Elife. 2024 Apr 26;12:RP88222. doi: 10.7554/eLife.88222.

ABSTRACT

Gene expression is known to be affected by interactions between local genetic variation and DNA accessibility, with the latter organized into three-dimensional chromatin structures. Analyses of these interactions have previously been limited, obscuring their regulatory context, and the extent to which they occur throughout the genome. Here, we undertake a genome-scale analysis of these interactions in a genetically diverse population to systematically identify global genetic-epigenetic interaction, and reveal constraints imposed by chromatin structure. We establish the extent and structure of genotype-by-epigenotype interaction using embryonic stem cells derived from Diversity Outbred mice. This mouse population segregates millions of variants from eight inbred founders, enabling precision genetic mapping with extensive genotypic and phenotypic diversity. With 176 samples profiled for genotype, gene expression, and open chromatin, we used regression modeling to infer genetic-epigenetic interactions on a genome-wide scale. Our results demonstrate that statistical interactions between genetic variants and chromatin accessibility are common throughout the genome. We found that these interactions occur within the local area of the affected gene, and that this locality corresponds to topologically associated domains (TADs). The likelihood of interaction was most strongly defined by the three-dimensional (3D) domain structure rather than linear DNA sequence. We show that stable 3D genome structure is an effective tool to guide searches for regulatory elements and, conversely, that regulatory elements in genetically diverse populations provide a means to infer 3D genome structure. We confirmed this finding with CTCF ChIP-seq that revealed strain-specific binding in the inbred founder mice. In stem cells, open chromatin participating in the most significant regression models demonstrated an enrichment for developmental genes and the TAD-forming CTCF-binding complex, providing an opportunity for statistical inference of shifting TAD boundaries operating during early development. These findings provide evidence that genetic and epigenetic factors operate within the context of 3D chromatin structure.

PMID:38669177 | DOI:10.7554/eLife.88222

Inflamm Res. 2024 Apr 26. doi: 10.1007/s00011-024-01885-6. Online ahead of print.

ABSTRACT

Lipoxins (LXs) are a class of endogenous bioactive lipid mediators that are involved in the regulation of inflammation. They exert immunomodulatory effects by regulating the behaviour of various immune cells, including neutrophils, macrophages, and T and B cells, by promoting the clearance of apoptotic neutrophils. This helps to dampen inflammation and promote tissue repair. LXs regulate the expression of many inflammatory genes by modulating the levels of transcription factors, such as nuclear factor κB (NF-κB), activator protein-1 (AP-1), nerve growth factor-regulated factor 1A binding protein 1 (NGF), and peroxisome proliferator activated receptor γ (PPAR-γ), which are elevated in various diseases, such as respiratory tract diseases, renal diseases, cancer, neurodegenerative diseases, and viral infections. Lipoxin-mediated signaling is involved in chronic inflammation, cancer, diabetes-associated kidney disease, lung injury, liver injury, endometriosis, respiratory tract diseases, neurodegenerative diseases, chronic cerebral hypoperfusion, and retinal degeneration. In this study, we systematically investigated the intricate network of lipoxin signaling by analyzing the relevant literature. The resulting map comprised 467 molecules categorized as activation/inhibition, enzyme catalysis, gene and protein expression, molecular associations, and translocation events. This map serves as a valuable resource for understanding the complexity of lipoxin signaling and its impact on various cellular functions.

PMID:38668877 | DOI:10.1007/s00011-024-01885-6

Eat Weight Disord. 2024 Apr 26;29(1):31. doi: 10.1007/s40519-024-01659-3.

ABSTRACT

PURPOSE: Several studies have investigated the association between anorexia nervosa and polymorphisms of genes regulating serotonin neurotransmission, with a focus on the rs6311 polymorphism of 5-HTR2A. However, inconsistent results of these studies and conflicting conclusions of existing meta-analyses complicate the understanding of a possible association. We have updated these results and evaluated the involvement of other serotonin receptor gene polymorphisms in anorexia nervosa.

METHODS: Adhering to PRISMA guidelines, we have searched studies on anorexia nervosa and serotonin-regulating genes published from 1997 to 2022, selected those concerning receptor genes and meta-analyzed the results from twenty candidate gene studies on the 5-HTR2A rs6311 polymorphism and the 5-HTR2C rs6318 polymorphism.

