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2 Publications visible to you, out of a total of 2

Abstract (Expand)

The molecular events underlying the development, manifestation, and course of schizophrenia, bipolar disorder, and major depressive disorder span from embryonic life to advanced age. However, little is known about the early dynamics of gene expression in these disorders due to their relatively late manifestation. To address this, we conducted a secondary analysis of post-mortem prefrontal cortex datasets using bioinformatics and machine learning techniques to identify differentially expressed gene modules associated with aging and the diseases, determine their time-perturbation points, and assess enrichment with expression quantitative trait loci (eQTL) genes. Our findings revealed early, mid, and late deregulation of expression of functional gene modules involved in neurodevelopment, plasticity, homeostasis, and immune response. This supports the hypothesis that multiple hits throughout life contribute to disease manifestation rather than a single early-life event. Moreover, the time-perturbed functional gene modules were associated with genetic loci affecting gene expression, highlighting the role of genetic factors in gene expression dynamics and the development of disease phenotypes. Our findings emphasize the importance of investigating time-dependent perturbations in gene expression before the age of onset in elucidating the molecular mechanisms of psychiatric disorders.

Authors: Arsen Arakelyan, Susanna Avagyan, Aleksey Kurnosov, Tigran Mkrtchyan, Gohar Mkrtchyan, Roksana Zakharyan, Karine R. Mayilyan, Hans Binder

Date Published: 17th Feb 2024

Publication Type: Journal

Abstract (Expand)

The novel SARS-CoV-2 coronavirus infection has become a global health concern, causing the COVID-19 pandemic. The disease symptoms and outcomes depend on the host immunity, in which the human leukocyte antigen (HLA) molecules play a distinct role. The HLA alleles have an inter-population variability, and understanding their link to the COVID-19 in an ethnically distinct population may contribute to personalized medicine. The present study aimed at detecting associations between common HLA alleles and COVID-19 susceptibility and severity in Armenians. In 299 COVID-19 patients (75 asymptomatic, 102 mild/moderate, 122 severe), the association between disease severity and classic HLA-I and II loci was examined. We found that the advanced age, male sex of patients, and sex and age interaction significantly contributed to the severity of the disease. We observed that an age-dependent effect of HLA-B*51:01 carriage [odds ratio (OR)=0.48 (0.28-0.80), Pbonf <0.036] is protective against severe COVID-19. Contrary, the HLA-C*04:01 allele, in a dose-dependent manner, was associated with a significant increase in the disease severity [OR (95% CI) =1.73 (1.20-2.49), Pbonf <0.021] and an advancing age (P<0.013). The link between HLA-C*04:01 and age was secondary to a stronger association between HLA-C*04:01 and disease severity. However, HLA-C*04:01 exerted a sex-dependent differential distribution between clinical subgroups [females: P<0.0012; males: P=0.48]. The comparison of HLA-C*04:01 frequency between subgroups and 2,781 Armenian controls revealed a significant incidence of HLA-C*04:01 deficiency in asymptomatic COVID-19. HLA-C*04:01 homozygous genotype in patients blueprinted a decrease in heterozygosity of HLA-B and HLA class-I loci. In HLA-C*04:01 carriers, these changes translated to the SARS-CoV-2 peptide presentation predicted inefficacy by HLA-C and HLA class-I molecules, simultaneously enhancing the appropriate HLA-B potency. In patients with clinical manifestation, due to the high prevalence of HLA-C*04:01, these effects provided a decrease of the HLA class-I heterozygosity and an ability to recognize SARS-CoV-2 peptides. Based on our observations, we developed a prediction model involving demographic variables and HLA-C*04:01 allele for the identification of potential cases with the risk of hospitalization (the area under the curve (AUC) = 86.2%) or severe COVID-19 (AUC =71%).

Authors: Anahit Hovhannisyan, Vergine Madelian, Sevak Avagyan, Mihran Nazaretyan, Armine Hyussyan, Alina Sirunyan, Rubina Arakelyan, Zorayr Manukyan, Levon Yepiskoposyan, Karine R. Mayilyan, Frieda Jordan

Date Published: 3rd Feb 2022

Publication Type: Journal

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