Spondyloarthritis comprises a group of inflammatory diseases of the joints and spine, with various clinical manifestations. The group includes ankylosing spondylitis, reactive arthritis, psoriatic arthritis, arthritis associated with inflammatory bowel disease, and undifferentiated spondyloarthritis. The exact etiology and pathogenesis of spondyloarthritis are still unknown, but five hypotheses explaining the pathogenesis exist. These hypotheses suggest that spondyloarthritis is caused by arthritogenic peptides, an unfolded protein response, HLA-B*27 homodimer formation, malfunctioning endoplasmic reticulum aminopeptidases, and, last but not least, gut inflammation and dysbiosis. Here we discuss the five hypotheses and the evidence supporting each. In all of these hypotheses, HLA-B*27 plays a central role. It is likely that a combination of these hypotheses, with HLA-B*27 taking center stage, will eventually explain the development of spondyloarthritis in predisposed individuals.

Liver fibrosis, a consequence of chronic liver injury, represents a major global health burden and is the leading cause of liver failure, morbidity, and mortality. The pathological hallmark of this condition is excessive extracellular matrix deposition, driven primarily by integrin-mediated mechanotransduction. Integrins, transmembrane heterodimeric proteins that serve as primary ECM receptors, orchestrate complex mechanosignaling networks that regulate the activation, differentiation, and proliferation of hepatic stellate cells and other ECM-secreting myofibroblasts. These mechanical signals create self-reinforcing feedback loops that perpetuate the fibrotic response. Recent advances have provided insight into the roles of specific integrin subtypes in liver fibrosis and revealed their regulation of key downstream effectors—including transforming growth factor beta, focal adhesion kinase, RhoA/Rho-associated, coiled-coil containing protein kinase, and the mechanosensitive Hippo pathway. Understanding these mechanotransduction networks has opened new therapeutic possibilities through pharmacological manipulation of integrin-dependent signaling.

Esophageal cancer stands as the eighth most prevalent cancer globally and the sixth most prevalent in Kazakhstan, with esophageal squamous cell carcinoma (ESCC) as its primary histological subtype, often diagnosed in advanced stages. This project aimed to unveil the genetic underpinnings of ESCC by examining differentially expressed genes (DEGs) via whole-transcriptome sequencing of Kazakhstani patients. Tissue samples from 22 individuals undergoing Ivor-Lewis esophagectomy at the Oncology Center in Astana were collected. Utilizing STAR software and DESeq2 package, DEGs were mapped and defined, followed by functional analysis using various R packages. The study encompassed 13 males and 9 females, averaging 65.72 ± 8.26 years old, with 86% diagnosed at advanced stages T3-T4. Analysis of tumor and normal esophageal tissues unveiled 6689 DEGs, including 2056 upregulated and 4633 downregulated genes (adjusted p-value <0.05). Additionally, 42 up-regulated and 2 down-regulated KEGG pathways were identified (p-value <0.05). The top 300 DEGs were mapped to a protein-protein interaction (PPI) network, and functional enrichment analysis revealed three modules comprising closely connected genes. Within our patient cohort, ESCC with moderate dysplasia emerged as the most prevalent histologic subtype, associated with poor prognosis. High-throughput sequencing techniques facilitate the identification of molecular pathways implicated in esophageal carcinogenesis, potentially revolutionizing diagnosis and treatment strategies. This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Program targeted funding BR18574184 and grant AP09058660), and Nazarbayev University funding CRP grant 021220CRP2222.

Background/Objectives: Alzheimer’s disease (AD) has a substantial genetic component, yet Central Asian populations remain markedly underrepresented in genomic studies of the disease. Methods: to address this gap, we generated array-based genotype data using an immune-focused genotyping platform from a Kazakh AD case–control cohort and performed an exploratory association analysis. Following quality control, 180 individuals of Kazakh ancestry, including 92 individuals with AD and 88 cognitively normal controls, were analyzed. Population structure was assessed using principal component analysis, and association testing was performed using covariate-adjusted logistic regression under an additive model (primary analysis), with case–control tests under several genetic models as secondary analyses. Results: no variant reached study-wide significance; however, several exploratory association signals (p < 1 × 10⁻⁴) were identified, including variants on chromosome 9p24 and in ADARB2, MAST4, and ADAM23, which remained nominally associated after adjustment for sex, age, and principal components. In addition, APOE ε4 carrier status was evaluated in cases and controls. The proportion of APOE ε4 carriers was numerically higher among individuals with AD than among controls (40.7% vs. 26.6%), although the difference did not reach statistical significance (p = 0.074). These findings should be considered hypothesis-generating and require replication in larger independent cohorts. Conclusions: this study provides one of the first immune-focused array-based genotype datasets for AD in a Central Asian population. The publicly available genotype data and association results provide a foundation for future replication, meta-analysis, and comparative population-genetic studies of AD across diverse ancestry groups.