RESULTS: Present analyses reveal an association for the 5-HTR2A rs6311 polymorphism, with G and A alleles, across eighteen studies (2049 patients, 2877 controls; A vs. G allele, Odds Ratio = 1.24; 95% Confidence Interval = 1.06-1.47; p = 0.009). However, after geographic subgrouping, an association emerged only in a Southern European area, involving five studies (722 patients, 773 controls; A vs. G allele, Odds Ratio = 1.82; 95% Confidence Interval = 1.41-2.37; p < 0.00001). No association was observed for the 5-HTR2C rs6318 polymorphism across three studies.

CONCLUSIONS: To date, the involvement in the pathophysiology of anorexia nervosa of the 5-HTR2A rs6311 polymorphism appears limited to a specific genetic and/or environmental context, while that of the 5-HTR2C rs6318 polymorphism seems excluded. Genome-wide association studies and epigenetic studies will likely offer deeper insights of genetic and environmental factors possibly contributing to the disorder.

LEVEL OF EVIDENCE: III Evidence obtained from well-designed cohort or case-control analytic studies. Clinical trial registration PROSPERO registration number: CRD42021246122.

PMID:38668826 | DOI:10.1007/s40519-024-01659-3

Metabolites. 2024 Apr 17;14(4):230. doi: 10.3390/metabo14040230.

ABSTRACT

During early lactation, dairy cows have a negative energy balance since their energy demands exceed their energy intake: in this study, we aimed to investigate the association between diet and plasma metabolomics profiles and how these relate to energy unbalance of course in the early-lactation stage. Holstein-Friesian cows were randomly assigned to a glucogenic (n = 15) or lipogenic (n = 15) diet in early lactation. Blood was collected in week 2 and week 4 after calving. Plasma metabolite profiles were detected using liquid chromatography-mass spectrometry (LC-MS), and a total of 39 metabolites were identified. Two plasma metabolomic profiles were available every week for each cow. Metabolite abundance and metabolite ratios were used for the analysis using the XGboost algorithm to discriminate between diet treatment and lactation week. Using metabolite ratios resulted in better discrimination performance compared with the metabolite abundances in assigning cows to a lipogenic diet or a glucogenic diet. The quality of the discrimination of performance of lipogenic diet and glucogenic diet effects improved from 0.606 to 0.753 and from 0.696 to 0.842 in week 2 and week 4 (as measured by area under the curve, AUC), when the metabolite abundance ratios were used instead of abundances. The top discriminating ratios for diet were the ratio of arginine to tyrosine and the ratio of aspartic acid to valine in week 2 and week 4, respectively. For cows fed the lipogenic diet, choline and the ratio of creatinine to tryptophan were top features to discriminate cows in week 2 vs. week 4. For cows fed the glucogenic diet, methionine and the ratio of 4-hydroxyproline to choline were top features to discriminate dietary effects in week 2 or week 4. This study shows the added value of using metabolite abundance ratios to discriminate between lipogenic and glucogenic diet and lactation weeks in early-lactation cows when using metabolomics data. The application of this research will help to accurately regulate the nutrition of lactating dairy cows and promote sustainable agricultural development.

PMID:38668358 | DOI:10.3390/metabo14040230

NAR Genom Bioinform. 2024 Apr 25;6(2):lqae031. doi: 10.1093/nargab/lqae031. eCollection 2024 Jun.

ABSTRACT

DNA variation analysis has become indispensable in many aspects of modern biomedicine, most prominently in the comparison of normal and tumor samples. Thousands of samples are collected in local sequencing efforts and public databases requiring highly scalable, portable, and automated workflows for streamlined processing. Here, we present nf-core/sarek 3, a well-established, comprehensive variant calling and annotation pipeline for germline and somatic samples. It is suitable for any genome with a known reference. We present a full rewrite of the original pipeline showing a significant reduction of storage requirements by using the CRAM format and runtime by increasing intra-sample parallelization. Both are leading to a 70% cost reduction in commercial clouds enabling users to do large-scale and cross-platform data analysis while keeping costs and CO2 emissions low. The code is available at https://nf-co.re/sarek.

