More population structure in the Netherlands (Lao et al. 2013)

There was a recent article on the topic by Abdellaoui et al., and here is another one.

Investigative Genetics 2013, 4:9 doi:10.1186/2041-2223-4-9

Clinal distribution of human genomic diversity across the Netherlands despite archaeological evidence for genetic discontinuities in Dutch population history

Oscar Lao et al.

Abstract (provisional)

Background

The presence of a southeast to northwest gradient across Europe in human genetic diversity is a well-established observation and has recently been confirmed by genome-wide single nucleotide polymorphism (SNP) data. This pattern is traditionally explained by major prehistoric human migration events in Palaeolithic and Neolithic times. Here, we investigate whether (similar) spatial patterns in human genomic diversity also occur on a micro-geographic scale within Europe, such as in the Netherlands, and if so, whether these patterns could also be explained by more recent demographic events, such as those that occurred in Dutch population history.

Methods

We newly collected data on a total of 999 Dutch individuals sampled at 54 sites across the country at 443,816 autosomal SNPs using the Genome-Wide Human SNP Array 5.0 (Affymetrix). We studied the individual genetic relationships by means of classical multidimensional scaling (MDS) using different genetic distance matrices, spatial ancestry analysis (SPA), and ADMIXTURE software. We further performed dedicated analyses to search for spatial patterns in the genomic variation and conducted simulations (SPLATCHE2) to provide a historical interpretation of the observed spatial patterns.

Results

We detected a subtle but clearly noticeable genomic population substructure in the Dutch population, allowing differentiation of a north-eastern, central-western, central-northern and a southern group. Furthermore, we observed a statistically significant southeast to northwest cline in the distribution of genomic diversity across the Netherlands, similar to earlier findings from across Europe. Simulation analyses indicate that this genomic gradient could similarly be caused by ancient as well as by the more recent events in Dutch history.

Conclusions

Considering the strong archaeological evidence for genetic discontinuity in the Netherlands, we interpret the observed clinal pattern of genomic diversity as being caused by recent rather than ancient events in Dutch population history. We therefore suggest that future human population genetic studies pay more attention to recent demographic history in interpreting genetic clines. Furthermore, our study demonstrates that genetic population substructure is detectable on a small geographic scale in Europe despite recent demographic events, a finding we consider potentially relevant for future epidemiological and forensic studies.

Link

Population structure in the Netherlands

The three PCs are color-coded in panels b,c,d.

European Journal of Human Genetics , (27 March 2013) | doi:10.1038/ejhg.2013.48

Population structure, migration, and diversifying selection in the Netherlands

Abdel Abdellaoui et al.

Genetic variation in a population can be summarized through principal component analysis (PCA) on genome-wide data. PCs derived from such analyses are valuable for genetic association studies, where they can correct for population stratification. We investigated how to capture the genetic population structure in a well-characterized sample from the Netherlands and in a worldwide data set and examined whether (1) removing long-range linkage disequilibrium (LD) regions and LD-based SNP pruning significantly improves correlations between PCs and geography and (2) whether genetic differentiation may have been influenced by migration and/or selection. In the Netherlands, three PCs showed significant correlations with geography, distinguishing between: (1) North and South; (2) East and West; and (3) the middle-band and the rest of the country. The third PC only emerged with minimized LD, which also significantly increased correlations with geography for the other two PCs. In addition to geography, the Dutch North–South PC showed correlations with genome-wide homozygosity (r=0.245), which may reflect a serial-founder effect due to northwards migration, and also with height (♂: r=0.142, ♀: r=0.153). The divergence between subpopulations identified by PCs is partly driven by selection pressures. The first three PCs showed significant signals for diversifying selection (545 SNPs - the majority within 184 genes). The strongest signal was observed between North and South for the functional SNP in HERC2 that determines human blue/brown eye color. Thus, this study demonstrates how to increase ancestry signals in a relatively homogeneous population and how those signals can reveal evolutionary history.

