# A cross-sectional and longitudinal study of gut microbiota in Parkinson's disease

> **NIH NIH U01** · UNIVERSITY OF CHICAGO · 2024 · $492,000

## Abstract

Project Summary/Abstract
The majority of the PD patients have a long history of constipation before the onset of the motor symptoms of
PD. Abnormal gut microbiota (dysbiosis) and its metabolomics have been proposed to play a crucial role in the
formation and migration of pathologies found in Parkinson’s disease (PD) – leading to the notion of a “Gut
Microbiome-Brain Axis” in the pathogenesis of PD. However, it remains unclear whether the PD-associated gut
dysbiosis is a cause or consequence. The goal of the proposed studies is to gain a better understanding of the
role of gut dysbiosis in the development, progression, and prognosis of PD, which will lay the foundation for the
identification of microbiome-based predictive biomarkers and open opportunities to develop gut microbiome-
based targeted interventions to prevent, mitigate and treat different phenotypes or forms of PD at various stages.
Our multi-disciplinary team proposes a multi-pronged approach that will include cross-sectional and longitudinal
studies of PD patients with different age at the onset, clinical manifestation, and severity of motor and non-motor
symptoms. Clinical metadata will be collected along with fecal microbiota samples that will be subjected to
functional multi’omic analyses that includes two discovery tools: a supervised metabolomics panel and a novel
transfer RNA-based (MSRseq) technology developed by our team that can simultaneously track gut microbial
membership and function on different time scales. These measures are important in defining states of gut
microbiota health and managing patients with gut dysbiosis back to eubiosis. Our studies will also be unique
because of the large Black PD patient population at the University of Chicago (35% here vs < 6% elsewhere)
who come from underserved urban communities on the South and West sides of Chicago. So little information
is available on Black populations with PD because of disparities in socioeconomic status and health care access.
The clinical study design is unique in having both cross-sectional and longitudinal arms and training and
validation cohort components, where fecal microbiota and skin and colonoscopic biopsies for α-synuclein will be
collected at years 1, 3 and 5 along with clinical metadata that includes PD phenotypes or forms, age at disease
onset (early vs usual mid vs late onset), clinical manifestations (tremor dominant vs akinetic rigidity or postural
instability and gait disorder form vs the mixed), severity of motor and non-motor symptoms, and race (Black vs
White), and age- and sex-matched healthy controls. Machine learning (ML) and artificial intelligence (AI) will be
used to identify best performing PD predictive gut microbiota and metabolic biomarkers. To gain additional
insights into potential gut microbial drivers and mediators that underpin etiopathogenesis of different PD
phenotypes and progression, we will identify PD-promoting microbiota candidates and mediators for which
microbiome-b...

## Key facts

- **NIH application ID:** 10987823
- **Project number:** 1U01DK140936-01
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** EUGENE B CHANG
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $492,000
- **Award type:** 1
- **Project period:** 2024-08-15 → 2029-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10987823

## Citation

> US National Institutes of Health, RePORTER application 10987823, A cross-sectional and longitudinal study of gut microbiota in Parkinson's disease (1U01DK140936-01). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10987823. Licensed CC0.

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