PMID:38666213 | PMC:PMC11044436 | DOI:10.1093/nargab/lqae031

Int J Endocrinol Metab. 2023 Nov 6;21(4):e140835. doi: 10.5812/ijem-140835. eCollection 2023 Oct.

ABSTRACT

BACKGROUND: Breast cancer (BC) is one of the most common cancers in women, significantly contributing to cancer-related death in the modern world. Obesity, as a worldwide epidemic besides the menopausal status, has a paradoxical association with BC.

OBJECTIVES: To determine the molecular mechanisms underlying the paradoxical effects of obesity on BC, a comprehensive systems biology analysis was performed.

METHODS: Data retrieval, data preprocessing, and differential expression analysis were conducted. Weighted correlation network analysis (WGCNA) identified the gene modules associated with clinical traits. Network analysis and hub gene identification techniques revealed key regulatory genes, and functional enrichment analysis uncovered biological pathways related to hub genes. A logistic regression model was developed to predict menopausal status based on hub genes. Additionally, gene expression analysis of two important genes was performed by qPCR.

RESULTS: The study identified the hub genes and molecular pathways (the PI3K-Akt signaling pathway, proteoglycans in cancer, and lipid metabolic and atherosclerosis pathways) associated with the obesity paradox in BC based on menopausal statutes.

CONCLUSIONS: These results may improve our understanding of the underlying mechanisms of the effects of body mass on BC and assist in identifying biomarkers and potential therapeutic targets for treating obese postmenopausal women with BC.

PMID:38666041 | PMC:PMC11041819 | DOI:10.5812/ijem-140835

Front Oncol. 2024 Apr 11;14:1397008. doi: 10.3389/fonc.2024.1397008. eCollection 2024.

ABSTRACT

For many cancer survivors, toxic side effects of treatment, lingering effects of the aftermath of disease and cancer recurrence adversely affect quality of life (QoL) and reduce healthspan. Data-driven approaches for quantifying and improving wellness in healthy individuals hold great promise for improving the lives of cancer survivors. The data-driven strategy will also guide personalized nutrition and exercise recommendations that may help prevent cancer recurrence and secondary malignancies in survivors.

PMID:38665952 | PMC:PMC11044254 | DOI:10.3389/fonc.2024.1397008

Npj Viruses. 2023;1(1):6. doi: 10.1038/s44298-023-00008-y. Epub 2023 Nov 27.

ABSTRACT

Rhinoviruses (RV), common human respiratory viruses, exhibit significant antigenic diversity, yet their dynamics across distinct social structures remain poorly understood. Our study delves into RV dynamics within Kenya by analysing VP4/2 sequences across four different social structures: households, a public primary school, outpatient clinics in the Kilifi Health and Demographics Surveillance System (HDSS), and countrywide hospital admissions and outpatients. The study revealed the greatest diversity of RV infections at the countrywide level (114 types), followed by the Kilifi HDSS (78 types), the school (47 types), and households (40 types), cumulatively representing >90% of all known RV types. Notably, RV diversity correlated directly with the size of the population under observation, and several RV type variants occasionally fuelled RV infection waves. Our findings highlight the critical role of social structures in shaping RV dynamics, information that can be leveraged to enhance public health strategies. Future research should incorporate whole-genome analysis to understand fine-scale evolution across various social structures.

PMID:38665239 | PMC:PMC11041716 | DOI:10.1038/s44298-023-00008-y

iScience. 2024 Mar 27;27(5):109594. doi: 10.1016/j.isci.2024.109594. eCollection 2024 May 17.

ABSTRACT

Renal ischemia-reperfusion injury (IRI) is a major cause of acute kidney injury (AKI). Recent findings suggest that Testis-Specific Protein Y-encoded-Like 2 (TSPYL2) plays a fibrogenic role in diabetes-associated renal injury. However, the role of TSPYL2 in IRI-induced kidney damage is not entirely clear. In this study, we found that the expression of TSPYL2 was upregulated in a mouse model of AKI and in the hypoxia/reoxygenation (H/R) cell model. Knockdown of TSPYL2 attenuated kidney injury after IRI. More specifically, the knockdown of TSPYL2 or aminocarboxymuconate-semialdehyde decarboxylase (ACMSD) alleviated renal IRI-induced mitochondrial dysfunction and oxidative stress in vitro and in vivo. Further investigation showed that TSPYL2 regulated SREBP-2 acetylation by inhibiting SIRT1 and promoting p300 activity, thereby promoting the transcriptional activity of ACMSD. In conclusion, TSPYL2 was identified as a pivotal regulator of IRI-induced kidney damage by activating ACMSD, which may lead to NAD+ content and the damaging response in the kidney.

