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Dear Colleagues,

Omics technologies are becoming increasingly popular for molecular research and human health assessment. Mass spectrometry (MS) coupled with separation techniques such as electrophoresis/chromatography/ion mobility is the main tool in omics studies (proteomics, metabolomics) and is the most powerful approach for clinical research which ensures reliable identification and discovery of new molecules and potential biomarkers. Overcoming many of its initial challenges related to sampling and MS analysis the new advanced methods for molecular profiling are constantly developed which has a great potential for translation to medical diagnostics. Thousands of new potential and candidate biomarkers were discovered in human body fluids (blood, urine, CSF, etc.), many of which are relevant to the specific clinician syndromes and pathologies.

Over the past few years, omics technologies have made many advances, especially in combination with Artificial intelligence (AI) and Machine learning (ML) approaches for assessing health states and combating new challenges and diseases such as COVID-19.

The current issue is focused on advanced mass spectrometry-based omics technologies in combination with artificial intelligence (AI) and machine learning (ML) approaches for assessing health state and new potential biomarkers discovery for diseases such as Alzheimer’s, cardiovascular diseases (CVD), breast cancer, chronic kidney diseases (CKD), COVID-19 and others. Other frontend non-MS omics technologies applicable for online/offline analysis of body fluids and their molecular profiling for clinical applications are also of interest.

Dr. Alexey Kononikhin
Dr. Vladimir Frankevich
Prof. Dr. Eugene Nikolaev
Guest Editors

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Keywords

omics technologies
proteomics
metabolomics
mass spectrometry
artificial intelligence (AI)
machine learning (ML)
human health
biomarkers

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Research

17 pages, 2093 KiB

Open AccessArticle

COVID-19 Infection during Pregnancy: Disruptions in Lipid Metabolism and Implications for Newborn Health

by Natalia Frankevich, Alisa Tokareva, Vitaly Chagovets, Natalia Starodubtseva, Natalia Dolgushina, Roman Shmakov, Gennady Sukhikh and Vladimir Frankevich

Int. J. Mol. Sci. 2023, 24(18), 13787; https://doi.org/10.3390/ijms241813787 - 07 Sep 2023

Cited by 1 | Viewed by 1133

Abstract

The COVID-19 pandemic has raised questions about indirect impact in pregnant women on the development of their future children. Investigating the characteristics of lipid metabolism in the “mother–placenta–fetus” system can give information about the pathophysiology of COVID-19 infection during pregnancy. A total of 234 women were included in study. Maternal plasma, cord blood, and amniotic fluid lipidome were analyzed using HPLC-MS/MS. Differences in lipid profile were searched by Mann–Whitney and Kruskall–Wallis test, and diagnostic model based on logistic regression were built by AIC. Elevated levels of lysophospholipids, triglycerides, sphingomyelins, and oxidized lipids were registered in patients’ maternal and cord plasma after COVID-19 infection. An increase in maternal plasma sphingomyelins and oxidized lipids was observed in cases of infection during the second trimester. In amniotic fluid, compared to the control group, nine lipids were reduced and six were elevated. Levels of phosphoglycerides, lysophosphoglycerides, and phosphatidylinositols decreased during infection in the second and third trimesters of pregnancy. A health diagnostic model for newborns based on maternal plasma was developed for each group and exhibited good diagnostic value (AUC > 0.85). Maternal and cord plasma’s lipidome changes during delivery, which are associated with COVID-19 infection during pregnancy, are synergistic. The most significant disturbances occur with infections in the second trimester of pregnancy. Full article

(This article belongs to the Special Issue Molecular Research Using Omics Technologies for Human Health 2.0)

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