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Nath, A. P.

Publications and source records attributed to Nath, A. P..

2 recordsLinked to original sources

Elevated alpha 1 antitrypsin is a major component of GlycA-associated risk for future morbidity and mortality

Integration of electronic health records with systems-level biomolecular data has led to the discovery that GlycA, a complex nuclear magnetic resonance (NMR) spectroscopy biomarker, predicts long-term risk of disease onset and death from myriad causes. To determine the molecular underpinnings of the disease risk of the heterogeneous GlycA signal, we used machine learning to build imputation models for GlycAs constituent glycoproteins, then estimated glycoprotein levels in 11,861 adults across two population-based cohorts with long-term follow-up. While alpha-1-acid glycoprotein had the strongest correlation with GlycA, our analysis revealed that alpha-1 antitrypsin (AAT) was the most predictive of morbidity and mortality for the widest range of diseases, including heart failure (HR=1.60 per s.d., P=1x10-10), influenza and pneumonia (HR=1.37, P=6x10-10), and liver diseases (HR=1.81, P=1x10-6). Despite emerging evidence of AAT's role in suppressing inflammation, transcriptional analyses revealed elevated expression of diverse inflammatory immune pathways with elevated AAT levels, suggesting AAT is elevating to compensate for low-grade chronic inflammation. This study clarifies the molecular underpinnings of the GlycA biomarker and its associated disease risk, and indicates a previously unrecognised association between elevated AAT and severe disease onset and mortality.

systems biology

An interaction map of circulating metabolites, immune gene networks and their genetic regulation

The interaction between metabolism and the immune system plays a central role in many cardiometabolic diseases. We integrated blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts, including a subset with 7-year follow-up sampling. We identified topologically robust gene networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules showed complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) revealed five modules with mQTLs of both cis and trans effects. The strongest mQTL was in ARHGEF3 (rs1354034) and affected a module enriched for platelet function. Mast cell/basophil and neutrophil function modules maintained their metabolite associations during 7-year follow-up, while our strongest mQTL in ARHGEF3 also displayed clear temporal stability. This study provides a detailed map of natural variation at the blood immuno-metabolic interface and its genetic basis, and facilitates subsequent studies to explain inter-individual variation in cardiometabolic disease.

genomics