medRxiv : serveur de preprint pour les sciences médicales

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 x 10-9). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in MTMR3 that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the POC5 and DMD loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.

Internalizing disorders (depression, anxiety, somatic symptom disorder) are among the most common mental health conditions that can substantially reduce daily life function. Early adolescence is an important developmental stage for the increase in prevalence of internalizing disorders and understanding specific factors that predict their onset may be germane to intervention and prevention strategies. We analyzed ~6,000 candidate predictors from multiple knowledge domains (cognitive, psychosocial, neural, biological) contributed by children of late elementary school age (9-10 yrs) and their parents in the ABCD cohort to construct individual-level models predicting the later (11-12 yrs) onset of depression, anxiety and somatic symptom disorder using deep learning with artificial neural networks. Deep learning was guided by an evolutionary algorithm that jointly performed optimization across hyperparameters and automated feature selection, allowing more candidate predictors and a wider variety of predictor types to be analyzed than the largest previous comparable machine learning studies. We found that the future onset of internalizing disorders could be robustly predicted in early adolescence with AUROCs [≥]~0.90 and [≥]~80% accuracy. Each disorder had a specific set of predictors, though parent problem behavioral traits and sleep disturbances represented cross-cutting themes. Additional computational experiments revealed that psychosocial predictors were more important to predicting early adolescent internalizing disorders than cognitive, neural or biological factors and generated models with better performance. We also observed that the accuracy of individual-level models was highly correlated to the relative importance of their constituent predictors, suggesting that principled searches for predictors with higher importance or effect sizes could support the construction of more accurate individual-level models of internalizing disorders. Future work, including replication in additional datasets, will help test the generalizability of our findings and explore their application to other stages in human development and mental health conditions.

Background Despite the escalating incidence of degenerative valvular heart disease (VHD), recommended preventive interventions are conspicuously absent. Physical activity has proven effective in preventing atherosclerotic cardiovascular disease, but its role in preventing VHD remains uncertain. This study aimed to explore the association between moderate-to-vigorous intensity physical activity (MVPA) and incident left-sided degenerative VHD in middle-aged adults from the UK biobank. Methods Data from wrist-worn accelerometer and self-reported questionnaires were utilized to assess the impact of MVPA volume on the incidence of aortic valve stenosis (AS), aortic valve regurgitation (AR), and mitral valve regurgitation (MR). Incident VHD were ascertained from hospital admissions and death reports. Cox proportional hazards regression models were employed to calculate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusted for sociodemographic characteristics, lifestyle risk factors, and comorbidities. Results In the accelerometer-derived MVPA cohort (n=90,865; median age 63; 43% male; median follow-up 8.1 years), the age- and sex-adjusted incidence rates per 1000 person-years were 0.70 for AS, 0.29 for AR, and 0.84 for MR. In the questionnaire-based MVPA cohort (n=397,335; median age 57; 47% male; median follow-up 13.8 years), the corresponding rates were 0.76 for AS, 0.29 for AR, and 0.76 for MR. The accelerometer-measured MVPA volume showed a curvilinear relationship with reduced risk of AS, plateauing above 300 min/week. Participants engaging in 150-299 minutes of MVPA per week, meeting the guideline recommendation, had the most significant reduction in AS risk compared to those with no MVPA [adjusted HR, 0.53 (95% CI, 0.37-0.76)]. Similar results were found in the questionnaire-based MVPA cohort, with 150-299 minutes of MVPA showing a relatively smaller reduction in HR [adjusted HR, 0.82 (95% CI, 0.73-0.91)]. The association remained consistent across subgroups at high risk for AS. However, there was no significant inverse association of MVPA with risk of AR or MR. Conclusion Adhering to the recommended MVPA duration (150-299 min/week) was associated with the lowest risk of developing AS. Encouraging the utilization of wearable devices to monitor activity levels enhances AS risk reduction. Nonetheless, MVPA's efficacy in preventing valvular regurgitation is limited, revealing distinctive pathological mechanisms in valvular stenotic and regurgitation lesions.

