“Symptoms, mechanisms and sex: Exploring the sex differences in ME/CFS
through integrated computational analyses”
Principal Investigator: Sara Ballouz (PhD)
Garvan-Weizmann Centre for Cellular Genomics
“Symptoms, mechanisms and sex: Exploring the sex differences in ME/CFS
through integrated computational analyses”
Principal Investigator: Sara Ballouz (PhD)
Garvan-Weizmann Centre for Cellular Genomics
Collaborators: Anna Liza Kretzschmar, PhD
Garvan-Weizmann Centre for Cellular Genomics
Dr. Sara Ballouz, PhD, (Principal Investigator), is the senior research officer at the Garvan-Weizmann Centre for Cellular Genomics in New South Wales, Australia. One of her main scientific interests includes studying genome variation, genetic architecture of complex diseases and the influence of different genotypes on gene and protein function.
Dr. Anna Liza Kretzschmar, PhD, is a postdoctoral fellow and research officer at the Garvan-Weizmann Centre for Cellular Genomics. Her work includes large dataset exploration through bioinformatics, such as developing molecular characterization approaches and monitoring systems of fish poisoning.
The team will build a network analysis tool to parse and homogenize survey-driven data to allow for comparability of phenotype information from patients with ME/CFS and with Long Covid in multiple registries.
These tools have the possibility of producing a better understanding of disease subsets, improve informatics approaches, and develop machine learning/algorithms for characterizing the disease. Both will also complete single-cell immune transcriptomic data in a sex-specific manner for ME/CFS patients, which could produce insight into how ME/CFS differs between males and females (an understudied question).
Study Summary
We plan to tackle how ME/CFS and sex differences manifest through an exploration of gene expression and cellular heterogeneity of the immune system in ME/CFS. We hope to find celltypes, genes and gene interactions associated with ME/CFS symptoms to eventually lead to better diagnoses and treatments.
Alongside this, we will address the problems in diagnosis and classification of ME/CFS through a computational analysis of phenotypic, survey and biomarker data. Both aims involve the use of biobanked samples and data: the first requires blood samples to profile the immune systems of ME/CFS sufferers and the second survey responses and quantitative traits to data mine and highlight features to aid in classification and diagnosis of disease.
It is anticipated that this research will provide characteristics of ME/CFS at the symptomatic, molecular and cellular levels. The ultimate goal is to use this knowledge for molecularly characterizing the blood of ME/CFS individuals and their symptoms to identify and diagnose patients, leading to improved clinical treatments.
350 N Glendale Ave.
Suite B #368
Glendale, CA 91206
SolveCFS@SolveCFS.org
704-364-0016
EIN: 56-1683450
Cookie | Duration | Description |
---|---|---|
cookielawinfo-checkbox-analytics | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics". |
cookielawinfo-checkbox-functional | 11 months | The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". |
cookielawinfo-checkbox-necessary | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary". |
cookielawinfo-checkbox-others | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other. |
cookielawinfo-checkbox-performance | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance". |
viewed_cookie_policy | 11 months | The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data. |
Please let us know more about you.
Please let us know more about you.
Please let us know more about you.
Join the Solve Together Real-World Data Platform