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Physiological signals such as pulse and respiration strongly contribute to non-neuronal signal change of the blood oxygenation level-dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI). This has been observed not only during task-based but also during resting-state fMRI measurements, where the confounding influence of physiological signals is most pronounced. Over the last decades, a variety of techniques evolved, aiming at detecting and removing physiological artifacts in fMRI time series. These follow either a solely data-driven approach or rely on externally recorded physiological data. To record cardiac and respiratory signals, typically pulse oximetry or electrocardiography (ECG) and a respiration belt are used, respectively. New technologies allow to capture respiratory signal directly with a sensor placed within the spine coil in the patient table, eliminating the need of a respiration belt, which considerably increases participants comfort. However, little is known about the effectiveness of these new technologies and how they compare to the standard respiration belt recording. In the current study, we compared the two devices, respiration belt and spine coil sensor, in their suitability for physiological noise removal during a visual perception task and during rest. We did not find any differences in resting-state functional connectivity (RSFC) or stimulus-related activity between data corrected with the two recording devices. However, we did find reduced residual noise in the time series corrected with spine coil-derived respiration signals compared to belt-based corrected data in the task dataset. Our results show that spine coil- derived respiration recordings are slightly superior to belt respiration recordings for physiological noise removal in task-induced activity, with spine coil recordings having an additional advantage in terms of subject comfort.

Adherence is a critical component of successful HIV treatment among people living with HIV/AIDS. It is essential for achieving and maintaining viral suppression, which is the primary goal of HIV care. The objective of this study was to assess the disparity of the treatment adherence of selected subpopulations among HIV adult patients in Tanzania. The study used a cross-sectional survey of 792 adults living with HIV/AIDS from 31 regions in Tanzania. A two-stage stratified cluster design was used in this survey and included jackknife replicate sampling weights. Frequency tables displaying frequencies, weighted proportions, and confidence intervals were employed to depict socio-demographic by treatment adherence. Treatment adherence was calculated as the (prescribed doses-missed doses)/ prescribed doses * 100. Rao-Scott chi-square was used to produce the weighted proportions of the adherence within subpopulations. Also, the Adjusted Wald Test was used to examine whether or not the subpopulations are similar to or different in terms of their level of treatment adherence. The results showed that there was a significant difference in treatment adherence between the selected subpopulations. The majority of the selected subpopulations, including those based on age, sex, marital status, and level of education, were found to have disparities in the level of treatment adherence. However, the study also revealed no disparities in treatment adherence between urban and rural settings, married and widowed, age groups of 25 to 34, and those of 55 and over. The study's findings revealed considerable disparities in treatment adherence between various subpopulations, emphasizing the necessity for specifically developed interventions to address these disparities so as to attain better health outcomes among adult living with HIV/AIDS.

Background: Breast cancer is a global public health problem, representing a significant burden at the personal, collective, economic and quality of life level. It is necessary to consider the incidence, prevalence and mortality of this disease with a regional approach, so the objective of this work is to describe the epidemiological behavior of this tumor in the departments of the Colombian Caribbean Region during the period 2018 to 2021. Methodology: Descriptive, retrospective study. Data from a secondary source (Cuenta de Alto Costo) was taken through the Higia platform. Rates x 100,000 of proportion of new cases reported, prevalence and incidence, by departments are analyzed. Data was imported from a downloadable .csv file into Excel and then into SPSS V22. Results: The indicators analyzed showed a heterogeneous behavior in the 8 departments of the Region. Atlantico and Bolivar were the departments with similar and higher figures in the 4 years observed than those of the country and there were atypical values in San Andres. La Guajira was the only department with a sustained tendency to increase in incidence, prevalence and mortality. Conclussion: There are differences in breast cancer indicators between colombian caribbean departments.