Link

Old and recent clines in Brabant

This paper uses genealogical data to show that while some clines observed today stretch back to pre-industrial times, others do not. This is a nice result that shows that:

• It's best to try to find test subjects with deep genealogies when one makes inferences about the past
• Clines in modern-day populations may reflect very recent events, and not necessarily deep historical or even archaeological events

It should be mentioned that the paper does not contradict broad trends within the mentioned haplogroups that have been previously described. And, of course, this makes sense, since broad trends are more difficult to establish than those at the small-scale geographical level.

There is evidence for discontinuity at the European level across thousands of years, and it seems that we won't be able to escape the inevitable chore of figuring out "who went were" across all time scales, rather than relying on simplistic models of Paleolithic hunters receiving Neolithic farmers, and the two living happily ever after around the same hearths until today.

Related: Y-chromosomes in Brabant.

European Journal of Human Genetics , (30 November 2011) | doi:10.1038/ejhg.2011.218

Temporal differentiation across a West-European Y-chromosomal cline: genealogy as a tool in human population genetics

Maarten HD Larmuseau et al.

Abstract
The pattern of population genetic variation and allele frequencies within a species are unstable and are changing over time according to different evolutionary factors. For humans, it is possible to combine detailed patrilineal genealogical records with deep Y-chromosome (Y-chr) genotyping to disentangle signals of historical population genetic structures because of the exponential increase in genetic genealogical data. To test this approach, we studied the temporal pattern of the ‘autochthonous’ micro-geographical genetic structure in the region of Brabant in Belgium and the Netherlands (Northwest Europe). Genealogical data of 881 individuals from Northwest Europe were collected, from which 634 family trees showed a residence within Brabant for at least one generation. The Y-chr genetic variation of the 634 participants was investigated using 110 Y-SNPs and 38 Y-STRs and linked to particular locations within Brabant on specific time periods based on genealogical records. Significant temporal variation in the Y-chr distribution was detected through a north–south gradient in the frequencies distribution of sub-haplogroup R1b1b2a1 (R-U106), next to an opposite trend for R1b1b2a2g (R-U152). The gradient on R-U106 faded in time and even became totally invisible during the Industrial Revolution in the first half of the nineteenth century. Therefore, genealogical data for at least 200 years are required to study small-scale ‘autochthonous’ population structure in Western Europe.

Link

"Comparing Ancient and Modern DNA Variability in Human Populations" abstracts

Excerpts from the conference site.

Temporal differentiation across a West-European Y-chromosomal cline - genealogy as a tool in human population genetics
Maarten H.D. Larmuseau et al.

The pattern of population genetic variation and allele frequencies within a species are unstable and are changing in time according to different evolutionary factors. For humans, it is possible to combine detailed patrilineal genealogical records with deep Y-chromosome genotyping to disentangle signals of historical population genetic structures due to the exponential increase of genetic genealogical data. To test this approach we studied the temporal pattern of the 'autochthonous' micro-geographical genetic structure in the region of Brabant in Belgium and The Netherlands (Northwest-Europe). Genealogical data of 881 individuals from Northwest-Europe were collected from which 634 family trees showed a residence within Brabant for at least one generation. The Y-chromosome genetic variation of the 634 participants was investigated using 110 Y-SNPs and 38 Y-STRs and linked to particular locations within Brabant on specific time periods based on genealogical records. Significant temporal variation in the Y-chromosome distribution was detected through a north-south gradient in the frequencies distribution of subhaplogroup R1b1b2a1 (R-U106), next to an opposite trend for R1b1b2a2g (R-152). The gradient on R-U106 faded in time and became even totally invisible during the Industrial revolution in the first half of the 19th century. Therefore, genealogical data for at least 200 year are required to study small-scale 'autochthonous' population structure in Western-Europe.

The Dutch medieval and post-medieval genetic landscapes
Eveline Altena et al.

