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- Addiction and Innovative Methodology (AIM) Lab
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Biobehavioral Health Studies Lab
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Bio-Qualitative Research Lab (BioQUAL)
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- Decision Neuroscience
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Epidemiology and Genetics across Populations & Societies Lab
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Family and Child Health Project
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- Molecular Genetics Lab
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Sleep, Health & Society Collaboratory
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Stress and Immunity Lab
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Stress and Nutrition Research Program
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Water, Health, & Nutrition Lab
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Veturi Lab
Research overview:
Individuals in a population have varying degrees of risk of disease, which is driven by a unique combination of rare and common variants that interact with each other and the environment in complex biological networks. My research passion is to understand the underlying genetic mechanisms that would help us better identify high-risk patients from Electronic Health Records (EHR) in advance of being afflicted with disease. The focus of our lab is to develop novel machine learning methods and workflows to integrate high dimensional information (imaging data, EHR and multi-“omic” data such as high-density genotyping/genome sequencing, gene expression) across ancestral groups, sexes and environments to better understand the genetic etiology of complex human diseases across the “phenome”, and their connections with cognitive decline.
We address the following questions of broad societal interest:
- What are shared genetic pathways (using rare/common variants associated with cognitive decline?
- What are the genetic underpinnings of how risk factors of cardiometabolic disease (e.g., stress) associate with cognitive decline?
- Are there causal pathways among these interrelationships?
- How do gene-gene and gene-environment interactions affect these interrelationships?
- How do sex and ancestry impact development of disease mechanisms that can guide improved clinical interventions in underrepresented groups in medicine?
- How do we leverage these new discoveries to improve prediction accuracy of risk of cognitive decline?
Current projects:
- Data-driven multi-omic analysis of pleiotropy between neuroimaging and diseases in EHR
- Methods to understand the genetic basis of sex differences in cognitive decline
Director, Yogasudha Veturi, Ph.D.
Consider joining Dr. Veturi's lab:
Candidates interested in a PhD, postdoc or staff scientist/programmer role are welcome to contact me by email: yzv101@psu.edu or on Twitter: @sudhaveturi.
Learn more about Dr. Veturi's work:
- https://www.nature.com/articles/s41588-021-00879-y
- http://reachmd.curatasite.com/articles/share/1635683/
- https://academic.oup.com/genetics/article/211/4/1395/5931519
- https://www.nature.com/articles/s41586-021-04064-3
- https://www.sciencedirect.com/science/article/pii/S2666979X22001410
- https://jamanetwork.com/journals/jamapsychiatry/article-abstract/2789902
- https://academic.oup.com/genetics/article/211/4/1395/5931519
Google Scholar https://scholar.google.com/citations?user=y75cFc0AAAAJ&hl=en