AndrewÌýGrotzinger

  • Adjunct Professor
  • PSYCHOLOGY & NEUROSCIENCE
  • INSTITUTE FOR BEHAVIORAL GENETICS

Research Interests:

Multivariate genomic methods development and their application to psychiatric and cognitive traits.

Active Grants:

  • NIA RF1 AG073593 (Tucker-Drob) 8/15/2021 – 7/31/2024 Large-scale Genomic Analysis of Aging-related Cognitive Change Prior to Dementia Onset. Role: Co-Investigator
  • NIMH R01 MH120219 (Nivard & Tucker-Drob) 07/17/2020-04/30/2025 Dissecting the Multivariate Genetic Architecture of Psychiatric Diseases. Role: Co-Investigator
  • Tommy Fuss Foundation Private Grant (Smoller) 1/1/2022 - 12/31/23. Mapping Genomics to Brain Structure, Psychiatric Disorders, and Therapeutic Targets. Role: Subcontract PI
  • HD027802 (PI: Willcutt), 7/1/23-6/30/28, "Differential Diagnosis in Learning Disabilities", Role: Co-Investigator on Data Core
  • NIA U01 AG083829 (Grotzinger), 9/30/2024 - 6/30/29, Longitudinal multi-omic biomarkers for neurocognitive decline prior to dementia onset, Role: Subcontract PI

Additional Resources:

Current CV

Grotzinger Current lab

Publications

Grotzinger News

Highlighted publications

This paper characterizes the genetic pathways for autism spectrum disorder (ASD) that are unique from the psychiatric disorder it has the highest genetic correlation with, ADHD. Results revealed clinical correlates (e.g., cognitive functions), functional annotations, and patterns of gene expression associated with this unique genetic signal in ASD.

(Molecular Autism, 2024)

Transcriptome-wide structural equation modeling (T-SEM) is applied to identify genes whose expression is associated with clusters of psychiatric disorders (e.g., internalizing disorders). Existing drugs that target these gene products are then identified for possible repurposing. As these pharmacological interventions target the genetic signal shared across multiple psychiatric disorders they could aid in reducing growing levels of polypharmacy, where several drugs are given to a single individual with comorbid presentations.

(JAMA Psychiatry, 2023)

Here we apply Genomic SEM to model the genetic architecture across 11 psychiatric disorders to find four genomic factors (Compulsive, Thought, Neurodevelopmental, Internalizing) defined by subclusters of disorders. We also introduce and validate Stratified Genomic SEM which can be used to model enrichment in a multivariate space.

(Nature Genetics, 2022)

This article provides an overview of recent findings in cross-disorder psychiatric genomics. This includes considering results at the genome-wide, functional, and genetic variant level of analysis along with possible future directions for the field.

(Psychological Medicine, 2021)

This article applies Genomic SEM to examine the genetic risk sharing across seven different cognitive traits from UK Biobank.
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(Nature Human Behavior, 2020)
In this publication we introduce and validate Genomic Structural Equation Modeling (Genomic SEM). Genomic SEM is a flexible, open-source, multivariate framework for modeling genetic overlap as estimated from GWAS summary statistics.
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(Nature Human Behavior, 2019)