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Dr Zhanna Balkhiiarova


Research Fellow in Statistical Multi-Omics

Academic and research departments

School of Biosciences and Medicine.

Publications

ZHANNA BALKHIIAROVA, Arie Nouwen, Sonya S. Deschênes, Zhanna Balkhiyarova, Juan R Albertorio-Díaz, INGA PROKOPENKO, Norbert Schmitz (2021)Measurement invariance testing of the patient health questionnaire-9 (PHQ-9) across people with and without diabetes mellitus from the NHANES, EMHS and UK Biobank datasets, In: Journal of Affective Disorders292pp. 311-318 Elsevier B.V

Background The prevalence of depression is higher among those with diabetes than in the general population. The Patient Health Questionnaire (PHQ-9) is commonly used to assess depression in people with diabetes, but measurement invariance of the PHQ-9 across groups of people with and without diabetes has not yet been investigated. Methods Data from three independent cohorts from the USA (n=1,886 with diabetes, n=4,153 without diabetes), Quebec, Canada (n= 800 with diabetes, n= 2,411 without diabetes), and the UK (n=4,981 with diabetes, n=145,570 without diabetes), were used to examine measurement invariance between adults with and without diabetes. A series of multiple group confirmatory factor analyses were performed, with increasingly stringent model constraints applied to assess configural, equal thresholds, and equal thresholds and loadings invariance, respectively. One-factor and two-factor (somatic and cognitive-affective items) models were examined. Results Results demonstrated that the most stringent models, testing equal loadings and thresholds, had satisfactory model fit in the three cohorts for one-factor models (RMSEA = .063 or below and CFI = .978 or above) and two-factor models (RMSEA = .042 or below and CFI = .989 or above). Limitations Data were from Western countries only and we could not distinguish between type of diabetes. Conclusions Results provide support for measurement invariance between groups of people with and without diabetes, using either a one-factor or a two-factor model. While the two-factor solution has a slightly better fit, the one-factor solution is more parsimonious. Depending on research or clinical needs, both factor structures can be used.

ZHANNA BALKHIIAROVA, Yanina R Timasheva, Zhanna Balkhiyarova, Timur R Nasibullin, Diana Sh Avzaletdinova, Tatiana V Morugova, Olga E Mustafina, INGA PROKOPENKO (2019)Multilocus associations of inflammatory genes with the risk of type 1 diabetes, In: Gene707pp. 1-8 Elsevier B.V

Background Genome-wide association studies have captured a large proportion of genetic variation related to type 1 diabetes mellitus (T1D). However, most of these studies are performed in populations of European ancestry and therefore the disease risk estimations can be inaccurate when extrapolated to other world populations. Methods We conducted a case-control study in 1866 individuals from the three major populations of the Republic of Bashkortostan (Russians, Tatars, and Bashkirs) in Russian Federation, using single-locus and multilocus approach to identify genetic predictors of T1D. Results We found that LTA rs909253 and TNF rs1800629 polymorphisms were associated with T1D in the group of Tatars. Meta-analysis of the association study results in the three ethnic groups has confirmed the association between the T1D risk and LTA rs909253 genetic variant. LTA rs909253 and TNF rs1800629 loci were also featured in combinations most significantly associated with T1D. Conclusion Our findings suggest that LTA rs909253 and TNF rs1800629 polymorphisms are associated with the risk of T1D both independently and in combination with polymorphic markers in other inflammatory genes, and the analysis of multi-allelic combinations provides valuable insight in the study of polygenic traits.

