Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits

Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P < 5 × 10-8) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5-18.2 mmHg, P = 2.22 × 10-126) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54-9.70; P = 4.13 × 10-44) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781-0.801) to 0.826 (95% CI, 0.817-0.836, ∆AUROC, 0.035, P = 1.98 × 10-34). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research.

Toward ovarian cancer screening with protein biomarkers using dried, self-sampled cervico-vaginal fluid

Early detection is key for increased survival in ovarian cancer, but no general screening program exists today due to lack of biomarkers and overall cost versus benefit over traditional clinical methods. Here, we used dried cervico-vaginal fluid (CVF) as sampling matrix coupled with mass spectrometry for detection of protein biomarkers. We find that self-collected CVF on paper cards yields robust results and is suitable for high-throughput proteomics. Artificial intelligence-based methods were used to identify an 11-protein panel that separates cases from controls. In validation data, the panel achieved a sensitivity of 0.97 (95% CI 0.91-1.00) at a specificity of 0.67 (0.40-0.87). Analyses of samples collected prior to development of symptoms indicate that the panel is informative also of future risk of disease. Dried CVF is used in cervical cancer screening, and our results opens the possibility for a screening program also for ovarian cancer, based on self-collected CVF samples.

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-α 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.

The association between genetically elevated polyunsaturated fatty acids and risk of cancer

BACKGROUND

The causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain.

METHODS

Using a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures.

FINDINGS

Genetically elevated PUFA desaturase activity was associated (P < 0.0007) with higher risk (OR [95% confidence interval]) of colorectal cancer (1.09 [1.07-1.11]), esophageal squamous cell carcinoma (1.16 [1.06-1.26]), lung cancer (1.06 [1.03-1.08]) and basal cell carcinoma (1.05 [1.02-1.07]). There was little evidence for associations with reproductive cancers (OR = 1.00 [95% CI: 0.99-1.01]; Pheterogeneity = 0.25), urinary system cancers (1.03 [0.99-1.06], Pheterogeneity = 0.51), nervous system cancers (0.99 [0.95-1.03], Pheterogeneity = 0.92) or blood cancers (1.01 [0.98-1.04], Pheterogeneity = 0.09). Findings for colorectal cancer and esophageal squamous cell carcinoma remained compatible with causality in sensitivity analyses for violations of assumptions. Secondary MR analyses highlighted higher omega 6 PUFAs (arachidonic acid, gamma-linolenic acid and dihomo-gamma-linolenic acid) as potential mediators. PUFA biosynthesis is known to interact with aspirin, which increases risk of bleeding and inflammatory bowel disease. In a phenome-wide MR study of non-neoplastic diseases, we found that genetic lowering of PUFA desaturase activity, mimicking a hypothetical intervention to reduce cancer risk, was associated (P < 0.0006) with increased risk of inflammatory bowel disease but not bleeding.

INTERPRETATION

The PUFA biosynthesis pathway may be an intervention target for prevention of colorectal cancer and esophageal squamous cell carcinoma but with potential for increased risk of inflammatory bowel disease.

FUNDING

Cancer Resesrch UK (C52724/A20138, C18281/A19169). UK Medical Research Council (MR/P014054/1). National Institute for Health Research (NIHR202411). UK Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4). National Cancer Institute (R00 CA215360). National Institutes of Health (U01 CA164973, R01 CA60987, R01 CA72520, U01 CA74806, R01 CA55874, U01 CA164973 and U01 CA164973).

