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Prince, N.

Publications and source records attributed to Prince, N..

4 recordsLinked to original sources

Network Analysis Reveals Protein Modules Associated with Childhood Respiratory Diseases

BackgroundThe first year of life is a period of rapid immune development that can impact health trajectories and the risk of developing respiratory-related diseases, such as asthma, recurrent infections, and eczema. However, the biology underlying subsequent disease development remains unknown. MethodsUsing weighted gene correlation network analysis (WGCNA), we derived modules of highly correlated immune-related proteins in plasma samples from children at age 1 year (N=294) from the Vitamin D Antenatal Asthma Reduction Trial (VDAART). We applied regression analyses to assess relationships between protein modules and development of childhood respiratory diseases up to age 6 years. We then characterized genomic, environmental, and metabolomic factors associated with modules. ResultsWGCNA identified four protein modules at age 1 year associated with incidence of childhood asthma and/or recurrent wheeze (Padj range: 0.02-0.03), respiratory infections (Padj range: 6.3x10-9-2.9x10-6), and eczema (Padj=0.01) by age 6 years; three modules were associated with at least one environmental exposure (Padj range: 2.8x10-10-0.03) and disrupted metabolomic pathway(s) (Padj range: 2.8x10-6-0.04). No genome-wide SNPs were identified as significant genetic risk factors for any protein module. Relationships between protein modules with clinical, environmental, and omic factors were temporally sensitive and could not be recapitulated in protein profiles at age 6 years. ConclusionThese findings suggested protein profiles as early as age 1 year predicted development of respiratory-related diseases through age 6 and were associated with changes in pathways related to amino acid and energy metabolism. These may inform new strategies to identify vulnerable individuals based on immune protein profiling.

bioinformatics↗

OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records

Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process.

bioinformatics↗

The metabolic role of vitamin D in children's neurodevelopment: a network study

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with various proposed environmental risk factors and a rapidly increasing prevalence. Mounting evidence suggests a potential role of vitamin D deficiency in ASD pathogenesis, though the causal mechanisms remain largely unknown. Here we investigate the impact of vitamin D on child neurodevelopment through an integrative network approach that combines metabolomic profiles, clinical traits, and neurodevelopmental data from a pediatric cohort. Our results show that vitamin D deficiency is associated with changes in the metabolic networks of tryptophan, linoleic, and fatty acid metabolism. These changes correlate with distinct ASD-related phenotypes, including delayed communication skills and respiratory dysfunctions. Additionally, our analysis suggests the kynurenine and serotonin sub-pathways may mediate the effect of vitamin D on early childhood communication development. Altogether, our findings provide metabolome-wide insights into the potential of vitamin D as a therapeutic option for ASD and other communication disorders.

systems biology↗

Gene-Gene interactions and pleiotropy in the brain nicotinic pathway associated with the heaviness and precocity of tobacco smoking among outpatients with multiple substance use disorders

IntroductionTobacco smoking is a major health burden worldwide, especially in populations suffering from other substance use disorders (SUDs). Several smoking phenotypes have been associated with single nucleotide polymorphisms (SNPs) of nicotinic acetylcholine receptors (nAChRs). Yet, little is known about the genetics of tobacco smoking in populations with other SUDs, particularly regarding gene-gene interactions and pleiotropy, which are likely involved in the polygenic architecture of SUDs. Thus, we undertook a candidate pathway association study of nAChR-related genes and smoking phenotypes in a sample of SUD patients.\n\nMethods493 patients with genetically-verified Caucasian ancestry were characterized extensively regarding patterns of tobacco smoking, other SUDs, and 83 SNPs from the nicotinic pathway, encompassing all brain nAChR subunits and metabolic/chaperone/trafficking proteins. Single-SNP, gene-based and SNP x SNP interactions analyses were performed to investigate associations with relevant tobacco smoking phenotypes. This included Bayesian analyses to detect pleiotropy, and adjustment on clinical and sociodemographic confounders.\n\nResultsAfter multiple adjustment, we found independent associations between CHRNA3 rs8040868 and a higher number of cigarettes per day (CPD), and between RIC3 rs11826236 and a lower age at smoking initiation. Two SNP x SNP interactions were associated with age at onset (AAO) of daily smoking. There was pleiotropy regarding three SNPs in CHRNA3 (CPD, AAO daily smoking), ACHE (CPD, HSI) and CHRNB4 (CPD, both AAOs).\n\nDiscussionDespite limitations, the present study shows that the genetics of tobacco smoking in SUD patients are both distinct and partially shared across smoking phenotypes, and involve metabolic and chaperone effectors of the nicotinic pathway.

genetics↗