Spirometry reference equations for central European populations from school age to old age.

Spirometry reference values are important for the interpretation of spirometry results. Reference values should be updated regularly, derived from a population as similar to the population for which they are to be used and span across all ages. Such spirometry reference equations are currently lacking for central European populations. To develop spirometry reference equations for central European populations between 8 and 90 years of age. We used data collected between January 1993 and December 2010 from a central European population. The data was modelled using "Generalized Additive Models for Location, Scale and Shape" (GAMLSS). The spirometry reference equations were derived from 118'891 individuals consisting of 60'624 (51%) females and 58'267 (49%) males. Altogether, there were 18'211 (15.3%) children under the age of 18 years. We developed spirometry reference equations for a central European population between 8 and 90 years of age that can be implemented in a wide range of clinical settings

The geography of recent genetic ancestry across Europe

The recent genealogical history of human populations is a complex mosaic formed by individual migration, large-scale population movements, and other demographic events. Population genomics datasets can provide a window into this recent history, as rare traces of recent shared genetic ancestry are detectable due to long segments of shared genomic material. We make use of genomic data for 2,257 Europeans (the POPRES dataset) to conduct one of the first surveys of recent genealogical ancestry over the past three thousand years at a continental scale. We detected 1.9 million shared genomic segments, and used the lengths of these to infer the distribution of shared ancestors across time and geography. We find that a pair of modern Europeans living in neighboring populations share around 10-50 genetic common ancestors from the last 1500 years, and upwards of 500 genetic ancestors from the previous 1000 years. These numbers drop off exponentially with geographic distance, but since genetic ancestry is rare, individuals from opposite ends of Europe are still expected to share millions of common genealogical ancestors over the last 1000 years. There is substantial regional variation in the number of shared genetic ancestors: especially high numbers of common ancestors between many eastern populations likely date to the Slavic and/or Hunnic expansions, while much lower levels of common ancestry in the Italian and Iberian peninsulas may indicate weaker demographic effects of Germanic expansions into these areas and/or more stably structured populations. Recent shared ancestry in modern Europeans is ubiquitous, and clearly shows the impact of both small-scale migration and large historical events. Population genomic datasets have considerable power to uncover recent demographic history, and will allow a much fuller picture of the close genealogical kinship of individuals across the world.Comment: Full size figures available from http://www.eve.ucdavis.edu/~plralph/research.html; or html version at http://ralphlab.usc.edu/ibd/ibd-paper/ibd-writeup.xhtm

Inferring Geographic Coordinates of Origin for Europeans Using Small Panels of Ancestry Informative Markers

Recent large-scale studies of European populations have demonstrated the existence of population genetic structure within Europe and the potential to accurately infer individual ancestry when information from hundreds of thousands of genetic markers is used. In fact, when genomewide genetic variation of European populations is projected down to a two-dimensional Principal Components Analysis plot, a surprising correlation with actual geographic coordinates of self-reported ancestry has been reported. This substructure can hamper the search of susceptibility genes for common complex disorders leading to spurious correlations. The identification of genetic markers that can correct for population stratification becomes therefore of paramount importance. Analyzing 1,200 individuals from 11 populations genotyped for more than 500,000 SNPs (Population Reference Sample), we present a systematic exploration of the extent to which geographic coordinates of origin within Europe can be predicted, with small panels of SNPs. Markers are selected to correlate with the top principal components of the dataset, as we have previously demonstrated. Performing thorough cross-validation experiments we show that it is indeed possible to predict individual ancestry within Europe down to a few hundred kilometers from actual individual origin, using information from carefully selected panels of 500 or 1,000 SNPs. Furthermore, we show that these panels can be used to correctly assign the HapMap Phase 3 European populations to their geographic origin. The SNPs that we propose can prove extremely useful in a variety of different settings, such as stratification correction or genetic ancestry testing, and the study of the history of European populations

Care seeking behaviour and barriers to accessing services for sexually transmitted infections among female sex workers in Laos: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Prompt, correct diagnosis and treatment with health information are essential components of reproductive tract infection (RTI) and sexually transmitted infection (STI) services. This study aims to describe care seeking behaviour and barriers to accessing RTI/STI services among female sex workers (FSWs) in Laos.</p> <p>Methods</p> <p>A cross-sectional survey using closed and open-ended questions was performed in six districts along Road 9, traversing Savannakhet province from Thailand to Vietnam. In total, 407 FSWs were interviewed. The data were analyzed and presented descriptively. Multiple logistic regression analysis was applied to assess associations between respondents' background characteristics and care seeking behaviour.</p> <p>Results</p> <p>About half of the respondents (49%) were less than or equal to 19 years of age, and 50% had started or completed secondary school. Fifty-eight percent had been engaged in sex work for less than 1 year. Eighty-six percent of the respondents reported RTI/STI signs or symptoms currently or in the last 3 months but only two-thirds of those with symptoms sought treatment. Source of treatment for the last RTI/STI episode was the drop-in centre (53%) followed by a public hospital (23%), private clinic (12%), private pharmacy (9%), and herbalist (2%). The main barriers to service use were long waiting time, inconvenient location of the clinic, not knowing where to get the services needed, and negative attitudes among healthcare providers. Care seeking behaviour was associated with longer duration of sex work (OR = 2.6, 95%CI 1.52-5.36). Forty-four percent received health information from peer educators, 34% from fellow friends, 26% from a pimp, and 26% had received information from a healthcare provider during the visit.</p> <p>Conclusion</p> <p>There were several barriers to accessing RTI/STI services and they were related to both structural and individual factors. Innovative STI service strategies to inform FSWs about the importance of early diagnosis and treatment should be established. Continuous training for STI service providers focusing on counseling skills and awareness of the sexual health care needs for FSWs is recommended in order to minimize the barriers experienced by FSWs in this particular setting.</p

