Losses of Both Products of the Cdkn2a/Arf Locus Contribute to Asbestos-Induced Mesothelioma Development and Cooperate to Accelerate Tumorigenesis

The CDKN2A/ARF locus encompasses overlapping tumor suppressor genes p16(INK4A) and p14(ARF), which are frequently co-deleted in human malignant mesothelioma (MM). The importance of p16(INK4A) loss in human cancer is well established, but the relative significance of p14(ARF) loss has been debated. The tumor predisposition of mice singly deficient for either Ink4a or Arf, due to targeting of exons 1 alpha or 1 beta, respectively, supports the idea that both play significant and nonredundant roles in suppressing spontaneous tumors. To further test this notion, we exposed Ink4a(+/-) and Arf(+/-) mice to asbestos, the major cause of MM. Asbestos-treated Ink4a(+/-) and Arf(+/-) mice showed increased incidence and shorter latency of MM relative to wild-type littermates. MMs from Ink4a(+/-) mice exhibited biallelic inactivation of Ink4a, loss of Arf or p53 expression and frequent loss of p15(Ink4b). In contrast, MMs from Arf(+/-) mice exhibited loss of Arf expression, but did not require loss of Ink4a or Ink4b. Mice doubly deficient for Ink4a and Arf, due to deletion of Cdkn2a/Arf exon 2, showed accelerated asbestos-induced MM formation relative to mice deficient for Ink4a or Arf alone, and MMs exhibited biallelic loss of both tumor suppressor genes. The tumor suppressor function of Arf in MM was p53-independent, since MMs with loss of Arf retained functional p53. Collectively, these in vivo data indicate that both CDKN2A/ARF gene products suppress asbestos carcinogenicity. Furthermore, while inactivation of Arf appears to be crucial for MM pathogenesis, the inactivation of both p16(Ink4a) and p19(Arf) cooperate to accelerate asbestos-induced tumorigenesis

Dynamic human liver proteome atlas reveals functional insights into disease pathways

Deeper understanding of liver pathophysiology would benefit from a comprehensive quantitative proteome resource at cell type resolution to predict outcome and design therapy. Here, we quantify more than 150,000 sequence‐unique peptides aggregated into 10,000 proteins across total liver, the major liver cell types, time course of primary cell cultures, and liver disease states. Bioinformatic analysis reveals that half of hepatocyte protein mass is comprised of enzymes and 23% of mitochondrial proteins, twice the proportion of other liver cell types. Using primary cell cultures, we capture dynamic proteome remodeling from tissue states to cell line states, providing useful information for biological or pharmaceutical research. Our extensive data serve as spectral library to characterize a human cohort of non‐alcoholic steatohepatitis and cirrhosis. Dramatic proteome changes in liver tissue include signatures of hepatic stellate cell activation resembling liver cirrhosis and providing functional insights. We built a web‐based dashboard application for the interactive exploration of our resource (www.liverproteome.org)

Patterns of seafloor morphology as a response to tectonic- and sedimentary processes south of the Messina Strait, Italy

The Ionian Sea between Sicily and Calabria is known for its complex geological setting, as it is located at the convergence zone of the African and Eurasian plates. The seismogenic potential in this region is manifested by several high magnitude and disastrous earthquakes like the 1908 Messina Earthquake. Furthermore, the area is affected by intense volcanism like the Aeolian Island volcanos in the Tyrrhenian Sea and Europe’s largest active volcano, Mt Etna, sitting directly at the eastern coast of Sicily. During the last years, the possible presence of Subduction Tear Edge Propagator faults (STEP-faults) has been heavily debated. The main candidates for these faults are the Ionian Fault in the Northeast and the Alfeo-Etna Fault in the Southwest of the working area between Sicily and Calabria. Nevertheless, only little is known about near seafloor deformation zones and sedimentary processes in the Ionian Sea directly south of the Messina Strait.peer-reviewe

Meta-analyses identify DNA methylation associated with kidney function and damage