PMID:38665207 | PMC:PMC11043847 | DOI:10.1016/j.isci.2024.109594

Expert Rev Vaccines. 2024 Apr 25. doi: 10.1080/14760584.2024.2345685. Online ahead of print.

ABSTRACT

INTRODUCTION: Zebrafishesrepresent a proven model for human diseases and systems biology, exhibitingphysiological and genetic similarities and having innate and adaptive immunesystems. However, they are underexplored for human vaccinology, vaccinedevelopment, and testing. Here we summarize gaps and challenges.

AREAS COVERED: Zebrafish models have fourpotential applications: 1) Vaccine safety: The pastsuccesses in using zebrafishes to test xenobiotics could extend to vaccine andadjuvant formulations for general safety or target organs due to the zebrafish embryos'optical transparency. 2) Innate immunity: The zebrafish offers refined ways toexamine vaccine effects through signaling via Toll-like or NOD-like receptors inzebrafish myeloid cells. 3) Adaptive immunity: Zebrafishes produce IgM, IgD,and two IgZ immunoglobulins, but these are understudied, due to a lack of immunologicalreagents for challenge studies. 4) Systems vaccinology: Due to the availabilityof a well-referenced zebrafish genome, transcriptome, proteome, and epigenome,this model offers potential here.

EXPERT OPINION: It remains unproven whether zebrafishes can beemployed for testing and developing human vaccines. We are still at thehypothesis-generating stage, although it is possible to begin outliningexperiments for this purpose. Throughtransgenic manipulation, zebrafish models could offer new paths for shapinganimal models and systems vaccinology.

PMID:38664959 | DOI:10.1080/14760584.2024.2345685

BMC Bioinformatics. 2024 Apr 25;25(1):166. doi: 10.1186/s12859-024-05782-x.

ABSTRACT

BACKGROUND: The Biology System Description Language (BiSDL) is an accessible, easy-to-use computational language for multicellular synthetic biology. It allows synthetic biologists to represent spatiality and multi-level cellular dynamics inherent to multicellular designs, filling a gap in the state of the art. Developed for designing and simulating spatial, multicellular synthetic biological systems, BiSDL integrates high-level conceptual design with detailed low-level modeling, fostering collaboration in the Design-Build-Test-Learn cycle. BiSDL descriptions directly compile into Nets-Within-Nets (NWNs) models, offering a unique approach to spatial and hierarchical modeling in biological systems.

RESULTS: BiSDL's effectiveness is showcased through three case studies on complex multicellular systems: a bacterial consortium, a synthetic morphogen system and a conjugative plasmid transfer process. These studies highlight the BiSDL proficiency in representing spatial interactions and multi-level cellular dynamics. The language facilitates the compilation of conceptual designs into detailed, simulatable models, leveraging the NWNs formalism. This enables intuitive modeling of complex biological systems, making advanced computational tools more accessible to a broader range of researchers.

CONCLUSIONS: BiSDL represents a significant step forward in computational languages for synthetic biology, providing a sophisticated yet user-friendly tool for designing and simulating complex biological systems with an emphasis on spatiality and cellular dynamics. Its introduction has the potential to transform research and development in synthetic biology, allowing for deeper insights and novel applications in understanding and manipulating multicellular systems.

PMID:38664639 | DOI:10.1186/s12859-024-05782-x

Mol Psychiatry. 2024 Apr 25. doi: 10.1038/s41380-024-02551-3. Online ahead of print.

