Gene Overdosage and comorbidities during the early lifetime in Down Syndrome

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1 August 2020

Down syndrome COVID-19 on-line survey

The “Trisomy 21 Research Society” (T21RS) is collecting vital information to understand the risks and course of COVID-19 among people with Down syndrome. The goal is to learn if people with Down syndrome are more vulnerable or have a different course of illness related to COVID-19 and if their illness is related to their pre-existing health profile. The survey is available in 5 European languages and can be filled out by carers/family mebers or clinicians.

Click here to access the on-line survey.

News & Events

More news
1 August 2020

Down syndrome COVID-19 on-line survey

The “Trisomy 21 Research Society” (T21RS) is collecting vital information to understand the risks and course of COVID-19 among people with Down syndrome. The goal is to learn if people with Down syndrome are more vulnerable or have a different course of illness related to COVID-19 and if their illness is related to their pre-existing health profile. The survey is available in 5 European languages and can be filled out by carers/family mebers or clinicians.

Click here to access the on-line survey.

Summary Statement

Clinicians, pathophysiologists, integrative bioinformaticians and artificial intelligence computer scientists working to unravel intrinsic and extrinsic mechanisms that impact on Down Syndrome (DS) comorbidity (focusing on obesity and intellectual disability. The examination of the pathways and mechanisms involved in comorbidities and multi-morbidities that induce the coexistence of two or more diseases in an individual is of major importance for the effective treatment of patients suffering from DS, obesity and mental disorders.

To achieve a system view to this disease we will integrate multiple datasets using new multi-layered approaches, which offer a unique opportunity for the integration and synthesis of molecular (multi-OMICS) preclinical (cellular and animal) and clinical datasets and metadata (environment, patient history) to understand the mechanisms of comorbidities.

In GO-DS21 we plan to use publicly available and self-developed bioinformatics tools, network science, statistical machine learning software and mathematical modeling approaches to unravel the shared etiological mechanisms in DS and the associated comorbidities, mainly obesity and intellectual disability.

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