14 research outputs found

    Epidemiology of fractures in Armenia: development of a country-specific FRAX model and comparison to its surrogate

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    Summary: Fracture probabilities derived from the surrogate FRAX model for Armenia were compared to those from the model based on regional estimates of the incidence of hip fracture. Disparities between the surrogate and authentic FRAX models indicate the importance of developing country-specific FRAX models. Despite large differences between models, differences in the rank order of fracture probabilities were minimal. Objective: Armenia has relied on a surrogate FRAX model based on the fracture epidemiology of Romania. This paper describes the epidemiology of fragility fractures in Armenia used to create an Armenia-specific FRAX model with an aim of comparing this new model with the surrogate model. Methods: We carried out a population-based study in two regions of Armenia (Ararat and Vayots Dzor representing approximately 11% of the country’s population). We aimed to identify all low-energy fractures: retrospectively from hospital registers in 2011–2012 and prospectively in 2013 with the inclusion of primary care sources. Results: The differences in incidence between the surveys with and without data from primary care suggested that 44% of patients sustaining a hip fracture did not receive specialized medical care. A similar proportion of forearm and humeral fractures did not come to hospital attention (48 and 49%, respectively). Only 57.7% of patients sustaining a hip fracture were hospitalized. In 2013, hip fracture incidence at the age of 50 years or more was 201/100,000 for women and 136/100,000 for men, and age- and sex-specific rates were incorporated into the new “authentic” FRAX model for Armenia. Compared to the surrogate model, the authentic model gave lower 10-year fracture probabilities in men and women aged less than 70 years but substantially higher above this age. Notwithstanding, there were very close correlations in fracture probabilities between the surrogate and authentic models ( >  0.99) so that the revisions had little impact on the rank order of risk. Conclusion: A substantial proportion of major osteoporotic fractures in Armenia do not come to hospital attention. The disparities between surrogate and authentic FRAX models indicate the importance of developing country-specific FRAX models. Despite large differences between models, differences in the rank order of fracture probabilities were minimal

    Genome-Wide Association Study Identifies CDKN1A as a Novel Locus Associated with Muscle Fiber Composition.

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    Muscle fiber composition is associated with physical performance, with endurance athletes having a high proportion of slow-twitch muscle fibers compared to power athletes. Approximately 45% of muscle fiber composition is heritable, however, single nucleotide polymorphisms (SNP) underlying inter-individual differences in muscle fiber types remain largely unknown. Based on three whole genome SNP datasets, we have shown that the rs236448 A allele located near the cyclin-dependent kinase inhibitor 1A (CDKN1A) gene was associated with an increased proportion of slow-twitch muscle fibers in Russian (n = 151; p = 0.039), Finnish (n = 287; p = 0.03), and Japanese (n = 207; p = 0.008) cohorts (meta-analysis: p = 7.9 × 10-5. Furthermore, the frequency of the rs236448 A allele was significantly higher in Russian (p = 0.045) and Japanese (p = 0.038) elite endurance athletes compared to ethnically matched power athletes. On the contrary, the C allele was associated with a greater proportion of fast-twitch muscle fibers and a predisposition to power sports. CDKN1A participates in cell cycle regulation and is suppressed by the miR-208b, which has a prominent role in the activation of the slow myofiber gene program. Bioinformatic analysis revealed that the rs236448 C allele was associated with increased CDKN1A expression in whole blood (p = 8.5 × 10-15) and with greater appendicular lean mass (p = 1.2 × 10-5), whereas the A allele was associated with longer durations of exercise (p = 0.044) reported amongst the UK Biobank cohort. Furthermore, the expression of CDKN1A increased in response to strength (p < 0.0001) or sprint (p = 0.00035) training. Accordingly, we found that CDKN1A expression is significantly (p = 0.002) higher in the m. vastus lateralis of strength athletes compared to endurance athletes and is positively correlated with the percentage of fast-twitch muscle fibers (p = 0.018). In conclusion, our data suggest that the CDKN1A rs236448 SNP may be implicated in the determination of muscle fiber composition and may affect athletic performance

    Equations of two-phase filtration

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    LogLoss-BERAF: An ensemble-based machine learning model for constructing highly accurate diagnostic sets of methylation sites accounting for heterogeneity in prostate cancer.

