Yanina Timasheva

Dr. Yanina Timasheva

Institute of Biochemistry and Genetics - Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Bashkortostan, Russia
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Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 December 2007 in Biochemical Genetics
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Yanina TimashevaYanina Timasheva
Yanina Timasheva
TNT. R. Nasibullin
T. R. Nasibullin
AZA. N. Zakirova
A. N. Zakirova
OMO. E. Mustafina
O. E. Mustafina

12 December 2015 in Molecular Biology Reports
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TNTimur R. Nasibullin
Timur R. Nasibullin
Yanina TimashevaYanina Timasheva
Yanina Timasheva
RSRegina I. Sadikova
Regina I. Sadikova
ITIlsiyar A. Tuktarova
Ilsiyar A. Tuktarova
VEVera Viktorovna Erdman
Vera Viktorovna Erdman
OMOlga E. Mustafina
Olga E. Mustafina

28 October 2015 in Cerebrovascular Diseases Extra
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Yanina TimashevaYanina Timasheva
Yanina Timasheva
TNTimur R. Nasibullin
Timur R. Nasibullin
OMOlga E. Mustafina
Olga E. Mustafina
Hypertension is the major risk factor for stroke, and genetic factors contribute to its development. Inflammation has been hypothesized to be the key link between blood pressure elevation and stroke. We performed an analysis of the association between inflammatory mediator gene polymorphisms and the incidence of stroke in patients with essential hypertension (EH). The study group consisted of 625 individuals (296 patients with noncomplicated EH, 71 hypertensive patients with ischemic stroke, and 258 control subjects). Both patients and controls were ethnic Tatars originating from the Republic of Bashkortostan (Russian Federation). The analysis has shown that the risk of ischemic stroke was associated with the CXCR2 rs1126579 polymorphism. Our results indicate that among patients with EH, the heterozygous genotype carriers had a higher risk of stroke (OR = 1.72, 95% CI 1.01-2.92), whereas the CXCR2*C/C genotype was protective against stroke (OR = 0.32, 95% CI 0.12-0.83). As shown by the gene-gene interaction analysis, the CXCR2 rs1126579 polymorphism was also present in all genotype/allele combinations associated with the risk of stroke. Genetic patterns associated with stroke also included polymorphisms in the CCL2, CCL18, CX3CR1, CCR5, and CXCL8(IL8) genes, although no association between these loci and stroke was detected by individual analysis.

2 August 2021 in Problems of Endocrinology
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Yanina TimashevaYanina Timasheva
Yanina Timasheva
Zhanna BalkhiyarovaZhanna Balkhiyarova
Zhanna Balkhiyarova
OKOlga Kochetova
Olga Kochetova
Obesity affects over 700 million people worldwide and its prevalence keeps growing steadily. The problem is particularly relevant due to the increased risk of COVID-19 complications and mortality in obese patients. Obesity prevalence increase is often associated with the influence of environmental and behavioural factors, leading to stigmatization of people with obesity due to beliefs that their problems are caused by poor lifestyle choices. However, hereditary predisposition to obesity has been established, likely polygenic in nature. Morbid obesity can result from rare mutations having a significant effect on energy metabolism and fat deposition, but the majority of patients does not present with monogenic forms. Microbiome low diversity significantly correlates with metabolic disorders (inflammation, insulin resistance), and the success of weight loss (bariatric) surgery. However, data on the long-term consequences of bariatric surgery and changes in the microbiome composition and genetic diversity before and after surgery are currently lacking. In this review, we summarize the results of studies of the genetic characteristics of obesity patients, molecular mechanisms of obesity, contributing to the unfavourable course of coronavirus infection, and the evolution of their microbiome during bariatric surgery, elucidating the mechanisms of disease development and creating opportunities to identify potential new treatment targets and design effective personalized approaches for the diagnosis, management, and prevention of obesity.

