Background/Objectives: Obstructive sleep apnea (OSA) is a sleep condition characterized by intermittent hypoxia, systemic inflammation, and metabolic dysfunction. Contemporary diagnosis criteria depend on polysomnography (PSG), a procedure that is limited by cost and accessibility. Identifying reliable circulating biomarkers may facilitate disease diagnosis and treatment monitoring. Methods: Insulin-like growth factor binding protein-7 (IGFBP-7) has been implicated in pathways relevant to OSA, although its precise role remains elusive. While we previously identified IGFBP-7 as a candidate of interest, in this report, we assessed circulating IGFBP-7 levels in a single-cohort study of 164 participants (124 with OSA, 40 controls) at the Dasman Diabetes Institute. A Type I PSG test was performed in a level 1 sleep laboratory to diagnose sleep apnea. Among the 124 patients with OSA who underwent multilevel sleep surgery (MLS), 67 completed the 3-month postoperative follow-up and were included in the longitudinal analyses. In these participants, we evaluated the apnea-hypopnea index (AHI) at baseline and 3 months after surgery and examined the associations between circulating IGFBP-7 levels, OSA severity indices, and metabolic parameters. Results: Our data revealed a significant increase in IGFBP-7 levels in people with OSA compared to controls (p < 0.001). Importantly, the increase in IGFBP-7 was positively correlated with AHI (r = 0.272, p < 0.001), indicating a potential link with this condition. IGFBP-7 levels declined significantly following MLS (p < 0.001), paralleling improvements in AHI and suggesting responsiveness to therapeutic intervention and a reduced hypoxic burden. IGFBP-4 levels increased significantly in patients with OSA (p = 0.006) but were not correlated with IGFBP-7. The receiver operating characteristic (ROC) analysis identified IGFBP-7 with a cut-off value of 14,003.21 pg/mL as a potential biomarker for OSA, with moderate performance (AUC = 0.722, 95% CI: 0.636-0.808; sensitivity 73%, specificity 84%). Notably, combining IGFBP-7 with IGFBP-4 resulted in a modest improvement (AUC = 0.755). Conclusions: Our data suggest that IGFBP-7 shows a modest association with OSA severity and may have exploratory value as part of a multi-marker or risk-stratification approach. Further large-scale and longitudinal studies are warranted to extensively explore the potential utility of IGFBP-7 within multi-marker approaches.

BackgroundType 1 diabetes (T1D) is associated with microbial dysbiosis. While most research has focused on the gut microbiome, limited data addresses the role of the oral microbiome in T1D. The oral and gut microbiomes overlap substantially, and the oral cavity may influence gut microbial composition. Saliva and dental plaque represent two distinct oral niches with unique microbial communities, but it remains unclear which is better associated to systemic disease states like T1D. This study compares the performance of salivary and plaque microbiomes in classifying pediatric T1D status.MethodsPaired saliva and plaque samples were collected from 46 children (23 with T1D, 23 healthy controls). Microbial DNA was extracted and sequenced targeting the 16S rRNA gene. Data were processed using QIIME 2 for taxonomic classification and centered log-ratio transformation. Alpha diversity, microbial abundance, and clustering analyses were performed to compare the oral microbiome between T1D and control groups. Random forest classifiers were used to evaluate and compare the predictive accuracy of saliva- and plaque-based models, both with and without clinical metadata.ResultsSaliva samples exhibited lower alpha diversity than plaque but had significantly higher bacterial load and total microbial abundance. Saliva-based models outperformed plaque-based models, achieving a classification accuracy of 94.2% with or without clinical metadata, compared to 73.3% accuracy for plaque-based models. ROC curve analysis further supported this difference, with saliva models reaching an AUC of approximately 0.94, versus 0.75 for plaque, indicating superior discriminative performance. UMAP clustering revealed more distinct separation of T1D and control groups in salivary profiles than in plaque. Feature importance analysis identified both unique and shared taxa predictive of T1D in each niche. Incorporating clinical and demographic metadata did not enhance model performance, underscoring the robustness and predictive strength of microbiome data alone.ConclusionThe salivary microbiome is a more effective biospecimen than dental plaque for characterizing T1D-associated microbial profiles in children. It offers superior classification accuracy and greater sensitivity in distinguishing T1D status, supporting saliva’s potential as a non-invasive, scalable medium for future microbiome-based monitoring.

