MMB8014 : Genetics of Common Disease
- Offered for Year: 2019/20
- Module Leader(s): Professor Heather Cordell
- Lecturer: Dr Joanna Elson, Dr Marc Woodbury-Smith, Professor Ann Daly, Dr Anna Mitchell, Dr John Mansfield, Professor John Loughlin, Dr Christopher Miles Morris, Dr Ian Wilson
- Owning School: FMS Graduate School
- Teaching Location: Newcastle City Campus
|Semester 1 Credit Value:||20|
This module aims to address a major area of current medical research and to provide students with an understanding of the strengths and weakness of both the current subject knowledge in this area and the practical approaches to it. Understanding the genetics of complex disease has been identified as a major post-genome challenge. The module aims to equip Level 7 students with the necessary skills to understand and develop research strategies to investigate the inheritance of complex diseases.
Specific aims are:
• To inform students in genetic variation and the genetics of non-Mendelian (complex) disease.
• To introduce students to the different strategies and information input required to identify genes in complex diseases.
• To compare the various practical approaches used to identify the genetic basis of common disease and to elucidate the role of genes in common disease.
• To outline the relevance and utility of genetic investigations to understanding the pathogenesis of common diseases.
Outline Of Syllabus
The module will cover:
• Genetic variation and the definition of complex genetic diseases.
• How to identify and assess the heritable component of a complex disease.
• Selecting and applying different research strategies.
• Linkage versus association analysis.
• Genome-wide association studies.
• Data/results interpretation and use of computer packages for performing statistical genetic analysis
• Knowledge of key examples of complex diseases, including examples such as: Crohn’s disease, Diabetes, Oesteoarthritis, Alzheimer’s Disease, Autism.
|Scheduled Learning And Teaching Activities||Lecture||20||1:00||20:00||Lectures|
|Scheduled Learning And Teaching Activities||Practical||3||2:00||6:00||Practicals|
|Scheduled Learning And Teaching Activities||Small group teaching||3||1:00||3:00||Tutorials|
|Scheduled Learning And Teaching Activities||Small group teaching||3||1:00||3:00||Seminar|
|Guided Independent Study||Reflective learning activity||30||1:00||30:00||Additional Reading and Reflective Learning|
|Guided Independent Study||Independent study||20||1:00||20:00||Preparation and Submission of Short Essay|
|Guided Independent Study||Independent study||50||1:00||50:00||Preparation for Examination|
|Guided Independent Study||Independent study||48||1:00||48:00||Preparation of Notes from Lectures and Reading|
|Guided Independent Study||Independent study||20||1:00||20:00||Preparation and submission of PC Assessment|
Teaching Rationale And Relationship
Interactive lectures will provide the students with a specific knowledge as a platform for private study. Together with computer practicals and seminars/tutorials these lectures will encourage the students to reflect both individually and in small groups on the state of knowledge in research in complex diseases. Students will practice critical appraisal, data analysis and interpretation during the computer practicals. Tutorials will encourage the students to reflect on their learning. All of these activities relate directly to the learning outcomes above.
The format of resits will be determined by the Board of Examiners
|Written Examination||60||1||A||50||Unseen examination with 1 essay from a choice of 3 options|
|Computer assessment||1||M||30||Open book assessment of practical/analytical skills.|
|Essay||1||M||20||Max 1000 - 1500 words|
Assessment Rationale And Relationship
The unseen written examination tests the student’s knowledge base, comprehension and ability to discuss the subject knowledge critically. The computer analysis exercise tests application of knowledge, understanding and ability to critically evaluate and interpret a given data set. The essay tests the student’s comprehension and ability to discuss the subject knowledge critically.
Open book assessment of practical/analytical skills involving statistical data analysis. Data set to be provided. The students will be given the data set and a worksheet (suggesting the various analysis approaches to be used) and will have one week in which to perform the analysis and to write up their findings. The analysis itself should take around 2-3 hours, with another 2-3 hours required for writing up.
Critical appraisal of a key recent paper in the field, to be chosen from a choice of a minimum of 8 (max 1000 - 1500 words).