Repository of Research and Investigative Information

Repository of Research and Investigative Information

Shahid Sadoughi University of Medical Sciences

Hematological Indices and Genetic Variants of Premature Ovarian Insufficiency: Machine Learning Approaches

(2024) Hematological Indices and Genetic Variants of Premature Ovarian Insufficiency: Machine Learning Approaches. Cardiovascular and Hematological Disorders - Drug Targets. pp. 98-109. ISSN 1871529X (ISSN)

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

Background: Premature Ovarian Insufficiency (POI) is associated with infertility. Little is known about the potential circulating biomarkers that could be used to predict POI. We have investigated the possible association between white and red blood cells, platelet indices, and eight established single nucleotide polymorphisms (SNPs) associated with POI risk. Methods: 117 women with premature menopause (PM) and 183 healthy women without a history of menopause before age 40 were recruited for this study. The tetra-primer amplification refractory mutation system-polymerase chain reaction (Tetra ARMS PCR) and allele-specific oligonucleotides-polymerase chain reaction (ASO-PCR) were carried out for genotyping for eight SNPs reported to be associated with POI. Decision tree analysis was applied to test the diagnostic value of hematological parameters to identify the risk of POI. Results: Women with POI had lower neutrophil (NEUT) and white blood cell (WBC), whereas red blood cell (RBC), hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), and mean cell hemoglobin (MCH) were higher. Platelet (PLT) count was also lower in affected women. Our data also indicated that HGB and HCT count were significantly associated with rs16991615 and rs244715. Mean Platelet volume (MPV) and platelet distribution width (PDW) were associated with rs244715, rs1046089, rs4806660, and rs2303369. The rs16991615 was also associated with RBC count, and rs451417 was associated with NEUTs. The decision tree (DT) model reveals that women with the NEUT count at a cut-off value of less than 2.8 and HCT equal to or more than 38.7 could be identified as high-risk cases for POI. Overall, we found the DT approach had a sensitivity = 85, specificity = 72, and accuracy = 74. Conclusion: The genetic variants involved in POI are associated with changes in reproductive hormone levels and with changes in hematological indices. © 2024 Bentham Science Publishers.

Item Type: Article
Keywords: platelet indices PM Primary ovarian insufficiency (POI) red blood cell indices SNP white blood cell indices Adult Female Humans Machine Learning Polymorphism, Single Nucleotide Primary Ovarian Insufficiency genomic DNA hemoglobin allele specific real time polymerase chain reaction Article cohort analysis controlled study decision making decision tree diagnostic accuracy diagnostic test accuracy study DNA extraction erythrocyte count genetic variability genotype genotyping hematocrit hematological parameters high risk patient human human experiment leukocyte count mean corpuscular hemoglobin mean corpuscular hemoglobin concentration mean corpuscular volume mean platelet volume menopause menstrual cycle neutrophil phenotype platelet count platelet distribution width polymerase chain reaction premature ovarian failure red blood cell distribution width sensitivity and specificity single nucleotide polymorphism support vector machine tetra primer amplification refractory mutation system polymerase chain reaction blood genetics
Page Range: pp. 98-109
Journal or Publication Title: Cardiovascular and Hematological Disorders - Drug Targets
Journal Index: Scopus
Volume: 24
Number: 2
Identification Number: https://doi.org/10.2174/011871529X297081240613075328
ISSN: 1871529X (ISSN)
Depositing User: ms soheila Bazm
URI: http://eprints.ssu.ac.ir/id/eprint/34233

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