Since 2005 many archeological human skeletons have been sampled for DNA research under forensic conditions in The Netherlands. This enables us to perform a large scale genetic survey on reliable genetic data from the prehistory until the present. The majority of the available archaeological DNA samples, though, originate from medieval and post-medieval sites. Here we present preliminary autosomal and Y-chromosomal data from more then 500 archaeological human skeletons, excavated at several medieval and post-medieval sites. We also compare these historical genetic data with data from more then 2000 modern Dutch males.

Comparing ancient and modern DNA variability in North Eastern Iberia: the Neolithic impact of first farmers
Cristina Gamba et al.

Archaeological, anthropological and demographic hypotheses can be tested by comparing ancient and modern DNA from human samples in a diachronical context. In this case, it was possible to evaluate genetic continuity or discontinuity between different periods, and/or to infer ancient human migrations in a set of Iberian samples. We evaluated the demographic impact associated to the spread of the Neolithic in North Eastern Iberia. We recovered mitochondrial DNA from 13 Early Neolithic specimens from three archaeological sites: Can Sadurní, Chaves and Sant Pau. A bayesian simulation approach was performed to compare the obtained results with Middle Neolithic and modern samples from the same region. We tested different scenarios to determine which among them better explained the analyzed data. By comparing simulated and observed FST values, we observed genetic differentiation between Early Neolithic and Middle Neolithic populations, which suggests that at the beginning of the Neolithic, genetic drift played an important role.
Genetic differentiation was also observed between Early Neolithic and modern- day populations. These data are compatible with the arrival of small genetically-distinctive groups at the beginning of the Neolithic, suggesting a pioneer colonization of North Eastern Iberia by first farmers.

The following abstract is interesting as it suggests we should not view the "Neolithic" as a singular event. X2 was also discovered in Megalithic France, as well as a likely immigrant population from the Near East and the Caucasus in the Tarim Basin, and Bronze Age Eulau. From a paper on the Reidla et al. (2003): Overall, it appears that the populations of the Near East, the Caucasus, and Mediterranean Europe harbor subhaplogroup X2 at higher frequencies than those of northern and northeastern Europe (P less than .05) and that X2 is rare in Eastern European as well as Central Asian, Siberian, and Indian populations and is virtually absent in the Finno-Ugric and Turkic-speaking people of the Volga-Ural region.

Where are all the "WIX"? Rare European maternal lineages W, I, and X2 in the past and present
Esther J. Lee et al.

Studies utilizing ancient DNA to examine past populations in Europe have increased dramatically in recent years. Specifically, mitochondrial DNA (mtDNA) sequences for over 100 individuals in prehistoric Europe have been sequenced and published. Scholars have intensively focused on the so-called Neolithic transition in Europe, the transformation from hunter-gatherer lifestyle to agro-pastoralism, and continue to debate whether the process was a result of population movement or cultural dispersion. Both hypotheses continue to be tested and genetics analyses from past and present populations have suggested a complex movement of people and cultures across Eurasia. This work focuses on the mtDNA haplogroups identified in past European populations that are rare in the present, haplogroups W, I, and X2. New data will be presented from Neolithic Funnel Beaker collective burials sites, a late Neolithic Bell Beaker site, and an Iron Age Halstatt site in Germany, in which the three maternal lineages are identified. Among the published European Neolithic data, haplogroup X2 appears in late Neolithic sites in Germany and France but not in the earlier LBK culture. Haplogroup X2 shows an intriguing phylogenetic landscape with a wide geographical distribution at an overall low frequency, but on the other hand, pockets of high diversity and frequency among certain modern western Eurasian populations have been described. The discussion focuses on whether the presence of the three haplogroups in the past is a result of ascertainment bias or some viable population movement.

The following seems to suggest Denisova admixture in the East Asian mainland, and not just the island groups, identified in the recent Reich et al. (2011) paper. The sentence about biased Neandertal similarity with increasing distance to Africa is also interesting; the data that is available so far shows non significant differences in Neandertal similarity among Eurasians, although the published values do seem to show higher (and perplexing) averages in China vs. Europe.

