Amali Mallawaarachchi

Dr. Amali Mallawaarachchi

Garvan Institute of Medical Research, Darlinghurst, Sydney, New South Wales, Australia

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2017 in Kidney International
Verified
Journal Article
Closed access
Andrew MallettAndrew Mallett
Andrew Mallett
HMHugh J. McCarthy
Hugh J. McCarthy
GHGladys Ho
Gladys Ho
KHKatherine Holman
Katherine Holman
EFElizabeth Farnsworth
Elizabeth Farnsworth
SAStephen I. Alexander
Stephen I. Alexander

11 May 2016 in European Journal of Human Genetics
Verified
Journal Article
Closed access
AMAmali Mallawaarachchi
Amali Mallawaarachchi
YHYvonne Hort
Yvonne Hort
MCMark Cowley
Mark Cowley
MMMark J McCabe
Mark J McCabe
AMAndré Minoche
André Minoche
TFTimothy J Furlong
Timothy J Furlong

16 August 2022 in Neurology
Verified
Journal Article
Open access
PDF file
RDRyan L. Davis
Ryan L. Davis
KKKishore Raj Kumar
Kishore Raj Kumar
CPClare Puttick
Clare Puttick
CLChristina Liang
Christina Liang
KAKate E. Ahmad
Kate E. Ahmad
CSCarolyn M. Sue
Carolyn M. Sue
Background and Objectives Mitochondrial diseases (MDs) are the commonest group of heritable metabolic disorders. Phenotypic diversity can make molecular diagnosis challenging, and causative genetic variants may reside in either mitochondrial or nuclear DNA. A single comprehensive genetic diagnostic test would be highly useful and transform the field. We applied whole-genome sequencing (WGS) to evaluate the variant detection rate and diagnostic capacity of this technology with a view to simplifying and improving the MD diagnostic pathway. Methods Adult patients presenting to a specialist MD clinic in Sydney, Australia, were recruited to the study if they satisfied clinical MD (Nijmegen) criteria. WGS was performed on blood DNA, followed by clinical genetic analysis for known pathogenic MD-associated variants and MD mimics. Results Of the 242 consecutive patients recruited, 62 participants had “definite,” 108 had “probable,” and 72 had “possible” MD classification by the Nijmegen criteria. Disease-causing variants were identified for 130 participants, regardless of the location of the causative genetic variants, giving an overall diagnostic rate of 53.7% (130 of 242). Identification of causative genetic variants informed precise treatment, restored reproductive confidence, and optimized clinical management of MD. Discussion Comprehensive bigenomic sequencing accurately detects causative genetic variants in affected MD patients, simplifying diagnosis, enabling early treatment, and informing the risk of genetic transmission.

23 March 2020 in Kidney International
Verified
Journal Article
Closed access
VHVinh T. Huynh
Vinh T. Huynh
MAMarie-Pierre Audrézet
Marie-Pierre Audrézet
JSJohn A. Sayer
John A. Sayer
AOAlbert C. Ong
Albert C. Ong
SLSiriane Lefevre
Siriane Lefevre
EGEmilie Cornec-Le Gall
Emilie Cornec-Le Gall

12 January 2021 in European Journal of Human Genetics
Verified
Journal Article
Closed access
PDF file
AMAmali Mallawaarachchi
Amali Mallawaarachchi
BLBen Lundie
Ben Lundie
YHYvonne Hort
Yvonne Hort
NSNicole Schonrock
Nicole Schonrock
SSSarah R. Senum
Sarah R. Senum
TFTimothy J. Furlong
Timothy J. Furlong

13 January 2018 in Human Mutation
Verified
Journal Article
Closed access
PDF file
SSSarah A. Sandaradura
Sarah A. Sandaradura
ABAdam Bournazos
Adam Bournazos
AMAmali Mallawaarachchi
Amali Mallawaarachchi
BCBeryl B. Cummings
Beryl B. Cummings
LWLeigh B. Waddell
Leigh B. Waddell
SCSandra T. Cooper
Sandra T. Cooper