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Principal Investigator Na Cai

Translational Genetics Group

Our aims

To use large-scale population-based association approaches to identify heterogenous subtypes of MDD.

To follow up genetic association results with multi-omics investigations of molecular mechanisms, so as to enable their clinical translation to improve diagnosis, monitoring and treatment of the disease.

Research

Na Cai’s research group focuses on understanding the etiology of neuropsychiatric conditions, with a particular focus on Major Depressive Disorder (MDD). MDD will be the second highest cause of morbidity by 2020 according to the World Health Organisation, with a lifetime prevalence of 10-20%. However, quantitative measures for its diagnosis and pharmaceutical interventions that are widely effective are still lacking. Following the first genome-wide association study (GWAS) that discovered 2 genetic loci for MDD in Han Chinese women (Cai et al., Nature 2015), large-scale biobanks, electronic health records (EHR) and commercial genotyping datasets have been utilized to discover more genetic association, with varying specificity to the disease (Cai et al., bioRxiv 2019). The challenge now is to uncover which of these associations are specific to MDD (or its subtype), and the molecular basis of heterogeneity in MDD. The group aims to approach this challenge in two related ways.

 

First aim

The first aims to identify the genetic, environmental and psychosocial factors that contribute to heterogeneity of MDD, the interactions between them, and how they may be shared with other psychiatric or other comorbid conditions. This can help us understand the basis of heterogeneity in MDD, as well as how best to study them using molecular means going forward. To this end, quantitative analysis on large population-based biobanks and disease datasets will be performed using state-of-the-art statistical models; this research also supports further development of appropriate models through collaborations (Speed et al., Na­ture Ge­net­ics 2017Weiss­brod et al., AJHG 2018Dahl et al., PLoS Ge­net­ics 2019Dahl et al., bioRxiv 2019)

Second aim

The second aim is to identify the molecular mechanisms indexed by genetic associations with MDD, which cell types in the body they occur in, and if they are modulated by the genetic background, the environment or the aging process. In particular, mitochondrial function is implicated by both persistent and environment-specific associations with MDD (Cai et al., Na­ture 2015Pe­ter­son and Cai et al., AJP 2018), mitochondrial DNA (mtDNA) is elevated in levels and mutations in MDD and chronic stress (Cai et al., Curr Bio 2015a-b), and mtDNA variations affect cellular metabolism with important implications on stress resilience (on-going work). To continue investigating mitochondria’s role in MDD and stress resilience, quantitative analysis on tissue-specific gene expression and function will be performed on multi-omic datasets, and experiments in cellular and animal models utilizing new sequencing and single cell technologies will be designed for testing specific hypotheses. 

By taking both population-based association and molecular genomics approaches, we aim to achieve the aim of translational genetics – where associations are followed up with molecular studies to arrive at a mechanistic understanding of the disease of interest and potential clinical translation.

Dr. Na Cai

Na is a statistical geneticist who recently completed her postdoc at the Wellcome Trust Sanger Institute and European Bioinformatics Institute (EMBL-EBI). She studied Natural Sciences (Biological) in Gonville and Caius College, Cambridge, then did her PhD on genetics of depression (Major Depressive Disorder, MDD) with Professor Jonathan Flint in the Wellcome Trust Centre for Human Genetics in Oxford.

While in Oxford, Na and colleagues found the first two robust and replicated genetic associations with MDD, and an intriguing phenomenon of increased levels of mitochondrial DNA (mtDNA) in cases of MDD compared to healthy controls. She further established chronic stress can cause reversible increases in mtDNA levels in multiple tissues in animal models. During her postdoc at the Sanger Institute and EMBL-EBI, she continued to study the genetic architecture of MDD, and assessed how large-scale biobank data may be utilised for it. She also worked to further the understanding of effects mtDNA has on cellular and systemic physiology using high-dimensional molecular data and functional studies in cell lines.

At HPC, Na’s work focus on finding the metabolic link to mental health conditions like MDD and how it may be shaped by genetics, environment and the aging process. Her ultimate goal is to use large-scale genetics, phenotyping, and multi-omics approaches to identify biological mechanisms, symptomatic profiles and biological markers to improve diagnosis, monitoring and treatment of the disease.