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    Although modern methods of whole genome DNA methylation analysis have a wide range of applications, they are not suitable for clinical diagnostics due to their high cost and complexity and due to the large amount of sample DNA required for the analysis. Therefore, it is crucial to be able to identify a relatively small number of methylation sites that provide high precision and sensitivity for the diagnosis of pathological states. We propose an algorithm for constructing limited subsamples from high-dimensional data to form diagnostic panels. We have developed a tool that utilizes different methods of selection to find an optimal, minimum necessary combination of factors using cross-entropy loss metrics (LogLoss) to identify a subset of methylation sites. We show that the algorithm can work effectively with different genome methylation patterns using ensemble-based machine learning methods. Algorithm efficiency, precision and robustness were evaluated using five genome-wide DNA methylation datasets (totaling 626 samples), and each dataset was classified into tumor and non-tumor samples. The algorithm produced an AUC of 0.97 (95% CI: 0.94-0.99, 9 sites) for prostate adenocarcinoma and an AUC of 1.0 (from 2 to 6 sites) for urothelial bladder carcinoma, two types of kidney carcinoma and colorectal carcinoma. For prostate adenocarcinoma we showed that identified differential variability methylation patterns distinguish cluster of samples with higher recurrence rate (hazard ratio for recurrence = 0.48, 95% CI: 0.05-0.92; log-rank test, p-value < 0.03). We also identified several clusters of correlated interchangeable methylation sites that can be used for the elaboration of biological interpretation of the resulting models and for further selection of the sites most suitable for designing diagnostic panels. LogLoss-BERAF is implemented as a standalone python code and open-source code is freely available from https://github.com/bioinformatics-IBCH/logloss-beraf along with the models described in this article

    EPIDEMIOLOGICAL STUDY OF LOW ENERGY FRACTURES IN REPUBLIC OF ARMENIA

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    Until present no data was available inArmeniain respect of incidence of low energy fractures that are typical of osteoporotic locations which consequently did not allow to evaluate the scope of this problem across the country.Purpose of the study – to identify the incidence of low energy fractures in proximal femur, in distal forearm, in proximal humerus and in distal tibia across population ofArmenia aged 50 years and older.Materials and methods. An observing population study was performed in two regions of Armenia during 2011-2013 where the frequency of selected locations in cases of moderate trauma was identified. During 2011-2012 the information was collected based on traumatology service records adding in 2013 other sources including primary level of healthcare due to observed infrequent applications for medical help in cases of trauma. Results. In 2013 the incidence of proximal femur fractures in men was reported as 136 cases per 100 000 of population aged 50 years and older, in women – 201 cases per 100 000. At the same time only 57.7% of patients with proximal femur fractures were admitted to hospital. Distal forearm fractures incidence in men and women was observed correspondingly 56/100 000 and 176/100 000 cases, proximal humerus fractures – 39/100 000 and 86/100 000 cases and distal tibia fractures – 39/100 000 and 86/100 000 cases. The predicted annual number of proximal femur fracture in Armenia amounts to 2067 cases, distal forearm fractures – 1205, proximal humerus fractures – 640.Conclusion. Epidemiological data that was collected for the first time on low energy fractures incidence confirmed the acute osteoporosis issue inArmenia and revealed the problems in organization of medical care for the group of senior patients with injuries

    Genome-Wide Association Study Identifies <i>CDKN1A</i> as a Novel Locus Associated with Muscle Fiber Composition

