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Predictive, Preventive and Personalised (3P) Medicine: From Bench to Bedside
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Predictive, Preventive and Personalised (3P) Medicine: From Bench to Bedside

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pathology, Diagnostics, and Therapeutics".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 10189

Special Issue Editor

Prof. Dr. Olga Golubnitschaja

E-Mail Website
Guest Editor
Predictive, Preventive Personalised (3P) Medicine, Department of Radiation Oncology, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, 53127 Bonn, Germany
Interests: predictive preventive personalised medicine (PPPM/3PM); suboptimal health; vasospasm; cancer and metastatic disease; stroke; diabetes; cardiovascular disease; noncommunicable disorder; COVID-19; phenotyping; genotyping; molecular diagnostics; biomarker panels; patient stratification; individualized profiling; liquid biopsy; articifial intelligence; disease modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

To successfully combat global epidemics of infectious and noncommunicable disorders (cancer, stoke, diabetes, cardiovascular diseases, etc.), the paradigm change from reactive medicine to a predictive approach, targeted prevention and treatments tailored to the patient is nonincremental in advanced biomedical sciences and healthcare. This Special Issue, entitled “Predictive, Preventive and Personalised (3P) Medicine: From Bench to Bedside”, is dedicated to molecular relevant research in biomedical sciences demonstrating a high level of innovation towards concepts of 3P medicine. Science-to-technology breakthroughs should address the vision of the predictive medical approach and targeted prevention. The methodology should consider the application of minimal and noninvasive diagnostics, such as liquid biopsy (blood, saliva and tear fluid, amongst others). Analytical tools include multiomics, circulating tumour cells, cell-free nucleic acids and computation technologies, such as big data analysis, machine learning and the application of artificial intelligence in medicine. A search of the literature and data interpretation in the context of 3P medicine are essential.

Prof. Dr. Olga Golubnitschaja
Guest Editor

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Keywords

  • predictive preventive personalised medicine (PPPM/3PM)
  • basic and translational research
  • suboptimal health
  • stress
  • vasospasm
  • stroke
  • cancer
  • metastatic disease
  • diabetes
  • cardiovascular disease
  • molecular mechanisms
  • liquid biopsy
  • multiomics
  • cell-free nucleid acids
  • mictobiome
  • biomarker patterns
  • computation analysis
  • disease modelling

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Published Papers (3 papers)

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Research

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14 pages, 5591 KiB  
Article
An Uncharacterised lncRNA Coded by the ASAP1 Locus Is Downregulated in Serum of Type 2 Diabetes Mellitus Patients
by Cristina Barbagallo, Michele Stella, Stefania Di Mauro, Alessandra Scamporrino, Agnese Filippello, Francesca Scionti, Maria Teresa Di Martino, Michele Purrello, Marco Ragusa, Francesco Purrello and Salvatore Piro
Int. J. Mol. Sci. 2023, 24(17), 13485; https://doi.org/10.3390/ijms241713485 - 30 Aug 2023
Viewed by 1055
Abstract
Diabetes mellitus (DM) is a complex and multifactorial disease characterised by high blood glucose. Type 2 Diabetes (T2D), the most frequent clinical condition accounting for about 90% of all DM cases worldwide, is a chronic disease with slow development usually affecting middle-aged or [...] Read more.
Diabetes mellitus (DM) is a complex and multifactorial disease characterised by high blood glucose. Type 2 Diabetes (T2D), the most frequent clinical condition accounting for about 90% of all DM cases worldwide, is a chronic disease with slow development usually affecting middle-aged or elderly individuals. T2D represents a significant problem of public health today because its incidence is constantly growing among both children and adults. It is also estimated that underdiagnosis prevalence would strongly further increase the real incidence of the disease, with about half of T2D patients being undiagnosed. Therefore, it is important to increase diagnosis accuracy. The current interest in RNA molecules (both protein- and non-protein-coding) as potential biomarkers for diagnosis, prognosis, and treatment lies in the ease and low cost of isolation and quantification with basic molecular biology techniques. In the present study, we analysed the transcriptome in serum samples collected from T2D patients and unaffected individuals to identify potential RNA-based biomarkers. Microarray-based profiling and subsequent validation using Real-Time PCR identified an uncharacterised long non-coding RNA (lncRNA) transcribed from the ASAP1 locus as a potential diagnostic biomarker. ROC curve analysis showed that a molecular signature including the lncRNA and the clinicopathological parameters of T2D patients as well as unaffected individuals showed a better diagnostic performance compared with the glycated haemoglobin test (HbA1c). This result suggests that the application of this biomarker in clinical practice would help to improve the diagnosis, and therefore the clinical management, of T2D patients. The proposed biomarker would be useful in the context of predictive, preventive, and personalised medicine (3PM/PPPM). Full article
(This article belongs to the Special Issue Predictive, Preventive and Personalised (3P) Medicine: From Bench to Bedside)
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Review

