Department of Medicine - Open Access Policy Deposits

Disruption of gut barrier integrity and host–microbiome interactions underlie MASLD severity in patients with type-2 diabetes mellitus

(2024)

Aberration of the "gut-liver axis" contributes to the development and progression of metabolic dysfunction-associated steatotic liver disease (MASLD). Here, we use multi-omics to analyze the gut microbiota composition and metabolic profile of patients with type-2 diabetes mellitus (T2DM). T2DM patients were screened for liver disease by blood tests, ultrasound, and liver stiffness measurements. Stool microbiota was analyzed by 16S rRNA gene sequencing; metabolomic profiling by Nuclear Magnetic Resonance spectroscopy and Ultra-High Performance-Mass Spectrometry. Microbiome and metabolic signatures were analyzed in the whole cohort and in matched subsets to identify signatures specific for steatosis (MASLD±) or fibrosis (Fibrosis±). Gut permeability was assessed in-vitro using monolayers of MDCK cells and trans-epithelial electric resistance (TEER). Cytokine profile was assessed in serum and stools.Overall, 285 patients were enrolled: 255 serum, 252 urine and 97 stool samples were analyzed. Anaeroplasma and Escherichia/Shigella ASVs were higher, while Butyricicoccus ASVs were lower in those with normal liver. In MASLD±, Butyricicoccus ASV was significantly higher in those with steatosis. In the Fibrosis±, Butyricicoccus ASV was significantly lower in those with fibrosis. Glycochenodeoxycholic acid-3-sulfate (G-UDCA-3S) appeared to be higher in MASLD with fibrosis. Fecal water from patients with MASLD and fibrosis caused the greatest drop in the TEER vs those with normal liver; this was reversed with protease inhibitors. Finally, fecal IL-13 was lower in MASLD with fibrosis. We identified microbiome signatures which were specific for steatosis and fibrosis and independent of other metabolic risk factors. Moreover, we conclude that protease-related gut permeability plays a role in those MASLD patients with fibrosis, and that disease progression is linked to a gut-liver axis which is at least partially independent of T2DM.

Stronger control of eating 3 months after sleeve gastrectomy predicts successful weight loss outcomes at one year

(2024)

Background

Weight loss response to sleeve gastrectomy (SG) is variable and predicting the effectiveness of surgery is challenging and elusive. The aim of our study was to assess and quantify the association between eating control and weight loss outcomes and identify the control of eating (CoE) attributes during the early postoperative period that might predict good vs. poor response to SG at one year.

Methods

A prospective longitudinal cohort study using the Control of Eating Questionnaire (CoEQ) was designed as a series before and at 3-, 6-, and 12-months post-SG. Primary outcomes were changes in CoE attributes and percent of total weight loss (%TWL) 12-months post-surgery. Subjects were categorized based on %TWL as good (GR, ≥25 %) or poor responders (PR, <25 %). A receiver operating characteristic and logistic regression analyses were performed.

Results

We included 41 participants (80.5% females, 51.2% Hispanic, mean age 41.7±10.6, median baseline body mass index (BMI) 43.6 kg/m² [range 35.2-66.3]) who completed the CoEQ at all four timepoints. The "Difficulty to control eating" score at 3 months revealed the highest area under the curve (AUC) (AUC 0.711; 95%CI 0.524-0.898; p=0.032). In a trade-off between a high Youden index and high sensitivity, the "Difficulty to control eating" score of 7 at 3 months was identified as the optimal cut-off for distinguishing between GRs and PRs. Score ≤7 at 3 months was strongly independently associated with a successful weight loss target of 25%TWL at one-year post-SG (Relative Risk 4.43; 95%CI 1.06-18.54; p=0.042).

Conclusion

"Difficulty to control eating" score at 3 months post-SG is an independent early predictor of optimal response (achieving a successful TWL target of ≥25 % at one-year post-SG). Our results support the utility of this easy-to-administer validated tool for predicting the effectiveness of SG and may assist in identifying individuals with suboptimal response early and helping them with interventions to attain optimal weight loss targets.