Purpose: Understanding health-related quality of life (HRQOL) in children and adolescents, during a pandemic and afterwards, aids in understanding how circumstances in their lives impact their well-being. We aimed to identify determinants of HRQOL from a set of biological, psychological and social factors. Methods: Data was taken from a longitudinal sample (n = 1843) of children and adolescents enrolled in the prospective school-based cohort study Ciao Corona in Switzerland. The primary outcome was HRQOL, assessed using the KINDL total score and its subscales (each from 0, worst, to 100, best). Potential determinants, including biological (physical activity, screen time, sleep, chronic conditions, etc), psychological (sadness, anxiousness, stress) and social (nationality, parents education, etc) factors, were assessed in 2020 and 2021, and HRQOL in 2022. Determinants were identified in a data-driven manner using recursive partitioning to define homogeneous subgroups, stratified by school level. Results: Median KINDL total score in the empirically identified subgroups ranged from 68 to 83 in primary school children and from 69 to 82 in adolescents in secondary school. The psychological factors sadness, anxiousness and stress in 2021 were identified as the most important determinants of HRQOL in both primary and secondary school children. Other factors, such as physical activity, screen time, chronic conditions or nationality, were determinants only in individual subscales. Conclusion: Recent mental health, more than biological, physical or social factors, played a key role in determining HRQOL in children and adolescents during pandemic times. Public health strategies to improve mental health may therefore be effective in improving HRQOL in this age group.

Stool samples for fecal immunochemical tests (FIT) are collected in large numbers worldwide as part of colorectal cancer screening programs, but to our knowledge, the utility of these samples for virome studies is still unexplored. Employing FIT samples from 1034 CRCbiome participants, recruited from a Norwegian colorectal cancer screening study, we identified and annotated more than 18000 virus clusters (vOTUs), using shotgun metagenome sequencing. Only six percent of vOTUs were assigned to a known taxonomic family, with Microviridae being the most prevalent viral family. Genome integration state was family-associated, and the majority of identified viruses were unintegrated. Linking individual profiles to comprehensive lifestyle and demographic factors showed 17/25 of them to be associated with the gut virome. Physical activity, smoking, and dietary fiber consumption exhibited strong and consistent associations with both diversity and relative abundance of individual vOTUs, as well as with enrichment for auxiliary metabolic genes. We demonstrate the suitability of FIT samples for virome analysis, opening an opportunity for large-scale studies of this yet enigmatic part of the gut microbiome. The diverse viral populations and their connections to the individual lifestyle uncovered herein paves the way for further exploration of the role of the gut virome in health and disease.

Correctional institutions are a crucial hotspot amplifying SARS-CoV-2 spread and disease disparity in the U.S. In the California state prison system, multiple massive outbreaks have been caused by transmission between prisons. Correctional staff are a likely vector for transmission into the prison system from surrounding communities. We used publicly available data to estimate the magnitude of flows to and between California state prisons, estimating rates of transmission from communities to prison staff and residents, among and between residents and staff within facilities, and between staff and residents of distinct facilities in the state's 34 prisons through March 22, 2021. We use a mechanistic model, the Hawkes process, reflecting the dynamics of SARS-CoV-2 transmission, for joint estimation of transmission rates. Using nested models for hypothesis testing, we compared the results to simplified models (i) without transmission between prisons, and (ii) with no distinction between prison staff and residents. We estimated that transmission between different facilities' staff is a significant cause of disease spread, and that staff are a vector of transmission between resident populations and outside communities. While increased screening and vaccination of correctional staff may help reduce introductions, large-scale decarceration remains crucially needed as more limited measures are not likely to prevent large-scale disease spread.

Background: The digital transformation of medical data enables health systems to leverage real-world data (RWD) from electronic health records (EHR) to gain actionable insights for improving hypertension care. Methods: We performed a serial cross-sectional analysis of outpatients of a large regional health system from 2010 to 2021. Hypertension was defined by systolic blood pressure (SBP) >/= 140 mmHg or diastolic blood pressure (DBP) >/= 90 mmHg) or recorded treatment with anti-hypertension medications. We evaluated four methods of using blood pressure measurements in the EHR to define hypertension. The primary outcomes were age-adjusted prevalence rates and age-adjusted control rates. Secondary outcomes were age-adjusted mean SBP and DBP and age-adjusted proportion of patients with a searchable diagnosis code of hypertension in the EHR. Results: Hypertension prevalence varied depending on the definition used, ranging from 36.5% to 50.9% initially and increasing over time by approximately 5%, regardless of the definition used. Control rates ranged from 61.2% to 71.3% initially, rose during 2018-2019 and fell during 2020-2021. The proportion of patients with a hypertension diagnosis ranged from 45.5% to 60.2% initially and improved during the study period. Non-Hispanic Black patients represented 25% of our regional population and consistently had higher prevalence rates, higher mean SBP and DBP and lower control rates compared with other racial and ethnic groups. Conclusion: In a large regional health system, we leveraged the EHR to provide real-world insights. The findings largely reflected national trends but showed distinctive regional demographics and findings. The findings have provided opportunities for improvement, with prevalence increasing, a quarter of the patients not controlled, and marked disparities. This approach could be emulated by regional health systems seeking to improve hypertension care.

