Principal Investigator Na Cai
Translational Genetics Group
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.
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 2017; Weissbrod et al., AJHG 2018; Dahl et al., PLoS Genetics 2019; Dahl et al., bioRxiv 2019)
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 2015; Peterson 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.
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.
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
Honors and Awards
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: 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).
Cai N. et al., Minimal phenotyping yields GWAS hits of low specificity for major depression, bioRxiv (2019) doi: 10.1101/440735More Details
Dahl A. et al., Reverse GWAS: Using genetics to identify and model phenotypic subtypes, PLoS Genetics (2019) doi: 10.1371/journal.pgen.1008009More Details
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.2017.17060621More Details
Speed D., et al., Reevaluation of SNP heritability in complex human traits, Nature Genetics (2019) doi: 10.1038/ng.3865More Details
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.2016.3578More Details
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
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.2015.03.008More Details
Helmholtz Pioneer Campus
Helmholtz Zentrum München
Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)
Ingolstädter Landstr. 1