Team Members - Ali, Alicia, Cayden, David, John
Link to dataset source from Cirstea et al. - https://doi.org/10.1002/mds.28052
Parkinson’s Disease (PD) is a neurodegenerative disorder associated with dopaminergic neuron loss, leading to dopamine dysregulation. Dopaminergic therapeutics are often administered to restore dopamine levels and have been associated with changes to the gut microbiota. Through a secondary data analysis of a cross-sectional cohort of PD patients, we aimed to explore the use of four dopaminergic drugs (entacapone, pramipexole, rasagiline, amantadine) and the associated changes in the gut microbiome. Although the use of dopaminergic therapeutics was not associated with compositional alterations to the microbial diversity of PD patients, we observed changes to specific taxa. Amantadine and pramipexole therapeutics were both associated with a core microbiome that contains Faecalibacterium – a genus contained in the core microbiome of healthy individuals but absent in untreated PD patients. Furthermore, entacapone and amantadine use was associated with taxa that are indicative of a healthy gut microbiome, including Lachnospiraceae and Colidextribacter. We also identified three genera that were differentially abundant with dopaminergic drug use. Dopaminergic therapeutic use was generally associated with increased Bifidobacterium, decreased Prevotella, and increased Akkermansia. While increased Bifidobacterium is associated with a healthier gut microbiome and Akkermansia is associated with gut dysbiosis, the effects of Prevotella remain unclear. Our findings suggest that dopaminergic therapeutics are associated with alterations in the gut microbiome of PD patients that provide an overall benefit to the host. Future studies could incorporate higher resolution analysis at the species level, and explore causational effects of dopaminergic drugs in a prospective study.
Click on the aim to view output files
Aim 1A - QIIME2 processing
Aim 1B - Metadata wrangling
Aim 2 - Alpha and beta diversity analysis in R
Aim 3 - Core microbiome analysis
Aim 4 - Indicator species analysis
Aim 5 - Differential abundance analysis
Final Consolidated Meeting Notes
Individual Meeting Notes - All
Includes brief summaries of what was completed throughout the project duration.
Alicia - updated core microbiome
Cayden - updated volcano plot titles
Ali - updated the diversity plots
Alicia - updated the color codes for core microbiome figures
Cayden - updated DESeq plots
Ali - Linear regression analysis of identified genera from DESeq
David - Added meeting notes of all previous meetings up to this point Ali - Added additional files Alicia - Added abundances for core microbiome along with a 3 way venn diagram
David - Minor changes to ISA
Cayden - minor changes to plots
Cayden - Updated the genus bar plots
David - Changed ISA output, adjusted and fixed some code Cayden - Added genus sums for DESeq analysis
Cayden - updated DESeq barplot titles
Cayden - Reformatted barplots Alicia - reconducted core microbiome analysis at 1% detection
Cayden:
- uploaded optional code for volcano plots including labels
- further DESeq analysis results
- including excel sheets (csvs) for comparison across all the genuses
John - changed formatting
Cayden - conducted DESeq analysis and uploaded code for DESeq, generated figures and plots John - fixing project files and file paths for DESeq
Ali - conducted pairwise beta diversity analysis and comparisons
David - Changed code for ISA, added excel sheets to generate tables for manuscript
Alicia - adding to core microbiome code and providing venn diagram images as potential figures
Ali - addded the alpha and beta diversity metrics, along with code
David - Updated script for indicator species analysis, added R script for ISA, edited some code
Ali - Added Meeting agenda, core microbiome analysis
Alicia - Added TSV and code for rough heatmap
David - Edited the R file, moved into R folder
John - fixed R file path script
Ali - Changed 'treatment' column from numeric to factor; saved metadata as .txt file; created new RProject for phyloseq object; created script for phyloseq object 'pd_phyloseq' and saved as .RData file
John - Uploaded new pd_metadata_treatment.tsv to server. Compiled table, taxa bar plots, and no mitochondria no chloroplast table as viewable .qzv files with new pd_metadata_treatment.tsv file.
John - Using table-no-mitochondria-no-chloroplast_treatment.qzv, we found a maximum sampling depth of 5421 in order to retain at least 6 samples in all treatment categories. Alpha-rarefaction curve displayed that 5421 falls under the plateau.
John - Created README file. Imported and demultiplexed parkinsons sequences. Denoising, clusterng, taxonomic training, filtering, and export conducted.
Ali - Removed NAs from PD drug columns. Added "treatment" column numbered 1-7 for the following treatments:
control = 1
pd_untreated = 2
pd_entac = 3
pd_prami = 4
pd_rasag = 5
pd_amant = 6
pd_combo = 7
John - All high quality reads throughout. Setting a standard of 30 for median quality score, no trimming is required. 251 is the trimming parameter and the length of all of the sequences.