Poor diets contribute to significantly and increasingly to the burden of chronic diseases in the United Kingdom, impacting both health and the economy. The introduction of fiscal measures that target unhealthy foods could provide a near-unique opportunity to shifting diets at scale for the benefit of both social and economic sustainability. This study estimates the expected health and economic benefits from the reduction in consumption of salt and sugar for four scenarios, each reflecting different manufacturer and consumer responses to a proposed tax on salt and sugar. The results of this modelling show that life expectancy in the UK could be increased by between 1.7 months and nearly 5 months, depending on the degree of industry and consumer response to the tax. The tax could also lead to almost 2 million fewer cases of preventable chronic diseases over 25 years. In addition, economic benefits of approximately 27 to 78 billion GBP from avoided ill-health could be achieved by introducing the proposed tax. The main part of these gains can be attributed to reduced mortality and morbidity from cardiovascular diseases. Our modelling show that significant benefits to both population health and the economy could be expected from the taxation of foods high in salt and sugar. The proposed dietary changes are likely to be insufficient to reach national public health targets; hence, additional measures to reduce the burden of chronic disease in the UK are equally critical to consider.

Background Iron has been proposed as a risk factor for atherosclerosis but the data are controversial. We previously showed that non-transferrin-bound iron (a fraction of iron appearing in iron overload) contributes to atherosclerosis. Here, we investigated whether iron within physiological limits influenced atherosclerosis by studying its association with vascular dysfunction and peripheral arterial disease (PAD). Further, we evaluated if this relationship was influenced by comorbidities. Methods We studied the association between iron biomarkers in blood and markers for vascular adhesion and PAD in 368 individuals registered in the Heidelberg Study on Diabetes and Complications (HEIST-DiC). Our observations were validated by analyzing the association between iron biomarkers and PAD in the National Health and Nutrition Examination Survey (NHANES 1999-2004) data. Results In both HEIST-DiC and NHANES cohorts, plasma ferritin levels are positively associated with PAD in females and not in males. We further identified negative associations between TIBC and plasma iron levels with PAD among females. These relationships were independent of the presence of other comorbidities including hypertension, insulin resistance, prediabetes, and diabetes. Conclusion We demonstrate a sex-specific alteration of markers of systemic iron availability in individuals with clinically apparent PAD implying that mechanisms of disease development may differ between males and females. Elevated ferritin levels and hypoferremia in females are indicative of an underlying inflammation that may affect the pathogenesis of PAD. The observed lack of a positive association of PAD with serum iron levels suggest that "physiological" iron concentrations are safe for vascular health.

Streptococcus dysgalactiae subspecies equisimilis (SDSE) and Streptococcus pyogenes share skin and throat niches with extensive genomic homology and horizontal gene transfer (HGT) possibly underlying shared disease phenotypes. It is unknown if cross-species transmission interaction occurs. We conducted a genomic analysis of a longitudinal household survey in remote Australian First Nations communities for patterns of cross-species transmission interaction and HGT. From 4,547 person-consultations, 294 SDSE and 315 S. pyogenes isolates were sequenced. SDSE and S. pyogenes transmission intersected extensively among households and the observed co-occurrence and transmission links were consistent with independent transmission without inter-species interference. At least one of three near-identical cross-species mobile genetic elements (MGEs) carrying antimicrobial resistance or streptodornase virulence genes was found in 55 (19%) SDSE and 23 (7%) S. pyogenes isolates. These findings demonstrate extensive co-circulation of both pathogens and HGT and support a need to integrate SDSE and S. pyogenes surveillance and control efforts.