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23 pages, 2118 KiB  
Review
Physiological Rhythms and Biological Variation of Biomolecules: The Road to Personalized Laboratory Medicine
by Abdurrahman Coskun, Atefeh Zarepour and Ali Zarrabi
Int. J. Mol. Sci. 2023, 24(7), 6275; https://doi.org/10.3390/ijms24076275 - 27 Mar 2023
Cited by 15 | Viewed by 4022
Abstract
The concentration of biomolecules in living systems shows numerous systematic and random variations. Systematic variations can be classified based on the frequency of variations as ultradian (<24 h), circadian (approximately 24 h), and infradian (>24 h), which are partly predictable. Random biological variations [...] Read more.
The concentration of biomolecules in living systems shows numerous systematic and random variations. Systematic variations can be classified based on the frequency of variations as ultradian (<24 h), circadian (approximately 24 h), and infradian (>24 h), which are partly predictable. Random biological variations are known as between-subject biological variations that are the variations among the set points of an analyte from different individuals and within-subject biological variation, which is the variation of the analyte around individuals’ set points. The random biological variation cannot be predicted but can be estimated using appropriate measurement and statistical procedures. Physiological rhythms and random biological variation of the analytes could be considered the essential elements of predictive, preventive, and particularly personalized laboratory medicine. This systematic review aims to summarize research that have been done about the types of physiological rhythms, biological variations, and their effects on laboratory tests. We have searched the PubMed and Web of Science databases for biological variation and physiological rhythm articles in English without time restrictions with the terms “Biological variation, Within-subject biological variation, Between-subject biological variation, Physiological rhythms, Ultradian rhythms, Circadian rhythm, Infradian rhythms”. It was concluded that, for effective management of predicting, preventing, and personalizing medicine, which is based on the safe and valid interpretation of patients’ laboratory test results, both physiological rhythms and biological variation of the measurands should be considered simultaneously. Full article
(This article belongs to the Special Issue Predictive, Preventive and Personalised (3P) Medicine: From Bench to Bedside)
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17 pages, 2829 KiB  
Review
The Role of Different Types of microRNA in the Pathogenesis of Breast and Prostate Cancer
by Ekaterina A. Sidorova, Yury V. Zhernov, Marina A. Antsupova, Kamilya R. Khadzhieva, Angelina A. Izmailova, Denis A. Kraskevich, Elena V. Belova, Anton A. Simanovsky, Denis V. Shcherbakov, Nadezhda N. Zabroda and Oleg V. Mitrokhin
Int. J. Mol. Sci. 2023, 24(3), 1980; https://doi.org/10.3390/ijms24031980 - 19 Jan 2023
Cited by 8 | Viewed by 3792
Abstract
Micro ribonucleic acids (microRNAs or miRNAs) form a distinct subtype of non-coding RNA and are widely recognized as one of the most significant gene expression regulators in mammalian cells. Mechanistically, the regulation occurs through microRNA binding with its response elements in the 3’-untranslated [...] Read more.
Micro ribonucleic acids (microRNAs or miRNAs) form a distinct subtype of non-coding RNA and are widely recognized as one of the most significant gene expression regulators in mammalian cells. Mechanistically, the regulation occurs through microRNA binding with its response elements in the 3’-untranslated region of target messenger RNAs (mRNAs), resulting in the post-transcriptional silencing of genes, expressing target mRNAs. Compared to small interfering RNAs, microRNAs have more complex regulatory patterns, making them suitable for fine-tuning gene expressions in different tissues. Dysregulation of microRNAs is well known as one of the causative factors in malignant cell growth. Today, there are numerous data points regarding microRNAs in different cancer transcriptomes, the specificity of microRNA expression changes in various tissues, and the predictive value of specific microRNAs as cancer biomarkers. Breast cancer (BCa) is the most common cancer in women worldwide and seriously impairs patients’ physical health. Its incidence has been predicted to rise further. Mounting evidence indicates that microRNAs play key roles in tumorigenesis and development. Prostate cancer (PCa) is one of the most commonly diagnosed cancers in men. Different microRNAs play an important role in PCa. Early diagnosis of BCa and PCa using microRNAs is very useful for improving individual outcomes in the framework of predictive, preventive, and personalized (3P) medicine, thereby reducing the economic burden. This article reviews the roles of different types of microRNA in BCa and PCa progression. Full article
(This article belongs to the Special Issue Predictive, Preventive and Personalised (3P) Medicine: From Bench to Bedside)
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