Dolores
Corella
Dolores Corella
Spain - Valencia
Biography
Dr. D. Corella is Full Professor of Preventive Medicine and Public Health, Director of the Molecular Epidemiology Laboratory at the School of Medicine, University of Valencia, Valencia, and group leader of the Omics epidemiology of cardiometabolic diseases group at the “CIBER Fisiopatología de la Obesidad y Nutrición", ISCIII, Madrid.
She has a strong background in Genomics, Molecular Epidemiology, statistics and other omics. She has been a pioneer in Spain in the study of gene-lifestyle interactions in determining cardiometabolic phenotypes and risk factors, mainly on gene-diet interactions. Currently she is incorporating other omics in the precision nutrition and personalized medicine field.
She has a strong background in Genomics, Molecular Epidemiology, statistics and other omics. She has been a pioneer in Spain in the study of gene-lifestyle interactions in determining cardiometabolic phenotypes and risk factors, mainly on gene-diet interactions. Currently she is incorporating other omics in the precision nutrition and personalized medicine field.
Affiliations
- School of Medicine, University of Valencia
- “CIBER Fisiopatología de la Obesidad y Nutrición", ISCIII, Madrid
- “CIBER Fisiopatología de la Obesidad y Nutrición", ISCIII, Madrid
Areas of expertise
- Genomics
- Molecular Epidemiology
- Statistics
- Other omics
- Molecular Epidemiology
- Statistics
- Other omics
Abstract
Personalized Nutrition and Health: The Future starts Now
Personalized Nutrition and Health: The Future starts Now
Despite the fact that numerous studies have found significant associations between nutrition and different diseases, it is well known that the relationship between diet and health is extremely difficult. Not only is the measurement of diet complex, but it is also known that there is considerable inter-individual variability that has not been accounted for. In the past decade, various international initiatives founded on so-called personalized nutrition or precision nutrition have been launched in response to these challenges. Although the personalized nutrition concept is complex, its objective is to improve the instruments for measuring diet and health phenotypes in nutritional studies and to analyze inter-individual variability in order to make more precise and personalized nutritional recommendations for preventing or treating diseases. The first omics biomarkers in personalized nutrition were based on genomics. Later, more omics were added, and we now have epigenomic, metabolomic, transcriptomic, proteomic, exposomic, and metagenomic biomarkers, which are a significant advancement in the field of personalized nutrition. We will analyze the most important findings from each of these investigations regarding the most prevalent cardiometabolic diseases and accelerated aging. However, precision nutrition has important constraints that must be considered. Among them are difficulties with polygenic risk scores and other omics scores, the limitations of Mendelian randomization, the low external validity of multi-omics analyses that apply AI algorithms, and a scarcity of account for the gender perspective and geographical diversity. However, despite these limitations, substantial technological and methodological advancements allow us to argue that personalized nutrition has never before had so many tools to enhance research in the field. These developments have allowed scientists to delve deeper into the intricate relationship between omics, diet, and health outcomes. In addition, the incorporation of novel machine learning algorithms will facilitate the discovery of new associations and patterns in precision nutrition and health.
Despite the fact that numerous studies have found significant associations between nutrition and different diseases, it is well known that the relationship between diet and health is extremely difficult. Not only is the measurement of diet complex, but it is also known that there is considerable inter-individual variability that has not been accounted for. In the past decade, various international initiatives founded on so-called personalized nutrition or precision nutrition have been launched in response to these challenges. Although the personalized nutrition concept is complex, its objective is to improve the instruments for measuring diet and health phenotypes in nutritional studies and to analyze inter-individual variability in order to make more precise and personalized nutritional recommendations for preventing or treating diseases. The first omics biomarkers in personalized nutrition were based on genomics. Later, more omics were added, and we now have epigenomic, metabolomic, transcriptomic, proteomic, exposomic, and metagenomic biomarkers, which are a significant advancement in the field of personalized nutrition. We will analyze the most important findings from each of these investigations regarding the most prevalent cardiometabolic diseases and accelerated aging. However, precision nutrition has important constraints that must be considered. Among them are difficulties with polygenic risk scores and other omics scores, the limitations of Mendelian randomization, the low external validity of multi-omics analyses that apply AI algorithms, and a scarcity of account for the gender perspective and geographical diversity. However, despite these limitations, substantial technological and methodological advancements allow us to argue that personalized nutrition has never before had so many tools to enhance research in the field. These developments have allowed scientists to delve deeper into the intricate relationship between omics, diet, and health outcomes. In addition, the incorporation of novel machine learning algorithms will facilitate the discovery of new associations and patterns in precision nutrition and health.