Archaic human ancestry in East Asia
Pontus Skoglund & Mattias Jakobsson

Recent studies of ancient genomes have suggested that gene flow from archaic hominin groups to the ancestors of modern humans occurred on two separate occasions during the modern human expansion out of Africa. At the same time, decreasing levels of human genetic diversity have been found at increasing distance from Africa as a consequence of human expansion out of Africa. We re-analyzed the signal of archaic ancestry in modern human populations and we investigated how serial founder models of human expansion affect the signal of archaic ancestry using simulations. We show that genetic drift coupled with an ascertainment bias for common alleles can cause artificial, but largely predictable, differences in affinity to archaic genomes between descendants of an admixture event. In genotype data from non-African humans, this effect results in a biased genetic similarity to Neandertal with increasing distance from Africa. In addition to the two previously reported connections between non-Africans and Neandertals as well as between Oceanians and a Denisovan archaic human genome from Siberia, we found a significant affinity between East Asians (in particular Southeast Asians) and the Denisovan genome, a pattern that is not expected under a model of solely Neandertal-related admixture in the ancestry of East Asians. This observation could be explained either by substantial migration from Oceania into East Asia, or more common history between anatomically modern- and archaic populations than previously proposed.

Y chromosomes in Brabant

From the paper:

The Duchy of Brabant was a historical region in the Low Countries between the 12th and 18th century and consisted of a present-day Dutch province and three contemporary Belgian provinces together with the Brussels-Capital Region. The total area is 14.425km2 with approximately 150 km between the two most remote places in Brabant. The main reason for selecting this region was the ability to obtain reliable genealogical data of the patrilineal line for each of the numerous donors living together on a small geographical scale.

The authors typed 37 Y-STRs, and 103 Y-SNPs. They write:

All individuals were correctly assigned to the main haplogroups using the Whit Atheys’ Haplogroup Predictor. In total, eight main haplogroups were observed with almost 85% of the samples belonging to haplogroup R(63%) and I(21%)(Table 1). On the lowest observed level of the phylogenetic tree 32subhaplogroups were found in the dataset, whereby nearly 70% of all samples belonged to only four subhaplogroups: R1b1b2a1(R-U106), R1b1b2a2* (R-P312*), R1b1b2a2g(R-U152) andI1*(I-M253*)

They found star-patterns in all their subhaplogroups, but uncovered some structure in their J2a* (J-M410*) chromosomes. Youngest expansion ages "were observed for E1b1b1a2(E-V13) and I1*(I-M253*), respectively 4182–5855 and 4531–6344 years ago."

Also:

a strong downward trend in the frequency of haplogroup R was observed from North to South (Table 1; Fig. S5). The difference in the frequency of R haplogroups was circa 10% between the most northern and southern part, mainly due to the downward frequency of R1b1b2a1(R-U106).

The European-wide distribution of R-U106 suggests to me that it was a Germanic lineage.

Also:

Moreover, it was even possible to detect further substructuring within subha-
plogroup J2a*(J-M410*)based on the network analysis of all single-allele Y-STR haplotypes. Nevertheless, it was remarkable that the network analyses could not differentiate all observed subhaplogroups within R1b1b2(R-M269) and I2b(I-M223). This might be due to the relatively young age of these specific subhaplogroups making it impossible to differentiate these groups based on the Y-STRs.

The extraordinary success of these subhaplogroups is one of the most interesting questions: natural selection, or demographic dominance of a recently formed population group storming Western Europe by force of numbers? Ancient Y-DNA urgently needed...

The occurrence of haplogroup Q1 in 2.6% at Kempen, and 1.59% at Mechelen is an oddity of the findings that might merit further study.

In short this might be called a "model study" of Y-chromosome variation, due to the large number of individuals (477) and markers tested.

Forensic Sci Int Genet. 2010 Oct 29. [Epub ahead of print]

Micro-geographic distribution of Y-chromosomal variation in the central-western European region Brabant.

Larmuseau MH, Vanderheyden N, Jacobs M, Coomans M, Larno L, Decorte R.

