Biology subjects

Lin, N.

Publications and source records attributed to Lin, N..

3 recordsLinked to original sources

bioRxiv2018

Multivariate Computational Analysis of Gamma Delta T cell Inhibitory Receptor Signatures Reveals the Divergence of Healthy and ART-Suppressed HIV+ Aging

Even with effective viral control, HIV-infected individuals are at a higher risk for morbidities associated with older age than the general population, and these serious non-AIDS events (SNAEs) track with plasma inflammatory and coagulation markers. The cell subsets driving inflammation in aviremic HIV infection are not yet elucidated. Also, whether ART-suppressed HIV infection causes premature induction of the inflammatory events found in uninfected elderly or if a novel inflammatory network ensues when HIV and older age co-exist is unclear. In this study we measured combinational expression of five inhibitory receptors (IRs) on seven immune cell subsets and 16 plasma markers from peripheral blood mononuclear cells (PBMC) and plasma samples, respectively, from a HIV and Aging cohort comprised of ART-suppressed HIV-infected and uninfected controls stratified by age ([≤]35 or [≥]50 years old). For data analysis, multiple multivariate computational algorithms (cluster identification, characterization, and regression (CITRUS), partial least squares regression (PLSR), and partial least squares-discriminant analysis (PLS-DA)) were used to determine if immune parameter disparities can distinguish the subject groups and to investigate if there is a cross-impact of aviremic HIV and age on immune signatures. IR expression on gamma delta ({gamma}{delta}) T cells exclusively separated HIV+ subjects from controls in CITRUS analyses and secretion of inflammatory cytokines and cytotoxic mediators from {gamma}{delta} T cells tracked with TIGIT expression among HIV+ subjects. Also, plasma markers predicted the percentages of TIGIT+ {gamma}{delta} T cells in subjects with and without HIV in PSLR models, and a PLS-DA model of {gamma}{delta} T cell IR signatures and plasma markers significantly stratified all four of the subject groups (uninfected younger, uninfected older, HIV+ younger, and HIV+ older). These data implicate {gamma}{delta} T cells as an inflammatory driver in ART-suppressed HIV infection and provide evidence of distinct inflamm-aging processes with and without ART-suppressed HIV infection.

immunology↗

bioRxiv2018

DNA methylation signature of smoking in lung cancer is enriched for exposure signatures in newborn and adult blood.

BackgroundSmoking impacts DNA methylation genome-wide in blood of both newborns from maternal smoking during pregnancy and adults from personal smoking. Smoking causes lung cancer which involves aberrant methylation. We examined whether DNA methylation smoking signatures identified in blood of newborns and adults are detectable in lung tumors.\n\nMethodsWe compared smoking-related DNA methylation in lung adenocarcinomas (61 never smokers, 91 current smokers, and 238 former smokers) quantified with the Illumina450k BeadArray in The Cancer Genome Atlas with published large consortium meta-analyses of newborn and adult blood. We assessed whether CpG sites related to smoking in blood from newborns and adults were enriched in lung adenocarcinoma.\n\nResultsTesting CpGs differentially methylated by smoke exposure (P<10-4) we identified 296 in lung tumors, while previous meta-analyses (False Discovery Rate (FDR)<0.05) identified 6,073 in newborn blood, and for adult smoking, 18,760 in blood. The lung signals were highly enriched for those seen in newborn (32 overlapping, Penrichment=1.2x10-19) and adult blood (86 overlapping, Penrichment = 9.5x10-49). The 65 genes annotated to CpGs differentially methylated in lung tumors, but not blood, were enriched for RNA processing ontologies.\n\nConclusionsWe found highly significant overlap between smoking-related DNA methylation signals in lung cancer and those seen in blood from newborns, from in utero exposure, or adults, from their own exposure. These results suggest that some epigenetic alterations associated with cigarette smoke exposure are tissue specific, but others are common across tissues. These findings support the value of blood-based methylation biomarkers for assessing exposure effects in target tissues.

cancer biology↗

bioRxiv2018

Large-Scale Genome-Wide Meta Analysis of Polycystic Ovary Syndrome Suggests Shared Genetic Architecture for Different Diagnosis Criteria.

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed with different criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease indicate shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. Only one locus differed in its association by diagnostic criteria, otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or Rotterdam criteria across common variants at 13 loci.

genetics↗