SIIK24003U Clinical Immunology

Volume 2024/2025
Education

MSc in Immunology and Inflammation - compulsory

Content

This course is designed to bring an in-depth understanding of the immune system’s role in the development of several common inflammatory human diseases.

To achieve this aim, we will take a disease-oriented approach with teaching sessions from experts in various inflammatory disorders that affect the lung (eg, asthma, COPD), intestines (eg, IBD, celiac disease), brain (eg, multiple sclerosis, Alzheimers), and other bodily tissues (eg, diabetes, rheumatoid arthritis, Sjøgren’s Syndrome, SLE).

Teaching sessions will describe the structure and composition of our body’s tissues - the cell types that can be expected to be found in these tissues and how immune cells live in these organs. We will touch on how these organs and immune cells operate in health, and what happens in the case of inflammation/disease. Different types of white blood cells (leukocytes) and their interplay with non-immune cells will be reviewed along with the role of various immune molecules such as antibodies, cell surface receptors, cytokines and chemokines (immune hormones).

When it comes to the different inflammatory conditions, we will ask:

1) what are the critical failures that lead to disease?

2) what are the major cell types that cause disease?

3) what are the critical molecules that cause disease?

4) how can we target the immune system to alleviate disease?

As well as learning from experts in the field by way of lectures and other types of teaching sessions, students will learn to analyse publicly available RNA-Sequencing datasets from some inflammatory conditions. The aim here will be to become more familiar with programming language and applications related to analysis of sequencing data. We will use datasets rich in immune cell infiltrates so that students can also explore the how immune cells behave and change in these disease conditions.  

Learning Outcome

After completing the course the student is expected to be able to:

Knowledge:

  • Understand the immunological and inflammatory mechanisms involved in the most common allergic, autoimmune and inflammatory diseases
  • Explain the characteristics of different categories of inflammation and application of these in diagnosis and therapeutic strategies
  • Explain the interplay between different parts of the immune system and with stromal and epithelial cells of various bodily organs
  • Explain and discuss the various types of antigens that may give rise to allergic and autoimmune diseases
  • Identify and discuss the use of cellular and antibody-based diagnostics of inflammatory diseases
  • Understand how computational tools may be used to analyse the immune response in human disease and the advantages and disadvantages of using such approaches

 

Skills:

  • Propose relevant immunological studies aimed at clarifying the role of endogenous and exogenous antigens, life style and environment, and genetic background in chronic inflammatory diseases.
  • Hypothesize experimental approaches that could give greater insights into specific inflammatory diseases
  • Conceptualise new strategies for immune-based treatments of inflammatory diseases
  • Analyse RNA-Sequencing datasets and produce standard outputs from data including gene expression analysis, principal component analysis and statistical analyses.

 

Competencies: 

  • Critically analyze and discuss clinical and experimental data in the field of inflammation and inflammatory diseases
  • Outline small research projects within experimental immunology and inflammation
  • Provide immunological inputs to interdisciplinary projects involving basic research, clinical research, biomarker and drug development within allergy, autoimmunity and inflammation

A literature list will be produced upon establishment of the faculty for this course.

Comprehensive knowledge in basic immunology and immune pathology is recommended.
Lectures online and on campus. Project work in the form of hands-on computational classes with leading experts, journal clubs and group learning sessions.
  • Category
  • Hours
  • Lectures
  • 40
  • Preparation
  • 120
  • Project work
  • 44
  • Exam
  • 2
  • Total
  • 206
Continuous feedback during the course of the semester
Credit
7,5 ECTS
Type of assessment
On-site written exam, 2 hours under invigilation
Type of assessment details
The exam will draw from course content and will be conducted without aids.
Exam registration requirements

Examination prerequisite are:

Approved course group project in form of a written report on the immunological mechanisms of a specific disease.

Aid
Without aids
Marking scale
7-point grading scale
Censorship form
No external censorship
Internal examiners
Criteria for exam assesment

To achieve the maximum grade of 12, the student shall be able to:

Knowledge:

  • Understand the immunological and inflammatory mechanisms involved in the most common allergic, autoimmune and inflammatory diseases
  • Explain the characteristics of different categories of inflammation and application of these in diagnosis and therapeutic strategies
  • Explain the interplay between different parts of the immune system and with stromal and epithelial cells of various bodily organs
  • Explain and discuss the various types of antigens that may give rise to allergic and autoimmune diseases
  • Identify and discuss the use of cellular and antibody-based diagnostics of inflammatory diseases
  • Understand how computational tools may be used to analyse the immune response in human disease and the advantages and disadvantages of using such approaches

 

Skills:

  • Propose relevant immunological studies aimed at clarifying the role of endogenous and exogenous antigens, life style and environment, and genetic background in chronic inflammatory diseases.
  • Hypothesize experimental approaches that could give greater insights into specific inflammatory diseases
  • Conceptualise new strategies for immune-based treatments of inflammatory diseases
  • Analyse RNA-Sequencing datasets and produce standard outputs from data including gene expression analysis, principal component analysis and statistical analyses.