The 2022 mpox outbreak has spread rapidly across multiple countries in the non-endemic region, mainly among men who have sex with men (MSM), while China only has limited recorded importation and no local outbreak. We constructed probabilistic models to simulate the risk of mpox importation in mainland China, with the help of reported monkeypox cases during this multi-country outbreak and the international air-travel data. And we further evaluated the mpox outbreak potential given that undetected mpox infections were introduced into men who have sex with men, considering different transmissibility, population immunity and population activity. We found that the reduced international air-travel volume and stringent border entry policy decreased about 94% and 69% mpox importations respectively. Once a mpox case is introduced into active MSM population with almost no population immunity, the risk of triggering local transmission is estimated at 42%, and would rise to >95% with over six cases. Our study demonstrates the key role of the reduced international air-travel volume and stringent border entry policy during the COVID-19 pandemic on reducing mpox importations, and the subsequent risk of triggering local outbreaks among MSM.

Background Surveillance of COVID-19/SARS-CoV-2 dynamics is crucial to understanding natural history and providing insights into the populations exposure risk and specific susceptibilities. This study investigated the seroprevalence of SARS-CoV-2 antibodies, its predictors, and immunological status among unvaccinated patients in Cameroon. Materials and Methods A multicentre cross-sectional study was conducted between January and September 2022 in the town of Douala. Patients were consecutively recruited, and data of interest were collected using a questionnaire. Blood samples were collected to determine Immunoglobin titres (IgM and IgG) by ALFA, CD4+ cells by flow cytometry, and interferon gamma (IFN- {gamma}) and interleukin-6 (IL-6) by ELISA. Results A total of 342 patients aged 41.5 {+/-} 13.9 years were included. Most participants (75.8%) were asymptomatic. The overall prevalence of IgM and IgG was 49.1% and 88.9%, respectively. Ageusia and anosmia have displayed the highest positive predictive values (90.9% and 82.4%) and specificity (98.9% and 98.3%). The predictors of IgM seropositivity were being aged 60 - 70 years (aOR = 0.54, p = 0.02) and ageusia (aOR = 9.31, p = 0.01), whereas those of IgG seropositivity included health facility (aOR = 0.23, p = 0.02) and ageusia (aOR = 0.21, p = 0.04). CD4+, IFN-{gamma}, and IL-6 were impaired in seropositive individuals, with a confounding role of socio-demographic factors or comorbidities. Conclusion Although the WHO declared the end of COVID-19 as a public health emergency, the findings of this study indicate the need for continuous surveillance to adequately control the disease in Cameroon.

Background: The primary care for acute coronary syndrome (ACS) includes the administration of nitroglycerin (GTN). This study aimed to investigate the association between the use of GTN before percutaneous coronary intervention (PCI) for ACS and clinical outcomes. Methods and Results: Nine-hundred and forty-seven patients who underwent PCI for ACS were examined and classified into two groups: those who were treated with GTN before PCI (GTN group) and those who were not (non-GTN group). The incidence of major adverse cardiovascular events (MACE), which consist of all-cause mortality, myocardial infarction, stroke, and rehospitalization for heart failure at 1 year, was compared between the two groups. This study identified 289 patients with ACS who used GTN preceding PCI. Pre-PCI systolic blood pressure was significantly lower in the GTN group than in the non-GTN group (median (interquartile range); 130.0 (112.5-144.2) mmHg vs. 142.0 (115.0-160.0) mmHg, respectively, p = 0.03). Multivariate Cox regression analysis indicated that GTN use preceding PCI was an independent determinant for the incidence of MACE (hazard ratio, 1.64; 95% confidence interval, 1.17-2.31; p = 0.004). Overall, the incidence of MACE 1 year after PCI for ACS was significantly higher in the GTN group than in the non-GTN group (log-rank test, p = 0.02); however, this trend was consistently found in elderly patients aged ? 75 years (p = 0.002) but not in non-elderly patients aged < 75 years (p = 0.77). Conclusions: GTN use preceding PCI for ACS is associated with lower blood pressure and adverse clinical outcomes in elderly patients.

