhibit significant spatial patterns. Only one pattern (IO; in the ABO system) may be described as purely clinal in an east-west direction; another (IB; in ABO) approximates a cline or at least north-south differentiation. A method was developed for testing the direction of maximal genetic autocorrelation. Two previously unrecorded patterns for the British Isles, north-south gradients for Rhesus and P, were detected. Twelve zones of rapid genetic change were discovered; some of these seem to reflect maritime and montane physical barriers as well as long-held cultural and linguistic differences, particularly between early Germanic and Celtic speakers. Moreover, some appear to reflect past historic events such as the invasions of Anglo-Saxons and Anglo-Normans.

Geographic variation of six dermatoglyphic traits in Eurasia.

We describe the geographic variation patterns of six dermatoglyphic traits from 144 samples in Eurasia. The methods of analysis include computation of interpolated surfaces, one-dimensional and directional correlograms, correlations between all pairs of surfaces, and distances between correlograms. There are at least two, probably three, distinct and significant patterns of variation. 1) A general NW-SE trend for pattern intensity, the main line index, and frequency of hypothenar patterns. 2) A trend from the Middle East to the north and east for frequency of axial triradius and of accessory interdigital triradii. 3) A patchy pattern for frequency of the thenar-interdigital 1. The results are compatible with a diffusion process between Europe and the peoples of Northern Asia, and possibly with a radiation of populations from the Middle East. The hypothesis of diffusion processes is supported by substantial interpopulation correlations between dermatoglyphic traits that contrast sharply with largely negligible intralocality correlations.

A spatial analysis of 100 surnames in England and Wales.

Spatial patterns are described and analysed for the 84 most common surnames in England and Wales, as well as 16 others selected for various reasons. At least three-quarters of the surname frequencies show spatial structure and are heterogeneous over the area of study. While they do not exhibit clines extending over the entire area of study, they do divide into four characteristics patterns. Spatial autocorrelation, while significant, is relatively low; similarity in surname frequency does not extend much beyond 100 km. Correlograms could be clustered to yield groups of surfaces denoting partial clines, isolation by distance, and differentiation at far distances. A method for detecting zones of rapid change found 21 such zones, mostly near the periphery of the study area. These boundaries do not indicate barriers to gene flow, but appear to be patterns brought about by historical factors. There are diffusion patterns between areas that differ greatly in surname composition, such as Wales and central England. There is little evidence of long-distance movements involving several surnames. At least three characteristic migration patterns, east-west and north-south diffusion and local dispersal, were found.

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.