Aygerim Serikzhan

Ms. Aygerim Serikzhan

orcid

Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

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

Representative Publications

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23 October 2025 in Scientific Data
Verified
Journal Article
Open access
PDF file
ASAygerim Serikzhan
Aygerim Serikzhan
ADAsset Daniyarov
Asset Daniyarov
AMAskhat Molkenov
Askhat Molkenov
AAAinur Akhmetova
Ainur Akhmetova
ZAZhannur Abilova
Zhannur Abilova
UKUlykbek Kairov
Ulykbek Kairov
Genomic studies on Central Asian populations are still limited, and this study presents the first comprehensive, high-quality genotyping dataset for 224 healthy individuals of Kazakh origin. The data were generated using the Illumina Infinium SNP Genotyping Array GSA MG v2, covering 665,608 SNPs, with 523,630 SNPs retained after quality control. This dataset serves as a valuable reference for comparative studies focused on human genomics, supporting research in population clustering, ethnicity validation, and diverse biomedical investigations on Kazakh individuals. This resource marks a significant contribution to genomic research on individuals from underrepresented region of Central Asia.

10 September 2026 in BMC Bioinformatics
Verified
Journal Article
Open access
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Ruslan KalendarRuslan Kalendar
Ruslan Kalendar
ADAsset Daniyarov
Asset Daniyarov
ASAygerim Serikzhan
Aygerim Serikzhan
UKUlykbek Kairov
Ulykbek Kairov
DBDiana Basharova
Diana Basharova
EZElena Zholdybayeva
Elena Zholdybayeva
Ultra-multiplex PCR has become essential for targeted amplicon sequencing in molecular biology and clinical genetics. We implemented PCRpanel, a command-li

25 October 2026 in Biomedicines
Verified
Journal Article
Open access
PDF file
AKAiym Kaiyrlykyzy
Aiym Kaiyrlykyzy
ASAygerim Serikzhan
Aygerim Serikzhan
AKAliya Kassenova
Aliya Kassenova
ASAigul Sharip
Aigul Sharip
DADinara Alzhanova
Dinara Alzhanova
SASholpan Askarova
Sholpan Askarova
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.

19 October 2026 in Biomedicines
Verified
Journal Article
Open access
PDF file
ASAygerim Serikzhan
Aygerim Serikzhan
ZAZhannur Abilova
Zhannur Abilova
AAAinur Akhmetova
Ainur Akhmetova
AGAidana Gabdulkayum
Aidana Gabdulkayum
ADAsset Daniyarov
Asset Daniyarov
DYDauren Yerezhepov
Dauren Yerezhepov
Background/Objectives: Genetic factors are known to influence overall immune vulnerability to diseases, such as tuberculosis (TB); however, isolating the genetic component can be challenging as social and environmental causes, such as smoking, alcohol consumption, and unemployment, also drive disease risk. To reduce heterogeneity related to these factors, we performed a targeted immunogenetic association study of TB susceptibility in a Kazakh case–control cohort selected among individuals without the typical socioeconomic and nutritional risk factors linked to TB. Methods: We performed genotyping using an immune-focused targeted array; after quality control at sample and variant level, removal of ancestry-based outliers, and adjustment for population stratification, the final dataset included 164 participants (84 cases, 80 controls) and 181,595 variants. We performed four complementary analyses: single-variant association testing using logistic regression with Firth correction where required adjusted for sex and genetic ancestry, gene-based aggregation testing, functional annotation, and polygenic risk scoring using existing multi-ancestry TB genetic resources. Results: While no variant reached formal significance, the top nominal signal, rs1560036 (OR = 2.98, p = 2.4 × 10−5), lies within CPLX2, which ranked among the top genes in gene-based analysis, a result driven largely by the same variant. A nominally associated variant in the classical MHC region, rs9263600, is separately reported in GTEx as a cis-eQTL for HLA-B and HLA-C. Similarly, polygenic risk scores showed directionally consistent but statistically non-significant associations with case status (Asia-base AUC = 0.560; Europe-base AUC = 0.537). Conclusions: Although our study was not adequately powered to detect small-to-moderate genetic effects, it offers an important perspective on TB genetics in a population underrepresented in existing research. These findings provide an openly available dataset and candidate signals for replication in larger, independent cohorts.