In Parkinson's disease (PD), gastrointestinal features are common and often precede the motor signs. Braak and colleagues proposed that PD may start in the gut, triggered by a pathogen, and spread to the brain. Numerous studies have examined the gut microbiome in PD; all found it to be altered, but found inconsistent results on associated microorganisms. Studies to date have been small (N = 20 to 306) and are difficult to compare or combine due to varied methodology. We conducted a microbiome-wide association study (MWAS) with two large datasets for internal replication (N = 333 and 507). We used uniform methodology when possible, interrogated confounders, and applied two statistical tests for concordance, followed by correlation network analysis to infer interactions. Fifteen genera were associated with PD at a microbiome-wide significance level, in both datasets, with both methods, with or without covariate adjustment. The associations were not independent, rather they represented three clusters of co-occurring microorganisms. Cluster 1 was composed of opportunistic pathogens and all were elevated in PD. Cluster 2 was shortchain fatty acid (SCFA)-producing bacteria and all were reduced in PD. Cluster 3 was carbohydrate-metabolizing probiotics and were elevated in PD. Depletion of anti-inflammatory SCFA-producing bacteria and elevated levels of probiotics are confirmatory. Overabundance of opportunistic pathogens is an original finding and their identity provides a lead to experimentally test their role in PD.

In Parkinson's disease (PD), gastrointestinal features are common and often precede the motor signs. Braak and colleagues proposed that PD may start in the gut, triggered by a pathogen, and spread to the brain. Numerous studies have examined the gut microbiome in PD, all found it to be altered, but found inconsistent results on associated microorganisms. Studies to date have been small (N=20 to 306) and are difficult to compare or combine due to varied methodology. We conducted a microbiome-wide association study (MWAS) with two large datasets for internal replication (N=333 and 507). We used uniform methodology when possible, interrogated confounders, and applied two statistical tests for concordance, followed by correlation network analysis to infer interactions. Fifteen genera were associated with PD at a microbiome-wide significance level, in both datasets, with both methods, with or without covariate adjustment. The associations were not independent, rather represented 3 clusters of co-occurring microorganisms. Cluster 1 was composed of opportunistic pathogens; all were elevated in PD. Cluster 2 were short-chain-fatty-acid producing bacteria; all were reduced in PD.Cluster 3 were carbohydrate-metabolizing probiotics; elevated in PD. Depletion of antiinflammatory short-chain-fatty-acid producing bacteria and elevated levels of probiotics are confirmatory. Overabundance of opportunistic pathogens is a novel finding and their identity provides a lead to experimentally test their role in PD. animal models. [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] Every study that has compared the global composition of the gut microbiome in PD vs. controls found it to be significantly altered; in contrast, attempts to identify PD-associated microorganisms have produced inconsistent results. 31,32 Low reproducibility has been attributed to small sample sizes (missing true associations due to low power), relaxed statistical thresholds (inflating false positive results), and publishing without a replication dataset (required for genomic studies). Differences in methods of DNA extraction, sequencing, bioinformatics and statistics can all contribute to inter-study variations. The choice of taxonomic resolution for analysis (PD has been tested at all levels from phylum to species) and the inconsistent taxonomic assignments and nomenclature used in various reference databases add to the confusion when comparing results. Last but not least, is confounding by heterogeneity in the populations that were studied: PD is heterogenous and so is the microbiome. PD subtypes cannot be readily identified thus patient populations are inevitably varied. A myriad of factors can affect the microbiome ranging from diet, health and medication to cultural habits, life-styles, race and geography. 33,34 Identifying microorganisms involved in the dysbiosis of the microbiome is essential for understanding their role in disease. We conducted a hypothesis-free microbiome-wide association study (MWAS) modeled after and usi...

In December 2020, the U.S. Food and Drug Administration licensed COVID-19 vaccines for emergency use authorization. We investigated the ocular adverse event reports in patients reported to the Vaccine Adverse Event Reporting System (VAERS) following vaccination against COVID-19. We searched the VAERS database for U.S. reports among persons who received COVID-19 vaccines between December 2020 and December 2021. Our goal was to analyze and quantify the ocular adverse events submitted to VAERS to provide clinicians and researchers with a broader view of these ocular side effects. During the analysis period, VAERS received 55,313 adverse event reports and, after data cleaning, 6688 reports met the inclusion criteria. Note that 2229 (33.33%) adverse events were classified as cases of eyelid swelling, ocular hyperemia and conjunctivitis, 1785 (26.69%) as blurred vision and 1322 (19.77%) as visual impairment. Females accounted for 73.8% of adverse event reports and the age group between 40 and 59 years had the most frequent adverse events. A higher proportion of these adverse events reported to VAERS was linked with the Janssen and Moderna COVID-19 vaccines. At the time of vaccination, a high proportion of patients reported conditions like allergies, hypertension, diabetes, thyroid disease, vascular and other autoimmune diseases. A review of these data suggests a possible association between COVID-19 vaccines and ocular adverse events. Physicians are cautioned not only to be aware of this potential problem, but to check any underlying patient conditions, and to carefully document in VAERS within a few weeks of vaccination. Future COVID-19 vaccine safety studies in healthy subjects would help clarify the vaccine’s safety profile.

The USA has become increasingly diverse resulting in greater strides to improve workforce diversity and inclusivity. The objective of this study is to compare the experiences of trainees in Graduate Medical Education who identify as Lesbian, Gay, Bisexual, Transgender or Questioning (LGBTQ) to the experiences of non-LGBTQ trainees within the medical workplace. We conducted a cross-sectional, exploratory survey from 1 December 2020 to 14 January 2021 at a single, large teaching institution. We collected data anonymously and stored it in a REDCap database. We excluded surveys in which trainees did not respond to sexual orientation. We used contingency tables and Fisher’s exact test to identify outcomes associated with sexual orientation and gender identity particularly with regard to professionalism, well-being, and satisfaction with training. We distributed the survey to 840 trainees. 730 trainees were included (23 (3.2%) LGBTQ and 707 (96%) Straight). LGBTQ trainees were more likely to experience offensive remarks based on race/ethnicity (p = 0.03) and sexual orientation (p = 0.01). Secondary analysis based on race found that Blacks and Other were more likely to report differences based on professionalism and satisfaction with their training program. There was no difference seen among LGBTQ trainees based on race. We found trainees who identified as LGBTQ were more likely to experience discrimination/microaggressions. Also, racial and ethnic groups that are underrepresented in medicine were more likely to encounter discrimination and dissatisfaction with their training. More efforts are needed in academics to promote safe and supportive LGBTQ and minority training experiences.

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