Person-specific dynamics between negative emotions and suicidal thoughts

(2024)

Introduction

Recent technology has enabled researchers to collect ecological momentary assessments (EMA) to examine within-person correlates of suicidal thoughts. Prior studies examined generalized temporal dynamics of emotions and suicidal thinking over brief periods, but it is not yet known how variable these processes are across people.

Method

We use data EMA data delivered over two weeks with youth/young adults (N = 60) who reported past year self-injurious thoughts/behaviors. We used group iterative multiple model estimation (GIMME) to model group- and person-specific associations of negative emotions (i.e., fear, sadness, shame, guilt, and anger) and suicidal thoughts.

Results

29 participants (48.33%) reported at least one instance of a suicidal thought and were included in GIMME models. In group level models, we consistently observed autoregressive effects for suicidal thoughts (e.g., earlier thoughts predicting later thoughts), although the magnitude and direction of this link varied from person-to-person. Among emotions, sadness was most frequently associated with contemporaneous suicidal thoughts, but this was evident for less than half of the sample, while other emotional correlates of suicidal thoughts broadly differed across people. No emotion variable was linked to future suicidal thoughts in >14% of the sample, CONCLUSIONS: Emotion-based correlates of suicidal thoughts are heterogeneous across people. Better understanding of the individual-level pathways maintaining suicidal thoughts/behaviors may lead to more effective, personalized interventions.

Unique features of dyslipidemia in women across a lifetime and a tailored approach to management.

(2024)

PURPOSE OF REVIEW: Cardiovascular disease is a leading cause of death worldwide. Dyslipidemia is a critical modifiable risk factor for the prevention of cardiovascular disease. Dyslipidemia affects a large population of women and is especially pervasive within racial/ethnic minorities. RECENT FINDINGS: Dyslipidemia in pregnancy leads to worse outcomes for patients and creates increased cardiovascular risk for women at an older age. However, women remain underscreened and undertreated compared to men. Females also comprise a small portion of clinical trial participants for lipid lowering agents with increased disease prevalence compared to trial representation. However, recent lipid trials have shown different efficacies of therapies such as ezetimibe, inclisiran, and bempedoic acid with a greater relative benefit for women. SUMMARY: Pathophysiology of dyslipidemia varies between men and women and across a womans lifetime. While increased lipid levels or lipid imbalances are more common in postmenopausal women over age 50, conditions such as PCOS and FH produce higher cardiovascular risk for young women.Best practices for management of women with dyslipidemia include early screening with lifestyle intervention and pharmacotherapy with statin and non-statin agents to achieve guideline directed LDL-C thresholds.

MDA5-autoimmunity and interstitial pneumonitis contemporaneous with the COVID-19 pandemic (MIP-C)

(2024)

Background

Anti-MDA5 (Melanoma differentiation-associated protein-5) positive dermatomyositis (MDA5⁺-DM) is characterised by rapidly progressive interstitial lung disease (ILD) and high mortality. MDA5 is an RNA sensor and a key pattern recognition receptor for the SARS-CoV-2 virus.

Methods

This is a retrospective observational study of a surge in MDA5 autoimmunity, as determined using a 15 muscle-specific autoantibodies (MSAs) panel, between Janurary 2018 and December 2022 in Yorkshire, UK. MDA5-positivity was correlated with clinical features and outcome, and regional SARS-CoV-2 positivity and vaccination rates. Gene expression patterns in COVID-19 were compared with autoimmune lung disease and idiopathic pulmonary fibrosis (IPF) to gain clues into the genesis of the observed MDA5⁺-DM outbreak.

