Detecting transcription of ribosomal protein pseudogenes in diverse human tissues from RNA-seq data

Background: Ribosomal proteins (RPs) have about 2000 pseudogenes in the human genome. While anecdotal reports for RP pseudogene transcription exists, it is unclear to what extent these pseudogenes are transcribed. The RP pseudogene transcription is difficult to identify in microarrays due to potential cross-hybridization between transcripts from the parent genes and pseudogenes. Recently, transcriptome sequencing (RNA-seq) provides an opportunity to ascertain the transcription of pseudogenes. A challenge for pseudogene expression discovery in RNA-seq data lies in the difficulty to uniquely identify reads mapped to pseudogene regions, which are typically also similar to the parent genes. Results: Here we developed a specialized pipeline for pseudogene transcription discovery. We first construct a composite genome that includes the entire human genome sequence as well as mRNA sequences of real ribosomal protein genes. We then map all sequence reads to the composite genome, and only exact matches were retained. Moreover, we restrict our analysis to strictly defined mappable regions and calculate the RPKM values as measurement of pseudogene transcription levels. We report evidences for the transcription of RP pseudogenes in 16 human tissues. By analyzing the Human Body Map 2.0 study RNA-sequencing data using our pipeline, we identified that one ribosomal protein (RP) pseudogene (PGOHUM-249508) is transcribed with RPKM 170 in thyroid. Moreover, three other RP pseudogenes are transcribed with RPKM \u3e 10, a level similar to that of the normal RP genes, in white blood cell, kidney, and testes, respectively. Furthermore, an additional thirteen RP pseudogenes are of RPKM \u3e 5, corresponding to the 20-30 percentile among all genes. Unlike ribosomal protein genes that are constitutively expressed in almost all tissues, RP pseudogenes are differentially expressed, suggesting that they may contribute to tissue-specific biological processes. Conclusions: Using a specialized bioinformatics method, we identified the transcription of ribosomal protein pseudogenes in human tissues using RNA-seq data

The pace of biological aging helps explain the association between insomnia and chronic low back pain

Chronic low back pain (cLBP) is associated with insomnia and advanced age. Emerging evidence suggests that the severity of both sleep disorders (like insomnia) and chronic pain are associated with a faster pace of biological aging. We aimed to determine whether the pace of biological age mediates the relationship between insomnia and the impact of cLBP in a sample of community-dwelling adults ages 19 to 85 years. Participants (49 with no pain, 32 with low-impact pain, and 37 with high-impact pain) completed sociodemographic, pain, insomnia, and short physical performance battery assessments. We calculated the pace of biological aging using DunedinPACE from blood leukocyte DNA. On average, individuals with high-impact cLBP had significantly faster biological aging than those with low-impact and no chronic pain

Metabolic and Inflammatory Biomarkers are Associated with Epigenetic Aging Acceleration Estimates in the GOLDN Study

Background: Recently, epigenetic age acceleration-or older epigenetic age in comparison to chronological age-has been robustly associated with mortality and various morbidities. However, accelerated epigenetic aging has not been widely investigated in relation to inflammatory or metabolic markers, including postprandial lipids. Methods: We estimated measures of epigenetic age acceleration in 830 Caucasian participants from the Genetics Of Lipid Lowering Drugs and diet Network (GOLDN) considering two epigenetic age calculations based on differing sets of 5′-Cytosine-phosphate-guanine-3′ genomic site, derived from the Horvath and Hannum DNA methylation age calculators, respectively. GOLDN participants underwent a standardized high-fat meal challenge after fasting for at least 8 h followed by timed blood draws, the last being 6 h postmeal. We used adjusted linear mixed models to examine the association of the epigenetic age acceleration estimate with fasting and postprandial (0- and 6-h time points) low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglyceride (TG) levels as well as five fasting inflammatory markers plus adiponectin. Results: Both DNA methylation age estimates were highly correlated with chronological age (r \u3e 0.90). We found that the Horvath and Hannum measures of epigenetic age acceleration were moderately correlated (r = 0.50). The regression models revealed that the Horvath age acceleration measure exhibited marginal associations with increased postprandial HDL (p = 0.05), increased postprandial total cholesterol (p = 0.06), and decreased soluble interleukin 2 receptor subunit alpha (IL2sRα, p = 0.02). The Hannum measure of epigenetic age acceleration was inversely associated with fasting HDL (p = 0.02) and positively associated with postprandial TG (p = 0.02), interleukin-6 (IL6, p = 0.007), C-reactive protein (C-reactive protein, p = 0.0001), and tumor necrosis factor alpha (TNFα, p = 0.0001). Overall, the observed effect sizes were small and the association of the Hannum residual with inflammatory markers was attenuated by adjustment for estimated T cell type percentages. Conclusions: Our study demonstrates that epigenetic age acceleration in blood relates to inflammatory biomarkers and certain lipid classes in Caucasian individuals of the GOLDN study. Future studies should consider epigenetic age acceleration in other tissues and extend the analysis to other ethnic groups

HDBStat!: A platform-independent software suite for statistical analysis of high dimensional biology data

BACKGROUND: Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing. RESULTS: Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis. CONCLUSION: HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website

Genetic Contributors of Incident Stroke in 10,700 African Americans with Hypertension: A Meta-Analysis from the Genetics of Hypertension Associated Treatments and Reasons for Geographic and Racial Differences in Stroke Studies