Background Following ART initiation, a spectrum of HIV-associated immune reconstitution inflammatory syndrome (IRIS), as opportunistic infections occurs, presenting as either paradoxical or unmasking IRIS. There are benefits of ART for maternal health and prevention of perinatal transmission, however, some risks may be possible with IRIS. The study sought to estimate the incidence, compare survival times to, and investigate the baseline clinical predictors of HIV-1 paradoxical and unmasking IRIS as well as identify the homogeneity defined by combinations of specific covariates in Art Naive Pregnant Women. Methods A prospective, active records observational study was conducted among ART- naive pregnant women attending antenatal care unit (ANCu) from Kenyatta National and Mbagathi Hospitals in Kenya. Participants enrolled were between the ages of 20 - 49 years with a clear documentation of HIV status and, an independent review committee adjudicated IRIS diagnosis. Associations between baseline pre-ART characteristics, biomarkers, and IRIS diagnosis were assessed with Cox models. Decision-tree analysis was finally performed to identify homogeneity defined by combinations of specific parameters. Results Of the initial total 532 women, (24.8%) (n=133) participants experienced IRIS by the 12th week post ART initiation, 27.3 % (n= 36) and 72.7% (n = 96) paradoxical and unmasking respectively. Maternal Basal Metabolic Index (MBMI) of (25 -29.9) significantly predicted unmasking IRIS [({beta})=0.907, Wald test ({beta}^) = 6.550, (HR = 2.478, 95% C.I 1.237 - 4.965, P = 0.010] same case to gravidity of above 5 [({beta})=0.743, P = 0.338] while that of 2-3 predicted paradoxical IRIS [({beta})= - 0.542, P = 0.037. WHO-HIV clinical stage 1 and 2 showed a link towards paradoxical IRIS, [({beta})= - 0.111 and ({beta})= - 0.276 (P < 0.05)], clinical stage 4 with unmasking IRIS [({beta})= 0.047, HR = 1.048,P = 0.941]. CD4 count > 500 cells/mm3 skewed towards unmasking IRIS diagnosis [({beta})= 0.192, HR = 1.211, P = 0.416], while RNA-HIV viral loads > 50 copies/ml towards paradoxical IRIS [({beta})= - 0.199, HR = 0.820, P = 0.360. On decision tree analysis, 76% (P = 0.729) of ART naive pregnant women aged 20-29 and 40-49 years of age presented with unmasking IRIS and a gravidity of 4-5 and 1 predicted 88% (P = 0.045) unmasking IRIS as compared to that of 2-3 62 % (P = 0.045). Conclusion Unmasking IRIS was the common type of IRIS post-ART initiation. Maternal BMI and RNA-HIV viral loads level predicted paradoxical IRIS while the baseline CD4 count and WHO- HIV clinical infection stage 1 and 4 were associated with unmasking IRIS. Gravidities of 1 and 4-5 predicted unmasking IRIS.

Cervical cancer is caused by human papillomavirus (HPV) infection, has few approved targeted therapeutics, and is the most common cause of cancer death in low-resource countries. We characterized 19 cervical and four head and neck cell lines using long-read DNA and RNA sequencing and identified the HPV types, HPV integration sites, chromosomal alterations, and cancer driver mutations. Structural variation analysis revealed telomeric deletions associated with DNA inversions resulting from breakage-fusion-bridge (BFB) cycles. BFB is a common mechanism of chromosomal alterations in cancer, and this is one of the first analyses of these events using long-read sequencing. Analysis of the inversion sites revealed staggered ends consistent with exonuclease digestion of the DNA after breakage. Some BFB events are complex, involving inter- or intra-chromosomal insertions or rearrangements. None of the BFB breakpoints had telomere sequences added to resolve the dicentric chromosomes and only one BFB breakpoint showed chromothripsis. Five cell lines have a Chr11q BFB event, with YAP1/BIRC2/BIRC3 gene amplification. Indeed, YAP1 amplification is associated with a 10-year earlier age of diagnosis of cervical cancer and is three times more common in African American women. This suggests that cervical cancer patients with YAP1/BIRC2/BIRC3-amplification, especially those of African American ancestry, might benefit from targeted therapy. In summary, we uncovered new insights into the mechanisms and consequences of BFB cycles in cervical cancer using long-read sequencing.