Abstract

One of the future issues in the forensic application of the haploid Y-chromosome (Y-chr) is surveying the distribution of the Y-chr variation on a micro-geographical scale. Studies on such a scale require observing Y-chr variation on a high resolution, high sampling efforts and reliable genealogical data of all DNA-donors. In the current study we optimised this framework by surveying the micro-geographical distribution of the Y-chr variation in the central-western European region named Brabant. The Duchy of Brabant was a historical region in the Low Countries containing three contemporary Belgian provinces and one Dutch province (Noord-Brabant). 477 males from five a priori defined regions within Brabant were selected based on their genealogical ancestry (known pedigree at least before 1800). The Y-haplotypes were determined based on 37 Y-STR loci and the finest possible level of substructuring was defined according to the latest published Y-chr phylogenetic tree. In total, eight Y-haplogroups and 32 different subhaplogroups were observed, whereby 70% of all participants belonged to only four subhaplogroups: R1b1b2a1 (R-U106), R1b1b2a2* (R-P312*), R1b1b2a2g (R-U152) and I1* (I-M253*). Significant micro-geographical differentiation within Brabant was detected between the Dutch (Noord-Brabant) vs. the Flemish regions based on the differences in (sub)haplogroup frequencies but not based on Y-STR variation within the main subhaplogroups. A clear gradient was found with higher frequencies of R1b1b2 (R-M269) chromosomes in the northern vs. southern regions, mainly related to a trend in the frequency of R1b1b2a1 (R-U106).

Link

Half of hidden heritability found (for height, at least)

This is a quite interesting paper, as it shows, by sampling a large number of individuals), that the heritability of height is not missing after all. The authors looked at a large number of individuals, and this allowed them to discover statitically significant associations between height and more SNPs than before.

This bears great promise as it may hint that genome-wide association studies, that have come under substantial criticism lately, may be failing not because of an inherent flaw, but rather because they are not sampling enough individuals.

The discovered SNPs account for 45% of the heritability of height. Where is the rest? The authors argue for two additional sources:

First, SNPs in current microarray chips sample the genome incompletely. Locations in-between discovered SNPs are in incomplete linkage disequilibrium with the discovered SNPs. So, there is undetected polymorphism, in the gaps between the hundreds of thousands of SNPs in current chips, that may explain a portion of the missing heritability.

Second, SNPs have different minor allele frequencies. For example, in one SNP the minor allele may occur at 10% of individuals, while in others at 30%. This is important, because it is more difficult to arrive at a statistically significant result in the former case.

Consider a SNP with a minor allele frequency of 2%. Then, if you sample 1,000 individuals, only about 20 of them are expected to have the minor allele. You cannot estimate the average height of the minor allele with a sample of 20 people as securely as you can with a sample of 500. Thus, if the SNP influences height in a small way, you will not be able to detect it.

A further complication, which I've written about before, is that some variation in the human genome is family-related, or at least occurs at fewer individuals than the allele frequency cutoff. If 99.9% of people have C at a given location and 0.1% of people have T, this variant is unlikely to be included in a microarray chp, because it is too rare to matter economically: you would only get a handful of individuals -if you're lucky- in a sample of 1,000 for such a variant. However, rarity does not mean that the variant is functionally unimportant, and the rare allele may play a substantial role in the height of the people who possess it.

The publication of this paper is a cause for optimism, as it shows that progress can be made by brute force: fuller genome coverage and more individuals. We'll have to wait and see whether or not the same approach will work for other complex traits, such as IQ or schizophrenia, that have been hitherto difficult to crack.

Obviously, the cost of sampling more individuals will become an issue in future studies, but the cost-per-individual is expected to drop. So, I'm guessing that more discoveries are in store for us in the next few years.

UPDATE (Jun 28):

Not the main point of the paper, but also included in the supplementary material (pdf) are some nice PCA results.

