A novel strategy for clustering major depression individuals using whole-genome sequencing variant data

Chenglong Yu South Australian Health and Medical Research Institute Bernhard T. Baune University of Adelaide Julio Licinio South Australian Health and Medical Research Institute Ma-Li Wong South Australian Health and Medical Research Institute

Data Analysis, Bio-Statistics, Bio-Mathematics mathscidoc:1703.42005

Scientific Reports, 7, (44389), 2017
Major depressive disorder (MDD) is highly prevalent, resulting in an exceedingly high disease burden. The identification of generic risk factors could lead to advance prevention and therapeutics. Current approaches examine genotyping data to identify specific variations between cases and controls. Compared to genotyping, whole-genome sequencing (WGS) allows for the detection of private mutations. In this proof-of-concept study, we establish a conceptually novel computational approach that clusters subjects based on the entirety of their WGS. Those clusters predicted MDD diagnosis. This strategy yielded encouraging results, showing that depressed Mexican-American participants were grouped closer; in contrast ethnically-matched controls grouped away from MDD patients. This implies that within the same ancestry, the WGS data of an individual can be used to check whether this individual is within or closer to MDD subjects or to controls. We propose a novel strategy to apply WGS data to clinical medicine by facilitating diagnosis through genetic clustering. Further studies utilising our method should examine larger WGS datasets on other ethnical groups.
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@inproceedings{chenglong2017a,
  title={A novel strategy for clustering major depression individuals using whole-genome sequencing variant data},
  author={Chenglong Yu, Bernhard T. Baune, Julio Licinio, and Ma-Li Wong},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20170314083718718191686},
  booktitle={Scientific Reports},
  volume={7},
  number={44389},
  year={2017},
}
Chenglong Yu, Bernhard T. Baune, Julio Licinio, and Ma-Li Wong. A novel strategy for clustering major depression individuals using whole-genome sequencing variant data. 2017. Vol. 7. In Scientific Reports. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20170314083718718191686.
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