A major limitation in current Alzheimer's disease (AD) research is the lack of the ability to measure cognitive performance at scale - robustly, remotely, and frequently. For the purposes of screening, recruitment, stratification, and longitudinal follow-up in clinical trials, there are no established online digital platforms validated against plasma biomarkers of AD. Here we report findings using a novel web-based platform that assessed different cognitive functions in AD patients (N=46) and elderly controls (N=53) who were also assessed for plasma biomarkers of AD (amyloid{beta} 42/40 ratio, pTau181, GFAP, NfL). Their performance was compared to a second, larger group of elderly controls (N=256). AD patients were significantly impaired across all digital cognitive tests, with performance correlating with plasma biomarker levels, particularly pTau181. These findings show how online testing can now be deployed in AD patients to measure cognitive function effectively and related to blood biomarkers of the disease.

Introduction: Pancreaticoduodenectomy (PD) for patients with pancreatic ductal adenocarcinoma (PDAC) is associated with a high risk of postoperative complications (PoCs) and risk prediction of these is therefore critical for optimal treatment planning. We hypothesize that novel deep learning network approaches through transfer learning may be superior to legacy approaches for PoC risk prediction in the PDAC surgical setting. Methods: Data from the US National Surgical Quality Improvement Program (NSQIP) 2002-2018 was used, with a total of 5,881,881 million patients, including 31,728 PD patients. Modelling approaches comprised of a model trained on a general surgery patient cohort and then tested on a PD specific cohort (general model), a transfer learning model trained on the general surgery patients with subsequent transfer and retraining on a PD-specific patient cohort (transfer learning model), a model trained and tested exclusively on the PD-specific patient cohort (direct model), and a benchmark random forest model trained on the PD patient cohort (RF model). The models were subsequently compared against the American College of Surgeons (ACS) surgical risk calculator (SRC) in terms of predicting mortality and morbidity risk. Results: Both the general model and transfer learning model outperformed the RF model in 14 and 16 out of 19 prediction tasks, respectively. Additionally, both models outperformed the direct model on 17 out of the 19 tasks. The transfer learning model also outperformed the general model on 11 out of the 19 prediction tasks. The transfer learning model outperformed the ACS-SRC regarding mortality and all the models outperformed the ACS-SRC regarding the morbidity prediction with the general model achieving the highest Receiver Operator Area Under the Curve (ROC AUC) of 0.668 compared to the 0.524 of the ACS SRC. Conclusion: DNNs deployed using a transfer learning approach may be of value for PoC risk prediction in the PD setting.

Introduction: Computer vision extracts meaning from pixelated images and holds promise in automating clinical tasks. Convolutional neural networks (CNN), deep learning networks used therein, have shown promise in X-ray images as well as joint photographs. We studied the performance of a CNN on standardized smartphone photographs in detecting inflammation in three hand joints. Methods: We enrolled consecutive patients with inflammatory arthritis of less than two years duration and excluded those with deformities. Each patient was examined by a rheumatologist and the presence of synovitis in each joint was recorded. Hand photographs were taken in a standardized manner and anonymized. Images were cropped to include joints of interest. A reNrt-101 backbone modified for two class outputs (inflamed or not) was used for training. We also tested a hue augmented dataset. We report accuracy, sensitivity and specificity for three joints: wrist, index finger proximal interphalangeal (IFPIP), middle finger interphalangeal (MFPIP). Results: The cohort had a mean age of 49.7 years; most had rheumatoid arthritis(n=68). The wrist (62.5%), MFPIP (47%) and IFPIP (41.5%) were the three most commonly inflamed joints. The CNN achieved the highest accuracy in being able to detect synovitis in the MFPIP (83%) followed by the IFPIP (74%) and the wrist (65%). Discussion: We show that computer vision was able to detect inflammation in three joints of the hand with reasonable accuracy on standardized photographs despite a small dataset. Feature engineering was not required, and the CNN worked despite a diversity in clinical diagnosis. Larger datasets are likely to improve accuracy and help explain the basis of classification. These data suggest a potential use of computer vision in screening and follow-up of inflammatory arthritis.

