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Type 2 Diabetes Biomarkers of Human Gut Microbiota Selected via Iterative Sure Independent Screening Method

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  • Lihua Cai
  • Honglong Wu
  • Dongfang Li
  • Ke Zhou
  • Fuhao Zou

Abstract

Type 2 diabetes, which is a complex metabolic disease influenced by genetic and environment, has become a worldwide problem. Previous published results focused on genetic components through genome-wide association studies that just interpret this disease to some extent. Recently, two research groups published metagenome-wide association studies (MGWAS) result that found meta-biomarkers related with type 2 diabetes. However, One key problem of analyzing genomic data is that how to deal with the ultra-high dimensionality of features. From a statistical viewpoint it is challenging to filter true factors in high dimensional data. Various methods and techniques have been proposed on this issue, which can only achieve limited prediction performance and poor interpretability. New statistical procedure with higher performance and clear interpretability is appealing in analyzing high dimensional data. To address this problem, we apply an excellent statistical variable selection procedure called iterative sure independence screening to gene profiles that obtained from metagenome sequencing, and 48/24 meta-markers were selected in Chinese/European cohorts as predictors with 0.97/0.99 accuracy in AUC (area under the curve), which showed a better performance than other model selection methods, respectively. These results demonstrate the power and utility of data mining technologies within the large-scale and ultra-high dimensional genomic-related dataset for diagnostic and predictive markers identifying.

Suggested Citation

  • Lihua Cai & Honglong Wu & Dongfang Li & Ke Zhou & Fuhao Zou, 2015. "Type 2 Diabetes Biomarkers of Human Gut Microbiota Selected via Iterative Sure Independent Screening Method," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-15, October.
    • Handle: RePEc:plo:pone00:0140827
    DOI: 10.1371/journal.pone.0140827
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    References listed on IDEAS

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    1. Fredrik H. Karlsson & Valentina Tremaroli & Intawat Nookaew & Göran Bergström & Carl Johan Behre & Björn Fagerberg & Jens Nielsen & Fredrik Bäckhed, 2013. "Gut metagenome in European women with normal, impaired and diabetic glucose control," Nature, Nature, vol. 498(7452), pages 99-103, June.
    2. Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
    3. Robert Tibshirani & Michael Saunders & Saharon Rosset & Ji Zhu & Keith Knight, 2005. "Sparsity and smoothness via the fused lasso," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(1), pages 91-108, February.
    4. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    5. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
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    Cited by:

    1. Green, Brittany & Lian, Heng & Yu, Yan & Zu, Tianhai, 2023. "Semiparametric penalized quadratic inference functions for longitudinal data in ultra-high dimensions," Journal of Multivariate Analysis, Elsevier, vol. 196(C).

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