Aims

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: Diabetes, Oesteoarthritis, Alzheimer’s Disease, Autism.

Teaching Rationale And Relationship

Lecture materials will provide the students with a specific knowledge as a platform for private study. Together with computer practicals and seminars these lecture materials 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. Seminars will encourage the students to reflect on their learning. All of these activities relate directly to the learning outcomes above.

Assessment Rationale And Relationship

The computer analysis exercise tests application of knowledge, understanding and ability to critically evaluate and interpret a given data set. The first essay tests the student’s comprehension and ability to discuss the subject knowledge critically. The second essay tests the student’s knowledge base, comprehension and ability to discuss the subject knowledge critically.

PC Assessment: 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 two weeks 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 preparation work and up to 10 hours for writing up. Essay 1: 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). Preparation work should take around 5 hours, with up to 10 hours for writing up. Essay 2: Description of the current state of knowledge of a topic in the field, to be chosen from 3 options (max 2000 words). Preparation work should take around 10 hours, with up to 10 hours for writing up.