Background: African Americans (AAs) suffer a higher stroke burden due to hypertension. Identifying genetic contributors to stroke among AAs with hypertension is critical to understanding the genetic basis of the disease, as well as detecting at-risk individuals. Methods: In a population comprising over 10,700 AAs treated for hypertension from the Genetics of Hypertension Associated Treatments (GenHAT) and Reasons for Geographic and Racial Differences in Stroke (REGARDS) studies, we performed an inverse variance-weighted meta-analysis of incident stroke. Additionally, we tested the predictive accuracy of a polygenic risk score (PRS) derived from a European ancestral population in both GenHAT and REGARDS AAs aiming to evaluate cross-ethnic performance. Results: We identified 10 statistically significant (p \u3c 5.00E-08) and 90 additional suggestive (p \u3c 1.00E-06) variants associated with incident stroke in the meta-analysis. Six of the top 10 variants were located in an intergenic region on chromosome 18 (LINC01443-LOC644669). Additional variants of interest were located in or near the COL12A1, SNTG1, PCDH7, TMTC1, and NTM genes. Replication was conducted in the Warfarin Pharmacogenomics Cohort (WPC), and while none of the variants were directly validated, seven intronic variants of NTM proximal to our target variants, had a p-value \u3c5.00E-04 in the WPC. The inclusion of the PRS did not improve the prediction accuracy compared to a reference model adjusting for age, sex, and genetic ancestry in either study and had lower predictive accuracy compared to models accounting for established stroke risk factors. These results demonstrate the necessity for PRS derivation in AAs, particularly for diseases that affect AAs disproportionately. Conclusion: This study highlights biologically plausible genetic determinants for incident stroke in hypertensive AAs. Ultimately, a better understanding of genetic risk factors for stroke in AAs may give new insight into stroke burden and potential clinical tools for those among the highest at risk

Genomic alterations associated with mutational signatures, DNA damage repair and chromatin remodeling pathways in cervical carcinoma

Despite recent advances in the prevention of cervical cancer, the disease remains a leading cause of cancer-related deaths in women worldwide. By applying the GISTIC2.0 and/or the MutSig2CV algorithms on 430 whole-exome-sequenced cervical carcinomas, we identified previously unreported significantly mutated genes (SMGs) (including MSN, GPX1, SPRED3, FAS, and KRT8), amplifications (including NFIA, GNL1, TGIF1, and WDR87) and deletions (including MIR562, PVRL1, and NTM). Subset analyses of 327 squamous cell carcinomas and 86 non-squamous cell carcinomas revealed previously unreported SMGs in BAP1 and IL28A, respectively. Distinctive copy number alterations related to tumors predominantly enriched for *CpG- and Tp*C mutations were observed. CD274, GRB2, KRAS, and EGFR were uniquely significantly amplified within the Tp*C-enriched tumors. A high frequency of aberrations within DNA damage repair and chromatin remodeling genes were detected. Facilitated by the large sample size derived from combining multiple datasets, this study reveals potential targets and prognostic markers for cervical cancer.publishedVersio

A genome-wide study of lipid response to fenofibrate in Caucasians: a combined analysis of the GOLDN and ACCORD studies

Fibrates are commonly prescribed for hypertriglyceridemia but also lower low-density lipoprotein cholesterol (LDL-C) and raise high-density lipoprotein cholesterol (HDL-C). Large inter-individual variation in lipid response suggests that some persons may benefit more than others and genetic studies could help identify those persons

Whole-Exome Sequencing and hiPSC Cardiomyocyte Models Identify \u3ci\u3eMYRIP\u3c/i\u3e, \u3ci\u3eTRAPPC11\u3c/i\u3e, and \u3ci\u3eSLC27A6\u3c/i\u3e of Potential Importance to Left Ventricular Hypertrophy in an African Ancestry Population

Background: Indices of left ventricular (LV) structure and geometry represent useful intermediate phenotypes related to LV hypertrophy (LVH), a predictor of cardiovascular (CV) disease (CVD) outcomes. Methods and Results: We conducted an exome-wide association study of LV mass (LVM) adjusted to height2.7, LV internal diastolic dimension (LVIDD), and relative wall thickness (RWT) among 1,364 participants of African ancestry (AAs) in the Hypertension Genetic Epidemiology Network (HyperGEN). Both single-variant and gene-based sequence kernel association tests were performed to examine whether common and rare coding variants contribute to variation in echocardiographic traits in AAs. We then used a data-driven procedure to prioritize and select genes for functional validation using a human induced pluripotent stem cell cardiomyocyte (hiPSC-CM) model. Three genes [myosin VIIA and Rab interacting protein (MYRIP), trafficking protein particle complex 11 (TRAPPC11), and solute carrier family 27 member 6 (SLC27A6)] were prioritized based on statistical significance, variant functional annotations, gene expression in the hiPSC-CM model, and prior biological evidence and were subsequently knocked down in the hiPSC-CM model. Expression profiling of hypertrophic gene markers in the knockdowns suggested a decrease in hypertrophic expression profiles. MYRIP knockdowns showed a significant decrease in atrial natriuretic factor (NPPA) and brain natriuretic peptide (NPPB) expression. Knockdowns of the heart long chain fatty acid (FA) transporter SLC27A6 resulted in downregulated caveolin 3 (CAV3) expression, which has been linked to hypertrophic phenotypes in animal models. Finally, TRAPPC11 knockdown was linked to deficient calcium handling. Conclusions: The three genes are biologically plausible candidates that provide new insight to hypertrophic pathways