A strand specific high resolution normalization method for chip-sequencing data employing multiple experimental control measurements

Background: High-throughput sequencing is becoming the standard tool for investigating protein-DNA interactions or epigenetic modifications. However, the data generated will always contain noise due to e. g. repetitive regions or non-specific antibody interactions. The noise will appear in the form of a background distribution of reads that must be taken into account in the downstream analysis, for example when detecting enriched regions (peak-calling). Several reported peak-callers can take experimental measurements of background tag distribution into account when analysing a data set. Unfortunately, the background is only used to adjust peak calling and not as a preprocessing step that aims at discerning the signal from the background noise. A normalization procedure that extracts the signal of interest would be of universal use when investigating genomic patterns. Results: We formulated such a normalization method based on linear regression and made a proof-of-concept implementation in R and C++. It was tested on simulated as well as on publicly available ChIP-seq data on binding sites for two transcription factors, MAX and FOXA1 and two control samples, Input and IgG. We applied three different peak-callers to (i) raw (un-normalized) data using statistical background models and (ii) raw data with control samples as background and (iii) normalized data without additional control samples as background. The fraction of called regions containing the expected transcription factor binding motif was largest for the normalized data and evaluation with qPCR data for FOXA1 suggested higher sensitivity and specificity using normalized data over raw data with experimental background. Conclusions: The proposed method can handle several control samples allowing for correction of multiple sources of bias simultaneously. Our evaluation on both synthetic and experimental data suggests that the method is successful in removing background noise

Are there educational disparities in health and functioning among the oldest old? : Evidence from the Nordic countries

With the ageing of the population and recent pressures on important welfare state arrangements, updated knowledge on the linkage between socioeconomic status and health in old age is pertinent for shedding light on emerging patterns of health inequalities in the Nordic countries. This study examined self-rated health (SRH), mobility and activities of daily living (ADL) according to level of education in the three oldest old age groups 75–84, 85–94, and 95+, in four Nordic countries. Altogether, 6132 individuals from Danish Longitudinal Study of Ageing, Norwegian Life Course, Ageing and Generation study, Swedish Panel Study of Living Conditions of the Oldest Old, the 5-Country Oldest Old (Sweden) and Vitality 90 + Study were analysed. First, associations of education level with SRH, mobility, and ADL were estimated for each individual study by means of age- and gender-adjusted logistic regression. Second, results from individual studies were synthesized in a meta-analysis. Older adults with higher education level were more likely to report good SRH, and they were more often independent in mobility and ADL than those with basic education when all age groups were combined. In mobility and ADL, differences between education groups remained stable across the age groups but for SRH, differences seemed to be weaker in older ages. With only a few exceptions, in all age groups, individuals with higher education had more favourable health and functioning than those with basic education. This study shows remarkable persistence of health and functioning inequalities in the Nordic countries throughout later life

SICTIN: Rapid footprinting of massively parallel sequencing data

BACKGROUND: Massively parallel sequencing allows for genome-wide hypothesis-free investigation of for instance transcription factor binding sites or histone modifications. Although nucleotide resolution detailed information can easily be generated, biological insight often requires a more general view of patterns (footprints) over distinct genomic features such as transcription start sites, exons or repetitive regions. The construction of these footprints is however a time consuming task. METHODS: The presented software generates a binary representation of the signals enabling fast and scalable lookup. This representation allows for footprint generation in mere minutes on a desktop computer. Several different input formats are accepted, e.g. the SAM format, bed-files and the UCSC wiggle track. CONCLUSIONS: Hypothesis-free investigation of genome wide interactions allows for biological data mining at a scale never before seen. Until recently, the main focus of analysis of sequencing data has been targeted on signal patterns around transcriptional start sites which are in manageable numbers. Today, focus is shifting to a wider perspective and numerous genomic features are being studied. To this end, we provide a system allowing for fast querying in the order of hundreds of thousands of features

Molecular interactions between HNF4a, FOXA2 and GABP identified at regulatory DNA elements through ChIP-sequencing

Gene expression is regulated by combinations of transcription factors, which can be mapped to regulatory elements on a genome-wide scale using ChIP experiments. In a previous ChIP-chip study of USF1 and USF2 we found evidence also of binding of GABP, FOXA2 and HNF4a within the enriched regions. Here, we have applied ChIP-seq for these transcription factors and identified 3064 peaks of enrichment for GABP, 7266 for FOXA2 and 18783 for HNF4a. Distal elements with USF2 signal was frequently bound also by HNF4a and FOXA2. GABP peaks were found at transcription start sites, whereas 94% of FOXA2 and 90% of HNF4a peaks were located at other positions. We developed a method to accurately define TFBS within peaks, and found the predicted sites to have an elevated conservation level compared to peak centers; however the majority of bindings were not evolutionary conserved. An interaction between HNF4a and GABP was seen at TSS, with one-third of the HNF4a positive promoters being bound also by GABP, and this interaction was verified by co-immunoprecipitations