Background: Wait times are reported to impede adolescents access to mental health treatment for anxiety and depression. However, there is limited quantitative research on current wait times for the treatment of anxiety and depression for Australian adolescents' and the impact of these on young help-seekers. Aims: This study examined Australian adolescents' experiences of wait times for the treatment of anxiety and depression, including the providers they were waiting to access, the self-reported duration and perceived acceptability of wait times, the association between these wait times and psychological distress, and the support and coping behaviours used by adolescents during this time. Method: From April to June 2022, 375 Australian adolescents aged 13-17 years who were currently waiting, or had previously waited in the past 12 months, for mental health treatment for anxiety and depression completed an anonymous cross-sectional online survey. Results: The mean wait time across all treatment providers was 94.1 days (SD: 69.65). Psychologists and psychiatrists were the most utilised services. Most participants felt their wait times were "too long" and longer wait times were significantly associated with increased psychological distress. Many participants perceived their mental health to have worsened during the wait time and engaged in maladaptive and risky coping behaviours while waiting. Most participants did not receive any support from their healthcare providers during the wait time. However, self-reported treatment attendance remained high. Conclusions: Many Australian adolescents face lengthy wait periods when trying to access mental health treatment and this period may exacerbate distress and maladaptive coping.

Background and aims: Maintenance of abstinence in alcohol-related liver disease (ARLD) is a major unmet therapeutic need. Digital therapeutics can deliver ongoing behavioural therapy, in real-time, for chronic conditions. The aim of this project was to develop and clinically test AlcoChange, a novel digital therapeutic for ARLD. Methods: AlcoChange was developed using validated behaviour change techniques (BCTs) and a digital alcohol breathalyser. This was an open-label, single-centre study. Patients with ARLD, ongoing alcohol use (within 1 month) and possession of a suitable smartphone were eligible. Patients were recruited from inpatient and outpatient settings, and received AlcoChange therapy for 3-months. The primary outcome was reduction in alcohol use from baseline to 3-months, measured by timeline follow-back (TLFB). Secondary outcomes included: (i) compliance with the AlcoChange app, (ii) alcohol-related and all-cause hospital re-admissions up to 1-year, (iii) qualitative analysis to determine factors associated with compliance. Results: Sixty-five patients were recruited, of whom forty-one completed the study per-protocol. Patients compliant with the intervention (>60 logins over 3-months) had a significant reduction in alcohol use from baseline compared to non-compliant patients [median (IQR): -100% (100% to -55.1%) vs -57.1% (-95.3% to +32.13%), p=0.029]. The proportion attaining abstinence at 3-months was higher in the compliant group (57.1% vs 22.2%, p=0.025). The compliant group had a significantly decreased risk of subsequent alcohol-related re-admission up to 12-months (p=0.008). Qualitative analysis demonstrated receiving in-app feedback and presence of health-related sentinel event were predictors of compliance with the intervention. Conclusions: Use of the novel digital therapeutic, AlcoChange, was associated with a significant reduction in alcohol use and increase in proportion attaining abstinence in ARLD patients. Definitive, randomized trials are warranted for this intervention.