Background:Diabetic nephropathy (DN) is a main complication of type 2 diabetes (T2D) and a major cause of chronic kidney disease and end stage renal failure. Early detection remains challenging, which has attracted interest in exploring novel biomarkers. Osteoactivin is a protein involved in inflammation, tissue repair, and metabolic stress, but its role in DN is not yet fully understood. Objective:To evaluate circulating osteoactivin as a potential biomarker of DN, and to examine its relationship with renal dysfunction, angiogenic markers, and diagnostic performance. Methods:This cross-sectional study included 42 non-diabetic controls, 50 patients with T2D, and 67 patients with DN. Plasma osteoactivin levels were measured using a customized Luminex multiplex assay. Group differences were analyzed using one-way ANOVA or the Kruskal- Walli's test, with post hoc comparisons performed where appropriate. Spearman's correlation was used to assess associations between osteoactivin and various nephropathy-related biomarkers, including Angiopoietin-1, Angiopoietin-2, ANGPTL3, ANGPTL4, ANGPTL6 and ANGPTL8. Multinomial logistic regression was used to examine associations with disease groups. Receiver operating characteristic (ROC) curve analysis was performed to assess diagnostic performance. Results:Circulating osteoactivin levels increased progressively from controls to T2D and were highest in DN (P < 0.001). Higher osteoactivin levels were associated with worse kidney function and showed positive associations with selected angiogenic markers, particularly Angiopoietin-2 (r = 0.414, P < 0.001), ANGPTL4 (r = 0.406, P < 0.001), and ANGPTL8 (r = 0.165, P = 0.039). ROC analysis showed that osteoactivin alone had moderate diagnostic performance (AUC = 0.786), but this improved substantially when combined with angiogenic markers, especially ANGPTL8 (AUC = 0.881), supporting the added value of a multi-marker approach. Conclusion:Circulating osteoactivin is associated with renal dysfunction and angiogenic activity in DN and demonstrated moderate diagnostic performance. This was further enhanced when combined with other angiogenic biomarkers, particularly ANGPTL8. These findings support its potential as a non-invasive biomarker tool for the detection and assessment of disease severity in DN.

Background and Objectives: Heart failure (HF) often leads to worsening renal function (WRF), negatively impacting patient outcomes. This study aims to examine the incidence of WRF in HF patients, identify its risk factors, and assess its effect on readmissions. Materials and Methods: This retrospective analysis included 297 HF patients admitted to Harlem Hospital Center between January 2019 and December 2021. WRF incidence and its association with risk factors, hospital stays, and readmissions were analyzed. Data on age, type 2 diabetes, chronic kidney disease, high-dose furosemide use, and biomarkers (ProBNP, troponin T, creatinine) were collected. A risk-scoring system was developed to identify patients at higher risk for WRF. Results: WRF occurred in 27% of patients, with a significant correlation to longer hospital stays and lower cardiology follow-up adherence. Risk factors for WRF included older age, type 2 diabetes, chronic kidney disease, high-dose furosemide, and elevated ProBNP, troponin T, and creatinine levels. The risk scoring system revealed that patients scoring 6 or higher were four times more likely to develop WRF. Interestingly, WRF did not increase 30-day readmission rates. Conclusions: This study highlights the high incidence of WRF among HF patients, its impact on hospital stays and follow-up adherence, and the utility of a risk-scoring system to identify vulnerable patients. The findings offer valuable insights into improving care in minority-serving hospitals and provide a foundation for future research on WRF in HF patients.

Objectives: This study aimed to investigate the obesity paradox in patients with congestive heart failure (CHF) at Harlem Hospital Center (HHC), examine the role of diabetes in CHF readmissions, and explore the combined impact of obesity and diabetes on readmission rates. Methods: A retrospective chart review was conducted on 390 patients from HHC’s CHF registry (January 2019–December 2021). CHF admissions and 30-day readmissions were analyzed, focusing on obesity, diabetes, and their interplay. Results: Preliminary analyses revealed a correlation between obesity and reduced 30-day readmission rates. Diabetes alone did not significantly influence readmissions; however, patients with both obesity and diabetes had higher readmission rates than those with obesity alone. However, after adjusting for confounders, none of the observed associations remained statistically significant, highlighting the complexity of interpreting the obesity paradox in this population. Conclusions: These findings suggest that the obesity paradox may exist but is attenuated by the presence of diabetes. Further research is needed to elucidate these relationships and their implications for managing CHF in obese diabetic patients.

