Dolores
Corella
Dolores Corella
Spain - Valencia
Biografía
La Dra. D. Corella es Profesora Titular de Medicina Preventiva y Salud Pública en la Facultad de Medicina de la Universidad de Valencia, Valencia. Además, es Directora del Laboratorio de Epidemiología Molecular y jefa del grupo de Epidemiología ómica de las enfermedades cardiometabólicas del "CIBER Fisiopatología de la Obesidad y Nutrición, ISCIII, Madrid".
La Dra. Corella cuenta con una sólida formación en Genómica, Epidemiología Molecular, estadística y otras áreas relacionadas con las ómicas. Es reconocida como pionera en España en el estudio de las interacciones gen-estilo de vida para la determinación de fenotipos cardiometabólicos y factores de riesgo, centrándose especialmente en las interacciones gen-dieta. Actualmente, su trabajo se enfoca en la integración de otras ómicas en el campo de la nutrición de precisión y la medicina personalizada.
La Dra. Corella cuenta con una sólida formación en Genómica, Epidemiología Molecular, estadística y otras áreas relacionadas con las ómicas. Es reconocida como pionera en España en el estudio de las interacciones gen-estilo de vida para la determinación de fenotipos cardiometabólicos y factores de riesgo, centrándose especialmente en las interacciones gen-dieta. Actualmente, su trabajo se enfoca en la integración de otras ómicas en el campo de la nutrición de precisión y la medicina personalizada.
Filiaciones
- Facultad de Medicina, Universidad de Valencia
- "CIBER Fisiopatología de la Obesidad y Nutrición", ISCIII, Madrid
- "CIBER Fisiopatología de la Obesidad y Nutrición", ISCIII, Madrid
Áreas de especialización
- Genómica
- Epidemiología molecular
- Estadística
- Otras ómicas
- Epidemiología molecular
- Estadística
- Otras ómicas
Abstract
Nutrición personalizada y salud: el futuro empieza hoy
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.