Elevated Lactobacillus salivarius and genus Akkermansia in fecal samples of Taiwanese patients with parkinson’s disease and diabetes mellitus – Nature

Executive Summary: Gut Microbiota’s Role in Non-Communicable Diseases

This report details a prospective clinical study investigating the gut microbiota’s role in Parkinson’s disease (PD) and diabetes mellitus (DM), directly addressing Sustainable Development Goal 3 (SDG 3): Good Health and Well-being. Analysis of fecal samples from four cohorts (PD only, DM only, concurrent PD+DM, and healthy controls) revealed significant alterations in microbial populations. Key findings indicate an increased abundance of Lactobacillus salivarius and the genus Akkermansia in both PD and DM patients compared to healthy controls. These results suggest a shared gut microbiota signature, highlighting a potential common pathogenic pathway that could inform future therapeutic strategies for these non-communicable diseases, contributing to SDG 3 Target 3.4.

Introduction: Aligning Health Research with Sustainable Development Goals

The Global Burden of Non-Communicable Diseases and SDG 3

• Parkinson’s disease (PD) and diabetes mellitus (DM) represent a significant global health challenge, impacting millions and hindering progress towards SDG 3 (Good Health and Well-being).
• Target 3.4 of the SDGs aims to reduce premature mortality from non-communicable diseases through prevention and treatment.
• This study explores the epidemiological link between PD and DM, investigating the gut-brain axis as a common pathogenic mechanism, which is crucial for developing innovative health solutions.

Research Objective in the Context of Sustainable Innovation

• The primary objective was to test the hypothesis that patients with concurrent PD and DM exhibit similar gut microbiota dysbiosis.
• This research leverages advanced scientific methods, aligning with SDG 9 (Industry, Innovation, and Infrastructure) by applying technological advancements to address critical health issues.

Methodology: A Framework for Sustainable and Ethical Research

Study Design and Participant Cohorts

A prospective clinical cohort study was conducted, adhering to ethical standards approved by the Institutional Review Board of China Medical University Hospital. Four distinct cohorts were established:

1. Parkinson’s Disease (PD) only (n=32)
2. Diabetes Mellitus (DM) only (n=170)
3. Concurrent PD and DM (n=10)
4. Healthy Controls (HC) (n=98)

Data Collection and Microbiota Analysis

• Non-invasive fecal sample collection was utilized, promoting patient comfort and participation.
• Full-length (V1-V9) 16S rRNA gene sequencing was performed using advanced PacBio SMRT sequencing technology, reflecting an investment in scientific innovation (SDG 9).
• Genomic DNA was extracted using an automated system to ensure high quality and reduce contamination.

Statistical and Diversity Analysis

Comprehensive statistical analyses were conducted, including:

• α-diversity and β-diversity analyses (Shannon, Faith’s, Bray-Curtis, Jaccard).
• Permutational multivariate analysis of variance (PERMANOVA).
• Linear discriminant analysis (LDA) effect size (LEfSe) to identify differentially abundant features.

This rigorous analytical approach ensures the reliability of findings, a cornerstone of impactful research contributing to global health goals.

Key Findings: Gut Microbiota Signatures in PD and DM

Distinct Microbial Compositions Across Study Groups

• Principal coordinates analysis (PCoA) revealed statistically significant differences in gut microbiota composition among the four groups (p=0.001).
• PERMANOVA analysis confirmed significant differences between patient groups and healthy controls, particularly between HC vs. DM-only (p=0.001) and HC vs. PD-only (p=0.002).

Elevated Abundance of Specific Bacterial Taxa

• LEfSe analysis identified specific bacterial taxa with significantly different abundances.
• A notable increase in the abundance of Lactobacillus salivarius was observed in both PD patients (LDA=2.58, p
• Similarly, an elevated abundance of the genus Akkermansia was found in both PD (LDA=4.39) and DM (LDA=3.92) cohorts.

Discussion: Implications for Global Health and Sustainable Development

A Shared Pathogenic Link and its Relevance to SDG 3

• The elevated levels of L. salivarius and Akkermansia in both PD and DM cohorts suggest a shared feature of gut dysbiosis. This finding is critical for advancing SDG 3 by potentially uncovering common mechanisms for non-communicable diseases.
• Understanding these microbial signatures could lead to the development of novel biomarkers for early diagnosis and targeted probiotic or dietary interventions, directly supporting the goal of improving health outcomes.

The Role of Innovation and Partnership (SDG 9 & SDG 17)

• The study’s reliance on full-length 16S rRNA sequencing demonstrates the power of technological innovation (SDG 9) in advancing medical research.
• The collaboration between neurologists, endocrinologists, and laboratory scientists within a single clinical setting exemplifies the multi-stakeholder partnerships essential for achieving the SDGs (SDG 17).