ABSTRACT

Depression in older adults with cognitive impairment increases progression to dementia. Microbiota is associated with current mood and cognition, but the extent to which it predicts future symptoms is unknown. In this work, we identified microbial features that reflect current and predict future cognitive and depressive symptoms. Clinical assessments and stool samples were collected from 268 participants with varying cognitive and depressive symptoms. Seventy participants underwent 2-year follow-up. Microbial community diversity, structure, and composition were assessed using high-resolution 16 S rRNA marker gene sequencing. We implemented linear regression to characterize the relationship between microbiome composition, current cognitive impairment, and depressive symptoms. We leveraged elastic net regression to discover features that reflect current or future cognitive function and depressive symptoms. Greater microbial community diversity associated with lower current cognition in the whole sample, and greater depression in participants not on antidepressants. Poor current cognitive function associated with lower relative abundance of Bifidobacterium, while greater GABA degradation associated with greater current depression severity. Future cognitive decline associated with lower cognitive function, lower relative abundance of Intestinibacter, lower glutamate degradation, and higher baseline histamine synthesis. Future increase in depressive symptoms associated with higher baseline depression and anxiety, lower cognitive function, diabetes, lower relative abundance of Bacteroidota, and lower glutamate degradation. Our results suggest cognitive dysfunction and depression are unique states with an overall biological effect detectable through gut microbiota. The microbiome may present a noninvasive readout and prognostic tool for cognitive and psychiatric states.

PMID:38664490 | DOI:10.1038/s41380-024-02551-3

Life Sci Alliance. 2024 Apr 25;7(7):e202302498. doi: 10.26508/lsa.202302498. Print 2024 Jul.

ABSTRACT

Mitochondrial transcription factor A, TFAM, is essential for mitochondrial function. We examined the effects of overexpressing the TFAM gene in mice. Two types of transgenic mice were created: TFAM heterozygous (TFAM Tg) and homozygous (TFAM Tg/Tg) mice. TFAM Tg/Tg mice were smaller and leaner notably with longer lifespans. In skeletal muscle, TFAM overexpression changed gene and protein expression in mitochondrial respiratory chain complexes, with down-regulation in complexes 1, 3, and 4 and up-regulation in complexes 2 and 5. The iMPAQT analysis combined with metabolomics was able to clearly separate the metabolomic features of the three types of mice, with increased degradation of fatty acids and branched-chain amino acids and decreased glycolysis in homozygotes. Consistent with these observations, comprehensive gene expression analysis revealed signs of mitochondrial stress, with elevation of genes associated with the integrated and mitochondrial stress responses, including Atf4, Fgf21, and Gdf15. These found that mitohormesis develops and metabolic shifts in skeletal muscle occur as an adaptive strategy.

PMID:38664021 | DOI:10.26508/lsa.202302498

J Agric Food Chem. 2024 Apr 25. doi: 10.1021/acs.jafc.3c08775. Online ahead of print.

ABSTRACT

In the past, taste interactions between sodium chloride (NaCl) and bitter tastants were investigated in human sensory studies, and the suppression of bitterness by sodium was observed. It is currently not clear if this phenomenon occurs predominantly peripherally or centrally and if the effect is general or only particular bitter compounds are blocked. Therefore, the influence of NaCl at the receptor level was tested by functional expression assays using four out of ∼25 human bitter taste receptors together with prototypical agonists. It was observed that NaCl affected only the responses of particular bitter taste receptor-compound pairs, whereas other bitter responses remained unchanged upon variations of the sodium concentrations. Among the tested receptors, TAS2R16 showed a reduction in signaling in the presence of NaCl. This demonstrates that for some receptor-agonist pairs, NaCl reduces the activation at the receptor level, whereas central effects may dominate the NaCl-induced bitter taste inhibition for other substances.

PMID:38663860 | DOI:10.1021/acs.jafc.3c08775

Biomater Adv. 2024 Apr 15;160:213861. doi: 10.1016/j.bioadv.2024.213861. Online ahead of print.

ABSTRACT

Novel strategies employing mechano-transducing materials eliciting biological outcomes have recently emerged for controlling cellular behaviour. Targeted cellular responses are achieved by manipulating physical, chemical, or biochemical modification of material properties. Advances in techniques such as nanopatterning, chemical modification, biochemical molecule embedding, force-tuneable materials, and artificial extracellular matrices are helping understand cellular mechanotransduction. Collectively, these strategies manipulate cellular sensing and regulate signalling cascades including focal adhesions, YAP-TAZ transcription factors, and multiple osteogenic pathways. In this minireview, we are providing a summary of the influence that these materials, particularly titanium-based orthopaedic materials, have on cells. We also highlight recent complementary methodological developments including, but not limited to, the use of metabolomics for identification of active biomolecules that drive cellular differentiation.