Background/Objectives: Obesity is increasing worldwide, driven by unhealthy dietary habits and sedentary lifestyles. Genetic variations in taste receptor genes, particularly TAS1R2 and TAS2R38, may influence taste preferences, dietary intake, and obesity risk. This study examined associations between TAS1R2 and TAS2R38 polymorphisms, sugar-sweetened beverage (SSB) intake, and obesity risk in Kuwaiti adolescents. Methods: A cross-sectional study was conducted among 260 adolescents aged 11–14 years recruited from public schools in Kuwait. Genotyping of five single-nucleotide polymorphisms (SNPs) was performed using TaqMan assays. Associations between SNPs, SSB intake, and obesity parameters were evaluated using multinomial logistic regression and non-parametric tests, adjusted for age, sex, nationality, BMI z-scores, basal metabolic rate, and physical activity. p-values were corrected using the Benjamini–Hochberg method. Results: The rs713598 SNP in TAS2R38 showed a marginal association with BMI percentiles and z-scores. Adolescents carrying the CC genotype of rs10246939 SNP in TAS2R38 had significantly lower odds of high SSB consumption (>3 servings/week) compared with T-allele carriers (p = 0.018, OR= 0.24, 95% CI = 0.08–0.79). No significant associations were detected for TAS1R2 SNPs. Conclusions: Variations in TAS2R38 were linked to obesity measures and beverage intake in Kuwaiti adolescents, supporting a potential genetic contribution to dietary behaviors. These findings highlight the importance of taste receptor genetics in obesity research, though replication in larger and more diverse populations is required.

Background: Crohn’s disease (CD) is a chronic disease perpetuated through key pro-inflammatory molecules, including tumor necrosis factor-alpha (TNFα). Angiopoietin-like protein 8 (ANGPTL8) may contribute to inflammation cascades. This study aimed to investigate how ANGPTL8 levels are influenced in patients with CD prior to and following anti-TNF therapy. Methods: Patients were divided into 3 groups. Patients with CD in clinical remission receiving IFX for at least 24 weeks (IFX-experienced group), patients scheduled to start IFX (IFX-naïve group), and healthy controls (control group). In the IFX-experienced group, ANGPTL8 levels were measured 24 h before the next maintenance IFX dose. In the IFX-naïve group, levels were measured at week 0 and week 24, and in the control group, they were measured randomly. Results: The total number of participants was 166. The numbers of IFX-experienced, IFX-naïve patients, and healthy controls were 82, 13, and 71, respectively. Mean age ranged from 27 to 33 years of age across the three groups. Eighty-four (51%) participants were female. ANGPTL8 levels were significantly higher in patients with CD (138.26 ± 8.47 pmol) compared to the healthy control group (102.52 ± 5.99 pmol, p = 0.001). Among IFX-naïve patients receiving anti-TNFα treatment, ANGPTL8 levels decreased significantly from 145.06 ± 17.93 pmol pre-treatment (week 0) to 81.78 ± 10.61 pmol post-treatment (week 24), p = 0.007. Conclusions: Our findings suggest that ANGPTL8 levels are elevated in CD and may be involved in the inflammatory process. The marked reduction in ANGPTL8 levels following anti-TNFα treatment indicates its potential as a biomarker for treatment response. Further research should focus on the exact mechanisms through which ANGPTL8 influences CD progression and its utility in clinical practice.

IntroductionObstructive sleep apnea (OSA) is a common sleep disorder characterized by intermittent hypoxia, systemic inflammation, and metabolic dysfunction. Current diagnostic standards rely on polysomnography (PSG), which is limited by cost and accessibility. The identification of a sensitive and specific biomarker has the potential to aid both diagnosis and treatment monitoring. Follistatin-like 1 (FSTL1) has been implicated in inflammatory pathways; however, its role in OSA remains largely unexplored.Materials and MethodsIn this study, we aimed to explore changes in circulating FSTL1 levels in individuals with OSA to assess alterations following multilevel sleep surgery (MLS). We also evaluated its association with various metabolic and hypoxia-related markers, including Orexin-A, TNF-α, and IGFBP4. Our study was conducted at Dasman Diabetes Institute (DDI) in Kuwait through a cohort of 164 individuals, comprising 124 patients with OSA and 40 participants as non-OSA controls. Participants with OSA underwent MLS as a corrective intervention. A Type I polysomnography (PSG) test was performed in a level 1 sleep laboratory to diagnose sleep apnea. The apnea-hypopnea index (AHI) was measured at baseline and 3 months post-surgery to evaluate improvement in their condition.ResultsCirculating FSTL1 levels were significantly lower in individuals with OSA (10,245.53 ± 174.94; p < 0.001) compared to the control group (13,783.33 ± 688.69), with levels restored following surgery. Our data presented an inverse association between FSTL1 and AHI (p < 0.001), highlighting its potential use in reflecting OSA severity. Additionally, FSTL1 levels showed a significant negative correlation with the hypoxia-related marker IGFBP4 in OSA participants (r = –0.440; p = 0.005), suggesting a potential link to hypoxic regulation. FSTL1 levels increased significantly (p = 0.041) following MLS, coinciding with improvements in AHI and indicating remission of OSA. Further, the receiver operating curve (ROC) analysis emphasized a potential role for FSTL1 as a biomarker with predictive qualities for OSA, showing moderate diagnostic accuracy (AUC 0.73, 95% CI: 0.64–0.83, p < 0.001; 8819.09; sensitivity of 86.4%, specificity of 76.2%).ConclusionFSTL1 demonstrates potential as a valuable biomarker that can aid current diagnostic tools for OSA and help evaluate treatment efficacy; however, additional research is warranted to confirm its clinical applicability and explore its therapeutic potential.

