During the 15th International Histocompatibility and Immunogenetics Workshop (IHIWS), 14 human leukocyte antigen (HLA) laboratories participated in the Analysis of HLA Population Data (AHPD) project where 18 new population samples were analyzed statistically and compared with data available from previous workshops. To that aim, an original methodology was developed and used (i) to estimate frequencies by taking into account ambiguous genotypic data, (ii) to test for Hardy-Weinberg equilibrium (HWE) by using a nested likelihood ratio test involving a parameter accounting for HWE deviations, (iii) to test for selective neutrality by using a resampling algorithm, and (iv) to provide explicit graphical representations including allele frequencies and basic statistics for each series of data. A total of 66 data series (1-7 loci per population) were analyzed with this standard approach. Frequency estimates were compliant with HWE in all but one population of mixed stem cell donors. Neutrality testing confirmed the observation of heterozygote excess at all HLA loci, although a significant deviation was established in only a few cases. Population comparisons showed that HLA genetic patterns were mostly shaped by geographic and/or linguistic differentiations in Africa and Europe, but not in America where both genetic drift in isolated populations and gene flow in admixed populations led to a more complex genetic structure. Overall, a fruitful collaboration between HLA typing laboratories and population geneticists allowed finding useful solutions to the problem of estimating gene frequencies and testing basic population diversity statistics on highly complex HLA data (high numbers of alleles and ambiguities), with promising applications in either anthropological, epidemiological, or transplantation studies.

Our aim was to analyze the incidence of mutations in BRCA1 and BRCA2 genes in 54 families with breast/ovarian cancer. Families were selected from three Institutions following the standard criteria for hereditary breast/ovarian cancer. PCR amplification of all exons was performed, followed by SSCP, heteroduplex, PTT and sequencing analysis. We identified eight truncation mutations, three in the BRCA1 gene and five in the BRCA2 gene. Three of these mutations have not been reported previously by other groups: 308insA in one family, 3936 C>T in two families, for BRCA1, and 4970insTG in one family for BRCA2. In addition two families having Ashkenazi Jewish ancestors present the well known mutations 185delAG and 6174delT. Interestingly, 5 out of 11 families have mutations recurrent in Spanish families. Among the 54 families selected, seven have breast and ovary cancer cases, and only two presented a mutation in BRCA1 or BRCA2 genes. Other cancers as prostate and stomach are frequent among relatives carrying the mutation. Five cases of very early onset (<31 years old) breast cancer were detected. The frequencies of BRCA1 (0.074) and BRCA2 (0.13) mutations in our families is low but similar to the incidence found in other populations, like in Spain. Since is widely known that risk factors that modulate the development of breast cancer such as lifestyle risk factors, geographic location, country of origin and socioeconomic status, besides a familial history of breast cancer our findings suggest that the history of colonization and immigrations is very relevant when studying hereditary factors associated to breast cancer.

HLA-NET (a European COST Action) aims at networking researchers working in bone marrow transplantation, epidemiology and population genetics to improve the molecular characterization of the HLA genetic diversity of human populations, with an expected strong impact on both public health and fundamental research. Such improvements involve finding consensual strategies to characterize human populations and samples and report HLA molecular typings and ambiguities; proposing user-friendly access to databases and computer tools and defining minimal requirements related to ethical aspects. The overall outcome is the provision of population genetic characterizations and comparisons in a standard way by all interested laboratories. This article reports the recommendations of four working groups (WG1-4) of the HLA-NET network at the mid-term of its activities. WG1 (Population definitions and sampling strategies for population genetics’ analyses) recommends avoiding outdated racial classifications and population names (e.g. ‘Caucasian’) and using instead geographic and/or cultural (e.g. linguistic) criteria to describe human populations (e.g. ‘pan-European’). A standard ‘HLA-NET POPULATION DATA QUESTIONNAIRE’ has been finalized and is available for the whole HLA community. WG2 (HLA typing standards for population genetics analyses) recommends retaining maximal information when reporting HLA typing results. Rather than using the National Marrow Donor Program coding system, all ambiguities should be provided by listing all allele pairs required to explain each genotype, according to the formats proposed in ‘HLA-NET GUIDELINES FOR REPORTING HLA TYPINGS’. The group also suggests taking into account a preliminary list of alleles defined by polymorphisms outside the peptide-binding sites that may affect population genetic statistics because of significant frequencies. WG3 (Bioinformatic strategies for HLA population data storage and analysis) recommends the use of programs capable of dealing with ambiguous data, such as the ‘gene[rate]’ computer tools to estimate frequencies, test for Hardy–Weinberg equilibrium and selective neutrality on data containing any number and kind of ambiguities. WG4 (Ethical issues) proposes to adopt thorough general principles for any HLA population study to ensure that it conforms to (inter)national legislation or recommendations/guidelines. All HLA-NET guidelines and tools are available through its website http://hla-net.eu.

