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From molecules to the mind: using big data towards earlier autism diagnosis
(D268)
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Submitted:
05/04/2021
Status: 
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Autism arises early in life, and parents are usually the first to notice that their child's social skills are slipping behind. However, autism is difficult to diagnose as there is no biological "test". This has long perplexed researchers, as autism is one of the most heritable psychiatric conditions. Instead, in Australia, clinicians rely on intensive interviews and observation, while families endure anxious 1-2 year diagnostic odysseys as their child diverges from their peers.

Diagnosis is a critical bottleneck in clinical care and social support. Time is of the essence: children with earlier support achieve better educational and employment outcomes.

The lack of known autism biomarkers probably reflects biology more complex than we yet understand: the fundamental question of how molecules culminate in the mind. Hence, I am integrating large molecular and clinical datasets to capture this complexity. Ultimately, I hope to identify biomarkers to aid autism diagnosis.

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