Single-nucleotide variant proportion in genes: a new concept to explore major depression based on DNA sequencing data

Chenglong Yu, Bernhard Baune, Julio Licinio, Ma-Li Wong

    Research output: Contribution to journalArticle

    11 Citations (Scopus)

    Abstract

    Major depressive disorder (MDD) is a common psychiatric illness with significant medical and socioeconomic impact. Genetic factors are likely to play important roles in the development of this condition. DNA sequencing technology has the ability to identify all private genetic mutations and provides new channels for studying the biology of MDD. In this proof-of-concept study we proposed a novel concept, single-nucleotide variant proportion (SNVP), to investigate MDD based on whole-genome sequencing (WGS) data. Our SNVP-based approach can be used to test newly found candidate genes as a complement to genome-wide genotyping analysis. Furthermore, we performed cluster analysis for MDD patients and ethnically matched healthy controls, and found that clusters based on SNVP may predict MDD diagnosis. Our results suggest that SNVP may be used as a potential biomarker associated with major depression. Our methodology could be a valuable predictive/diagnostic tool as one can test whether a new subject falls within or close to an existing MDD cluster. Advances in this study design have the potential to personalized treatments and could include the ability to diagnose patients based on their full or part DNA sequencing data.

    Original languageEnglish
    Pages (from-to)577-580
    Number of pages4
    JournalJOURNAL OF HUMAN GENETICS
    Volume62
    Issue number5
    DOIs
    Publication statusPublished - 2017

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