Tunable hot-carrier photodetection beyond the bandgap spectral limit

The spectral response of common optoelectronic photodetectors is restricted by a cutoff wavelength limit λ that is related to the activation energy (or bandgap) of the semiconductor structure (or material) (Δ) through the relationship λ = hc/Δ. This spectral rule dominates device design and intrinsically limits the long-wavelength response of a semiconductor photodetector. Here, we report a new, long-wavelength photodetection principle based on a hot-cold hole energy transfer mechanism that overcomes this spectral limit. Hot carriers injected into a semiconductor structure interact with cold carriers and excite them to higher energy states. This enables a very long-wavelength infrared response. In our experiments, we observe a response up to 55 μm, which is tunable by varying the degree of hot-hole injection, for a GaAs/AlGaAs sample with Δ = 0.32 eV (equivalent to 3.9 μm in wavelength)

A Novel Adaptive Method for the Analysis of Next-Generation Sequencing Data to Detect Complex Trait Associations with Rare Variants Due to Gene Main Effects and Interactions

There is solid evidence that rare variants contribute to complex disease etiology. Next-generation sequencing technologies make it possible to uncover rare variants within candidate genes, exomes, and genomes. Working in a novel framework, the kernel-based adaptive cluster (KBAC) was developed to perform powerful gene/locus based rare variant association testing. The KBAC combines variant classification and association testing in a coherent framework. Covariates can also be incorporated in the analysis to control for potential confounders including age, sex, and population substructure. To evaluate the power of KBAC: 1) variant data was simulated using rigorous population genetic models for both Europeans and Africans, with parameters estimated from sequence data, and 2) phenotypes were generated using models motivated by complex diseases including breast cancer and Hirschsprung's disease. It is demonstrated that the KBAC has superior power compared to other rare variant analysis methods, such as the combined multivariate and collapsing and weight sum statistic. In the presence of variant misclassification and gene interaction, association testing using KBAC is particularly advantageous. The KBAC method was also applied to test for associations, using sequence data from the Dallas Heart Study, between energy metabolism traits and rare variants in ANGPTL 3,4,5 and 6 genes. A number of novel associations were identified, including the associations of high density lipoprotein and very low density lipoprotein with ANGPTL4. The KBAC method is implemented in a user-friendly R package

X-Ray Repair Cross-Complementing Group 1 (XRCC1) Genetic Polymorphisms and Risk of Childhood Acute Lymphoblastic Leukemia: A Meta-Analysis

Background: Recently, there have been a number of studies on the association between XRCC1 polymorphisms and childhood acute lymphoblastic leukemia (ALL) risk. However, the results of previous reports are inconsistent. Thus, we performed a meta-analysis to clarify the effects of XRCC1 variants on childhood ALL risk. Methods: A meta-analysis was performed to examine the association between XRCC1 polymorphisms (Arg399Gln, Arg194Trp, and Arg280His) and childhood ALL risk. We critically reviewed 7 studies with a total of 880 cases and 1311 controls for Arg399Gln polymorphism, 3 studies with a total of 345 cases and 554 controls for Arg280His polymorphism, and 6 studies with a total of 783 cases and 1180 controls for Arg194Trp polymorphism, respectively. Odds ratio (OR) and its 95% confidence interval (CI) were used. Results: Significant association between XRCC1 Arg399Gln polymorphism and childhood ALL risk was observed in total population analyses (OR additive model = 1.501, 95 % CI 1.112–2.026, P OR = 0.008; OR dominant model = 1.316, 95 % CI = 1.104–1.569, POR = 0.002) and Asian subgroup analyses (ORadditive model = 2.338, 95%CI = 1.254–4.359, POR = 0.008; ORdominant model = 2.108, 95%CI = 1.498–2.967, POR = 0.000). No association was detected in Caucasians, Metizo and mixed populations. Ethnicity was considered as a significant source of heterogeneity in the meta-regression model. For the other two XRCC1 polymorphisms, no association with childhood ALL risk was found

Analysis of Population Structure: A Unifying Framework and Novel Methods Based on Sparse Factor Analysis

We consider the statistical analysis of population structure using genetic data. We show how the two most widely used approaches to modeling population structure, admixture-based models and principal components analysis (PCA), can be viewed within a single unifying framework of matrix factorization. Specifically, they can both be interpreted as approximating an observed genotype matrix by a product of two lower-rank matrices, but with different constraints or prior distributions on these lower-rank matrices. This opens the door to a large range of possible approaches to analyzing population structure, by considering other constraints or priors. In this paper, we introduce one such novel approach, based on sparse factor analysis (SFA). We investigate the effects of the different types of constraint in several real and simulated data sets. We find that SFA produces similar results to admixture-based models when the samples are descended from a few well-differentiated ancestral populations and can recapitulate the results of PCA when the population structure is more “continuous,” as in isolation-by-distance models