Chronic kidney disease is a major public health burden. Elevated urinary albumin-to-creatinine ratio is a measure of kidney damage, and used to diagnose and stage chronic kidney disease. To extend the knowledge on regulatory mechanisms related to kidney function and disease, we conducted a blood-based epigenome-wide association study for estimated glomerular filtration rate (n = 33,605) and urinary albumin-to-creatinine ratio (n = 15,068) and detected 69 and seven CpG sites where DNA methylation was associated with the respective trait. The majority of these findings showed directionally consistent associations with the respective clinical outcomes chronic kidney disease and moderately increased albuminuria. Associations of DNA methylation with kidney function, such as CpGs at JAZF1, PELI1 and CHD2 were validated in kidney tissue. Methylation at PHRF1, LDB2, CSRNP1 and IRF5 indicated causal effects on kidney function. Enrichment analyses revealed pathways related to hemostasis and blood cell migration for estimated glomerular filtration rate, and immune cell activation and response for urinary albumin-to-creatinineratio-associated CpGs

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

Background: Immunometabolism plays a central role in many cardiometabolic diseases. However, a robust map of immune-related gene networks in circulating human cells, their interactions with metabolites, and their genetic control is still lacking. Here, we integrate blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts (total N = 2168), including a subset of individuals with matched multi-omic data at 7-year follow-up. Results: We identify topologically replicable gene networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules show complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, small molecules, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) reveal five modules with mQTLs that have both cis and trans effects. The strongest mQTL is in ARHGEF3 (rs1354034) and affects a module enriched for platelet function, independent of platelet counts. Modules of mast cell/basophil and neutrophil function show temporally stable metabolite associations over 7-year follow-up, providing evidence that these modules and their constituent gene products may play central roles in metabolic inflammation. Furthermore, the strongest mQTL in ARHGEF3 also displays clear temporal stability, supporting widespread trans effects at this locus. Conclusions: This study provides a detailed map of natural variation at the blood immunometabolic interface and its genetic basis, and may facilitate subsequent studies to explain inter-individual variation in cardiometabolic disease.Peer reviewe

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression

Track D Social Science, Human Rights and Political Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138414/1/jia218442.pd

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Association of maternal prenatal smoking GFI1-locus and cardiometabolic phenotypes in 18,212 adults

Background: DNA methylation at the GFI1-locus has been repeatedly associated with exposure to smoking from the foetal period onwards. We explored whether DNA methylation may be a mechanism that links exposure to maternal prenatal smoking with offspring's adult cardio-metabolic health. Methods: We meta-analysed the association between DNA methylation at GFI1-locus with maternal prenatal smoking, adult own smoking, and cardio-metabolic phenotypes in 22 population-based studies from Europe, Australia, and USA (n= 18,212). DNA methylation at the GFI1-locus was measured in whole-blood. Multivariable regression models were fitted to examine its association with exposure to prenatal and own adult smoking. DNA methylation levels were analysed in relation to body mass index (BMI), waist circumference (WC), fasting glucose (FG), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), diastolic, and systolic blood pressure (BP). Findings: Lower DNA methylation at three out of eight GFI1-CpGs was associated with exposure to maternal prenatal smoking, whereas, all eight CpGs were associated with adult own smoking. Lower DNA methylation at cg14179389, the strongest maternal prenatal smoking locus, was associated with increased WC and BP when adjusted for sex, age, and adult smoking with Bonferroni-corrected P < 0.012. In contrast, lower DNA methylation at cg09935388, the strongest adult own smoking locus, was associated with decreased BMI, WC, and BP (adjusted 1 x 10(-7) < P < 0.01). Similarly, lower DNA methylation at cg12876356, cg18316974, cg09662411, and cg18146737 was associated with decreased BMI and WC (5 x 10(-8) < P < 0.001). Lower DNA methylation at all the CpGs was consistently associated with higher TG levels. Interpretation: Epigenetic changes at the GFI1 were linked to smoking exposure in-utero/in-adulthood and robustly associated with cardio-metabolic risk factors. Fund: European Union's Horizon 2020 research and innovation programme under grant agreement no. 633595 DynaHEALTH