Future Directions for Sustainable Healthcare

• Further research is required to elucidate the precise mechanisms by which these bacteria influence disease pathogenesis.
• Future studies incorporating biomarkers and larger patient cohorts will provide deeper insights, potentially leading to personalized and more sustainable therapeutic strategies that reduce the global burden of chronic disease.

Conclusion

This study provides significant evidence of a shared gut microbiota signature, characterized by elevated Lactobacillus salivarius and Akkermansia, in patients with PD and DM. These findings contribute directly to the ambitions of Sustainable Development Goal 3 by enhancing the understanding of non-communicable diseases. By leveraging scientific innovation (SDG 9) and collaborative partnerships (SDG 17), this research paves the way for future strategies aimed at improving prevention, diagnosis, and treatment, ultimately promoting good health and well-being for all.

Analysis of Sustainable Development Goals (SDGs) in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 3: Good Health and Well-being

  The article directly addresses health issues by focusing on two significant non-communicable diseases (NCDs): Parkinson’s disease (PD) and diabetes mellitus (DM). It investigates their pathogenesis, the connection between them, and explores the role of gut microbiota, which contributes to the broader goal of understanding and managing chronic diseases to ensure healthy lives.

• SDG 9: Industry, Innovation, and Infrastructure

  The study is built upon scientific research and technological innovation. The article explicitly mentions “advancements in non-invasive collection methods and technological innovations” and details the use of sophisticated techniques like “full-length (V1-V9) 16 S rRNA sequencing analysis” and automated DNA extraction systems. This commitment to advanced scientific research aligns with the goal of fostering innovation and upgrading technological capabilities.

2. What specific targets under those SDGs can be identified based on the article’s content?

• Under SDG 3: Good Health and Well-being

  • Target 3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being.

    The research into the pathogenesis of Parkinson’s disease and diabetes is a fundamental step toward developing better prevention and treatment strategies. The article discusses the increasing incidence of PD and considers DM a risk factor, highlighting the need for research that can lead to “disease-modifying agents” to combat these NCDs.

  • Target 3.b: Support the research and development of vaccines and medicines for the communicable and non-communicable diseases…

    The entire study is an example of research and development aimed at understanding NCDs. The introduction states, “scientists have been trying to develop disease-modifying agents, including gut microbiota interventions, based on the gut-brain axis theory for PD pathogenesis.” This directly supports the call for R&D to tackle major health challenges.

• Under SDG 9: Industry, Innovation, and Infrastructure

  • Target 9.5: Enhance scientific research, upgrade the technological capabilities of industrial sectors in all countries… encouraging innovation and substantially increasing the number of research and development workers…

    The study exemplifies the enhancement of scientific research. It was conducted at a “major academic healthcare center in Taichung, Taiwan,” involved a large team of researchers from multiple institutions, and was supported by grants from the “Ministry of Science and Technology, Taiwan.” The detailed methodology section, describing advanced sequencing and analysis pipelines, showcases the upgrading of technological capabilities in a research context.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

• For Target 3.4 (Reduce mortality from NCDs):

  • Incidence and prevalence of NCDs: The article mentions that the “incidence is increasing in the aging population” for PD and that there is an “increased incidence of PD among patients with type 2 diabetes mellitus.” These statistics are crucial for monitoring the burden of NCDs.
  • Clinical and biochemical markers of disease: The study collects data on “Hoehn and Yahr stage,” “Unified Parkinson’s Disease Rating Scale (UPDRS),” and “glycated hemoglobin (HbA1c).” These are specific, measurable indicators used to assess disease severity and control, which are essential for evaluating treatment effectiveness and progress in managing NCDs.

• For Target 3.b (Support R&D for medicines):

  • Number and scope of clinical studies: The existence of this “prospective clinical cohort microbiota study” is itself an indicator of ongoing R&D efforts.
  • Funding for medical research: The article acknowledges support from specific grants from “China Medical University Hospital” and the “Ministry of Science and Technology, Taiwan,” implying that R&D expenditure is being tracked and allocated to this area.

• For Target 9.5 (Enhance scientific research):

  • Investment in research infrastructure: The use of advanced equipment like the “PacBio Sequel® IIe system” and “QIAcube HT (an automated nucleic acid extraction system)” implies investment in and access to modern scientific infrastructure.
  • Number of researchers and scientific publications: The long list of authors and their affiliations with various research centers and universities, along with the publication of the study itself, serves as an indicator of the number of active researchers and the output of their work.

4. Summary Table of SDGs, Targets, and Indicators

Source: nature.com