OMICS: A Journal of Integrative Biology

Sickle cell disease (SCD) affects nearly 300,000 newborns annually worldwide, with 80% born in Africa. Sickle cell nephropathy (SCN) affects 5–18% of patients with SCD and contributes significantly to morbidity and mortality. Identifying SCN-associated factors would promote effective clinical management. We conducted a global systematic review in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines (Prospective Register of Systematic Reviews, registration number: CRD42020185763) to explore clinical and genetic correlates of SCN. We sought after cohort, case–control, and cross-sectional studies published up to December 31, 2024 that reported on clinical and/or genetic predictors of SCN in different populations globally. A total of 70 hospital-based study articles were finally included, with a leading percentage (45.7%) of the included studies performed in the United States, whereas 24.3% were from Sub-Saharan Africa. Most had a cross-sectional design (68.6%) involving children and adults. Genetic studies (17/70) identified associations with α-thalassemia, APOL1, and HMOX1 genes. The only genome-wide association study identified six suggestive variants in CRYL1, VWF, ADAMTS7, LRP1B, linc02288, and FPGT-TNNI3K/TNNI3K among adult patients. In conclusion, this systematic review (1) unpacks and highlights the role of clinical, genetic, and biochemical factors in the pathogenesis and progression of SCN and (2) reveals the consistent association of SCN with the 3.7 Kb deletion in HBA and variants in APOL1 and HMOX1 genes. This systematic review underscores the paucity of data from Africa, emphasizing the need for large-scale prospective studies on African SCN cohorts. Our findings also provide a foundation for the early identification of individuals at risk for SCN and the avenues for clinical and public health management strategies. To the best of our knowledge, this is the first systematic review summarizing risk factors for kidney dysfunction in SCD populations worldwide, which includes, specifically, a meta-analysis for APOL1 association with albuminuria.

Asthma is a heterogeneous respiratory disease with complex pathogenesis involving immune dysregulation, environmental triggers, and increasingly recognized to have contributions from the human microbiome. Emerging evidence from longitudinal birth cohorts and multi-omics studies reveals that early-life microbial colonization patterns in both the gastrointestinal and respiratory tracts play a crucial role in shaping immune trajectories and influencing asthma susceptibility. This expert review highlights the findings from pivotal studies that associate dysbiosis in the gut and airway microbiota with asthma development and its diverse phenotypic manifestations. Reduced abundance of immunomodulatory genera such as Bifidobacterium, Faecalibacterium, and Lachnospira in the gut has been consistently associated with increased asthma risk. In the airways, increased colonization by potentially pathogenic taxa, including Moraxella, Haemophilus, and Streptococcus, correlates with viral respiratory infections and persistent wheezing. Microbiome diversity patterns also differ between asthma phenotypes: eosinophilic asthma typically features a community profile closer to healthy individuals, while neutrophilic asthma is marked by enrichment of pro-inflammatory bacterial species. Moreover, protective genera such as Dolosigranulum and Corynebacterium in the upper airways are associated with lower risk of asthma and reduced respiratory infections. Elucidating these microbiome-mediated mechanisms holds promise for the development of targeted microbiota-based strategies for asthma prevention and phenotype-specific therapeutic interventions. The present review unpacks these localized microbial patterns and their mechanistic implications for asthma development, severity, and endotypic variation. Finally, unraveling the microbiome–asthma axis from airway and gut microbial communities also has implications for new ways of thinking personalized medicine in the future.

