November 14, 2019

Postcards from the edge-how founder

populations and the universities that serve

them can change the world

Terry-Lynn Young, PhD

Professor and Director of Genomics Research

Founder Populations—why are they useful for gene discovery?

• Founder effect:• Mutations get amplified through

population bottleneck and subsequent amplification

Founder Populations (Genetic isolates)

NewfoundlandAzores, Portugal

Holland

Finland

Sardinia, Italy

Costa Rica

Antioquia, Columbia

Afrikaner (South Africa)

NewfoundlandAzores, Portugal

Holland

Finland

Sardinia, Italy

Costa Rica

Antioquia, Columbia

Afrikaner (South Africa)

Quebec

Population History of the Island of Newfoundland

• 1497: John Cabot first reached NL

• 1610: established seasonal fishing colonies (outports)

• Mid-1700’s: Peak immigration, mainly Protestant settlers (south-west England), Catholic settlers (southern Ireland)

Settlement along the coast

(fishing villages=outports)

20,000-30,000 founders

Large families

50% of outports < 2000 resident

Little emigration or immigration

Segregation by religion

Founder effects

High coefficient of kinship

Founder Populations—limited variation in the human genome

• Founder effect:• Mutations get amplified through

population bottleneck and subsequent amplification

Clans-Clusters of related families

•Clinically difficult to diagnose

•First presentation SCD

•Lethal tachyarrhythmias: VT/VF

Arrhythmogenic Right Ventricular Cardiomyopathy

Genetic condition affecting heart muscle

• Autosomal Dominant (HIGH RECURRENCE RISK)

• Difficult to diagnose clinically

• Sudden cardiac death (SCD) often first presentation due to ventricular tachycardia (VT) or fibrillation (VF)

Single mutation, single gene

*

Common

Ancestor*

** * * *

transmembrane protein: TMEM43

Single missense mutation (S358L)

Survival ICD No ICD

Median N/A 8.9yrs. (SE

1.7)

5 year 95.4% 64.6%

10 year 88.3% 36.7%

RR 9.3 (95% CI 3.3-26.0)

Survival ICD No ICD

Median 16.9 (SE

N/A)

4.5yrs. (SE

1.4)

5 year 100% 50%

10 year 81.6% 25.4%

RR 9.7 (95% CI 3.2-29.6)

Survival ICD No ICD

Median N/A 25.5yrs.

(SE 3.7)

5 year 96.7% 84.7%

10 year 88.2% 69.3%

RR 3.6 (95% CI 1.3-9.5)

Males with ICDs for primary prophylaxis compared with controls

Males with ICDs for secondary prophylaxis

compared with controls

Females with ICDs for primary prophylaxis

compared with controls

Time to death or last follow-up from the start of the study in 148 ICD individuals and 148

matched controls for PP in males (A), SP in males (B) and PP in females (C)

TMEM43 p.S358L mutation worldwide

European ancestry dating mutation to 400 – 700 AD

Denmark1

Germany2

Canada3,4

United States5

New Zealand3

Sri Lanka6

Spain6

1Christensen et al. Clin Genet 2011;80:256-64.2Klauke et al. Cell Tissue Res 2012;348:368.3Baskin et al. Hum Genet 2013;132:1245-52.4Merner et al. Am J Hum Genet 2008;82:809-21.5Milting et al. European heart journal 2015;36:872-81. 6Personal communication

Personalized Medicine:R&D Opportunities in revolutionizing hearing Aid (HA) technology

http://www.globalcarecompany.com/anatomy-of-the-ear.html

Hearing Loss-most cases due to mutations in genes

Genetics

50%Idiopathic

25%Environment

25%

• Most common sensory deficit

• Prevalence:

– Newborn: 1/500

– Adult: 1/5

• Causes:

– Environment

– Idiopathic

– Genetic

TECTACOL11A2

OTOFMYO7ACDH23PCDH17

GJB2GJB6GJB3

Animal research tell us about the functions of these genes in hearing

OTOASTRCMYO7ACDH23PCDH17

National Rural Healthcare Innovation in Grand Falls-Windsor,NL

The Genomics-Based R&D Centre for Health

The Project

Use NL families with mutations in these hearing genes to make models of different types of hearing loss

Improve efficacy of hearing devices

Create a competitive advantage for

industry

Challenges of Aiding Hearing Loss

Clinical testing (audiogram) does not provide accurate data

on specifics of loss

Lack of data restricts ability to customize

hearing device

Clinical community doesn’t understand the major role that

genetics plays

Addressing these Challenges

• Genomics reveals the exact site of lesion in the auditory pathway

Clinical testing (audiogram) does not provide accurate data

on specifics of loss

• Computer modeling will provide key data points to develop lesion-specific algorithms; multiplex families will provide patient feedback

Lack of data restricts ability to customize

hearing device

• Knowledge translation/education of audiologists/ENT clinicians, and patients is integral to this program of research

Clinical community doesn’t understand the major role that

genetics plays

The Process

Recruit research clients to GFW

Run sophisticated phenotype tests in GFW site to make the link between gene mutation

and hearing deficit

Design Computer models to mimic effect of lesion in auditory pathway

Develop novel algorithms to

address hearing deficit

University-community partnerships at work

Stay tuned…

Balance clinic for GFW

will be announced soon

New private-public

partnership

35

Phenotyping

Susan G. Stanton

Western

Amanda Morgan

Matthew Lucas

Modeling

Ian C. Bruce

McMaster

Michael R.

Wirtzfeld

Genetics

Terry Lynn Young

Memorial

University

Newfoundland

Data collection

Anne Griffin

Genomics-based

hearing research

centre,

Grand Falls-Windsor

Jill Lowther

Questions???????