PMID:38663159 | DOI:10.1016/j.bioadv.2024.213861

Clin Infect Dis. 2024 Apr 25;78(Supplement_2):S175-S182. doi: 10.1093/cid/ciae096.

ABSTRACT

BACKGROUND: Neglected tropical diseases are responsible for considerable morbidity and mortality in low-income populations. International efforts have reduced their global burden, but transmission is persistent and case-finding-based interventions rarely target asymptomatic individuals.

METHODS: We develop a generic mathematical modeling framework for analyzing the dynamics of visceral leishmaniasis in the Indian sub-continent (VL), gambiense sleeping sickness (gHAT), and Chagas disease and use it to assess the possible contribution of asymptomatics who later develop disease (pre-symptomatics) and those who do not (non-symptomatics) to the maintenance of infection. Plausible interventions, including active screening, vector control, and reduced time to detection, are simulated for the three diseases.

RESULTS: We found that the high asymptomatic contribution to transmission for Chagas and gHAT and the apparently high basic reproductive number of VL may undermine long-term control. However, the ability to treat some asymptomatics for Chagas and gHAT should make them more controllable, albeit over relatively long time periods due to the slow dynamics of these diseases. For VL, the toxicity of available therapeutics means the asymptomatic population cannot currently be treated, but combining treatment of symptomatics and vector control could yield a quick reduction in transmission.

CONCLUSIONS: Despite the uncertainty in natural history, it appears there is already a relatively good toolbox of interventions to eliminate gHAT, and it is likely that Chagas will need improvements to diagnostics and their use to better target pre-symptomatics. The situation for VL is less clear, and model predictions could be improved by additional empirical data. However, interventions may have to improve to successfully eliminate this disease.

PMID:38662705 | DOI:10.1093/cid/ciae096

Clin Infect Dis. 2024 Apr 25;78(Supplement_2):S108-S116. doi: 10.1093/cid/ciae071.

ABSTRACT

BACKGROUND: Lymphatic filariasis (LF) is a neglected tropical disease targeted for elimination as a public health problem by 2030. Although mass treatments have led to huge reductions in LF prevalence, some countries or regions may find it difficult to achieve elimination by 2030 owing to various factors, including local differences in transmission. Subnational projections of intervention impact are a useful tool in understanding these dynamics, but correctly characterizing their uncertainty is challenging.

METHODS: We developed a computationally feasible framework for providing subnational projections for LF across 44 sub-Saharan African countries using ensemble models, guided by historical control data, to allow assessment of the role of subnational heterogeneities in global goal achievement. Projected scenarios include ongoing annual treatment from 2018 to 2030, enhanced coverage, and biannual treatment.

RESULTS: Our projections suggest that progress is likely to continue well. However, highly endemic locations currently deploying strategies with the lower World Health Organization recommended coverage (65%) and frequency (annual) are expected to have slow decreases in prevalence. Increasing intervention frequency or coverage can accelerate progress by up to 5 or 6 years, respectively.

CONCLUSIONS: While projections based on baseline data have limitations, our methodological advancements provide assessments of potential bottlenecks for the global goals for LF arising from subnational heterogeneities. In particular, areas with high baseline prevalence may face challenges in achieving the 2030 goals, extending the "tail" of interventions. Enhancing intervention frequency and/or coverage will accelerate progress. Our approach facilitates preimplementation assessments of the impact of local interventions and is applicable to other regions and neglected tropical diseases.

PMID:38662704 | DOI:10.1093/cid/ciae071

Clin Infect Dis. 2024 Apr 25;78(Supplement_2):S117-S125. doi: 10.1093/cid/ciae072.

ABSTRACT

BACKGROUND: Lymphatic filariasis (LF) is a debilitating, poverty-promoting, neglected tropical disease (NTD) targeted for worldwide elimination as a public health problem (EPHP) by 2030. Evaluating progress towards this target for national programmes is challenging, due to differences in disease transmission and interventions at the subnational level. Mathematical models can help address these challenges by capturing spatial heterogeneities and evaluating progress towards LF elimination and how different interventions could be leveraged to achieve elimination by 2030.