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Yanina TimashevaYanina Timasheva
Yanina Timasheva
Zhanna BalkhiyarovaZhanna Balkhiyarova
Zhanna Balkhiyarova
DADiana Avzaletdinova
Diana Avzaletdinova
GKGulnaz Faritovna Korytina
Gulnaz Faritovna Korytina
TMTatiana V. Morugova
Tatiana V. Morugova
OKOlga Kochetova
Olga Kochetova
We tested associations between 13 established genetic variants and type 2 diabetes (T2D) in 1371 study participants from the Volga-Ural region of the Eurasian continent, and evaluated the predictive ability of the model containing polygenic scores for the variants associated with T2D in our dataset, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis, we found associations with T2D for the CCL20 rs6749704 (OR = 1.68, PFDR = 3.40 × 10−5), CCR5 rs333 (OR = 1.99, PFDR = 0.033), ADIPOQ rs17366743 (OR = 3.17, PFDR = 2.64 × 10−4), TCF7L2 rs114758349 (OR = 1.77, PFDR = 9.37 × 10−5), and CCL2 rs1024611 (OR = 1.38, PFDR = 0.033) polymorphisms. We showed that the most informative prognostic model included weighted polygenic scores for these five loci, and non-genetic factors such as age and sex (AUC 85.8%, 95%CI 83.7–87.8%). Compared to the model containing only non-genetic parameters, adding the polygenic score for the five T2D-associated loci showed improved net reclassification (NRI = 37.62%, 1.39 × 10−6). Inclusion of all 13 tested SNPs to the model with age and sex did not improve the predictive ability compared to the model containing five T2D-associated variants (NRI = −17.86, p = 0.093). The five variants associated with T2D in people from the Volga-Ural region are linked to inflammation (CCR5, CCL2, CCL20) and glucose metabolism regulation (TCF7L, ADIPOQ2). Further studies in independent groups of T2D patients should validate the prognostic value of the model and elucidate the molecular mechanisms of the disease development.

1 November 2013 in Placenta
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Yanina TimashevaYanina Timasheva
Yanina Timasheva
MPM. Putku
M. Putku
RKR. Kivi
R. Kivi
VKViktor Kožich
Viktor Kožich
JMJaan Männik
Jaan Männik
MLM. Laan
M. Laan
Given the physiological role of placental growth hormone (PGH) during intrauterine development and growth, genetic variation in the coding Growth hormone 2 (GH2) gene may modulate developmental programming of adult stature. Two major GH2 variants were described worldwide, determined by single polymorphism (rs2006123; c.171 + 50C > A). We sought to study whether GH2 variants may contribute to adult anthropometric measurements. Genotyping of GH2 SNP rs2006123 by RFLP, testing its genetic association with adult height and Body Mass Index (BMI) by linear regression analysis, and combining the results of three individual study samples in meta-analysis. HYPEST (Estonia), n = 1464 (506 men/958 women), CADCZ (Czech), n = 871 (518/353); UFA (Bashkortostan), n = 954 (655/299); meta-analysis, n = 3289 (1679/1610). Meta-analysis across HYPEST, CADCZ and UFA samples (n = 3289) resulted in significant association of GH2 rs2006123 with height (recessive model: AA-homozygote effect: beta (SE) = 1.26 (0.46), P = 5.90 × 10⁻³; additive model: A-allele effect: beta (SE) = 0.45 (0.18), P = 1.40 × 10⁻²). Among men (n = 1679), the association of the A-allele with taller stature remained significant after multiple-testing correction (additive effect: beta = 0.86 (0.28), P = 1.83 × 10⁻³). No association was detected with BMI. Notably, rs2006123 was in strong LD (r² ≥ 0.87) with SNPs significantly associated with height (rs2665838, rs7209435, rs11658329) and mapped near GH2 in three independent meta-analyses of GWA studies. This is the first study demonstrating a link between a placental gene variant and programming of growth potential in adulthood. The detected association between PGH encoding GH2 and adult height promotes further research on the role of placental genes in prenatal programming of human metabolism.