Phytophthora meadii is a polyphagous oomycete causing fatal diseases in economically important cash crops such as rubber, arecanut, cardamom, and other crops and plants of economic significance. Although information on the proteogenomic and proteomic analysis is available for several Phytophthora species, no information on the proteome repertoire of P. meadii is available. In the present study, a gel-free protein annotation was performed using liquid chromatography with tandem mass spectrometry analysis of the P. meadii hyphae, followed by bioinformatics analysis. The results were compared with a global Phytophthora proteome database-based search and an in-house P. meadii genome database, along with RefSeq proteome databases of other selected species of Phytophthora. A total of 7725 and 3979 proteins were exclusively matched with global and in-house databases, respectively. Basic Local Alignment Search Tool analysis showed 209 unique peptide sequences belonging to 85 proteins of P. meadii. Gene Ontology-based functional analysis of the P. meadii mycelial proteome categorized the proteins based on their role in cellular components, molecular functions, and biological processes. Kyoto Encyclopedia of Genes and Genomes pathway and protein–protein network analysis further revealed the role of these proteins in growth and development functions. In addition, proteins potentially involved in virulence, infections in the host system, and several signaling mechanisms were deduced. The current study is the first report on the P. meadii mycelial proteins under optimum growth conditions. These omics data also have socioeconomic implications since Phytophthora causes disease in a wide range of economically noteworthy crops and forest ecosystems.

The Rugose Spiraling Whitefly (RSW) (Aleurodicus rugioperculatus Martin), a pest native to Central America, infests coconut palms and has been introduced to other regions of the world including North America (e.g., Florida) and Southeast Asia. In India, RSW was first reported in 2016, and rapidly expanded to multiple states nationwide. Currently, RSW has growing global relevance as an agricultural insect pest. In addition to coconut, the RSW exhibits a broad host range, causing damage to various palms, fruit crops such as guava, vegetables, and ornamental shrubs. In this study, we present a high-quality draft genome assembly for this insect pest, generated using Pacific Bioscience long-read HiFi sequencing. The assembled genome spans 1.10 Gb, with a contig N50 value of 10.23 Mb. Approximately 521 Mb of sequences, accounting for 47.30% of the genome, were identified as repeat elements. The assembly includes 35,884 predicted coding sequences and exhibits high completeness, with 98.4% of Benchmarking Universal Single-Copy Orthologs genes recovered for the core insect gene set. The sequencing of the RSW genome offers valuable insights into the biology of one of the most significant and pervasive agricultural pests. The expansion of gene families associated with insecticide resistance may indicate this pest’s ability to metabolize selective insecticides. These data have the potential to greatly enhance strategies for managing the RSW insect population size and limiting its invasive capacity for pest control. Additionally, the genome provides a foundation for comparative studies of whitefly genomes, and possibly informing the future design and development of novel insecticides.

Head and neck squamous cell carcinoma (HNSCC) displays significant molecular heterogeneity, which hinders effective and safe treatments and clinical outcomes. This predicament also points to the need for an individually tailored personalized/precision medicine approach in HNSCC that includes the oral, hypopharyngeal, nasopharyngeal, and laryngeal subtypes. This study, with the overarching aim of personalized/precision medicine, attempted to identify (1) a molecular target shared by the HNSCC subtypes and (2) screen for potential anticancer drugs for repurposing that may work across the HNSCC subtypes. The National Center for Biotechnology Information—Gene Expression Omnibus database was used to select the datasets (GSE127165, GSE2379, GSE37991, and GSE12452) for the analyses of differentially expressed genes in HNSCC subtypes. Our transcriptome analyses of the HNSCC subtypes revealed 305 upregulated genes. Subsequently, protein network construction with 305 genes showed three closely interconnected high-risk HNSCC prognostic clusters. Importantly, COL1A1 was identified as the pivotal target regulating the pathogenic cluster protein implicated in cancer pathways. Molecular docking with 1040 anticancer drugs identified bleomycin as a potential candidate, exhibiting a binding affinity of −12.425 kcal/mol and a favorable binding free energy of −92.05 kcal/mol. The dynamic simulations confirmed the stability of the system, with stable interactions over 200 ns. Quantum calculations provided insights into bleomycin’s chemical and electronic properties, revealing crucial interactions with COL1A1. In conclusion, our study proposes COL1A1 as a promising potential therapeutic target among HNSCC subtypes, with bleomycin demonstrating notable repurposing potential for HNSCC.