Gut feelings: the relations between depression, anxiety, psychotropic drugs and the gut microbiome

The gut microbiome is involved in the bi-directional relationship of the gut - brain axis. As most studies of this relationship are small and do not account for use of psychotropic drugs (PTDs), we explored the relations of the gut microbiome with several internalizing disorders, while adjusting for PTDs and other relevant medications, in 7,656 Lifelines participants from the Northern Netherlands (5,522 controls and 491 participants with at least one internalizing disorder). Disorders included dysthymia, major depressive disorder (MDD), any depressive disorder (AnyDep: dysthymia or MDD), generalized anxiety disorder (GAD) and any anxiety disorder (AnyAnx: GAD, social phobia and panic disorder). Compared to controls, 17 species were associated with depressive disorders and 3 were associated with anxiety disorders. Around 90% of these associations remained significant (FDR <0.05) after adjustment for PTD use, suggesting that the disorders, not PTD use, drove these associations. Negative associations were observed for the butyrate-producing bacteria Ruminococcus bromii in participants with AnyDep and for Bifidobacterium bifidum in AnyAnx participants, along with many others. Tryptophan and glutamate synthesis modules and the 3,4-Dihydroxyphenylacetic acid synthesis module (related to dopamine metabolism) were negatively associated with MDD and/or dysthymia. After additional adjustment for functional gastrointestinal disorders and irritable bowel syndrome, these relations remained either statistically (FDR <0.05) or nominally (P < 0.05) significant. Overall, multiple bacterial species and functional modules were associated with internalizing disorders, including gut - brain relevant components, while associations to PTD use were moderate. These findings suggest that internalizing disorders rather than PTDs are associated with gut microbiome differences relative to controls.

Environmental factors shaping the gut microbiome in a Dutch population

The gut microbiome is associated with diverse diseases^1-3, but a universal signature of a healthy or unhealthy microbiome has not been identified, and there is a need to understand how genetics, exposome, lifestyle and diet shape the microbiome in health and disease. Here we profiled bacterial composition, function, antibiotic resistance and virulence factors in the gut microbiomes of 8,208 Dutch individuals from a three-generational cohort comprising 2,756 families. We correlated these to 241 host and environmental factors, including physical and mental health, use of medication, diet, socioeconomic factors and childhood and current exposome. We identify that the microbiome is shaped primarily by the environment and cohabitation. Only around 6.6% of taxa are heritable, whereas the variance of around 48.6% of taxa is significantly explained by cohabitation. By identifying 2,856 associations between the microbiome and health, we find that seemingly unrelated diseases share a common microbiome signature that is independent of comorbidities. Furthermore, we identify 7,519 associations between microbiome features and diet, socioeconomics and early life and current exposome, with numerous early-life and current factors being significantly associated with microbiome function and composition. Overall, this study provides a comprehensive overview of gut microbiome and the underlying impact of heritability and exposures that will facilitate future development of microbiome-targeted therapies.

Genetic relationship between bacteria isolated from intraoperative air samples and surgical site infections at a major teaching hospital in Ghana

BACKGROUND

In low- and middle-income countries (LMICs) the rate of surgical site infections (SSI) is high, leading to negative patient outcomes and excess healthcare costs. A causal relationship between airborne bacteria in the operating room and SSI has not been established, at a molecular or genetic level. We studied the relationship between intraoperative airborne bacteria and bacteria causing SSI in an LMIC.

METHODS

Active air sampling using a portable impactor was performed during clean or clean-contaminated elective surgical procedures. Active patient follow-up consisting of phone calls and clinical examinations was performed 3, 14 and 30 days after surgery. Bacterial isolates recovered from SSI and air samples were compared by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) identification, ribotyping, whole genome sequencing (WGS), and metagenomic analysis.

RESULTS

Of 128 included patients, 116 (91%) completed follow-up and 11 (9%) developed SSI. Known pathogenic bacteria were isolated from intraoperative air samples in all cases with SSI. A match between air and SSI isolates was found by MALDI-TOF in eight cases. Matching ribotypes were found in six cases and in one case both WGS and metagenomic analysis showed identity between air- and SSI-isolates.

CONCLUSION

The study showed high levels of intraoperative airborne bacteria, an SSI-rate of 9% and a genetic link between intraoperative airborne bacteria and bacteria isolated from SSIs. This indicates the need for awareness of intraoperative air quality in LMICs.