Background Type 1 diabetes (T1D) is associated with microbial dysbiosis. While most research has focused on the gut microbiome, limited data address the role of the oral microbiome in T1D. The oral and gut microbiomes overlap substantially, and the oral cavity may influence the gut microbial composition. Saliva and dental plaque represent two distinct oral niches with unique microbial communities, but it remains unclear which better reflects systemic disease states such as T1D. This study compared the performance of salivary and plaque microbiomes in classifying pediatric T1D status. Methods Paired saliva and plaque samples were collected from 46 children (23 with T1D and 23 healthy controls). Microbial DNA was extracted and sequenced to target the 16S rRNA gene. The data were processed via QIIME 2 for taxonomic classification and centered log-ratio transformation. Alpha diversity, microbial abundance, and clustering analyses were performed to compare the oral microbiome between the T1D and control groups. Random forest classifiers were used to evaluate and compare the predictive accuracy of saliva- and plaque-based models, both with and without clinical metadata. Results Saliva samples presented lower alpha diversity than plaque samples did but presented significantly greater bacterial loads and total microbial abundances. Saliva-based models outperformed plaque-based models, achieving a classification accuracy of 94.2% with or without clinical metadata, compared with 73.3% accuracy for plaque-based models. ROC curve analysis further supported this difference, with saliva models reaching an AUC of approximately 0.94 versus 0.75 for plaque, indicating superior discriminative performance. UMAP clustering revealed more distinct separation of the T1D and control groups in terms of the salivary profiles than in the plaque profiles. Feature importance analysis revealed both unique and shared taxa predictive of T1D in each niche. The incorporation of clinical and demographic metadata did not enhance model performance, underscoring the robustness and predictive strength of microbiome data alone. Conclusion The salivary microbiome is a more effective biospecimen than dental plaque for detecting T1D-associated microbial profiles in children. It offers superior classification accuracy and greater sensitivity in distinguishing T1D status, supporting saliva’s potential as a noninvasive, scalable medium for future microbiome-based monitoring. ### Competing Interest Statement The authors have declared no competing interest. Dasman Diabetes Institute, https://ror.org/05tppc012

Established evidence indicates that oral microbiota plays a crucial role in modulating host immune responses to viral infection. Following severe acute respiratory syndrome coronavirus 2, there are coordinated microbiome and inflammatory responses within the mucosal and systemic compartments that are unknown. The specific roles the oral microbiota and inflammatory cytokines play in the pathogenesis of coronavirus disease 2019 (COVID-19) are yet to be explored. Here, we evaluated the relationships between the salivary microbiome and host parameters in different groups of COVID-19 severity based on their oxygen requirement. Saliva and blood samples (n = 80) were collected from COVID-19 and from noninfected individuals. We characterized the oral microbiomes using 16S ribosomal RNA gene sequencing and evaluated saliva and serum cytokines and chemokines using multiplex analysis. Alpha diversity of the salivary microbial community was negatively associated with COVID-19 severity, while diversity increased with health. Integrated cytokine evaluations of saliva and serum showed that the oral host response was distinct from the systemic response. The hierarchical classification of COVID-19 status and respiratory severity using multiple modalities separately (i.e. microbiome, salivary cytokines, and systemic cytokines) and simultaneously (i.e. multimodal perturbation analyses) revealed that the microbiome perturbation analysis was the most informative for predicting COVID-19 status and severity, followed by the multimodal. Our findings suggest that oral microbiome and salivary cytokines may be predictive of COVID-19 status and severity, whereas atypical local mucosal immune suppression and systemic hyperinflammation provide new cues to understand the pathogenesis in immunologically compromised populations.