Justiina Ronkainen, Rozenn Nedelec, Angelica Atehortua, ZHANNA BALKHIIAROVA, Anna Cascarano, Vien Ngoc Dang, Ahmed Elhakeem, Esther van Enckevort, Ana Goncalves Soares, Sido Haakma, Miia Halonen, Katharina F Heil, Anni Heiskala, Eleanor Hyde, B Jacquemin, Elina Keikkala, Jules Kerckhoffs, Anton Klåvus, Joanna A Kopinska, Irina Motoc, Johanna Lepeule, Francesca Marazzi, Mari Näätänen, Anton Ribbenstedt, Amanda Rundblad, Otto Savolainen, Valentina Simonetti, Nina de Toro Eadie, Evangelia Tzala, ANNA ULRICH, Thomas Wright, Iman Zarei, Enrico d’Amico, Federico Belotti, Carl Brunius, Christopher Castleton, Marie-Aline Charles, Romy Gaillard, Kati Hanhineva, Gerard Hoek, Kirsten B Holven, Vincent W.V Jaddoe, MARIKA KAAKINEN, Eero Kajantie, M Kavousi, Timo A. Lakka, Jason Matthews, Andrea Piano Mortari, Marja Vääräsmäki, Trudy Voortman, C Webster, Marie Zins, Vincenzo Atella, Maria Bulgheroni, M Chadeau-Hyam, Gabriella Conti, Jayne Evans, Janine F. Felix, Barbara Heude, Marjo-Riitta Jarvelin, Marjukka Kolehmainen, Rikard Landberg, Karim Lekadir, Stefano Parusso, INGA PROKOPENKO, Susanne R de Rooij, Tessa Roseboom, Morris Swertz, Nicholas J. Timpson, Stine M Ulven, Roel Vermeulen, Teija Juola, Sylvain Sebert (2022)LongITools: Dynamic longitudinal exposome trajectories in cardiovascular and metabolic noncommunicable diseases, In: Environmental epidemiology6(1)e184

The current epidemics of cardiovascular and metabolic noncommunicable diseases have emerged alongside dramatic modifications in lifestyle and living environments. These correspond to changes in our “modern” postwar societies globally characterized by rural-to-urban migration, modernization of agricultural practices, and transportation, climate change, and aging. Evidence suggests that these changes are related to each other, although the social and biological mechanisms as well as their interactions have yet to be uncovered. LongITools, as one of the 9 projects included in the European Human Exposome Network, will tackle this environmental health equation linking multidimensional environmental exposures to the occurrence of cardiovascular and metabolic noncommunicable diseases.

Zhanna Balkhiyarova, Rosa Luciano, Marika Kaakinen, Anna Ulrich, Aleksey Shmeliov, Marzia Bianchi, Laura Chioma, Bruno Dallapiccola, Inga Prokopenko, Melania Manco (2021)Relationship between glucose homeostasis and obesity in early life—a study of Italian children and adolescents, In: Human Molecular Geneticsddab287 Oxford University Press

Epidemic obesity is the most important risk factor for prediabetes and type 2 diabetes (T2D) in youth as it is in adults. Obesity shares pathophysiological mechanisms with T2D and is likely to share part of the genetic background. We aimed to test if weighted genetic risk scores (GRSs) for T2D, fasting glucose (FG) and fasting insulin (FI) predict glycaemic traits and if there is a causal relationship between obesity and impaired glucose metabolism in children and adolescents. Genotyping of 42 SNPs established by genome-wide association studies for T2D, FG and FI was performed in 1660 Italian youths aged between 2 and 19 years. We defined GRS for T2D, FG and FI and tested their effects on glycaemic traits, including FG, FI, indices of insulin resistance/beta cell function and body mass index (BMI). We evaluated causal relationships between obesity and FG/FI using one-sample Mendelian randomization analyses in both directions. GRS-FG was associated with FG (beta = 0.075 mmol/l, SE = 0.011, P = 1.58 × 10 −11) and beta cell function (beta = −0.041, SE = 0.0090 P = 5.13 × 10 −6). GRS-T2D also demonstrated an association with beta cell function (beta = −0.020, SE = 0.021 P = 0.030). We detected a causal effect of increased BMI on levels of FI in Italian youths (beta = 0.31 ln (pmol/l), 95%CI [0.078, 0.54], P = 0.0085), while there was no effect of FG/FI levels on BMI. Our results demonstrate that the glycaemic and T2D risk genetic variants contribute to higher FG and FI levels and decreased beta cell function in children and adolescents. The causal effects of adiposity on increased insulin resistance are detectable from childhood age.