Background Aside from liver related complications, non-alcoholic fatty liver disease (NAFLD) and alcohol-related liver disease (ArLD) are associated with an increased risk of cardiovascular disease (CVD). Liver fibrosis, determined via histology and non-invasive serum fibrosis markers, is associated with cardiovascular events. The association between liver fibrosis and heart failure, and the relationship between PNPLA3 rs738409 and TM6SF2 rs58542926 and heart failure is of particular interest, given the known associations of these genetic polymorphisms with increased risk of liver fibrosis and decreased risk of coronary artery disease. Methods Using data from the UK Biobank (UKBB), we examined the relationship between liver fibrosis, determined using non-invasive markers (NAFLD fibrosis score, Fibrosis-4 (FIB-4) and AST to platelet ratio index (APRI score)) and hospitalization or death from heart failure in 413,860 people. Participants were followed up prospectively via electronic linkage to hospital and death records. Cox-regression estimated the hazard ratios (HR) for death or admission with heart failure. The effects of PNPLA3 and TM6SF2 on the association between liver fibrosis and incident heart failure were estimated in an analysis stratified by genotype and by testing for an interaction between genotype and liver fibrosis using a likelihood ratio test. Results 12,527 incident cases of heart failure occurred over a median of 10.7 years. Liver fibrosis, determined by single or combination non-invasive tests, was associated with an increased risk of hospitalization or death from heart failure; multivariable adjusted high risk NFS score HR 1.59 [1.45-1.76], p<0.0001, FIB-4 HR 1.69 [1.55-1.84], p<0.0001, APRI HR 1.85 [1.56-2.19], p<0.0001, combined fibrosis scores HR 1.90 [1.44-2.49], p<0.0001). These associations persisted for people with NAFLD or harmful alcohol consumption. Polymorphisms linked to liver fibrosis (PNPLA3 rs738409 GG and TM6SF2 rs58542926 TT) further amplified the positive association between non-invasive liver fibrosis markers and heart failure. A statistically significant interaction was found between PNPLA3 rs738409, FIB-4, APRI score and heart failure. Conclusion Liver fibrosis, determined via non-invasive tests, is associated with an increased risk of hospitalization/death from heart failure in a general population cohort with mixed etiologies of chronic liver disease, including individuals with NAFLD and harmful alcohol consumption. Genetic polymorphisms associated with increased risk of liver fibrosis further increased the risk of heart failure. These findings have important mechanistic, clinical, and public health implications.

The worldwide decline in malaria incidence is revealing the extensive burden of non-malarial febrile illness (NMFI), which remains poorly understood and difficult to diagnose. To characterize NMFI in Senegal, we collected venous blood and clinical metadata from febrile patients and healthy controls in a low malaria burden area. Using 16S and unbiased sequencing, we detected viral, bacterial, or eukaryotic pathogens in 29% of NMFI cases. Bacteria were the most common, with relapsing fever Borrelia and spotted fever Rickettsia found in 15% and 3.7% of cases, respectively. Four viral pathogens were found in a total of 7 febrile cases (3.5%). Sequencing also detected undiagnosed Plasmodium, including one putative P. ovale infection. We developed a logistic regression model to distinguish Borrelia from NMFIs with similar presentation based on symptoms and vital signs. These results highlight the challenge and importance of improved diagnostics, especially for Borrelia, to support diagnosis and surveillance.