Genetics of circulating inflammatory proteins identifies drivers of immune-mediated disease risk and therapeutic targets

Circulating proteins have important functions in inflammation and a broad range of diseases. To identify genetic influences on inflammation-related proteins, we conducted a genome-wide protein quantitative trait locus (pQTL) study of 91 plasma proteins measured using the Olink Target platform in 14,824 participants. We identified 180 pQTLs (59 cis, 121 trans). Integration of pQTL data with eQTL and disease genome-wide association studies provided insight into pathogenesis, implicating lymphotoxin-alpha in multiple sclerosis. Using Mendelian randomization (MR) to assess causality in disease etiology, we identified both shared and distinct effects of specific proteins across immune-mediated diseases, including directionally discordant effects of CD40 on risk of rheumatoid arthritis versus multiple sclerosis and inflammatory bowel disease. MR implicated CXCL5 in the etiology of ulcerative colitis (UC) and we show elevated gut CXCL5 transcript expression in patients with UC. These results identify targets of existing drugs and provide a powerful resource to facilitate future drug target prioritization. Here the authors identify genetic effectors of the level of inflammation-related plasma proteins and use Mendelian randomization to identify proteins that contribute to immune-mediated disease risk

Evidence for large-scale gene-by-smoking interaction effects on pulmonary function

Background: Smoking is the strongest environmental risk factor for reduced pulmonary function. The genetic component of various pulmonary traits has also been demonstrated, and at least 26 loci have been reproducibly associated with either FEV1 (forced expiratory volume in 1 second) or FEV1/FVC (FEV1/forced vital capacity). Although the main effects of smoking and genetic loci are well established, the question of potential gene-by-smoking interaction effect remains unanswered. The aim of the present study was to assess, using a genetic risk score approach, whether the effect of these 26 loci on pulmonary function is influenced by smoking. Methods: We evaluated the interaction between smoking exposure, considered as either ever vs never or pack-years, and a 26-single nucleotide polymorphisms (SNPs) genetic risk score in relation to FEV1 or FEV1/FVC in 50 047 participants of European ancestry from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) and SpiroMeta consortia. Results: We identified an interaction (beta(int) = -0.036, 95% confidence interval, -0.040 to -0.032, P = 0.00057) between an unweighted 26 SNP genetic risk score and smoking status (ever/never) on the FEV1/FVC ratio. In interpreting this interaction, we showed that the genetic risk of falling below the FEV1/FVC threshold used to diagnose chronic obstructive pulmonary disease is higher among ever smokers than among never smokers. A replication analysis in two independent datasets, although not statistically significant, showed a similar trend in the interaction effect. Conclusions: This study highlights the benefit of using genetic risk scores for identifying interactions missed when studying individual SNPs and shows, for the first time, that persons with the highest genetic risk for low FEV1/FVC may be more susceptible to the deleterious effects of smoking.Peer reviewe

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health

Immune cells lacking Y chromosome show dysregulation of autosomal gene expression

Funder: Kjell och Märta Beijers Stiftelse (SE)Funder: Hjärnfonden; doi: http://dx.doi.org/10.13039/501100003792Funder: Cancerfonden; doi: http://dx.doi.org/10.13039/501100002794Funder: Vetenskapsrådet; doi: http://dx.doi.org/10.13039/501100004359Funder: Alzheimerfonden; doi: http://dx.doi.org/10.13039/501100008599Funder: Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse (SE)Funder: Science for Life Laboratory (SE)Funder: Fundacja na rzecz Nauki Polskiej (PL)Funder: Uppsala UniversityAbstract: Epidemiological investigations show that mosaic loss of chromosome Y (LOY) in leukocytes is associated with earlier mortality and morbidity from many diseases in men. LOY is the most common acquired mutation and is associated with aberrant clonal expansion of cells, yet it remains unclear whether this mosaicism exerts a direct physiological effect. We studied DNA and RNA from leukocytes in sorted- and single-cells in vivo and in vitro. DNA analyses of sorted cells showed that men diagnosed with Alzheimer’s disease was primarily affected with LOY in NK cells whereas prostate cancer patients more frequently displayed LOY in CD4 + T cells and granulocytes. Moreover, bulk and single-cell RNA sequencing in leukocytes allowed scoring of LOY from mRNA data and confirmed considerable variation in the rate of LOY across individuals and cell types. LOY-associated transcriptional effect (LATE) was observed in ~ 500 autosomal genes showing dysregulation in leukocytes with LOY. The fraction of LATE genes within specific cell types was substantially larger than the fraction of LATE genes shared between different subsets of leukocytes, suggesting that LOY might have pleiotropic effects. LATE genes are involved in immune functions but also encode proteins with roles in other diverse biological processes. Our findings highlight a surprisingly broad role for chromosome Y, challenging the view of it as a “genetic wasteland”, and support the hypothesis that altered immune function in leukocytes could be a mechanism linking LOY to increased risk for disease