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Na Cai - understanding the metabolic involvement behind mental health conditions

Dr. Na Cai

Dr. Na Cai is interested in understanding the metabolic involvement behind mental health conditions, specifically Major Depressive Disorder (MDD), and how it can be shaped by genetics, environment, and the aging process.

How? Using large-scale genetics, phenotyping, and multi-omics approaches to identify symptomatic profiles and biological markers to improve diagnosis, monitoring and treatment of the disease.


In this interview, she shares her motivation and future ambitions.


What is your main scientific aspiration?

I want to understand the etiology behind mental health conditions, specifically Major Depressive Disorder (MDD), predicted to be the second highest cause of morbidity by 2020 according to the World Health Organisation. Specifically, I want to look for the metabolic involvement to the disease, and how it can be shaped by genetics, environment, and the aging process.

Having always believed there is a physical basis for cognition and behaviour, I studied Neuroscience while I was an undergraduate in Cambridge. I was surprised that the vast quantity of knowledge in this field had yet to help researchers discover the physical basis of mental health conditions like MDD. Instead, MDD is still routinely diagnosed and characterized with interview-based diagnostic scales that are not always consistent, and there are no physiological measures for it like there is for Diabetes. As such, MDD remains a heterogeneous disease with diverse clinical features (depending on which scales or criteria were used for diagnosis).  The debate of whether MDD is one or many different diseases, each with its own (though potentially overlapping) molecular basis and symptom manifestations, is very much on-going.

Molecular understanding of the disease through genetics and genomics, in combination with deep-phenotyping of both clinical features and environmental factors, is the way forward. My ultimate goal is to use large-scale genetics, phenotyping, and multi-omics approaches to identify symptomatic profiles and biological markers to improve diagnosis, monitoring and treatment of the disease.


Why did you choose to join the HPC?

HPC brings together early career investigators from diverse backgrounds, allowing and prompting us to find synergies across disciplines – I am certain this will lead to breakthroughs that would not otherwise be possible, and I am privileged to be a part of it. Further, HPC is embedded in a larger research community in Munich that I can introduce my research to, learn from, and seek collaborations with. I am very excited to be in close proximity to the world-leading expertise in both population-scale quantitative genetics and single-cell analysis methods from the Institutes of Translational Genomics and Computational Biology in HGMU, as well as the psychiatric genetics, neuroscience, and molecular biology communities in HGMU, the Max Planck Institutes, TUM and LMU. Lastly and importantly, the support and resources HPC has given me will enable me to hit the ground running.


How are you planning to answer your scientific questions?

Large-scale biobanks, electronic health records (EHR) and omics databases provide unprecedented opportunities for genetic research, and are transforming the way we design studies and test hypotheses. Following my work on phenotype benchmarking for genome-wide association studies (GWAS) on MDD in the UKBiobank dataset, which has demonstrated the utility of different phenotyping approaches, I now hope to design more targeted studies using data available from these resources. Further, through analysis of environmental or psychosocial factors in disease cohorts, my collaborators and I have already started identifying factors that stratify heterogeneous cases of MDD, and identified genetic factors specific to subtypes. As such, the first part of my plan would be to further dissect the heterogeneity in MDD leveraging clinical, environmental, comorbidity and molecular data from biobanks, EHR and omics databases.

Using the agnostic approach of genome-wide association studies (GWAS), my previous work has shown that there is likely a metabolic link to severe recurrent MDD, and a small part of our genome called the mitochondrial DNA (mtDNA) may be key. I would like to find the mechanism through which mtDNA copy number and somatic mutations (heteroplasmy) are elevated by chronic stress, and how that relates to the same phenomenon in depression. In addition, my on-going work is starting to illuminate how common inherited variations in the mtDNA affect efficiency of oxidative phosphorylation (OXPHOS), with important implications on oxidative damage accumulation and resilience to stress signals. Taken together, both inherited and somatic mtDNA variations may have roles to play in health and disease. My plan would therefore be to investigate the impact of mtDNA variations on molecular traits, how they may affect each tissue differently, how this effect may be age and environment dependent, and how they may be related to risk for neuropsychiatric conditions and molecular changes in MDD.


Which are your interests beside research?

I am very excited to check out Munich’s cultural scene. My PhD supervisor attributes my “stage presence” in giving academic talks to my experience as a flute soloist in a Chinese Orchestra when I was in high school in Singapore. I have not played in years, and probably shouldn’t be allowed to, but I enjoy going to performances.