In the European-only PCA we see the familiar north-south gradient (anchored by Tuscans TSI and Netherlands NET on either side), and the orthogonal deviation of the Finns. Swedes (SWE) occupy a northern European end of the spectrum like the Dutch, but are spread towards Finns, reflecting low-level Finnish admixture in that population. Conversely, Finns are variable along the same axis, reflecting variable levels of admixture. Australians (AUS) and UK, on the other hand, are on the northern European edge of the main European gradient, with a number of individuals spread toward the Tuscan side.

The PCA with all populations is also quite interesting. East Eurasians (Chinese and Japanese) form a tight pole at the bottom right. Gujarati Indians (GIH) form a different pole, spread towards Europeans, reflecting variable levels of West Eurasian admixture in that population, probably corresponding to the ANI element recently discovered in Indian populations. Mexicans (MEX) are spread towards East Asians, reflecting their Amerindian admixture, but notice how they are not positioned exactly on the European-East Asian axis, probably reflecting the third, minority, Sub-Saharan element in their ancestry, as well as the fact that Amerindians are not perfectly represented by East Asians. Finns are tilted towards East Asians, as expected, reflecting the fact that their genetic specificity vis a vis Northern Europeans is due to low-level East Eurasian ancestry.

An interesting aspect of the first two PCs is the fact that the Maasai (MKK) and Luhya (LUW) from Kenya are not separated from Caucasoids, and neither are Yoruba from Nigeria (YRI). This is a good reminder of the fact that identity in the first two principal components may mask difference revealed in higher order components. This difference (at least for Maasai) is seen in the next two PCs.

Nature Genetics doi:10.1038/ng.608

Common SNPs explain a large proportion of the heritability for human height

Jian Yang et al.

Abstract

SNPs discovered by genome-wide association studies (GWASs) account for only a small fraction of the genetic variation of complex traits in human populations. Where is the remaining heritability? We estimated the proportion of variance for human height explained by 294,831 SNPs genotyped on 3,925 unrelated individuals using a linear model analysis, and validated the estimation method with simulations based on the observed genotype data. We show that 45% of variance can be explained by considering all SNPs simultaneously. Thus, most of the heritability is not missing but has not previously been detected because the individual effects are too small to pass stringent significance tests. We provide evidence that the remaining heritability is due to incomplete linkage disequilibrium between causal variants and genotyped SNPs, exacerbated by causal variants having lower minor allele frequency than the SNPs explored to date.

Link

Intermarriage and the risk of divorce in the Netherlands

Prompted by my recent post on Constantinus Porphyrogenitus and inter-ethnic marriage.

From the paper:

We therefore introduce two hypotheses. The first hypothesis is the main-effects hypothesis, which argues that the more traditional the value orientation of a religious or national origin group, the lower the risk of divorce.

...

Our second hypothesis concerns the effect of the spouses’ religion and national origin, and argues that when the religions or national origins of the two spouses are dissimilar, the risk of divorce is higher.We call this the heterogamy hypothesis. Assumingthat the main-effects hypothesis is valid, we need to decide what constitutes evidence for the heterogamy hypothesis. If the divorce risk of a mixed marriage (between, say, a member of group A and a member of group B) is higher than the divorce risk of AA marriages but lower than the divorce risk of BB marriages, we argue that adaptation is taking place. The behaviour of those couples is in between the two groups, and one can argue that this is simply the average of the two group effects and not a heterogamy effect (Jones 1996). To analyse real heterogamy effects, we employ both a strong and a weak form of the heterogamy hypothesis. According to the strong heterogamy hypothesis, AB marriages will have a divorce risk that is higher than the maximum divorce risk of AA and BB marriages. For example, we expect that a marriage between a Catholic and an unaffiliated person will have a divorce risk that is higher than the (already) high risk for unaffiliated couples. According to the weak heterogamy hypothesis, AB marriages will have a divorce risk that is higher than the average risk of AA and BB marriages. In our example, the risk of the mixed group will be higher than the average of the low risk for Catholics and the high risk for unaffiliated couples.

