Blood-Based ASD Detection: Dr. Howsmon

Dr. Daniel Howsmon is a postdoctoral researcher at the University of Texas at Austin. He shares latest research on detection of Autism Spectrum Disorder (ASD) with blood-based measurements. Classification methods are discussed with an outline of promising future work. Dr. Howsmon is the AIChE CAST (Computing and Systems Technology) division award winner of the W. David Smith Jr. Graduate Publication Award.

Autism spectrum disorder (ASD) represents a broad range of neurological disorders characterized by restricted, repetitive behaviors and interests as well as defects in social communication and interaction. Without a biological understanding of the pathophysiology of ASD, diagnoses are restricted to observational assessments and caregiver questionnaires. Folate-dependent one-carbon metabolism and transsulfuration (FOCM/TS) pathways incorporate many genetic and environmental contributions reported to influence ASD liability. We developed classifiers based on FOCM/TS measurements to separate children with ASD from their neurotypical peers and provide an overview of the steps taken to validate the classifiers and transition these measurements with their associated classifiers to the clinic.

Daniel Howsmon is currently a postdoctoral fellow in the Oden Institute for Computational Engineering and Sciences at the University of Texas at Austin where he studies the transition of valve interstitial cells from quiescent fibroblasts to active myofibroblasts under the direction of Michael Sacks. Daniel completed his PhD in Chemical and Biological Engineering in 2017 under Juergen Hahn and B. Wayne Bequette at Rensselaer Polytechnic Institute where he studied diverse clinical problems such as classification of autism spectrum disorder from metabolites and fault detection in the artificial pancreas. Daniel completed Bachelors of Science in both Chemical Engineering and Biochemistry at Texas A&M University in 2012.