Genetic basis of depressive disorders

Давыдова, Ю. Д.; Enikeeva, R. F.; Казанцева, А.; Мустафин, Р. Н.; Романова, А. Р.; Malykh, Sergey; Khusnutdinova, Elza

doi:10.18699/vj19.515

Cited by 8 publications

(5 citation statements)

References 59 publications

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“…Для создания модели достаточно два агрессора на 12-15 животных. Конфликтную ситуацию следует создавать несколько раз (2)(3)(4)(5)(6). Одной из модификаций является модель сенсорного контакта.…”

Section: способы моделирования депрессии у грызуновunclassified

“…Описано большое количество нейробиологических процессов, которые могут лежать в основе различных типов депрессии. Установлено и во многом изучено влияние генетических факторов на развитие заболевания [4]. Описана значительная роль травматических стрессовых событий пренатального и раннего постнатального онтогенеза при развитии депрессии.…”

Section: Introductionunclassified

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Current methods of modeling depression in animals and approaches to the study of their efficiency in biomedical research (review of the problem)

Gromova,

Popova,

Pavlova

et al. 2023

vmirvz

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Depressive disorders are one of the leading problems of modern health care. Their prevalence in the world ranges from 4.4 to 20 % of the population, and in Russia the incidence of depression reaches 20 %. The study of depressive disorders is relevant not only from the point of view of psychiatry and behavioral therapy, but also occupies a leading place in neurological practice, since more than a quarter of the population with chronic neurological diseases suffer from depression. Currently, most basic biomedical research on depressive disorders is carried out using laboratory animals. However, the protocols for experimental modeling and analysis of behavioral patterns are very diverse, which creates certain difficulties in planning research. This review is aimed at describing, analyzing, comparing and systematizing possible approaches to creating experimental models of depression in animals, and also contains criteria for model validation and a description of behavioral tests to assess anxiety-depressive disorders.

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Section: способы моделирования депрессии у грызуновunclassified

Section: Introductionunclassified

Current methods of modeling depression in animals and approaches to the study of their efficiency in biomedical research (review of the problem)

Gromova,

Popova,

Pavlova

et al. 2023

vmirvz

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“…Multiple efforts were made to unravel the hypothesis-driven [3][4][5] and/or hypothesisfree approaches [6][7][8][9][10][11] to dissect a genetic cause of depression. Existing molecular mechanisms underlying depressive pathology are based on the impaired neurotransmitter signaling [12], hypothalamic-pituitary-adrenal (HPA) axis [5], oxytocin and arginine vasopressin systems [4,13,14], inflammatory response [3,15], telomere length-associated molecular pathways [16,17], nucleotide changes in target mRNA-miRNA binding sites [18,19], etc. Genome-wide association studies (GWAS) of depression and their meta-analyses implementing a hypothesis-free approach identified multiple genetic loci [7][8][9]11,[20][21][22].…”

Section: Introductionmentioning

confidence: 99%

A Combined Effect of Polygenic Scores and Environmental Factors on Individual Differences in Depression Level

Казанцева¹,

Davydova²,

Enikeeva³

et al. 2023

Genes

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The risk of depression could be evaluated through its multifactorial nature using the polygenic score (PGS) approach. Assuming a “clinical continuum” hypothesis of mental diseases, a preliminary assessment of individuals with elevated risk for developing depression in a non-clinical group is of high relevance. In turn, epidemiological studies suggest including social/lifestyle factors together with PGS to address the “missing heritability” problem. We designed regression models, which included PGS using 27 SNPs and social/lifestyle factors to explain individual differences in depression levels in high-education students from the Volga–Ural region (VUR) of Eurasia. Since issues related to population stratification in PGS scores may lead to imprecise variant effect estimates, we aimed to examine a sensitivity of PGS calculated on summary statistics of depression and neuroticism GWAS from Western Europeans to assess individual proneness to depression levels in the examined sample of Eastern Europeans. A depression score was assessed using the revised version of the Beck Depression Inventory (BDI) in 1065 young adults (age 18–25 years, 79% women, Eastern European ancestry). The models based on weighted PGS demonstrated higher sensitivity to evaluate depression level in the full dataset, explaining up to 2.4% of the variance (p = 3.42 × 10−7); the addition of social parameters enhanced the strength of the model (adjusted r2 = 15%, p < 2.2 × 10−16). A higher effect was observed in models based on weighted PGS in the women group, explaining up to 3.9% (p = 6.03 × 10−9) of variance in depression level assuming a combined SNPs effect and 17% (p < 2.2 × 10−16)—with the addition of social factors in the model. We failed to estimate BDI-measured depression based on summary statistics from Western Europeans GWAS of clinical depression. Although regression models based on PGS from neuroticism (depression-related trait) GWAS in Europeans were associated with a depression level in our sample (adjusted r2 = 0.43%, p = 0.019—for unweighted model), the effect was mainly attributed to the inclusion of social/lifestyle factors as predictors in these models (adjusted r2 = 15%, p < 2.2 × 10−16—for unweighted model). In conclusion, constructed PGS models contribute to a proportion of interindividual variability in BDI-measured depression in high-education students, especially women, from the VUR of Eurasia. External factors, including the specificity of rearing in childhood, used as predictors, improve the predictive ability of these models. Implementation of ethnicity-specific effect estimates in such modeling is important for individual risk assessment.