Findings

Sixty new anti-MDA5+, but not other MSAs surged between 2020 and 2022, increasing from 0.4% in 2019 to 2.1% (2020), 4.8% (2021) and 1.7% (2022). Few (8/60) had a prior history of confirmed COVID-19, peak rates overlapped with regional SARS-COV-2 community positivity rates in 2021, and 58% (35/60) had received anti-SARS-CoV-2 vaccines. 25/60 cases developed ILD which rapidly progression with death in 8 cases. Among the 35/60 non-ILD cases, 14 had myositis, 17 Raynaud phenomena and 10 had dermatomyositis spectrum rashes. Transcriptomic studies showed strong IFIH1 (gene encoding for MDA5) induction in COVID-19 and autoimmune-ILD, but not IPF, and IFIH1 strongly correlated with an IL-15-centric type-1 interferon response and an activated CD8+ T cell signature that is an immunologic hallmark of progressive ILD in the setting of systemic autoimmune rheumatic diseases. The IFIH1 rs1990760TT variant blunted such response.

Interpretation

A distinct pattern of MDA5-autoimmunity cases surged contemporaneously with circulation of the SARS-COV-2 virus during COVID-19. Bioinformatic insights suggest a shared immunopathology with known autoimmune lung disease mechanisms.

Funding

This work was supported in part by the National Institute for Health Research (NIHR) Leeds Biomedical Research Centre (BRC), and in part by the National Institutes of Health (NIH) grant R01-AI155696 and pilot awards from the UC Office of the President (UCOP)-RGPO (R00RG2628, R00RG2642 and R01RG3780) to P.G. S.S was supported in part by R01-AI141630 (to P.G) and in part through funds from the American Association of Immunologists (AAI) Intersect Fellowship Program for Computational Scientists and Immunologists.

Aspirin use for primary prevention among US adults with and without elevated Lipoprotein(a).

(2024)

OBJECTIVE: Lipoprotein(a) [Lp(a)] is an atherogenic and prothrombotic lipoprotein associated with atherosclerotic cardiovascular disease (ASCVD). We assessed the association between regular aspirin use and ASCVD mortality among individuals with versus without elevated Lp(a) in a nationally representative US cohort. METHODS: Eligible participants were aged 40-70 years without clinical ASCVD, reported on aspirin use, and had Lp(a) measurements from the Third National Health and Nutrition Examination Survey (NHANES III, 1988-1994), the only cycle of this nationally representative US cohort to measure Lp(a). Regular aspirin use was defined as taking aspirin ≥30 times in the previous month. Using NHANES III linked mortality records and weighted Cox proportional hazards regression, the association between regular aspirin use and ASCVD mortality was observed in those with and without elevated Lp(a) (≥50 versus <50 mg/dL) over a median 26-year follow-up. RESULTS: Among 2,990 persons meeting inclusion criteria (∼73 million US adults), the mean age was 50 years, 86% were non-Hispanic White, 9% were non-Hispanic Black, 53% were female, and 7% reported regular aspirin use. The median Lp(a) was 14 mg/dL and the proportion with elevated Lp(a) was similar among those with versus without regular aspirin use (15.1% versus 21.9%, p = 0.16). Among individuals with elevated Lp(a), the incidence of ASCVD mortality per 1,000 person-years was lower for those with versus without regular aspirin use (1.2, 95% CI: 0.1-2.3 versus 3.9, 95% CI: 2.8-4.9). In multivariable modeling, regular aspirin use was associated with a 52% lower risk of ASCVD mortality among individuals with elevated Lp(a) (HR=0.48, 95% CI: 0.28-0.83), but not for those without elevated Lp(a) (HR=1.01, 95% CI: 0.81-1.25; p-interaction=0.001). CONCLUSION: Regular aspirin use was associated with significantly lower ASCVD mortality in adults without clinical ASCVD who had elevated Lp(a). These findings may have clinical and public health implications for aspirin utilization in primary prevention.

Integrated Genomic and Social Network Analyses of SARS-CoV-2 Transmission in the Healthcare Setting

(2024)

Background

Infection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2.

Methods

We performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs.

Results

Among 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001).