Factsheet

Positions and Career

 

2019 – Current: Principal Investigator Helmholtz Pioneer Campus, Helmholtz Zentrum München

2016 – 2019: EBI-Sanger Postdoctoral Fellow, Wellcome Sanger Insitute and European Bioinformatics Institute (EMBL-EBI)

 

 

 

2011 – 2016: DPhil in Clinical Medicine, Wellcome Trust Centre for Human Genetics, University of Oxford

 

2008 – 2011: BA (Hons), MA in Natural Sciences (Biological), University of Cambridge

 

 

 

2017 – 2019: Raymond and Beverley Sackler By-Fellowship (postdoctoral), Churchill College, University of Cambridge

 

2016 – 2019: EBI-Sanger Postdoctoral Fellowship (ESPOD), European Bioinformatics Institute, Wellcome Trust Sanger Institute

 

2011 – 2015: A*STAR Graduate Scholarship (Overseas), Agency of Science, Technology and Research, Singapore

 

2008 – 2011: Honorary Scholar, Cambridge Commonwealth Trust

 

2008 – 2011: National Science Scholarship, Agency of Science, Technology and Research, Singapore

 

 

2019: Chair of Gordon Research Seminar on Quantitative Genetics and Genomics

2019: Faculty at UCLA Computational Genetics Summer Institute (CGSI)

 

Na Cai will be the Vice-chair of Gordon Research Conference (GRC) on Quantitative Genetics and Genomics 2021 and Co-chair of GRC on Quantitative Genetics and Genomics 2023, and she is a faculty member at the UCLA Computational Genetics Summer Institute (CGSI). 

 

 

Join the Team

We are looking for talented individuals willing to develop and execute the next breakthrough ideas. A background in Genetics, Statistics, Computer Science, Bioinformatics or related biological or quantitative disciplines is desired. As research is a human enterprise, we recognize the individuality and humanity of each member of the team, and are committed to supporting their development and growth towards reaching their potential.

Selected Publications

Minimal phenotyping yields GWAS hits of low specificity for major depression

Cai N. et al., Minimal phenotyping yields GWAS hits of low specificity for major depression, bioRxiv (2019) doi: 10.1101/440735

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Using genetics to identify and model phenotypic subtypes

Dahl A. et al., Reverse GWAS: Using genetics to identify and model phenotypic subtypes, PLoS Genetics (2019) doi: 10.1371/journal.pgen.1008009

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Molecular genetic analysis subdivided by adversity exposure reveals etiologic heterogeneity in major depression

Peterson R. E., Cai N. et al., Molecular genetic analysis subdivided by adversity exposure reveals etiologic heterogeneity in major depression, American Journal of Psychiatry (2018) doi: 10.1176/appi.ajp.2017.17060621

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Reevaluation of SNP heritability in complex human traits

Speed D., et al., Reevaluation of SNP heritability in complex human traits, Nature Genetics (2019) doi: 10.1038/ng.3865

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Molecular genetic analysis subdivided by adversity exposure suggests etiologic heterogeneity in major depression

Peterson R. E., Cai N., Bigdeli T. B. et al., Molecular genetic analysis subdivided by adversity exposure suggests etiologic heterogeneity in major depression, JAMA Psychiatry (2017) doi: 10.1001/jamapsychiatry.2016.3578

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Genetic control over mtDNA and its relationship to major depressive disorder

Cai N. et al., Genetic control over mtDNA and its relationship to major depressive disorder, Current Biology (2015) doi: 10.1016/j.cub.2015.10.065
 

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Sparse whole genome sequencing identifies two loci for major depressive disorder

Cai N., Bigdeli T. B., Kretzschmar W. W., Li Y. et al., Sparse whole genome sequencing identifies two loci for major depressive disorder, Nature (2015) doi: 10.1016/j.cub.2015.03.008

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Molecular Signatures of Major Depression

Cai N., Chang S., Li Y. et al., Molecular Signatures of Major Depression, Current Biology (2015) doi: 10.1038/nature14659
 

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Contact us

HPC contact Engel

Contact

 

Helmholtz Pioneer Campus
Helmholtz Zentrum München
Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)

Ingolstädter Landstr. 1
85764 Neuherberg
Germany