We present here the results of the Analysis of HLA Population Data (AHPD) project of the 16th International HLA and Immunogenetics Workshop (16IHIW) held in Liverpool in May-June 2012. Thanks to the collaboration of 25 laboratories from 18 different countries, HLA genotypic data for 59 new population samples (either well-defined populations or donor registry samples) were gathered and 55 were analysed statistically following HLA-NET recommendations. The new data included, among others, large sets of well-defined populations from north-east Europe and West Asia, as well as many donor registry data from European countries. The Gene[rate] computer tools were combined to create a Gene[rate] computer pipeline to automatically (i) estimate allele frequencies by an expectation-maximization algorithm accommodating ambiguities, (ii) estimate heterozygosity, (iii) test for Hardy-Weinberg equilibrium (HWE), (iv) test for selective neutrality, (v) generate frequency graphs and summary statistics for each sample at each locus and (vi) plot multidimensional scaling (MDS) analyses comparing the new samples with previous IHIW data. Intrapopulation analyses show that HWE is rarely rejected, while neutrality tests often indicate a significant excess of heterozygotes compared with neutral expectations. The comparison of the 16IHIW AHPD data with data collected during previous workshops (12th-15th) shows that geography is an excellent predictor of HLA genetic differentiations for HLA-A, -B and -DRB1 loci but not for HLA-DQ, whose patterns are probably more influenced by natural selection. In Europe, HLA genetic variation clearly follows a north to south-east axis despite a low level of differentiation between European, North African and West Asian populations. Pacific populations are genetically close to Austronesian-speaking South-East Asian and Taiwanese populations, in agreement with current theories on the peopling of Oceania. Thanks to this project, HLA genetic variation is more clearly defined worldwide and better interpreted in relation to human peopling history and HLA molecular evolution.

The development of molecular typing techniques applied to the study of population genetic diversity originates data with increasing precision but at the cost of some ambiguities. As distinct techniques may produce distinct kinds of ambiguities, a crucial issue is to assess the differences between frequency distributions estimated from data produced by alternative techniques for the same sample. To that aim, we developed a resampling scheme that allows evaluating, by statistical means, the significance of the difference between two frequency distributions. The same approach is then shown to be applicable to test selective neutrality when only sample frequencies are known. The use of these original methods is presented here through an application to the genetic study of a Munda human population sample, where three different HLA loci were typed using two different molecular methods (reverse PCR-SSO typing on microbeads arrays based on Luminex technology and PCR-SSP typing), as described in details in the companion article by Riccio et al.[The Austroasiatic Munda population from India and its enigmatic origin: An HLA diversity study. Hum. Biol. 38:405-435 (2011)]. The differences between the frequency estimates of the two typing techniques were found to be smaller than those resulting from sampling. Overall, we show that using a resampling scheme in validating frequency estimates is effective when alternative frequency estimates are available. Moreover, resampling appears to be the unique way to test selective neutrality when only frequency data are available to describe the genetic structure of populations. Abstract The development of molecular typing techniques applied to the study of population genetic diversity originates data with increasing precision but at the cost of some ambiguities. As distinct techniques may produce distinct kinds of ambiguities, a crucial issue is to assess the differences between frequency distributions estimated from data produced by alternative techniques for the same sample. To that aim, we developed a resampling scheme that allows evaluating, by statistical means, the significance of the difference between two frequency distributions. The same approach is then shown to be applicable to test selective neutrality when only sample frequencies are known. The use of these original methods is presented here through an application to the genetic study of a Munda human population sample, where three different HLA loci were typed using two different molecular methods (reverse PCR-SSO typing on microbeads arrays based on Luminex technology and PCR-SSP typing), as described in details in the companion article by Riccio et al. [The Austroasiatic Munda population from India and its enigmatic origin: An HLA diversity study. Hum. Biol. 38:405-435 (2011)]. The differences between the frequency estimates of the two typing techniques were found to be smaller than those resulting from sampling. Overall, we show that using a resampling scheme in validating frequency estimates is effective when ...