Background:

Dr. Sha received his Ph.D. in Cognitive Neuroscience from Beijing Normal University, where he established the foundation for his research in neuroscience and neuropsychiatric disorders. He completed postdoctoral training in neuroimaging at the Department of Psychiatry at the University of Pittsburgh, the Language & Genetics Department at the Max Planck Institute for Psycholinguistics, and the Department of Psychiatry at the University of Pennsylvania and the Children’s Hospital of Philadelphia.

Dr. Sha’s research leverages advanced computational models to identify endophenotypes that characterize brain development and neurodevelopmental disorders (e.g., autism and genetic syndromes). His work integrates multi-omics biomedical data, bridging genetic variation, brain MRI, exposure (e.g., early life adversity), psychopathological phenotypes, and treatment outcomes. His overarching research goal is to develop detailed mechanistic and developmental hypotheses that can inform future clinical applications in understanding both cognitive development and clinical psychopathology in the human brain.

Research interests:

Understanding heterogeneity in neurodevelopmental disorders: Traditional diagnostic labels for neurodevelopmental disorders—such as autism spectrum disorder—are largely based on shared behavioral characteristics. While these labels help clinicians reach consensus on observable symptoms, they often obscure the substantial individual differences that exist among people with the same diagnosis. This clinical heterogeneity is evident across multiple levels of analysis, including genomic variation, neural architecture, phenotypic expression, treatment response, and long-term outcomes. Our lab is particularly interested in exploring this heterogeneity not as a confounding factor, but as a critical window into understanding the underlying mechanisms of neurodevelopmental disorders. To this end, our future research will focus on using multimodal technologies (3T and 7T MRI, genetic, and behavioral data) to examine the neurophysiological mechanisms and heterogeneity associated with autism and related genetic syndromes. We aim to build a more precise, mechanistic understanding of brain development in both typical and atypical populations.

Unraveling the pathways of resilience and risk: How early life adversity shapes brain development, physical health, and psychopathological outcomes: Research has established that early life stress disrupts normative developmental processes, leading to lifelong mental and physical health challenges. Early life stress, especially during sensitive periods such as infancy and early childhood, can dysregulate stress response systems (e.g., the hypothalamic-pituitary-adrenal axis) and epigenetic processes, which, in turn, influence brain circuit maturation. This dysregulation increases vulnerability to mental health disorders, including anxiety, depression, and cognitive decline. Biological aging markers, such as epigenetic clocks and cortisol dysregulation, have emerged as critical mediators of early life stress effects. For example, dysregulated cortisol levels are associated with disruptions in brain circuits governing emotion regulation and cognition. Brain alterations, measured as deviations from normative trajectories in structure and function, have also been observed in individuals with histories of early life stress, suggesting that stress-related biological mechanisms underpin neural and cognitive alterations.

Neuroimaging-genomics framework accelerates the discovery of intermediate phenotypes that affect brain development and neurodevelopmental disorders: Increasing evidence demonstrates that alterations in brain function and structure are present in both individuals with neurodevelopmental disorders and their unaffected relatives. For example, patients and unaffected siblings tend to present with cognitive dysfunction and brain circuit deficits, suggesting genetic burden of neurodevelopmental psychiatric risk is reflected in these neural pathways. An investigation of the genetic basis of these tracts is essential to identify endophenotypes that mediate the influence of genetic risk for neurodevelopmental disorders and cognition on brain circuits. We used neuroimaging-genomics technology to reveal the neural mechanisms through which genetic and molecular differences impact cognition, behavior, and clinical profiles in health and disease. Our central goal is that the imaging-genomics framework will accelerate the discovery of genetic variants that influence the development of brain function and structure and their association with neurodevelopmental disorders.

Recent publications:

1. Sha, Z., Warrier, V., Bethlehem, R.A.I., Schultz, L.M., Merikangas, A., Sun, K.Y., Gur, R.C., Gur, R.E., Shinahara R.T., Seidlitz, J., Laura, A., Andreassen O.A., Alexander-Bloch, A.F., 2025. The overlapping genetic architecture of psychiatric disorders and brain structure. Nature Mental Health
DOI: https://www.nature.com/articles/s44220-025-00475-7

2. Sha, Z., Sun, K., Jung, B., Barzilay, B., Moore, T., Almasy, L., Forsyth, J., Prem, S., Gandal, M., Seidlitz, J., Glessner, J., Alexander-Bloch, A., 2025. The copy number variant architecture of child psychopathology and cognitive development in the ABCD study. American Journal of Psychiatry
DOI: https://psychiatryonline.org/doi/full/10.1176/appi.ajp.20240445

3. Sha, Z., Pepe, A., Schijven, D., Carrion-Castillo, A., Roe, J.M., Westerhausen, R., Joliot, M., Fisher, S.E., Crivello, F., Francks, C., 2021. Handedness and its genetic influences are associated with structural asymmetries of the cerebral cortex in 31,864 individuals. The Proceedings of the National Academy of Sciences 118.
DOI: https://doi.org/10.1073/pnas.2113095118

4. Sha, Z., Schijven, D., Fisher, S.E., Francks, C, 2023. Genetic architecture of the white matter connectome of the human brain. Science Advances 9: eadd2870.
DOI: https://www.science.org/doi/10.1126/sciadv.add2870

5. Sha, Z., Schijven, D., Carrion-Castillo, A., Joliot, M., Mazoyer, B., Fisher, S.E., Crivello, F., Francks, C., 2021. The genetic architecture of structural left-right asymmetry of the human brain. Nature Human Behaviour 5, 1226-1239.
DOI: https://dx.doi.org/10.1038/s41562-021-01069-w

6. Sha, Z., Van Rooij, D., Anagnostou, E,…, Thompson, P. M., Fisher, S. E., Buitelaar, J. K., & Francks, C., 2021. Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium. 2021. Molecular Psychiatry 27(4), 2114– 2125.
DOI: https://doi.org/10.1038/s41380-022-01452-7

7. Sha, Z., Wager, T.D., Mechelli, A., He, Y., 2019. Common Dysfunction of Large-Scale Neurocognitive Networks Across Psychiatric Disorders. Biological Psychiatry 85, 379-388.
DOI: https://doi.org/10.1016/j.biopsych.2018.11.011