The data is supportive of the strong heterogamy hypothesis, according to which an AB has a higher chance of a divorce than the highest of AA and BB:

Are there effects of heterogamy on the risk of divorce? Table 8 shows that the answer is clear: most mixed combinations have a risk of divorce that is higher than the highest level of divorce in the two homogamous groups. The average ratio is 2.02, indicating that mixed marriages have a risk of divorce twice as high as that of the maximum level of divorce in the two corresponding groups. This effect is quite strong and clearly supports the strong heterogamy hypothesis.

...

We also find variations in the magnitude of the effects that are consistent with our hypothesis about value orientations. Combinations of Dutch and Turkish or Moroccan persons reveal a stronger heterogamy effect than combinations involving Dutch and Western European persons. The effects for combinations involving Southern Europeans are in between the combinations with Turks or Moroccans and the combinations with Western Europeans. When looking at combinations involving
minority men, the differences are quite strong. The ratio is 4.7 for combinations involving Turkish men, 2.4 for combinations involving Moroccan men, and 1.5 for combinations involving Western European men. Because European groups are more similar than Moroccan and Turkish groups to the Dutch in values and lifestyle, this finding is consistent with theoretical interpretations of the heterogamy effect
in terms of value similarity.

The paper has detailed tables on the various combinations of intermarriage between different Dutch religious denominations and national origins. What seems clear is that Constantinus' ideas about religious and ethnic homogamy as more conducive to harmonious cohabitation seem to be supported by the data.

Population Studies, Vol. 59, No. 1, 2005, pp. 71-85

Intermarriage and the risk of divorce in the Netherlands: The effects of differences in religion and in nationality, 1974-94

Matthijs Kalmijn et al.

A textbook hypothesis about divorce is that heterogamous marriages are more likely to end in divorce than homogamous marriages. We analyse vital statistics on the population of the Netherlands, which provide a unique and powerful opportunity to test this hypothesis. All marriages formed between 1974 and 1984 (nearly 1 million marriages) are traced in the divorce records and multivariate logistic regression models are used to analyse the effects on divorce of heterogamy in religion and national origin. Our analyses confirm the hypothesis for marriages that cross the Protestant-Catholic or the Jewish-Gentile boundary. Heterogamy effects are weaker for marriages involving Protestants or unaffiliated persons. Marriages between Dutch and other nationalities have a higher risk of divorce, the more so the greater the cultural differences between the two groups. Overall, the evidence supports the view that, in the Netherlands, new group boundaries are more difficult to cross than old group boundaries.

Link

Supplement on "Geographical structure and differential natural selection amongst North European populations" (McEvoy et al. 2009)

From the supplemental material of a paper I covered in March, here are a couple of PCA plots of the first two principal components of the studied populations, with or without the Finns.


In the plot without the Finns, we see the expected British Isles -> Continental Europe differentiation in the order of Ireland, UK, Netherlands, along PC1. Swedes, and to a much lesser extent Danes deviate from this gradient in an orthogonal direction.
When Finns are included, PC1 now captures the major difference between them and the other Celto-Germanic populations which appear strikingly homogeneous along this component. The reason for the Swedes' divergence is now clear, as they are seemingly drawn towards the Finns, although the two clusters can be cleanly separated by a line at around PC1=-0.03.

It is fairly clear by now, that in northern Europe, there are two major distinctions (in that order): (i) between the Finns, and Finno-Ugrian influenced populations on the one hand, and the rest, and (b) a less important West-East gradient from Ireland to the Baltic.

The fact that factor (i) is the most important one pretty much vindicates the views of traditional physical anthropology since the time of Deniker at least. Despite the lack of data and statistical knowledge available at his time, Deniker, in the late 19th century, divided the light-pigmented northern European xanthochrooi of earlier classifications into two: the race nordique, associated primarily with the Germanic peoples, and the race orientale associated primarily with the eastern Slavs and Finns.

This classification scheme was continued by the better writers that followed, e.g., as razza nordica and razza baltica by Renato Biasutti, and as Атланто-балтийская раса (Atlanto-Baltic race) and Беломорско-балтийская раса (White Sea-Baltic race) in works written in Russian.