Background: Atrial fibrillation and heart failure are closely related and share multiple risk factors. We aimed to apply the mendelian randomization (MR) analysis to explore the bidirectional causal link between atrial fibrillation and heart failure, and the independent effect of potential risk factors on the risk of both conditions. Methods: This is a two-sample MR study using publicly available summary-level statistics of genome-wide association studies (GWAS). Bidirectional MR was performed to explore the relation between atrial fibrillation and heart failure. A total of 14 factors were selected as potential risk factors, univariable MR analyses were used to identify shared risk factors, and then the multivariable MR analyses were further used to investigate the independent effect of these factors on both conditions. Inverse-variance-weighted MR (IVW-MR) were used to obtain the effect estimates. Results: MR analysis found evidence of causal relationship between atrial fibrillation and heart failure (odds ratio [OR], 1.24; 95% confidence interval [CI], 1.19-1.29), as well as between heart failure and atrial fibrillation (OR, 3.88; 95% CI, 1.45-10.37). Univariable MR analyses identified several shared risk factors for both conditions, including body mass index (BMI), blood pressure, smoking, coronary heart disease and myocardial infarction. After adjusting for atrial fibrillation, the observed associations between shared factors and heart failure kept stable, such as BMI, smoking, coronary heart disease and myocardial infarction. However, after adjusting for heart failure, the relationships between most risk factors and atrial fibrillation attenuated to null. Conclusions: This two-sample MR study found a bidirectional relationship between atrial fibrillation and heart failure, and identified several shared risk factors of both conditions, which had an independent effect on the risk of heart failure while probably affected the risk of atrial fibrillation via cardiac impairment. Funding: Start-up Fund for high-level talents of Fujian Medical University (grant no.XRCZX2021026) and Natural Science Foundation of Fujian Province (grant no. 2022J01706).

Background Metabolite abundance is a dynamic trait that is not only variable in a fasting state, but also varies in response to environmental stimuli, such as food consumption. Postprandial abundance and response to a meal are emergent traits in studies of disease and which themselves may be subject to specific risk factors. We investigated body mass index (BMI) as a recognized risk factor for numerous health outcomes that may influence metabolite response to feeding. Here we use the Netherlands Epidemiology of Obesity (NEO) study to examine associations between BMI and metabolite response to a liquid meal and extend this by using Mendelian randomization (MR) to estimate potential causal effects. Methods and findings The NEO study conducted a liquid meal challenge and collected metabolite profiles using the Nightingale metabolomics platform in 5744 study participants. Observational and one-sample MR analysis were conducted to estimate the effect of BMI on metabolites and ratios of metabolites (n = 229) in the fasting, postprandial and response (or change in abundance) states. After an appropriate multiple testing correction, we observed 473 associations with BMI (175 fasting, 188 postprandial, 110 response) in observational analyses. In MR analyses, we observed 20 metabolite traits (5 fasting, 12 postprandial, 3 response) to be associated with BMI. In both the fasting and postprandial state, this included citrate and the ratios of linoleic acid, omega-6 fatty acid and polyunsaturated fatty acids to total fatty acids. In addition, the glucogenic amino acid alanine was inversely associated with BMI in the response state, suggesting that as alanine increased in postprandial abundance, that increase was attenuated with increasing BMI. Conclusions Overall, MR estimates were strongly correlated with observational effect estimates suggesting that the broad associations seen between BMI and metabolite variation in fasting, postprandial and response states have a causal underpinning. Specific effects in previously unassessed postprandial and response states were detected and these may likely mark novel life course risk exposures driven by regular nutrition.

Background: The Dietary Inflammatory Index (DII), has been specifically designed to capture the inflammatory content of diet and has shown association with neurodegenerative disease related outcomes. But literature is limited on the role of diet-driven inflammation measured by the DII on incident all-cause dementia and Alzheimer's disease dementia (AD). Objective: We evaluated whether higher DII scores were associated with increased incidence of all-cause dementia and AD over 22.3 years of follow-up in the community-based Framingham Heart Study (FHS) Offspring cohort. Design, Setting, and Participants Observational longitudinal study in the FHS Offspring cohort. Dementia surveillance for present study: until 2020. Data were analyzed from December 2020 to June 2022. Participants completed a validated 126-item food frequency questionnaires (FFQ), administered at FHS examination cycle 7 (1998-2001) and examination cycle 5 (1991-1995), and/or 6 (1995-1998). Individuals aged <60 years, with prevalent dementia, no dementia follow-up, other relevant neurological diseases, and/or no FFQ data were excluded. Exposure A DII score (based on the published method by Shivappa et al. 2014) was created based on previous studies linking individual dietary factors to six inflammatory markers (i.e. C-reactive protein, interleukin (IL)-1 beta;, IL-4, IL-6, IL-10, and tumor necrosis factor-alpha), consisting of 36 components. A cumulative DII score was calculated by averaging across a maximum of three FFQs. Main outcomes and measures Incident all-cause dementia and AD. Results We included 1487 participants (mean age in years 69 (SD=6);53.2% women;31.6% college graduates]). 246 participants developed all-cause dementia (including AD n=187) over a median follow up time of 13.1 years. Higher DII scores were associated with an increased incidence of all-cause dementia and AD following adjustment for age and sex (Hazard ratio (HR)1.16, 95% confidence interval (CI) 1.07 to 1.25,p<.001;HR1.16, 95% CI1.06 to 1.26,p=.001). The relationships remained after additional adjustment for demographic, lifestyle, and clinical covariates (HR1.21, 95% CI1.10 to 1.33,p<0.001;HR1.20, 95% CI1.07 to 1.35,p=.001). Conclusion and relevance Higher DII scores were associated with a higher risk of incident all-cause dementia and AD. Although these promising findings need to be replicated and further validated, our results suggest that diets which correlate with low DII scores may prevent late-life dementia.