Angiopoietins are crucial growth factors for maintaining a healthy, functional endothelium. Patients with type 2 diabetes (T2D) exhibit significant levels of angiogenic markers, particularly Angiopoietin-2, which compromises endothelial integrity and is connected to symptoms of endothelial injury and failure. This report examines the levels of circulating angiopoietins in people with T2D and diabetic nephropathy (DN) and explores its link with ANGPTL proteins. We quantified circulating ANGPTL3, ANGPTL4, ANGPTL8, Ang1, and Ang2 in the fasting plasma of 117 Kuwaiti participants, of which 50 had T2D and 67 participants had DN. The Ang2 levels increased with DN (4.34 ± 0.32 ng/mL) compared with T2D (3.42 ± 0.29 ng/mL). This increase correlated with clinical parameters including the albumin-to-creatinine ratio (ACR) (r = 0.244, p = 0.047), eGFR (r = −0.282, p = 0.021), and SBP (r = −0.28, p = 0.024). Furthermore, Ang2 correlated positively to both ANGPTL4 (r = 0.541, p < 0.001) and ANGPTL8 (r = 0.41, p = 0.001). Multiple regression analysis presented elevated ANGPTL8 and ACRs as predictors for Ang2’s increase in people with DN. In people with T2D, ANGPTL4 positively predicted an Ang2 increase. The area under the curve (AUC) in receiver operating characteristic (ROC) analysis of the combination of Ang2 and ANGPTL8 was 0.77 with 80.7% specificity. In conclusion, significantly elevated Ang2 in people with DN correlated with clinical markers such as the ACR, eGFR, and SBP, ANGPTL4, and ANGPTL8 levels. Collectively, this study highlights a close association between Ang2 and ANGPTL8 in a population with DN, suggesting them as DN risk predictors.

Introduction: The increased obesity rates worldwide are associated with increased rates of Non-alcoholic fatty liver disease (NAFLD). Proprotein Convertase Subtilisin/Kexin type 7 (PCSK7) is an enzyme involved in lipid metabolism but its role in the development and progression of NAFLD remains unclear. This study aims to investigate the association between PCSK7 levels and NAFLD severity. Methods: A total of 255 participants were recruited in KADEM study and screened for NAFLD using liver FibroScan machine. Participants were divided into two groups based on controlled attenuation parameter (CAP) scores: 208 dB/m with CAP scores above 294 dB/m, and 47 with CAP scores >294 dB/m. PCSK7 levels were measured using ELISA. Results: PCSK7 levels were higher in people with a CAP score >294 dB/m, with levels of 0.9 ± 0.1 ng/mL compared to 0.5 ± 0.1 ng/mL in individuals with CAP scores lower than 294 dB/m (p=0.022). When the population was divided into tertiles based on CAP scores, PCSK7 levels were 0.30 ± 0.1 ng/mL for CAP scores ≤229, 0.7 ± 0.1 ng/mL for CAP scores between 230-271, and 0.8 ± 0.1 ng/mL for CAP scores ≥272 (p<0.001). PCSK9 levels were positively associated with CAP score (r=0.387, p<0.001), HbA1C (r=0.497, p<0.001), FBG (r=0.497, p<0.001), insulin (r=0.497, p<0.001), HOMA-IR (r=0.480, p<0.001), TG (r=0.366, p<0.001), LDL (r=0.133, p=0.049), and VLDL (r=0.366, p<0.001), while negatively associated with HDL (r=-0.271, p<0.001). Conclusion: Our findings indicate a significant association between elevated PCSK7 levels and increased NAFLD severity implicating a potential role for PCSK7 in NAFLD pathogenesis. Disclosure M. Qaddoumi: None. J. Abubaker: None. I. Al-khairi: None. P.T. Cherian: None. D. Sriraman: None. A.T. Thangavel: None. A.M. Channanath: None. M. Abdul-Ghani: None. F. Almulla: None. M. Abu-farha: None. Funding Dasman Diabetes Institute (RA HM-2019-030)