Purpose Structural variants such as multi-exon deletions and duplications are an important cause of disease, but are often overlooked in standard exome/genome sequencing analysis. We aimed to evaluate the detection of copy number variants (CNVs) from exome sequencing (ES) in comparison to genome-wide low-resolution and exon-resolution chromosomal microarrays (CMA), and to characterise the properties of de novo CNVs in a large clinical cohort. Methods We performed CNV detection using ES of 13,462 parent-offspring trios in the Deciphering Developmental Disorders (DDD) study, and compared them to CNVs detected from exon-resolution array comparative genomic hybridization (aCGH) in 5,197 probands from the DDD study. Results Integrating calls from multiple ES-based CNV algorithms using random forest machine learning generated a higher quality dataset than using individual algorithms. Both ES- and aCGH-based approaches had the same sensitivity of 89% and detected the same number of unique pathogenic CNVs not called by the other approach. Of DDD probands pre-screened with low resolution CMA, 2.6% had a pathogenic CNV detected by higher resolution assays. De novo CNVs were strongly enriched in known DD-associated genes and exhibited no bias in parental age or sex. Conclusion ES-based CNV calling has higher sensitivity than low-resolution CMAs currently in clinical use, and comparable sensitivity to exon-resolution CMA. With sufficient investment in bioinformatic analysis, exome-based CNV detection could replace low-resolution CMA for detecting pathogenic CNVs.

Background Participatory approaches are considered essential to ensure community health in the context of the COVID-19 pandemic. Previous reviews on community participation have explored different aspects of participation in specific contexts, such as public health emergencies, but none has examined participatory approaches both in depth and in breadth across diverse activities during the COVID-19 pandemic and considering diverse communities in all country contexts. This scoping review seeks to: (a) provide an overview of participatory approaches in terms of the features and depth of participation, the breadth of the communities and stakeholders involved, and for what types of activities and interventions in light of the COVID-19 pandemic across all country contexts; (b) explore the challenges and facilitators of participation processes; and (c) analyse to what extent participation impacts community health, including health equity, in the context of a public health emergency. Methods We developed this protocol following the latest JBI guidance on scoping reviews. A comprehensive search strategy combining the concepts of participation, community health, and COVID-19 was used to search the databases of Medline/Ovid, Embase.com, Cochrane CENTRAL, Web of Science, APA PsycInfo/Ovid, Global Health/Ovid, ERIC/OvidSP, CINAHL/EBSCOhost, ClinTrials.gov, and the grey literature through Google Scholar. At least two reviewers will perform screening of titles/abstracts and full text using the inclusion and exclusion criteria defined in this protocol. Article characteristics and data on participatory approaches and community health will be charted to provide an overview of the literature, map the variations in participatory approaches and community health, and explore patterns in the links between participation, community health, and the type of activities to address the challenges related to the COVID-19 pandemic. Discussion We anticipate that review findings will contribute to advance innovative thinking about community participation and facilitating better application and integration of participatory approaches to ensure community health in a future public health emergency or in building back better fairer in the new normal.

Background: Artificial intelligence (AI)-powered digital therapies which detect meth cravings delivered on consumer devices have the potential to reduce these disparities by providing remote and accessible care solutions to Native Hawaiians, Filipinos, and Pacific Islanders (NHFPI) communities with limited care solutions. However, NHFPI are fully understudied with respect to digital therapeutics and AI health sensing despite using technology at the same rates as other races. Objective: We seek to fulfill two research aims: (1) Understand the feasibility of continuous remote digital monitoring and ecological momentary assessments (EMAs) in NHFPI in Hawaii by curating a novel dataset of longitudinal FitBit biosignals with corresponding craving and substance use labels. (2) Develop personalized AI models which predict meth craving events in real time using wearable sensor data. Methods: We will develop personalized AI/ML (artificial intelligence/machine learning) models for meth use and craving prediction in 40 NHFPI individuals by curating a novel dataset of real-time FitBit biosensor readings and corresponding participant annotations (i.e., raw self-reported substance use data) of their meth use and cravings. In the process of collecting this dataset, we will glean insights about cultural and other human factors which can challenge the proper acquisition of precise annotations. With the resulting dataset, we will employ self-supervised learning (SSL) AI approaches, which are a new family of ML methods that allow a neural network to be trained without labels by being optimized to make predictions about the data itself. The inputs to the proposed AI models are FitBit biosensor readings and the outputs are predictions of meth use or craving. This paradigm is gaining increased attention in AI for healthcare. Conclusions: We expect to develop models which significantly outperform traditional supervised methods by fine-tuning to an individual subject's data. Such methods will enable AI solutions which work with the limited data available from NHFPI populations and which are inherently unbiased due to their personalized nature. Such models can support future AI-powered digital therapeutics for substance abuse.