Conclusions

IP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission.

Cover page of Nicotine inhalant via E‐cigarette facilitates sensorimotor function recovery by upregulating neuronal BDNF–TrkB signalling in traumatic brain injury

Nicotine inhalant via E‐cigarette facilitates sensorimotor function recovery by upregulating neuronal BDNF–TrkB signalling in traumatic brain injury

(2024)

Background and purpose

Traumatic brain injury (TBI) causes lifelong physical and psychological dysfunction in affected individuals. The current study investigated the effects of chronic nicotine exposure via E-cigarettes (E-cig) (vaping) on TBI-associated behavioural and biochemical changes.

Experimental approach

Adult C57/BL6J male mice were subjected to controlled cortical impact (CCI) followed by daily exposure to E-cig vapour for 6 weeks. Sensorimotor functions, locomotion, and sociability were subsequently evaluated by nesting, open field, and social approach tests, respectively. Immunoblots were conducted to examine the expression of mature brain-derived neurotrophic factor (mBDNF) and associated downstream proteins (p-Erk, p-Akt). Histological analyses were performed to evaluate neuronal survival and neuroinflammation.

Key results

Post-injury chronic nicotine exposure significantly improved nesting performance in CCI mice. Histological analysis revealed increased survival of cortical neurons in the perilesion cortex with chronic nicotine exposure. Immunoblots revealed that chronic nicotine exposure significantly up-regulated mBDNF, p-Erk and p-Akt expression in the perilesion cortex of CCI mice. Immunofluorescence microscopy indicated that elevated mBDNF and p-Akt expression were mainly localized within cortical neurons. Immunolabelling of Iba1 demonstrated that chronic nicotine exposure attenuated microglia-mediated neuroinflammation.

Conclusions and implications

Post-injury chronic nicotine exposure via vaping facilitates recovery of sensorimotor function by upregulating neuroprotective mBDNF/TrkB/Akt/Erk signalling. These findings suggest potential neuroprotective properties of nicotine despite its highly addictive nature. Thus, understanding the multifaceted effects of chronic nicotine exposure on TBI-associated symptoms is crucial for paving the way for informed and properly managed therapeutic interventions.

Live bacterial therapeutics for detection and treatment of colorectal cancer

(2024)

Live microorganisms can be manipulated and engineered for colorectal cancer detection and treatment through methods such as faecal microbiota transplantation, native bacteria engineering and synthetic circuit engineering. Although promising, substantial effort is required to translate these approaches for clinical use.

Assessing transmission attribution risk from simulated sequencing data in HIV molecular epidemiology

(2024)

Background

HIV molecular epidemiology (ME) is the analysis of sequence data together with individual-level clinical, demographic, and behavioral data to understand HIV epidemiology. The use of ME has raised concerns regarding identification of the putative source in direct transmission events. This could result in harm ranging from stigma to criminal prosecution in some jurisdictions. Here we assessed the risks of ME using simulated HIV genetic sequencing data.

Methods

We simulated social networks of men-who-have-sex-with-men, calibrating the simulations to data from San Diego. We used these networks to simulate consensus and next-generation sequence (NGS) data to evaluate the risks of identifying direct transmissions using different HIV sequence lengths, and population sampling depths. To identify the source of transmissions, we calculated infector probability and used phyloscanner software for the analysis of consensus and NGS data, respectively.

Results

Consensus sequence analyses showed that the risk of correctly inferring the source (direct transmission) within identified transmission pairs was very small and independent of sampling depth. Alternatively, NGS analyses showed that identification of the source of a transmission was very accurate, but only for 6.5% of inferred pairs. False positive transmissions were also observed, where one or more unobserved intermediaries were present when compared to the true network.

Conclusion

Source attribution using consensus sequences rarely infers direct transmission pairs with high confidence but is still useful for population studies. In contrast, source attribution using NGS data was much more accurate in identifying direct transmission pairs, but for only a small percentage of transmission pairs analyzed.

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