Wesley K. Thompson, Ph.D. 

Associate Professor In-Residence

 

Contact Information

wkthompson@ucsd.edu

Biography

Dr. Thompson earned his Ph.D. in Statistics from Rutgers University in 2003, with a focus on statistical methods for longitudinal data analysis. He was appointed Assistant Professor of Statistics and Psychiatry at the University of Pittsburgh in 2005, where he received a five year NIH K25 Career Development Award to develop novel methods for studying co-variation in brain function and depression. Dr. Thompson joined the UCSD Department of Psychiatry in 2008. His current work involves Bayesian semi-parametric and mixture models with applications to (i) improving effect size estimation, replication, and prediction in genome-wide association studies, (ii) predicting onset of illness from multivariate biomarker trajectories, (iii) applications of functional data analysis to functional MRI data.

Research Interests

Research Focus

Dr. Thompson's research focuses on the development and application of semi-parametric Bayesian hierarchical and mixture models for multivariate data, with applications to diverse areas of biological psychiatry. These applications include: 1) human brain imaging and other biological markers of mental illness; 2) improved replication and polygenic risk score estimation from genome-wide association studies; 3) estimation of developmental trajectories and prediction of outcomes from incomplete longitudinal data; and 4) prediction of clinical outcomes from intensively sampled longitudinal data.

Publications

  • Thompson WK, Gershon A, O’Hara R, Depp C (2014). The Prediction of Study-Emergent Suicidal Ideation in Bipolar Disorder: A Pilot Study Using Ecological Momentary Assessment Data. Bipolar Disorders. To appear.
  • Zablocki RW, Levine R, Schork AJ, Andreassen OA, Dale AM, and Thompson WK (2014). Covariate-Modulated Local False Discovery Rate for Genome-Wide Association Studies. Bioinformatics. doi: 10.1093/bioinformatics/btu145.
  • Andreassen OA, Thompson WK, Dale AM (2014). Boosting the power of schizophrenia genetics by leveraging new statistical tools. Schizophrenia Bulletin. 40, 13-17.
  • Rosen O and Thompson WK (2014). Bayesian Semiparametric Copula Estimation with Application to Psychiatric Genetics. Biometrical Journal.
  • Schork AJ, Thompson WK, Pham P, Torkamani A, Roddey JC, Sullivan PF, Kelsoe JR, Purcell SR, O’Donovan MC, the Tobacco Consortium, The Bipolar Disorder Psychiatric Genome-Wide Association Study (GWAS) Consortium, The Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium, Schork NJ, Andreassen OA, Dale AM (2013). All SNPs Are Not Created Equal: Genome-Wide Association Studies Reveal a Consistent Pattern of Enrichment among Functionally Annotated SNPs. PLoS Genetics 9, e1003449. doi:10.1371/journal.pgen.1003449.
  • Andreassen OA, Thompson WK, Ripke S, Schork AJ, Mattingsdal M, Kelsoe J, Kendler KS, O’Donovan MC, Rujescu D, Werge T, Sklar P, The Psychiatric Genomics Consortium (PGC) Bipolar Disorder and Schizophrenia Working Groups, Roddey JC, Chen C-H, Desikan RS, Djurovic S, Dale AM (2013). Improved detection of common variants associated with schizophrenia and bipolar disorder using pleiotropy-informed conditional False Discovery Rate method. PLoS Genetics 9: e1003455. doi:10.1371/journal.pgen.1003455.
  • Thompson WK, Choi J, Anderson S (2013). Prediction Models. In Lavretsky et al. (Eds.) Late Life Mood Disorders. Oxford University Press: New York.
  • Thompson WK, Savla G, Vahia I, Depp C, O’Hara R, Jeste DV, Palmer B. (2013). Trajectories of Cognitive Functioning in Older Adults with Schizophrenia: Does Method Matter? Schizophrenia Research, 143: 90-96.
  • Siegle G, Thompson WK, Thase M, Collier A, Berman S, Friedman E (2012). Towards clinically employable neuroimaging in depression treatment: Is subgenual cingulate activity robustly prognostic for depression outcome in Cognitive Therapy across studies, scanners, and patient characteristics? Arch Gen Psychiatry 69, 913-923.
  • Thompson WK and Holland D (2011). Bias in Tensor Based Morphometry Stat-ROI Measures May Result in Unrealistic Power Estimates. NeuroImage; 57, 1-4.
  • Thompson WK, Hallmayer J., O’Hara R (2011). Design Considerations for Characterizing Psychiatric Trajectories across the Lifespan. Am J Psychiatry; 9, 894-903.
  • Versace A, Thompson WK, Zhou D, Almeida J, Hassel S, Klein C, Kupfer DJ, Phillips ML. (2010). Right-left asymmetry in orbitomedial prefrontal cortical-amygdala functional connectivity to negative versus positive emotion in adult bipolar disorder. Biol Psychiatry, 67, 5, 422-431. Zhou D, Thompson WK, Siegle GJ. (2009). MATLAB toolbox for functional connectivity. NeuroImage, 47, 4, 1590-1607.
  • Thompson WK and Siegle GJ (2009). A Stimulus-Locked Vector Autoregressive Model for Slow Event-Related fMRI Designs. NeuroImage, 46, 3, 739-748.
  • Siegle GJ, Thompson WK, Carter CS, Steinhauer SR, and Thase ME (2007). Increased amygdala and decreased prefrontal BOLD responses in depression: Related and independent features. Biological Psychiatry. 61, 198-209.
  • Thompson WK and Rosen O (2008). A Bayesian model for sparse functional data. Biometrics. 64, 54-63.