Background: The availability of deep brain stimulation (DBS), a highly efficacious treatment for several movement disorders, remains low in developing countries, with scarce data available on utilization and outcomes. Objectives: We characterized the DBS cohort and outcomes at a Malaysian quaternary medical centre. Methods: A retrospective chart review was done on DBS-related surgery at the University of Malaya, including clinico-demographic, genetics, and outcomes data focusing on post-operative medication reduction and complications. Results: 149 Parkinson disease (PD) patients underwent DBS targeting the subthalamic nucleus. Six had globus pallidus internus DBS (primarily for dystonia). Only 16.1% of cases were government-funded. Of the 133 PD patients operated in the past decade (2013-2022), 25 (18.8%) had disease duration <5 years. At 6-12 months post-DBS, median levodopa-equivalent daily dosage (LEDD) reduction was 440.5 [418.9] mg/day, corresponding to a reduction of at least 50% and at least 30% in 42.2% and 69.8% of patients, respectively. LEDD reductions were larger in the early-onset and short-duration subgroups. Three patients (1.9% of 155) had symptomatic intracranial hemorrhage, resulting in stroke in two. Pathogenic monogenic or GBA1 variants were detected in 12/61 (19.7%) of patients tested, mostly comprising the GBA1 variant p.L483P (14.8%). Conclusion: This is the largest report on DBS from Southeast Asia. The procedures were effective, and complication rates on par with international norms. Our study found a high frequency of GBA1-PD; and included a substantial number of patients with short-duration PD, who had good outcomes. It also highlights the inequity of access to device-aided therapy.

Aims: Limited recent data exist on prescribing patterns and patient characteristics for glucagon-like peptide 1 receptor agonists (GLP-1 RAs), an important drug class for patients with type 2 diabetes mellitus (T2D) and/or overweight or obesity. We describe trends in first-time prescribing of GLP-1 RAs. Materials and Methods: Using aggregated US electronic health record data, we identified first-time prescriptions of GLP-1 RAs between January 2018 and June 2023 for adults receiving regular care. We describe prescribing volumes stratified by patient characteristics, specific drug, and FDA-labelled indication. The 5.5-year analysis period was divided into six-month periods. Results : In total, 274,562 patients were newly prescribed a GLP-1 RA, with a significant increase over time (January to June, 2018: 9,642 versus 2023: 66,569; p < 0.001). Overall, 181,860 (66.2%) patients had T2D and 229,715 (83.7%) had obesity or overweight. The proportion with T2D decreased over time (January to June, 2018: 84.1% versus 2023: 49%; p < 0.001), while the proportion with overweight or obesity increased (January to June, 2018: 75.9% versus 2023: 90.7%; p <.001). Of prescriptions with a known FDA-labelled indication (74.2%), 87% were labelled for T2D and 13% were labelled for overweight or obesity. Patients first prescribed a GLP-1 RA labelled for T2D were 59.1% female with a mean (SD) age of 58.6 (13) years, while those prescribed a GLP-1 RA labelled for overweight or obesity were 82.9% female, with a mean (SD) age of 48.2 (12.2) years. Conclusions: We observed an increase in first-time prescribing of GLP-1 RAs overall, and a shift away from a predominately T2D population.