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“…Together with a traditional approach, the use of bioinformatic pipelines to estimate telomere length under whole-genome sequencing (TelSeq) revealed that shortening of telomeres in depressive disorders was associated with adverse environmental conditions [ 1 ]. It is known that adverse stress conditions at an early age cause a pleiotropic behavioral, physiological, and epigenetic effect on various systems of the body [ 13 ] owing to the changes in the stress response of the hypothalamic-pituitary-adrenal (HPA) system, which, in turn, can result in impaired mental health disorders [ 14 , 15 ]. Environmental factors affecting telomere length include age-dependent decrease in RTL [ 8 ], specificity of child–parent relations [ 16 ], adverse traumatic events in childhood [ 15 ], stressful life effects [ 17 ], environmental influence [ 18 ], and the level of family income [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

Individual Differences in Relative Telomere Length in Mentally Healthy Subjects: The Effect of TERT Gene Polymorphism and Urban Residency

Казанцева

Davydova²,

Enikeeva³

et al. 2022

Russ J Genet

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The changes in the telomere length caused by the terminal underreplication in the existing literature are related to depressive disorders. However, the use of the telomere length as a biomarker of depressive states is ambiguous, which is due to the effect of various environmental factors on both the psychoemotional state and cellular aging of an organism. In order to identify the possible use of the relative telomere length (RTL) measured in peripheral blood leukocytes as a biomarker of enhanced liability to depression prior to the clinical symptoms, as well as to determine the link between telomere length, sociodemographic factors, allelic variants of the genes involved in the regulation of telomere elongation, and depression level, the association analysis of reverse transcriptase ( TERT rs7726159), telomerase RNA component ( TERC rs1317082), and the CST complex encoding protein ( OBFC1 rs2487999) gene polymorphisms was performed with RTL and depression level in mentally healthy individuals ( N = 1065) aged 18–25 years. Together with genetic variants, the examined regression models included various sociodemographic parameters as predictors. As a result of statistical analysis, we failed to observe the association between RTL and individual differences in depression level in the studied sample. Nevertheless, multiple regression analysis allowed us to construct a statistically significant model of individual variance in RTL ( P = 4.3е–4; r 2 = 0.018), which included rs7726159 in the TERT gene ( P = 0.020; β = 0.078) and such environmental predictors as age ( P = 0.001; β = –0.027) and place of residence in childhood (urban/rural area) ( P = 0.048; β = 0.063). The data obtained confirm the involvement of TERT gene variants and age in telomere length in mentally healthy individuals aged 18–25 years and indicate a negative effect of urban residency on telomere length shortening, which reflects the cellular aging of an organism.

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Genetic basis of depressive disorders

Cited by 8 publications

References 59 publications

Current methods of modeling depression in animals and approaches to the study of their efficiency in biomedical research (review of the problem)

Current methods of modeling depression in animals and approaches to the study of their efficiency in biomedical research (review of the problem)

A Combined Effect of Polygenic Scores and Environmental Factors on Individual Differences in Depression Level

Individual Differences in Relative Telomere Length in Mentally Healthy Subjects: The Effect of TERT Gene Polymorphism and Urban Residency

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