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    Muscle fiber composition is associated with physical performance, with endurance athletes having a high proportion of slow-twitch muscle fibers compared to power athletes. Approximately 45% of muscle fiber composition is heritable, however, single nucleotide polymorphisms (SNP) underlying inter-individual differences in muscle fiber types remain largely unknown. Based on three whole genome SNP datasets, we have shown that the rs236448 A allele located near the cyclin-dependent kinase inhibitor 1A (CDKN1A) gene was associated with an increased proportion of slow-twitch muscle fibers in Russian (n = 151; p = 0.039), Finnish (n = 287; p = 0.03), and Japanese (n = 207; p = 0.008) cohorts (meta-analysis: p = 7.9 × 10−5. Furthermore, the frequency of the rs236448 A allele was significantly higher in Russian (p = 0.045) and Japanese (p = 0.038) elite endurance athletes compared to ethnically matched power athletes. On the contrary, the C allele was associated with a greater proportion of fast-twitch muscle fibers and a predisposition to power sports. CDKN1A participates in cell cycle regulation and is suppressed by the miR-208b, which has a prominent role in the activation of the slow myofiber gene program. Bioinformatic analysis revealed that the rs236448 C allele was associated with increased CDKN1A expression in whole blood (p = 8.5 × 10−15) and with greater appendicular lean mass (p = 1.2 × 10−5), whereas the A allele was associated with longer durations of exercise (p = 0.044) reported amongst the UK Biobank cohort. Furthermore, the expression of CDKN1A increased in response to strength (p p = 0.00035) training. Accordingly, we found that CDKN1A expression is significantly (p = 0.002) higher in the m. vastus lateralis of strength athletes compared to endurance athletes and is positively correlated with the percentage of fast-twitch muscle fibers (p = 0.018). In conclusion, our data suggest that the CDKN1A rs236448 SNP may be implicated in the determination of muscle fiber composition and may affect athletic performance

    Between Lake Baikal and the Baltic Sea: genomic history of the gateway to Europe

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    Abstract Background The history of human populations occupying the plains and mountain ridges separating Europe from Asia has been eventful, as these natural obstacles were crossed westward by multiple waves of Turkic and Uralic-speaking migrants as well as eastward by Europeans. Unfortunately, the material records of history of this region are not dense enough to reconstruct details of population history. These considerations stimulate growing interest to obtain a genetic picture of the demographic history of migrations and admixture in Northern Eurasia. Results We genotyped and analyzed 1076 individuals from 30 populations with geographical coverage spanning from Baltic Sea to Baikal Lake. Our dense sampling allowed us to describe in detail the population structure, provide insight into genomic history of numerous European and Asian populations, and significantly increase quantity of genetic data available for modern populations in region of North Eurasia. Our study doubles the amount of genome-wide profiles available for this region. We detected unusually high amount of shared identical-by-descent (IBD) genomic segments between several Siberian populations, such as Khanty and Ket, providing evidence of genetic relatedness across vast geographic distances and between speakers of different language families. Additionally, we observed excessive IBD sharing between Khanty and Bashkir, a group of Turkic speakers from Southern Urals region. While adding some weight to the “Finno-Ugric” origin of Bashkir, our studies highlighted that the Bashkir genepool lacks the main “core”, being a multi-layered amalgamation of Turkic, Ugric, Finnish and Indo-European contributions, which points at intricacy of genetic interface between Turkic and Uralic populations. Comparison of the genetic structure of Siberian ethnicities and the geography of the region they inhabit point at existence of the “Great Siberian Vortex” directing genetic exchanges in populations across the Siberian part of Asia. Slavic speakers of Eastern Europe are, in general, very similar in their genetic composition. Ukrainians, Belarusians and Russians have almost identical proportions of Caucasus and Northern European components and have virtually no Asian influence. We capitalized on wide geographic span of our sampling to address intriguing question about the place of origin of Russian Starovers, an enigmatic Eastern Orthodox Old Believers religious group relocated to Siberia in seventeenth century. A comparative reAdmix analysis, complemented by IBD sharing, placed their roots in the region of the Northern European Plain, occupied by North Russians and Finno-Ugric Komi and Karelian people. Russians from Novosibirsk and Russian Starover exhibit ancestral proportions close to that of European Eastern Slavs, however, they also include between five to 10 % of Central Siberian ancestry, not present at this level in their European counterparts. Conclusions Our project has patched the hole in the genetic map of Eurasia: we demonstrated complexity of genetic structure of Northern Eurasians, existence of East-West and North-South genetic gradients, and assessed different inputs of ancient populations into modern populations
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