With the advent of Large Language Models (LLMs) like ChatGPT, the integration of AI into clinical medicine is becoming increasingly feasible. This study aimed to evaluate the ability of the freely available ChatGPT-3.5 to generate complex differential diagnoses, comparing its output to case records of the Massachusetts General Hospital published in the New England Journal of Medicine (NEJM). Forty case records were presented to ChatGPT-3.5, with prompts to provide a differential diagnosis and then narrow it down to the most likely diagnosis. Results indicated that the final diagnosis was included in ChatGPT-3.5's original differential list in 42.5% of the cases. After narrowing, ChatGPT correctly determined the final diagnosis in 27.5% of the cases, demonstrating a decrease in accuracy compared to previous studies using common chief complaints. These findings emphasize the need for further investigation into the capabilities and limitations of LLMs in clinical scenarios, while highlighting the potential role of AI as an augmented clinical opinion. With anticipated growth and enhancements to AI tools like ChatGPT, physicians and other healthcare workers will likely find increasing support in generating differential diagnoses. However, continued exploration and regulation are essential to ensure the safe and effective integration of AI into healthcare practice. Future studies may seek to compare newer versions of ChatGPT or investigate patient outcomes with physician integration of this AI technology. By understanding and expanding AIs capabilities, particularly in differential diagnosis, the medical field may foster innovation and provide additional resources, especially in underserved areas.

Perinatal traits are influenced by genetic variants from both fetal and maternal genomes. Genome-wide association studies (GWAS) of these phenotypes have typically involved separate fetal and maternal scans, however, this approach may be inefficient as it does not utilize the information shared across the individual GWAS. In this manuscript we investigate the performance of three strategies to detect loci in maternal and fetal GWAS of the same trait: (i) the traditional strategy of analysing maternal and fetal GWAS separately; (ii) a novel two degree of freedom test which combines information from maternal and fetal GWAS; and (iii) a novel one degree of freedom test where signals from maternal and fetal GWAS are meta-analysed together conditional on the estimated sample overlap. We demonstrate through a combination of analytical formulae and data simulation that the optimal strategy depends on the extent of sample overlap/relatedness between the maternal and fetal GWAS, the correlation between own and offspring phenotypes, whether loci jointly exhibit fetal and maternal effects, and if so, whether these effects are directionally concordant. We apply our methods to summary results statistics from a recent GWAS meta-analysis of birth weight from deCODE, the UK Biobank and the Early Growth Genetics (EGG) consortium. Both the two degree of freedom (213 loci) and meta-analytic approach (226 loci) dramatically increase the number of robustly associated genetic loci for birth weight relative to separately analysing the scans (183 loci). Our best strategy identifies an additional 62 novel loci compared to the most recent published meta-analysis of birth weight and implicates both known and new biological pathways in the aetiology of the trait. We implement our methods in the online DINGO (Direct and INdirect effects analysis of Genetic lOci) software package, which allows users to perform one and/or two degree of freedom tests easily and computationally efficiently across the genome. We conclude that whilst the novel two degree of freedom test may be particularly useful for the analysis of certain perinatal phenotypes where many loci exhibit discordant maternal and fetal genetic effects, for most phenotypes, a simple meta-analytic strategy is likely to perform best, particularly in situations where maternal and fetal GWAS only partially overlap.

Background: Tuberculosis (TB) is a significant health issue in sub-Saharan African (SSA) countries, and artisanal mining (AM) may be a contributing factor. However, no systematic review has investigated the association between AM and TB in SSA. Therefore, this study aims to assess the burden of TB among artisanal miners in SSA. Methods: We conducted a comprehensive search of PubMed, Medline-OVID, EMBASE, and Scopus databases for studies on AM and TB published up to January 25, 2022. We presented the findings of seven studies that met our inclusion criteria narratively and through figure synthesis, and used inverse-variance weighted random-effects models to combine effect estimates for meta-analysis. Results: The overall prevalence of TB among artisanal workers was estimated to be 15% (95%CI: 8, 23), with higher rates in high TB burden countries (19%, 95%CI: 11, 28) compared to upper-moderate burden countries (8%, 95%CI: 3, 19. Further, exposure to silica dust, a common byproduct of AM, significantly increased the incidence of TB, with a pooled relative risk of 2.19 (95% CI: 1.77, 2.71). Additionally, we found that a higher number of artisanal miners in Ghana was associated with a reduction in TB incidence. Conclusion: Our findings suggest that exposure to silica dust in AM is a neglected but a significant risk factor for TB in SSA. More studies and efforts are needed to address this threat to TB control. Keywords: Risk factor, Tuberculosis, Artisanal mining, Review, Sub-Saharan Africa