Outline

Overview

This unit of study provides a comprehensive introduction to the research methods that can be used in the identification and characterisation of genetic variants underlying neuropsychiatric and neurodegenerative diseases. Understanding genetic variants in the context of genomic medicine is essential for patient management and predicting disease outcomes. This unit will provide students with and overview of bench to bedside genomic medicine. Students will be taught skills to identify causative and susceptibility gene variants from next generation sequencing data and shown bioinformatics tools to analyse variants. The variant information will then be considered in a diagnostic setting through the clinical application of genetic counselling for patient management and well-being. The first part of the unit will focus on statistical methods to quantify the contribution of genetic factors to complex genetic disorders in the population. The principles of genetic association will be discussed, using examples of cognitive traits and neurodegenerative disorders. The course will then discuss concepts of pedigree analysis for Mendelian neurodegenerative diseases with practical exercises in identifying candidate variants using filtering strategies of next generation sequencing data. The final part of the course will introduce a suite of bioinformatics tools and resources to generate a research report. This report will form an introduction to the genetic counselling practices required for clinical interpretation and use of information for patient-centred genomic healthcare delivery. This is a capstone unit of study that will require students to develop over the semester a scholarly piece of work using current practice bioinformatics skills and interpreting the information for a clinical setting. Over the assessments in this unit, students will identify genetic variants associated with a complex neurodegeneration disorder, map and identify possible causative genes for a Mendelian neurodegenerative disease, examine the suitability of DNA variants identified as disease candidates using bioinformatics tools, and interpret the clinical implications for the patient and their family.

Unit details and rules

Academic unit	Brain and Mind Science
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Eryn Werry, eryn.werry@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Report and extended responses Written report	60%	Formal exam period Due date: 17 Nov 2023 at 23:59	3000 words
Outcomes assessed:
Assignment	Pseudo-journal article Written report	40%	Week 09 Due date: 03 Oct 2023 at 23:59	2000 words
Outcomes assessed:

Assessment summary

Pseudo-journal article: Each student will be given a genome wide association studies output for a neurodegenerative disorder. Students must present the results and interpretation of this analysis in the form of a brief report.
Brief report and extended responses: Students will be asked to write a brief report and complete a template that will provide a research variant report for a patient next generation sequencing test. Students will also answer a number of extended response questions.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Please refer to the Brain and Mind Centre Postgraduate Program Course Rules and Policies Canvas site: https://canvas.sydney.edu.au/courses/12062/pages/course-rules-and-policies?module_item_id=666352

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction to the Unit	Seminar (8 hr)
Week 05	Understanding genetic contributions to complex traits	Workshop (8 hr)
Week 11	Clinical application of pedigree analysis and next generation sequencing variant filtering for Mendelian disease	Workshop (8 hr)
Week 12	1. Bioinformatics to explore the genome and DNA variants; 2. Genetic counselling: clinical and psychosocial implications of genomic medicine	Workshop (8 hr)

Attendance and class requirements

Attendance. Students are expected to attend 80% of classes either on campus or via Zoom.
Passing the course. Students must earn an average mark of at least 50% for the unit as a whole by passing their assessments.
Academic honesty. Academic honesty must be demonstrated in all forms of assessment. Similarity detection software (i.e. Turnitin) will be used for all submitted written work.

Please refer to our Course Rules and Policies: https://canvas.sydney.edu.au/courses/12062/pages/course-rules-and-policies?module_item_id=666352

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed through the Library Reading List, available on Canvas.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. interpret measures for genetic association in brain and mind disorders
LO2. demonstrate a practical understanding of genome-wide association studies and their limitations
LO3. demonstrate a practical understanding of family disease histories represented in pedigrees and extended haplotype analysis
LO4. demonstrate a practical understanding of next generation sequencing variant filtering for identifying causative alleles in Mendelian disease
LO5. use bioinformatics tools to assess properties of candidate variants for determining population frequency and pathogenicity prediction
LO6. use bioinformatics resources to investigate a gene’s function, expression pattern, protein outcomes and evolutionary history
LO7. demonstrate interpretation of susceptibility versus causative variants and the role of genetic counselling in translating information to patients who have undergone genetic testing
LO8. demonstrate an understanding of the role of genetic counselling in genomic education and healthcare delivery
LO9. interpret the psychosocial and clinical implications of genomic results on patient and family.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

We value your feedback about any aspect of the unit of study and your experience as a student of Sydney Medical School. To help ensure our courses meet your needs and maintain a high standard, we welcome your feedback at any time and we ask you to complete the Unit of Study Survey at the end of the semester. You can also rate any component of the unit using our star rating system found at the bottom of many pages as you progress through the unit. Your ratings and comments are anonymous and specifying what you liked and didn’t like about any of the learning materials, assessment items, discussion forums, feedback etc will help us to target our improvement efforts. Please note that your participation in this unit of study permits de-identified information about your learning experience and interaction with learning resources to be used for the purpose of improving the student learning experience.

Additional information

Help and Resources - Brain and Mind Centre Postgraduate Program

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

BMRI5017: Genetics of Brain and Mind Disorders

Semester 2, 2023 [Block mode] - Mallett Street, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect