Aberrant bowel movement frequencies coincide with increased microbe-derived blood metabolites associated with reduced organ function.

Bowel movement frequency (BMF) directly impacts the gut microbiota and is linked to diseases like chronic kidney disease or dementia. In particular, prior work has shown that constipation is associated with an ecosystem-wide switch from fiber fermentation and short-chain fatty acid production to more detrimental protein fermentation and toxin production. Here, we analyze multi-omic data from generally healthy adults to see how BMF affects their molecular phenotypes, in a pre-disease context. Results show differential abundances of gut microbial genera, blood metabolites, and variation in lifestyle factors across BMF categories. These differences relate to inflammation, heart health, liver function, and kidney function. Causal mediation analysis indicates that the association between lower BMF and reduced kidney function is partially mediated by the microbially derived toxin 3-indoxyl sulfate (3-IS). This result, in a generally healthy context, suggests that the accumulation of microbiota-derived toxins associated with abnormal BMF precede organ damage and may be drivers of chronic, aging-related diseases.

Using Large Language Models to Annotate Complex Cases of Social Determinants of Health in Longitudinal Clinical Records.

Social Determinants of Health (SDoH) are an important part of the exposome and are known to have a large impact on variation in health outcomes. In particular, housing stability is known to be intricately linked to a patient's health status, and pregnant women experiencing housing instability (HI) are known to have worse health outcomes. Most SDoH information is stored in electronic health records (EHRs) as free text (unstructured) clinical notes, which traditionally required natural language processing (NLP) for automatic identification of relevant text or keywords. A patient's housing status can be ambiguous or subjective, and can change from note to note or within the same note, making it difficult to use existing NLP solutions. New developments in NLP allow researchers to prompt LLMs to perform complex, subjective annotation tasks that require reasoning that previously could only be attempted by human annotators. For example, large language models (LLMs) such as GPT (Generative Pre-trained Transformer) enable researchers to analyze complex, unstructured data using simple prompts. We used a secure platform within a large healthcare system to compare the ability of GPT-3.5 and GPT-4 to identify instances of both current and past housing instability, as well as general housing status, from 25,217 notes from 795 pregnant women. Results from these LLMs were compared with results from manual annotation, a named entity recognition (NER) model, and regular expressions (RegEx). We developed a chain-of-thought prompt requiring evidence and justification for each note from the LLMs, to help maximize the chances of finding relevant text related to HI while minimizing hallucinations and false positives. Compared with GPT-3.5 and the NER model, GPT-4 had the highest performance and had a much higher recall (0.924) than human annotators (0.702) in identifying patients experiencing current or past housing instability, although precision was lower (0.850) compared with human annotators (0.971). In most cases, the evidence output by GPT-4 was similar or identical to that of human annotators, and there was no evidence of hallucinations in any of the outputs from GPT-4. Most cases where the annotators and GPT-4 differed were ambiguous or subjective, such as "living in an apartment with too many people". We also looked at GPT-4 performance on de-identified versions of the same notes and found that precision improved slightly (0.936 original, 0.939 de-identified), while recall dropped (0.781 original, 0.704 de-identified). This work demonstrates that, while manual annotation is likely to yield slightly more accurate results overall, LLMs, when compared with manual annotation, provide a scalable, cost-effective solution with the advantage of greater recall. At the same time, further evaluation is needed to address the risk of missed cases and bias in the initial selection of housing-related notes. Additionally, while it was possible to reduce confabulation, signs of unusual justifications remained. Given these factors, together with changes in both LLMs and charting over time, this approach is not yet appropriate for use as a fully-automated process. However, these results demonstrate the potential for using LLMs for computer-assisted annotation with human review, reducing cost and increasing recall. More efficient methods for obtaining structured SDoH data can help accelerate inclusion of exposome variables in biomedical research, and support healthcare systems in identifying patients who could benefit from proactive outreach.

Machine learning to understand risks for severe COVID-19 outcomes: a retrospective cohort study of immune-mediated inflammatory diseases, immunomodulatory medications, and comorbidities in a large US health-care system.

BACKGROUND: In the context of immune-mediated inflammatory diseases (IMIDs), COVID-19 outcomes are incompletely understood and vary considerably depending on the patient population studied. We aimed to analyse severe COVID-19 outcomes and to investigate the effects of the pandemic time period and the risks associated with individual IMIDs, classes of immunomodulatory medications (IMMs), chronic comorbidities, and COVID-19 vaccination status. METHODS: In this retrospective cohort study, clinical data were derived from the electronic health records of an integrated health-care system serving patients in 51 hospitals and 1085 clinics across seven US states (Providence St Joseph Health). Data were observed for patients (no age restriction) with one or more IMID and for unmatched controls without IMIDs. COVID-19 was identified with a positive nucleic acid amplification test result for SARS-CoV-2. Two timeframes were analysed: March 1, 2020-Dec 25, 2021 (pre-omicron period), and Dec 26, 2021-Aug 30, 2022 (omicron-predominant period). Primary outcomes were hospitalisation, mechanical ventilation, and mortality in patients with COVID-19. Factors, including IMID diagnoses, comorbidities, long-term use of IMMs, and COVID-19 vaccination status, were analysed with multivariable logistic regression (LR) and extreme gradient boosting (XGB). FINDINGS: Of 2 167 656 patients tested for SARS-CoV-2, 290 855 (13·4%) had confirmed COVID-19: 15 397 (5·3%) patients with IMIDs and 275 458 (94·7%) without IMIDs. In the pre-omicron period, 169 993 (11·2%) of 1 517 295 people who were tested for COVID-19 tested positive, of whom 23 330 (13·7%) were hospitalised, 1072 (0·6%) received mechanical ventilation, and 5294 (3·1%) died. Compared with controls, patients with IMIDs and COVID-19 had higher rates of hospitalisation (1176 [14·6%] vs 22 154 [13·7%]; p=0·024) and mortality (314 [3·9%] vs 4980 [3·1%]; p<0·0001). In the omicron-predominant period, 120 862 (18·6%) of 650 361 patients tested positive for COVID-19, of whom 14 504 (12·0%) were hospitalised, 567 (0·5%) received mechanical ventilation, and 2001 (1·7%) died. Compared with controls, patients with IMIDs and COVID-19 (7327 [17·3%] of 42 249) had higher rates of hospitalisation (13 422 [11·8%] vs 1082 [14·8%]; p<0·0001) and mortality (1814 [1·6%] vs 187 [2·6%]; p<0·0001). Age was a risk factor for worse outcomes (adjusted odds ratio [OR] from 2·1 [95% CI 2·0-2·1]; p<0·0001 to 3·0 [2·9-3·0]; p<0·0001), whereas COVID-19 vaccination (from 0·082 [0·080-0·085]; p<0·0001 to 0·52 [0·50-0·53]; p<0·0001) and booster vaccination (from 2·1 [2·0-2·2]; p<0·0001 to 3·0 [2·9-3·0]; p<0·0001) status were associated with better outcomes. Seven chronic comorbidities were significant risk factors during both time periods for all three outcomes: atrial fibrillation, coronary artery disease, heart failure, chronic kidney disease, chronic obstructive pulmonary disease, chronic liver disease, and cancer. Two IMIDs, asthma (adjusted OR from 0·33 [0·32-0·34]; p<0·0001 to 0·49 [0·48-0·51]; p<0·0001) and psoriasis (from 0·52 [0·48-0·56] to 0·80 [0·74-0·87]; p<0·0001), were associated with a reduced risk of severe outcomes. IMID diagnoses did not appear to be significant risk factors themselves, but results were limited by small sample size, and vasculitis had high feature importance in LR. IMMs did not appear to be significant, but less frequently used IMMs were limited by sample size. XGB outperformed LR, with the area under the receiver operating characteristic curve for models across different time periods and outcomes ranging from 0·77 to 0·92. INTERPRETATION: Our results suggest that age, chronic comorbidities, and not being fully vaccinated might be greater risk factors for severe COVID-19 outcomes in patients with IMIDs than the use of IMMs or the IMIDs themselves. Overall, there is a need to take age and comorbidities into consideration when developing COVID-19 guidelines for patients with IMIDs. Further research is needed for specific IMIDs (including IMID severity at the time of SARS-CoV-2 infection) and IMMs (considering dosage and timing before a patient's first COVID-19 infection). FUNDING: Pfizer, Novartis, Janssen, and the National Institutes of Health.

Generally-healthy individuals with aberrant bowel movement frequencies show enrichment for microbially-derived blood metabolites associated with reduced kidney function.

Bowel movement frequency (BMF) has been linked to changes in the composition of the human gut microbiome and to many chronic conditions, like metabolic disorders, neurodegenerative diseases, chronic kidney disease (CKD), and other intestinal pathologies like irritable bowel syndrome and inflammatory bowel disease. Lower BMF (constipation) can lead to compromised intestinal barrier integrity and a switch from saccharolytic to proteolytic fermentation within the microbiota, giving rise to microbially-derived toxins that may make their way into circulation and cause damage to organ systems. However, the connections between BMF, gut microbial metabolism, and the early-stage development and progression of chronic disease remain underexplored. Here, we examined the phenotypic impact of BMF variation in a cohort of generally-healthy, community dwelling adults with detailed clinical, lifestyle, and multi-omic data. We showed significant differences in microbially-derived blood plasma metabolites, gut bacterial genera, clinical chemistries, and lifestyle factors across BMF groups that have been linked to inflammation, cardiometabolic health, liver function, and CKD severity and progression. We found that the higher plasma levels of 3-indoxyl sulfate (3-IS), a microbially-derived metabolite associated with constipation, was in turn negatively associated with estimated glomerular filtration rate (eGFR), a measure of kidney function. Causal mediation analysis revealed that the effect of BMF on eGFR was significantly mediated by 3-IS. Finally, we identify self-reported diet, lifestyle, and psychological factors associated with BMF variation, which indicate several common-sense strategies for mitigating constipation and diarrhea. Overall, we suggest that aberrant BMF is an underappreciated risk factor in the development of chronic diseases, even in otherwise healthy populations.

Risk factors for severe COVID-19 outcomes: a study of immune-mediated inflammatory diseases, immunomodulatory medications, and comorbidities in a large US healthcare system.

Background: COVID-19 outcomes, in the context of immune-mediated inflammatory diseases (IMIDs), are incompletely understood. Reported outcomes vary considerably depending on the patient population studied. It is essential to analyse data for a large population, while considering the effects of the pandemic time period, comorbidities, long term use of immunomodulatory medications (IMMs), and vaccination status. Methods: In this retrospective case-control study, patients of all ages with IMIDs were identified from a large U.S. healthcare system. COVID-19 infections were identified based on SARS-CoV-2 NAAT test results. Controls without IMIDs were selected from the same database. Severe outcomes were hospitalisation, mechanical ventilation (MV), and death. We analysed data from 1 March 2020 to 30 August 2022, looking separately at both pre-Omicron and Omicron predominant periods. Factors including IMID diagnoses, comorbidities, long term use of IMMs, and vaccination and booster status were analysed using multivariable logistic regression (LR) and extreme gradient boosting (XGB). Findings: Out of 2 167 656 patients tested for SARS-CoV-2, there were 290 855 with confirmed COVID-19 infection: 15 397 patients with IMIDs and 275 458 controls (patients without IMIDs). Age and most chronic comorbidities were risk factors for worse outcomes, whereas vaccination and boosters were protective. Patients with IMIDs had higher rates of hospitalisation and mortality compared with controls. However, in multivariable analyses, few IMIDs were rarely risk factors for worse outcomes. Further, asthma, psoriasis and spondyloarthritis were associated with reduced risk. Most IMMs had no significant association, but less frequently used IMM drugs were limited by sample size. XGB outperformed LR, with the AUROCs for models across different time periods and outcomes ranging from 0·77 to 0·92. Interpretation: For patients with IMIDs, as for controls, age and comorbidities were risk factors for worse COVID-19 outcomes, whereas vaccinations were protective. Most IMIDs and immunomodulatory therapies were not associated with more severe outcomes. Interestingly, asthma, psoriasis and spondyloarthritis were associated with less severe COVID-19 outcomes than those expected for the population overall. These results can help inform clinical, policy and research decisions. Funding: Pfizer, Novartis, Janssen, NIH.

Plant mitochondrial FMT and its mammalian homolog CLUH controls development and behavior in Arabidopsis and locomotion in mice.

Mitochondria in animals are associated with development, as well as physiological and pathological behaviors. Several conserved mitochondrial genes exist between plants and higher eukaryotes. Yet, the similarities in mitochondrial function between plant and animal species is poorly understood. Here, we show that FMT (FRIENDLY MITOCHONDRIA) from Arabidopsis thaliana, a highly conserved homolog of the mammalian CLUH (CLUSTERED MITOCHONDRIA) gene family encoding mitochondrial proteins associated with developmental alterations and adult physiological and pathological behaviors, affects whole plant morphology and development under both stressed and normal growth conditions. FMT was found to regulate mitochondrial morphology and dynamics, germination, and flowering time. It also affects leaf expansion growth, salt stress responses and hyponastic behavior, including changes in speed of hyponastic movements. Strikingly, Cluh± heterozygous knockout mice also displayed altered locomotive movements, traveling for shorter distances and had slower average and maximum speeds in the open field test. These observations indicate that homologous mitochondrial genes may play similar roles and affect homologous functions in both plants and animals.