METHODS: Here we used a novel approach to combine historical geo-spatial disease prevalence maps of LF in Ethiopia with 3 contemporary disease transmission models to project trends in infection under different intervention scenarios at subnational level.

RESULTS: Our findings show that local context, particularly the coverage of interventions, is an important determinant for the success of control and elimination programmes. Furthermore, although current strategies seem sufficient to achieve LF elimination by 2030, some areas may benefit from the implementation of alternative strategies, such as using enhanced coverage or increased frequency, to accelerate progress towards the 2030 targets.

CONCLUSIONS: The combination of geospatial disease prevalence maps of LF with transmission models and intervention histories enables the projection of trends in infection at the subnational level under different control scenarios in Ethiopia. This approach, which adapts transmission models to local settings, may be useful to inform the design of optimal interventions at the subnational level in other LF endemic regions.

PMID:38662702 | DOI:10.1093/cid/ciae072

Clin Infect Dis. 2024 Apr 25;78(Supplement_2):S160-S168. doi: 10.1093/cid/ciae108.

ABSTRACT

BACKGROUND: The Global Programme to Eliminate Lymphatic Filariasis (GPELF) aims to reduce and maintain infection levels through mass drug administration (MDA), but there is evidence of ongoing transmission after MDA in areas where Culex mosquitoes are the main transmission vector, suggesting that a more stringent criterion is required for MDA decision making in these settings.

METHODS: We use a transmission model to investigate how a lower prevalence threshold (<1% antigenemia [Ag] prevalence compared with <2% Ag prevalence) for MDA decision making would affect the probability of local elimination, health outcomes, the number of MDA rounds, including restarts, and program costs associated with MDA and surveys across different scenarios. To determine the cost-effectiveness of switching to a lower threshold, we simulated 65% and 80% MDA coverage of the total population for different willingness to pay per disability-adjusted life-year averted for India ($446.07), Tanzania ($389.83), and Haiti ($219.84).

RESULTS: Our results suggest that with a lower Ag threshold, there is a small proportion of simulations where extra rounds are required to reach the target, but this also reduces the need to restart MDA later in the program. For 80% coverage, the lower threshold is cost-effective across all baseline prevalences for India, Tanzania, and Haiti. For 65% MDA coverage, the lower threshold is not cost-effective due to additional MDA rounds, although it increases the probability of local elimination. Valuing the benefits of elimination to align with the GPELF goals, we find that a willingness to pay per capita government expenditure of approximately $1000-$4000 for 1% increase in the probability of local elimination would be required to make a lower threshold cost-effective.

CONCLUSIONS: Lower Ag thresholds for stopping MDAs generally mean a higher probability of local elimination, reducing long-term costs and health impacts. However, they may also lead to an increased number of MDA rounds required to reach the lower threshold and, therefore, increased short-term costs. Collectively, our analyses highlight that lower target Ag thresholds have the potential to assist programs in achieving lymphatic filariasis goals.

PMID:38662697 | DOI:10.1093/cid/ciae108

Bioinformatics. 2024 Apr 25:btae283. doi: 10.1093/bioinformatics/btae283. Online ahead of print.

ABSTRACT

SUMMARY: Existing clustering methods for characterizing cell populations from single-cell RNA sequencing are constrained by several limitations stemming from the fact that clusters often cannot be homogeneous, particularly for transitioning populations. On the other hand, dominant cell populations within samples can be identified independently by their strong gene co-expression signatures using methods unrelated to partitioning. Here, we introduce a clustering method, CASCC, designed to improve biological accuracy using gene co-expression features identified using an unsupervised adaptive attractor algorithm. CASCC outperformed other methods as evidenced by multiple evaluation metrics, and our results suggest that CASCC can improve the analysis of single-cell transcriptomics, enabling potential new discoveries related to underlying biological mechanisms.

AVAILABILITY AND IMPLEMENTATION: The CASCC R package is publicly available at https://github.com/LingyiC/CASCC and https://zenodo.org/doi/10.5281/zenodo.10648327.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:38662553 | DOI:10.1093/bioinformatics/btae283