- Docente: Stefania Evangelisti
- Credits: 5
- SSD: BIO/12
- Language: English
- Moduli: Stefania Evangelisti (Modulo 1) Luca Morandi (Modulo 2)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Medical Biotechnology (cod. 9081)
Learning outcomes
Discuss conventional and innovative technologies for the quantitative mapping of in vivo central nervous system and neuromuscular metabolic biomarkers. Describe in vivo neurometabolism in relationship to physiological and pathological conditions. Discuss the application of in vivo connectome imaging for the investigation of ageing and pathogenetic mechanisms, and for diagnostic, prognostic and follow-up purposes in pathological conditions. Develop expertise in the advanced processing and multi-level analyses of neurometabolic networks in line with the rapidly developing biomedical research and clinical settings. Develop skills for working in multidisciplinary team including clinicians, neuropsychologists, physicists, bioinformaticists and technicians.
Course contents
Module 1
- Course introduction
- Introduction to clinical biochemistry and biomarkers
- Laboratory medicine: the pre-analytical, analytical and post-analytical phases
- Variability and standardization of laboratory testing
- Performance of a laboratory test: sensibility, specificity, predicting values and ROC curves
- In vivo metabolic investigation techniques of the central and peripheral nervous system
- Elements of acquisition and analysis of magnetic resonance data (brain proton MR spectroscopy, muscle phosphorus MR spectroscopy, diffusion tensor imaging, functional MRI, quantitative susceptibility mapping)
- Elements of nuclear medicine
- Application of in vivo metabolic-microstructural investigation methods to the main groups of pathologies of the nervous system (genetic, toxic-metabolic, degenerative, neoplastic and inflammatory)
- Advanced analysis methods and tools: elements of connectome imaging and analysis and elements of machine learning methods for medical research
- Principles of radiogenomics
Module 2
- Course introduction
- DNA sequencing and personalized medicine
- DNA sequencing: from Sanger method to 2nd, 3rd and 4th generation sequencing in neurological disorders and brain tumours
- Cloud computing tools for genomic assay designing
- Personalized medicine: new diagnostic and bioinformatic approaches that provide understanding of the molecular basis of neurological diseases and brain tumours
- Principle of epigenetics
- The use of genetic and epigenetic biomarkers in neurological disorders and tumours of the central nervous system
- The assessment of diagnostic, prognostic and predictive tests with examples from new assays based on Next Generation and nanopore Sequencing
- Clinical validation of a new diagnostic assay
- Liquid biopsy to monitor the evolution of neurometabolic diseases and brain cancers through a minimally invasive technique
- Cerebrospinal fluid analysis in the central nervous system diseases
- Bioinformatic tools in clinical molecular biology: cloud computing approaches for NGS analysis identifying single point mutation, indels, genome rearrangements, copy number variations, variant allele frequency, gene fusions, epigenetic modifications
- Bioinformatic tools in clinical molecular biology: hierarchical clustering, principal component analysis, phylogenetic trees, methylation plot, ROC, Kaplan-Meier graph
- Principles of radiogenomics
Readings/Bibliography
Teaching materials in PDF
Teaching methods
Lectures and group practice exercises
Assessment methods
The exam consists of an oral interview with specific questions on at least two topics.
Teaching tools
Power point slides
Office hours
See the website of Stefania Evangelisti
See the website of Luca Morandi