# Methods for Unraveling the Impact of Dietary Xenobiotics on COPD Exacerbations with Multi-Dimensional Networks

> **NIH NIH K25** · BRIGHAM AND WOMEN'S HOSPITAL · 2024 · $162,677

## Abstract

PROJECT SUMMARY/ABSTRACT
Chronic obstructive pulmonary disease (COPD) is projected to become the third leading cause of
death globally by 2030. While smoking is a primary risk factor, a growing body of epidemiological
research points to the role of nutrition in modulating the risk for COPD and COPD-related
manifestations, including acute COPD exacerbations (AE-COPD). However, the mechanisms
underlying the impact of dietary components on COPD and AE-COPD are not well understood.
The primary objective of this proposal is to develop and implement a new set of machine learning
and network science-based methods specifically designed to explore the impact of dietary
xenobiotics (DXs) on AE-COPD. DXs are small molecules directly derived from food digestion,
absorption, and related metabolism, captured by untargeted metabolomics. This study ultimately
aims to gain a precise molecular understanding of the mechanisms driving the systemic effects
of diet on AE-COPD. The research design involves developing new methods that leverage the
multi-omics data from COPDGene and SPIROMICS, including longitudinal clinical and molecular
profiling of smokers with and without COPD. First, we will develop ensemble learning techniques
using plasma metabolomic data to identify a DX signature predictive of AE-COPD. Multiple
statistical strategies will be integrated to rank and group DXs based on their ability to predict AE-
COPD frequency and severity (Aim 1). Second, we will combine metric learning algorithms and
spectral theory to quantify the coordinated effect of DXs and circulating proteins on AE-COPD.
The goal is to capture the interplay between proteins and DXs in discerning exacerbation-prone
phenotypes (Aim 2). Third, we will utilize pre-trained deep learning models and network science
to implicate potential mechanisms of action of DXs on AE-COPD. A pipeline will be designed to
annotate and predict DXs’ protein targets and assess their proximity on the interactome to
different subregions of the COPD disease module, to key inflammatory proteins and epigenetic
modifiers (Aim 3). This K25 award will facilitate Dr. Menichetti’s comprehensive training in
longitudinal analysis, pulmonology, inflammatory processes, and integrative omics methods.
Addressing these training gaps will enhance her ability to develop reliable and translationally
relevant methods establishing the foundation for personalized dietary interventions based on
distinct COPD endotypes. Dr. Menichetti has crafted a detailed training plan and assembled a
mentoring team with complementary expertise, ensuring she will receive the necessary guidance
and support to successfully complete her proposal. This K25 will ultimately enable Dr. Menichetti’s
independent career in the methodological foundation of Precision Nutrition for lung disease.

## Key facts

- **NIH application ID:** 10863293
- **Project number:** 1K25HL173665-01
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** Giulia Menichetti
- **Activity code:** K25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $162,677
- **Award type:** 1
- **Project period:** 2024-04-01 → 2029-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10863293

## Citation

> US National Institutes of Health, RePORTER application 10863293, Methods for Unraveling the Impact of Dietary Xenobiotics on COPD Exacerbations with Multi-Dimensional Networks (1K25HL173665-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10863293. Licensed CC0.

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