# Statistical Methods for Enhanced Mapping of Microbiome Relationships

> **NIH NIH R01** · FRED HUTCHINSON CANCER CENTER · 2024 · $300,219

## Abstract

PROJECT SUMMARY/ABSTRACT
The human microbiome is integrally related to a vast range of human disorders and represents an imperative
gateway toward mitigating the burden of these diseases, particularly as the microbiome is eminently modifiable.
This has culminated in microbially oriented risk reduction and clinical interventions, which have proven
efficacious in diverse situations ranging from infections to cancer immunotherapy. However, despite some high-
profile successes, many other studies have failed. A central theme underlying these failures, and even many of
the success stories, is our fundamentally limited understanding of how microbes interact with each other, with
host genomics, and with outcomes. Recently, efforts to assess and map these relationships are taking place
within large-scale profiling studies, but unfortunately, the tools used for elucidating these connections may be
underpowered, difficult to interpret, or even subject to severe false positives due to strong underlying
assumptions. Therefore, motivated by problems within three of the largest and richest microbiome profiling
studies, this proposal seeks to fill critical gaps in the methodological literature by addressing four major areas.
Specifically, we aim to develop a comprehensive suite of tools for (1) enhanced microbial co-occurrence network
construction; (2) enhanced discovery of SNPs and rare variants associated with individual microbial taxa; and
(3) assessing the role of microbes through Mendelian Randomization. These approaches are all based on
rigorous prior data emphasizing the importance of the problems as well as the limitations of existing strategies.
Our work is motivated by and will directly enable analyses in three of the largest and richest microbiome profiling
studies, including the MEC and SOL cohorts which study the gut microbiome, and the PIN cohort, which explores
the vaginal microbiome in pregnancy. Accordingly, the methods we develop have the potential to improve our
fundamental knowledge of the microbiome and propel the field towards enhanced risk reduction and clinical
interventions.

## Key facts

- **NIH application ID:** 10928193
- **Project number:** 5R01GM151301-02
- **Recipient organization:** FRED HUTCHINSON CANCER CENTER
- **Principal Investigator:** MICHAEL Chiao-An WU
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $300,219
- **Award type:** 5
- **Project period:** 2023-09-15 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10928193

## Citation

> US National Institutes of Health, RePORTER application 10928193, Statistical Methods for Enhanced Mapping of Microbiome Relationships (5R01GM151301-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10928193. Licensed CC0.

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