Plasticity of calcium-permeable AMPA glutamate receptors in Pro-opiomelanocortin neurons.

POMC neurons integrate metabolic signals from the periphery. Here, we show in mice that food deprivation induces a linear current-voltage relationship of AMPAR-mediated excitatory postsynaptic currents (EPSCs) in POMC neurons. Inhibition of EPSCs by IEM-1460, an antagonist of calcium-permeable (Cp) AMPARs, diminished EPSC amplitude in the fed but not in the fasted state, suggesting entry of GluR2 subunits into the AMPA receptor complex during food deprivation. Accordingly, removal of extracellular calcium from ACSF decreased the amplitude of mEPSCs in the fed but not the fasted state. Ten days of high-fat diet exposure, which was accompanied by elevated leptin levels and increased POMC neuronal activity, resulted in increased expression of Cp-AMPARs on POMC neurons. Altogether, our results show that entry of calcium via Cp-AMPARs is inherent to activation of POMC neurons, which may underlie a vulnerability of these neurons to calcium overload while activated in a sustained manner during over-nutrition.

Viral Spread to Enteric Neurons Links Genital HSV-1 Infection to Toxic Megacolon and Lethality.

Herpes simplex virus 1 (HSV-1), a leading cause of genital herpes, infects oral or genital mucosal epithelial cells before infecting the peripheral sensory nervous system. The spread of HSV-1 beyond the sensory nervous system and the resulting broader spectrum of disease are not well understood. Using a mouse model of genital herpes, we found that HSV-1-infection-associated lethality correlated with severe fecal and urinary retention. No inflammation or infection of the brain was evident. Instead, HSV-1 spread via the dorsal root ganglia to the autonomic ganglia of the enteric nervous system (ENS) in the colon. ENS infection led to robust viral gene transcription, pathological inflammatory responses, and neutrophil-mediated destruction of enteric neurons, ultimately resulting in permanent loss of peristalsis and the development of toxic megacolon. Laxative treatment rescued mice from lethality following genital HSV-1 infection. These results reveal an unexpected pathogenesis of HSV associated with ENS infection.

Developmental programming of hypothalamic neuroendocrine systems.

There is increasing evidence to suggest that the perinatal environment may alter the developmental programming of hypothalamic neuroendocrine systems in a manner that predisposes offspring to the development of metabolic syndrome. Although it is unclear how these effects might be mediated, it has been shown that changes in neuroendocrine programing during critical periods of development, either via maternal metabolic programming or other factors, can alter a fetus's metabolic fate. This review summarizes the hypothalamic circuits that mediate energy homeostasis and discusses the various factors that may influence the development and functioning of these neural systems, as well as the possible cognitive impairments that may arise as a result of these metabolic influences.

Heterotrimeric Gα subunit from wheat (Triticum aestivum), GA3, interacts with the calcium-binding protein, Clo3, and the phosphoinositide-specific phospholipase C, PI-PLC1.

The canonical Gα subunit of the heterotrimeric G protein complex from wheat (Triticum aestivum), GA3, and the calcium-binding protein, Clo3, were revealed to interact both in vivo and in vitro and Clo3 was shown to enhance the GTPase activity of GA3. Clo3 is a member of the caleosin gene family in wheat with a single EF-hand domain and is induced during cold acclimation. Bimolecular Fluorescent Complementation (BiFC) was used to localize the interaction between Clo3 and GA3 to the plasma membrane (PM). Even though heterotrimeric G-protein signaling and Ca²âº signaling have both been shown to play a role in the response to environmental stresses in plants, little is known about the interaction between calcium-binding proteins and Gα. The GAP activity of Clo3 towards GA3 suggests it may play a role in the inactivation of GA3 as part of the stress response in plants. GA3 was also shown to interact with the phosphoinositide-specific phospholipase C, PI-PLC1, not only in the PM but also in the endoplasmic reticulum (ER). Surprisingly, Clo3 was also shown to interact with PI-PLC1 in the PM and ER. In vitro analysis of the protein-protein interaction showed that the interaction of Clo3 with GA3 and PI-PLC1 is enhanced by high Ca²âº levels. Three-way affinity characterizations with GA3, Clo3 and PI-PLC1 showed the interaction with Clo3 to be competitive, which suggests that Clo3 may play a role in the Ca²âº-triggered feedback regulation of both GA3 and PI-PLC1. This hypothesis was further supported by the demonstration that Clo3 has GAP activity with GA3.