ABSTRACTPrediabetes is one of the main health concerns in public health, and various etiological factors contribute to its onset. This study aimed to evaluate genetic associations and gene‐macronutrient interaction with prediabetes‐related metabolites to understand how genetic variation and dietary intake contribute to dysglycemia. We analyzed a total of 482 self‐identified Mexican American participants recruited from Starr County, Texas in 2018‐2019. Untargeted metabolomic profiling was performed using LC‐MS. Nutrient densities of six macronutrients were derived from a 106‐item food frequency questionnaire. Genetic associations for each metabolite were tested using Generalized linear Mixed Model Association Tests (GMMAT). Gene‐macronutrient interactions on prediabetes‐associated metabolites were assessed with the Mixed Model Association Test for GEne‐Environment Interaction (MAGEE). Age, gender, and BMI were included as covariates in all association tests. Among 308 named and 2,471 unnamed metabolites, 17 novel variant‐metabolite pairs were discovered, including rs10947898 in LRFN2 associated with diacylglycerol DG32:1(p‐value: 8.95E‐09). Among 145 named and 687 unnamed metabolites after filtering, gene‐macronutrient interaction analyses identified seven named metabolites, including a variant(rs111251222) in MXD3 that interacted with monounsaturated fat to influence eicosadienoic acid levels (Interaction p‐value: 9.88E‐09). Prediabetes and nutrient‐related metabolites in Mexican Americans showed significant genetic associations and gene‐nutrient interactions.

RNA-Protein Interactions This cover art symbolizes RNA-protein interaction methodologies. The boy's fishing line represents RNA bait, while the hooked carp embodies RNA-binding proteins captured via dynamic interplay. In article number 2500011, Wenkai Yi and Jian Yan dissect cutting-edge techniques-from RNA-centric to protein-centric-that decode these molecular dialogues, emphasizing their roles in gene regulation and disease. The metaphor underscores how innovative tools "reel in" elusive targets, bridging mechanistic discovery with therapeutic potential.

Despite efforts in developing treatments, malaria, tuberculosis (TB), human immunodeficiency virus (HIV), and coronavirus disease of 2019 (COVID-19) remain a global health burden, especially in Africa. Disease susceptibility and severity varies among individuals. Host genetics potentially contribute a significant portion to disease susceptibility and severity. Common host genes and polymorphisms that associate with these pathogens are reviewed here.

Advanced GeneticsVolume 4, Issue 1 2370012 Editorial BoardOpen Access Editorial Board: (Advanced Genetics 1/04) First published: 10 March 2023 https://doi.org/10.1002/ggn2.202370012AboutPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume4, Issue1March 20232370012 RelatedInformation

Domestication of animals can lead to profound phenotypic modifications within short evolutionary time periods, and for many species behavioral selection is likely at the forefront of this process. Animal studies have strongly implicated that the gut microbiome plays a major role in host behavior and cognition through the microbiome–gut–brain axis. Consequently, herein, it is hypothesized that host gut microbiota may be one of the earliest phenotypes to change as wild animals were domesticated. Here, the gut microbiome community in two selected lines of red junglefowl that are selected for either high or low fear of humans up to eight generations is examined. Microbiota profiles reveal taxonomic differences in gut bacteria known to produce neuroactive compounds between the two selection lines. Gut–brain module analysis by means of genome‐resolved metagenomics identifies enrichment in the microbial synthesis and degradation potential of metabolites associated with fear extinction and reduces anxiety‐like behaviors in low fear fowls. In contrast, high fear fowls are enriched in gut–brain modules from the butyrate and glutamate pathways, metabolites associated with fear conditioning. Overall, the results identify differences in the composition and functional potential of the gut microbiota across selection lines that may provide insights into the mechanistic explanations of the domestication process.