ObjectivesObstructive sleep apnea (OSA) can adversely affect the immune response through clinical factors such as hypoxia, inflammation, and sleep disturbance. Since SARS-CoV-2 heavily relies on local and systemic host immune responses, this study aims to examine the links between the severity of OSA risk, cytokine levels, and the severity of symptoms associated with SARS-CoV-2 infection.MethodsSaliva and blood samples from 50 COVID-19 patients and 30 non-infected hospital staff members were collected. Using Luminex multiplex analysis, 65 blood and salivary cytokines were examined from the collected samples. Ordinal logistic regression analysis was utilized to examine the association between the self-reported risk of OSA, assessed through the STOP-Bang questionnaire, and the likelihood of experiencing severe symptoms of COVID-19. Mann–Whitney test was then performed to compare the cytokine levels between individuals with moderate to severe risk of OSA to those with a mild risk of OSA.ResultsOrdinal logistic regression analysis revealed that individuals with a moderate to severe risk of OSA were 7.60 times more likely to experience more severe symptoms of COVID-19 compared to those with a mild risk of OSA (OR = 7.60, 95%CI: 3.03, 19.06, p < 0.001). Moreover, among COVID-19-positive patients with a moderate to severe risk of OSA, there was a statistically significant negative correlation with serum IL-6 (p < 0.05), Eotaxin (CCL11) (p = 0.04), and salivary MIP-3α/CCL20 (p = 0.04). In contrast, individuals without COVID-19 who had a moderate to severe risk of OSA exhibited a significant positive correlation with serum IL-6 (p = 0.04).ConclusionIndividuals with moderate to severe risk of OSA were more likely to experience severe COVID-19 symptoms than those with mild risk for OSA. Additional analysis from the present studies revealed distinct patterns of oral and systemic immune responses between individuals with mild and moderate to severe risk of OSA. Findings from the present study underscores the importance of early detection and management of OSA to improve clinical outcomes, particularly when faced with the subsequent superimposed infection such as COVID-19.

Introduction: CHF is defined as a chronic disease that impacts more than 5 million adults in the United States with significant population-wide impact on morbidity, mortality and hospitalization burden, especially amonth high-risk and vulnerable populations. Although the intricacies of CHF and readmission risk have been well documented, there have been fewer studies investigating the effect of illicit drug use on CHF patients and readmission outcomes especially in a population at high risk of health disparities. Objective: The purpose of this study was to examine the effects of illicit drug use on CHF patients and hospital readmission rates at Harlem Hospital Center with a high density of patients with health disparities. Methods: We included all patients admitted during a 2 year period (2019-2020) with a primary diagnosis of heart failure to Harlem Hospital Center and conducted in depth assessment of drug use history including patient history, available laboratory analysis, and collateral EMR information. Rehospitalization was assessed by review of EMR by trained medical professionals. Our results were analyzed using standard statistical methods between the two groups with and without history of drug use. Results: Our study population included 380 admitted CHF patients. The overall prevalence of illicit drug use in CHF patients was 32.89%, with the most common drug used being cocaine. CHF patients who used illicit drugs had a 22.58% 30-day readmission rate in comparison to 13.78% among CHF patients who didn’t use illicit drugs. In addition, CHF patients who used illicit drugs had higher all-time hospitalizations and were more likely to be admitted than non-illicit drug users in terms of heart failure hospitalizations. Overall, CHF patients who used any type of illicit drug were twice as likely to be readmitted after index hospitalization compared to CHF patients who didn’t use illicit drugs. We also found that CHF patients who used illicit drugs were slightly younger, more likely to be male, and more likely to smoke cigarettes. Lastly, we observed that at least 50% of CHF patients who used illicit drugs were on government assistance, lacked family support, and were unemployed. Conclusion: Drug use is a common problem among patients with CHF in this vulnerable population and is associated with significant adverse outcomes such as increased rehospitalization. Systemic efforts to address this at the patient and community level are justified.

BackgroundCoronavirus disease 2019 (COVID-19) caused by the coronavirus SARS-CoV-2, has emerged as a rapidly spreading contagious disease across the globe. Recent studies showed that people with diabetes mellitus, severe obesity, and cardiovascular disease are at higher risk of mortality from COVID-19. It has been suggested that the increased risk is due to the chronic inflammatory state associated with type 2 diabetes. This study aimed to evaluate the efficacy of pioglitazone, a strong insulin sensitizer with anti-inflammatory properties, in improving the clinical outcomes of patients with type 2 diabetes admitted with moderate–severe COVID-19.MethodWe enrolled 350 patients with type 2 diabetes who were admitted to hospitals in Qatar and Kuwait with COVID-19. Patients were randomized to receive, in a double-blind fashion, pioglitazone (n = 189) or a matching placebo (n = 161) for 28 days. The study had two primary outcomes: (1) the incidence of a composite outcome composed of (a) the requirement for mechanical ventilation, (b) death, and (c) myocardial damage; and (2) an increase in C-reactive protein (CRP) levels.ResultsThe first primary outcome occurred in 28 participants (8%), and the secondary outcome occurred in 17. Treatment with pioglitazone showed a significant reduction in interleukin (IL)-3 levels compared with placebo treatment (mean (SD) 2.73 (± 2.14) [95% CI: 0.02, 1.1], p = 0.043 vs. 2.28 (± 1.67) [95% CI: − 0.23, 0.86], p = 0.3, respectively), with no effect seen in the levels of other inflammatory markers. Even though not significant, a few of the patients on pioglitazone exhibited serum troponin levels > 3 times higher than the normal range seen in patients on placebo. On the other hand, more patients on pioglitazone were admitted to the ICU than those with placebo, and no significant difference in the CRP reduction was observed between the two groups.ConclusionThe results of the present study demonstrate that pioglitazone treatment did not independently provide any additional clinical benefit to patients with type 2 diabetes admitted with a COVID-19 infection.Clinical trial registrationhttps://clinicaltrials.gov, identifier NCT04604223.