Background Dengue is an increasing health burden that has spread throughout the tropics and sub-tropics. There is currently no effective vaccine and control is only possible through integrated vector management. Early warning systems to alert potential dengue outbreaks are currently being explored but despite showing promise are yet to come to fruition. This study addresses the use of meteorological variables for predicting both entomological indices and dengue incidences and assesses the added value of additionally using entomological indices for predicting dengue incidences. Methodology/Principal Findings Entomological surveys were carried out monthly for 14 months in six sites spread across three environmentally different cities of the Philippines. Meteorological and dengue data were acquired. Non-linear generalized additive models were fitted to test associations with the meteorological variables and both entomological indices and dengue cases. Rain and the diurnal temperature range (DTR) contributed most to explaining the variation in both entomological indices and number of dengue cases. DTR and minimum temperature also explained variation in dengue cases occurring one and two months later. The number of adult mosquitoes did associate with the number of dengue cases, but contributed no additional value for predicting dengue cases. Conclusions/Significance The use of meteorological variables to predict future risk of dengue holds promise. The lack of added value of using entomological indices confirms several previous studies and given the onerous nature of obtaining such information, more effort should be placed on improving meteorological information at a finer scale to evaluate efficacy in early warning of dengue outbreaks.

Background: Sodium-glucose cotransporter-2 inhibitors (SGLT2I) have been suggested to have beneficial effects against atherosclerotic cardiovascular disease. The comparative risks of new onset peripheral arterial disease (PAD) between SGLT2Is, dipeptidyl peptidase-4 inhibitors (DPP4Is) and glucagon-like peptide-1 receptor agonist (GLP1a) remain unknown. Objective: This real-world study aims to compare the risks of PAD upon exposure to SGLT2I and dipeptidyl peptidase-4 inhibitors (DPP4I). Methods: This was a retrospective population-based cohort study of patients with type-2 diabetes mellitus (T2DM) on either SGLT2I or DPP4I between 1st January 2015 and 31st December 2020 using a territory-wide registry in Hong Kong. The primary outcome was new-onset PAD. The secondary outcome was all-cause mortality. Propensity score matching (1:1 ratio) using the nearest neighbour search was performed. Multivariable Cox regression was applied to identify significant associations. A three-arm sensitivity analysis including the GLP1a cohort was conducted. Results: This cohort included 75470 T2DM patients (median age: 62.3 years old [SD: 12.8]; 55.79 % males). The SGLT2I and DPP4I groups consisted of 28753 patients and 46717 patients, respectively. After matching, 186 and 256 patients suffered from PAD in the SGLT2I and DPP4I groups respectively, over a median follow-up of 5.6 years. SGLT2I use was associated with lower risks of PAD (Hazard ratio [HR]: 0.85; 95% Confidence Interval [CI]: 0.67-0.98) compared to DPP4I use after adjustments for demographics, comorbidities, medications, renal function, and diabetic laboratory tests. Similar associations were observed in subgroup analyses in male patients above 65 years old, with hypertension, and low HbA1c levels. In the sensitivity analysis, SGLT2I was not associated with lower risks of PAD compared to GLP1a (HR: 0.88; 95% CI: 0.65-1.18). The results remained consistent in the competing risk and the sensitivity analyses. Conclusions: SGLT2I use amongst T2DM patients was associated with lower risks of new-onset PAD and PAD-related outcomes when compared to DPP4I after adjustments.

