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Scientific Reports (2022) 12:12098

https://doi.org/10.1038/s41598-022-16326-9

Temporal response characterization across individual multiomics profiles of prediabetic and diabetic subjects

Minzhang Zheng1,2, Carlo Piermarocchi3, George I. Mias1,2,3*

1 Biochemistry and Molecular Biology, Michigan State University

2 Institute for Quantitative Health Science and Engineering, MSU

3 Physics and Astronomy, Michigan State University

Abstract

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Introduction

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Figure 1. Cohort description
Figure 1. Cohort description. Summary distributions across sexes for (a) Age, (b) observation window, (c) visits for different conditions, and (d) proportion of time series from different data modalities.
Figure 2. Workflow
Figure 2. Workflow for single-subject and multi-subject similarity analysis.

Methods

Summary of cohort details and data

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Data preprocessing

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Individual subject analysis

Time series categorization

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Clustering and heatmaps

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Reactome enrichment analysis

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Across subject comparisons

Network construction

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Network communities calculation

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Mann–Whitney U tests

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Results

Single subject analysis

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Figure 3. Single individuals’ multiomics clusters
Figure 3. Single individuals’ multiomics clusters.

Table 1. Statistically significant Reactome pathways

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Table 2. Frequency of signals with statistically significant temporal trends

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Multi-subject similarity analysis

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Figure 4. Similarity analysis across individuals
Figure 4. Similarity analysis across individuals.

Table 3. Mann–Whitney U test between communities

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Table 4. Reactome pathways for Communities 0 and 2

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Discussion

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Data availability

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References

  1. [References 1–49]

Acknowledgements

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Author contributions

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Competing Interests

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