SARS-CoV-2, a severe respiratory disease primarily targeting the lungs, was the leading cause of death worldwide during the pandemic. Understanding the interplay between the oral microbiome and inflammatory cytokines during acute infection is crucial for elucidating host immune responses. This study aimed to explore the relationship between the oral microbiome and cytokines in COVID-19 patients, particularly those with and without sputum production. Saliva and blood samples from 50 COVID-19 patients were subjected to 16S ribosomal RNA gene sequencing for oral microbiome analysis, and 65 saliva and serum cytokines were assessed using Luminex multiplex analysis. The Mann-Whitney test was used to compare cytokine levels between individuals with and without sputum production. Logistic regression machine learning models were employed to evaluate the predictive capability of oral microbiome, salivary, and blood biomarkers for sputum production. Significant differences were observed in the membership (Jaccard dissimilarity: p = 0.016) and abundance (PhILR dissimilarity: p = 0.048; metagenomeSeq) of salivary microbial communities between patients with and without sputum production. Seven bacterial genera, including Prevotella, Streptococcus, Actinomyces, Atopobium, Filifactor, Leptotrichia, and Selenomonas, were more prevalent in patients with sputum production (p<0.05, Fisher’s exact test). Nine genera, including Prevotella, Megasphaera, Stomatobaculum, Selenomonas, Leptotrichia, Veillonella, Actinomyces, Atopobium, and Corynebacteria, were significantly more abundant in the sputum-producing group, while Lachnoanaerobaculum was more prevalent in the non-sputum-producing group (p<0.05, ANCOM-BC). Positive correlations were found between salivary IFN-gamma and Eotaxin2/CCL24 with sputum production, while negative correlations were noted with serum MCP3/CCL7, MIG/CXCL9, IL1 beta, and SCF (p<0.05, Mann-Whitney test). The machine learning model using only oral bacteria input outperformed the model that included all data: blood and saliva biomarkers, as well as clinical and demographic variables, in predicting sputum production in COVID-19 subjects. The performance metrics were as follows, comparing the model with only bacteria input versus the model with all input variables: precision (95% vs. 75%), recall (100% vs. 50%), F1-score (98% vs. 60%), and accuracy (82% vs. 66%).

ABSTRACT Background Autosomal dominant polycystic kidney disease (ADPKD) is the most common renal monogenic disease, characterized by bilateral accumulation of renal fluid-filled cysts leading to progressive renal volume enlargement and gradual impairment of kidney function, often resulting in end-stage renal disease. Kuwait could provide valuable genetic insights about ADPKD, including intrafamilial phenotypic variation, given its large household size. This study aims to provide a comprehensive description of the pathogenic variants linked to ADPKD in the Kuwaiti population using multiple genetic analysis modalities and to describe and analyse the ADPKD phenotypic spectrum in terms of kidney function, kidney volume and renal survival. Methods A total of 126 ADPKD patients from 11 multiplex families and 25 singletons were recruited into the study. A combination of targeted next-generation sequencing (tNGS), long-range polymerase chain reaction, Sanger sequencing and multiplex ligation-dependent probe amplification were utilized for genetic diagnosis. Clinical evaluation was conducted through renal function testing and ultrasonographic kidney volume analysis. Results We identified 29 ADPKD pathogenic mutations from 36 families achieving an overall molecular genetic diagnostic rate of 112/126 (88.9%), including 29/36 (80.6%) in families. A total of 28/36 (77.8%) families had pathogenic mutations in PKD1, of which 17/28 (60.7%) were truncating, and 1/36 (2.8%) had a pathogenic variant in the IFT140 gene. A total of 20/29 (69%) of the identified ADPKD mutations were novel and described for the first time, including a TSC2-PKD1 contiguous syndrome. Clinical analysis indicated that genetically unresolved ADPKD cases had no apparent association between kidney volume and age. Conclusion We describe for the first time the genetic landscape of ADPKD in Kuwait. The observed genetic heterogeneity underlining ADPKD along with the wide phenotypic spectrum reveal the level of complexity in disease pathophysiology. ADPKD genetic testing could improve the care of patients through improved disease prognostication, guided treatment and genetic counselling. However, to fulfil the potential of genetic testing, it is important to overcome the hurdle of genetically unresolved ADPKD cases.