Objectives: Epileptiform activity (EA) worsens outcomes in patients with acute brain injuries (e.g., aneurysmal subarachnoid hemorrhage [aSAH]). Randomized trials (RCTs) assessing anti-seizure interventions are needed. Due to scant drug efficacy data and ethical reservations with placebo utilization, RCTs are lacking or hindered by design constraints. We used a pharmacological model-guided simulator to design and determine feasibility of RCTs evaluating EA treatment. Methods: In a single-center cohort of adults (age >18) with aSAH and EA, we employed a mechanistic pharmacokinetic-pharmacodynamic framework to model treatment response using observational data. We subsequently simulated RCTs for levetiracetam and propofol, each with three treatment arms mirroring clinical practice and an additional placebo arm. Using our framework we simulated EA trajectories across treatment arms. We predicted discharge modified Rankin Scale as a function of baseline covariates, EA burden, and drug doses using a double machine learning model learned from observational data. Differences in outcomes across arms were used to estimate the required sample size. Results: Sample sizes ranged from 500 for levetiracetam 7 mg/kg vs placebo, to >4000 for levetiracetam 15 vs. 7 mg/kg to achieve 80% power (5% type I error). For propofol 1mg/kg/hr vs. placebo 1200 participants were needed. Simulations comparing propofol at varying doses did not reach 80% power even at samples >1200. Interpretation: Our simulations using drug efficacy show sample sizes are infeasible, even for potentially unethical placebo-control trials. We highlight the strength of simulations with observational data to inform the null hypotheses and assess feasibility of future trials of EA treatment.

Background In the wake of the 2022-2023 mpox outbreak, crucial knowledge gaps exist regarding orthopoxvirus-specific immunity in risk groups and its impact on future outbreaks. Here, we combined cross-sectional seroprevalence studies in two cities in the Netherlands with mathematical modelling to evaluate the risk of future mpox outbreaks among men who have sex with men (MSM). Methods Serum samples were obtained from 1,065 MSM visiting the Centres for Sexual Health (CSH) in Rotterdam or Amsterdam after the introduction of vaccination and the peak of the Dutch mpox outbreak. For MSM visiting the CSH in Rotterdam, sera were linked to epidemiological and vaccination data. An in-house developed ELISA was used to detect vaccinia virus (VACV)-specific IgG; plaque reduction neutralization tests (PRNT) were performed on a selection of samples. These observations were combined with literature data on infection dynamics and vaccine effectiveness to inform a stochastic transmission model to estimate the risk on future mpox outbreaks. Findings The seroprevalence of VACV-specific IgG was 45.4% and 47.1% in Rotterdam and Amsterdam, respectively. Based on the correlation between serological parameters, we identified confirmed MPXV infections and inferred nine undiagnosed infections in individuals without childhood smallpox vaccination in the Rotterdam cohort (5.1%). Transmission modelling showed that the overall number of mpox cases in new outbreaks would be low, but that the current level of immunity alone may not prevent future outbreaks. Maintaining a short time-to-diagnosis will be a key component of any strategy to prevent new outbreaks. Interpretation Our findings indicate a reduced likelihood of future mpox outbreaks among MSM in the Netherlands under the current conditions, but emphasise the importance of maintaining population immunity, diagnostic capacities, and disease awareness. Funding National Institute for Public Health and the Environment (RIVM), HORIZON-HLTH-2022-MPX-14 (101115188).