Mental health disorders affect approximately one in five American adults, with significant genetic components. Recent advances in Precision Medicine promise to transform clinical practice, through the integration of medical records, family history, lifestyle, and genetic risk models, offering hope for more personalized and effective treatments in psychiatry. However, psychiatric disorders are inherently complex and heterogeneous, presenting a wide range of symptoms and outcomes that vary significantly among individuals, which complicates diagnosis and treatment. This variability underscores the need for innovative approaches to better capture the nuanced nature of these conditions.
A new project at the New York Genome Center (NYGC) aims to develop novel artificial intelligence frameworks and computational infrastructure to effectively harness the wealth of information contained in medical records and genomic data, and deploy that knowledge in a novel framework for Precision Psychiatry. Gamze Gursoy, PhD, a Core Faculty Member at the NYGC, along with Thomas Lehner, PhD, MPH, Scientific Director of Neuropsychiatric Disease Genomics at NYGC, has received a $2.2 million grant from The Warren Alpert Foundation to develop advanced machine learning-based methodologies to integrate and analyze genetic data and electronic health records (EHRs) from patients living with mental health disorders and to implement strategies to disseminate these data while preserving patient privacy.
Specifically, they aim to develop deep phenotyping approaches to better capture the information in EHRs and leverage machine learning techniques to enhance the precision of phenome-wide association studies. These approaches aim to improve the accuracy of associations between genetic variation and clinical traits and reveal new insights into the genetic bases of psychiatric disorders and their co-morbidities. The team also seeks to implement a cutting-edge privacy framework tailored to the complexities of genetic data. This framework will be integrated, in collaboration with Michael Zody, Scientific Director of Computational Biology, and Charles Gagnon, Chief Information Officer at the NYGC, into a Data Commons established to disseminate phenotype and genotype data from the Genomic Medicine for Mental Health Advancement (GeMMA) initiative at NYGC. Collectively, these efforts promise to significantly advance Precision Psychiatry by enabling more accurate disease-gene associations and facilitating democratized data sharing, all while maintaining high standards of data privacy.
“The complexity and heterogeneity of psychiatric disorders have long posed challenges for effective treatment,” says Dr. Lehner. “With the generous investment from The Warren Alpert Foundation, our innovative approaches aim to address these challenges head-on, enhancing our understanding of the genetic and phenotypic architecture of clinical conditions.”