Objectives Poor sleep behavior can trigger an inflammatory response and contribute to the development of inflammatory diseases. Cytokines can act as indicators of inflammation and may precede the onset of inflammatory diseases. This study aimed to determine the association between sleep timing parameters (bedtime, sleep duration, sleep debt, and social jetlag) and the levels of nine serum and salivary inflammatory and metabolic biomarkers. Methods Data were collected from 352 adolescents aged 16–19 years enrolled in Kuwait’s public high schools. The levels of C-reactive protein (CRP), interleukin-6 (IL-6), interleukin-8 (IL-8), interleukin-10 (IL-10), vascular endothelial growth factor (VEGF), monocyte chemoattractant protein-1 (MCP-1), adiponectin, leptin, and insulin were measured from saliva and serum samples. We conducted mixed-effect multiple linear regression modeling to account for the school variable as a random effect to assess the relationship between the sleep variables and salivary and serum biomarkers. Mediation analysis was conducted to check if BMI was a mediator between bedtime and the biomarkers. Results There was a statistically significant elevation in serum IL-6 level associated with later bedtime (0.05 pg./mL, p = 0.01). Adolescents with severe sleep debt of ≥2 h had an increase in salivary IL-6 biomarker levels (0.38 pg./mL, p = 0.01) compared to those who had sleep debt of <1 h. Adolescents with sleep debt of ≥2 h had significantly higher levels of serum CRP (0.61 μg/mL, p = 0.02) than those without sleep debt. Additionally, we found that the inflammatory biomarkers (CRP, IL-6, IL-8, IL-10, VEGF, and MCP-1) and metabolic biomarkers (adiponectin, leptin, and insulin) had more statistically significant associations with the bedtime variables than with sleep duration variables. CRP, IL-6, and IL-8 were associated with sleep debt, and IL-6, VEGF, adiponectin, and leptin levels were associated with social jetlag. BMIz was a full mediator in the relationship between late bedtime and increased serum levels of CRP, IL-6, and insulin. Conclusion Adolescents who go to bed at or later than midnight had dysregulated levels of salivary and serum inflammatory biomarkers, suggesting that disrupted circadian rhythm can trigger higher levels of systemic inflammation and potentially exacerbate chronic inflammation and the risk of metabolic diseases.

At the beginning of the COVID-19 pandemic, the precise extent of the risks in pregnancy was uncertain. Because of the known deleterious effects of COVID-19 in patients with diabetes, we need to assess the risk imposed by COVID-19 on maternal and neonatal outcomes in GDM pregnant women with COVID-19. To evaluate the risks associated with COVID-19 & GDM in pregnancy on maternal and neonatal outcomes. This is a cohort study that took place over 1 year during covid-19 pandemic in one centre. COVID-19 infected pregnant women, with or without Gestational Diabetes Mellitus were identified. They were included regardless of gestational age and type of delivery. Women and neonates were followed up until discharge from hospital. A total of 314 pregnant women with COVID-19 were enrolled, all with broadly similar demographic characteristics. GDM was diagnosed in 95 women (30.3%). Women with GDM and COVID-19 were at higher risk for pregnancy complications: Euglycemic DKA.preeclampsia/eclampsia, severe infections (88.4%), intensive care unit admission (29.5%), maternal mortality (1.2%), preterm birth (18.9%), medically indicated preterm birth (1.1%), severe neonatal morbidity index (8.4%). Non GDM women with COVID-19 diagnosis remained at higher risk only for maternal morbidity (2.2%), Intensive care unit admission (11.8%), preterm birth (26.4%), severe neonatal morbidity index (2.8%). Fever and shortness of breath for any duration were associated with an increased risk of severe maternal complications (65.3%) and neonatal complications (8.4%) in GDM, where in non GDM was reduced the risk for maternal complications (35.4%) and as well for neonatal complications (2.8%). In this cohort study, COVID-19 and GDM were associated with a consistent and substantial increases in severe maternal morbidity and mortality and neonatal complications when pregnant women infected with COVID-19 diagnosed. The findings should alert clinicians as well as pregnant women to strictly implement all the recommended COVID-19 preventive measures including vaccination against COVID-19.