Forensic prediction of sex, age, height, body mass index, hip-to-waist ratio, smoking status and lipid lowering drugs using epigenetic markers and plasma proteins

The prediction of human characteristics from blood using molecular markers would be very helpful in forensic science. Such information can be particularly important in providing investigative leads in police casework from, for example, blood found at crime scenes in cases without a suspect. Here, we investigated the possibilities and limitations of predicting seven phenotypic traits (sex, age, height, body mass index [BMI], hip-to-waist [WTH] ratio, smoking status and lipid-lowering drug use) using either DNA methylation or plasma proteins separately or in combination. We developed a prediction pipeline starting with the prediction of sex followed by sex-specific, stepwise, individual age, sex-specific anthropometric traits and, finally, lifestyle-related traits. Our data revealed that age, sex and smoking status can be accurately predicted from DNA methylation alone, while the use of plasma proteins was highly accurate for prediction of the WTH ratio, and a combined analysis of the best predictions for BMI and lipid-lowering drug use. In unseen individuals, age was predicted with a standard error of 3.3 years for women and 6.5 years for men, while the accuracy in smoking prediction across both men and women was 0.86. In conclusion, we have developed a stepwise approach for the de-novo prediction of individual characteristics from plasma proteins and DNA methylation markers. These models are accurate and may provide valuable information and investigative leads in future forensic casework.

Unraveling Neuro-Proteogenomic Landscape and Therapeutic Implications for Human Behaviors and Psychiatric Disorders

Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioral traits and the disease etiology of neuropsychiatric disorders. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-related proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-related traits such as sleeping, smoking, feelings, alcohol intake, mental health, and psychiatric disorders. Integrating with established drug information, we validated 13 out of 13 matched combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets. This consortium effort provides a large-scale proteogenomic resource for biomedical research on human behaviors and other neuro-related phenotypes.

Genetic mechanisms of 184 neuro-related proteins in human plasma

Understanding the genetic basis of neuro-related proteins is essential for dissecting the disease etiology of neuropsychiatric disorders and other complex traits and diseases. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-reiated proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-reiated traits as well as complex diseases such as hypertension, high cholesterol, immune-related disorders, and psychiatric disorders. Integrating with established drug information, we validated 13 combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets for diseases and comorbidities. This consortium effort provides a large-scale proteogenomic resource for biomedical research.

Data-driven analysis of a validated risk score for ovarian cancer identifies clinically distinct patterns during follow-up and treatment

Background

Ovarian cancer is the eighth most common cancer among women and due to late detection prognosis is poor with an overall 5-year survival of 30-50%. Novel biomarkers are needed to reduce diagnostic surgery and enable detection of early-stage cancer by population screening. We have previously developed a risk score based on an 11-biomarker plasma protein assay to distinguish benign tumors (cysts) from malignant ovarian cancer in women with adnexal ovarian mass.

Methods

Protein concentrations of 11 proteins were characterized in plasma from 1120 clinical samples with a custom version of the proximity extension assay. The performance of the assay was evaluated in terms of prediction accuracy based on receiver operating characteristics (ROC) and multiple hypothesis adjusted Fisher's Exact tests on achieved sensitivity and specificity.

Results

The assay's performance is validated in two independent clinical cohorts with a sensitivity of 0.83/0.91 and specificity of 0.88/0.92. We also show that the risk score follows the clinical development and is reduced upon treatment, and increased with relapse and cancer progression. Data-driven modeling of the risk score patterns during a 2-year follow-up after diagnosis identifies four separate risk score trajectories linked to clinical development and survival. A Cox proportional hazard regression analysis of 5-year survival shows that at time of diagnosis the risk score is the second-strongest predictive variable for survival after tumor stage, whereas MUCIN-16 (CA-125) alone is not significantly predictive.

Conclusion

The robust performance of the biomarker assay across clinical cohorts and the correlation with clinical development indicates its usefulness both in the diagnostic work-up of women with adnexal ovarian mass and for predicting their clinical course.

Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention

Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

Genetic Landscape of the ACE2 Coronavirus Receptor

BACKGROUND

SARS-CoV-2, the causal agent of COVID-19, enters human cells using the ACE2 (angiotensin-converting enzyme 2) protein as a receptor. ACE2 is thus key to the infection and treatment of the coronavirus. ACE2 is highly expressed in the heart and respiratory and gastrointestinal tracts, playing important regulatory roles in the cardiovascular and other biological systems. However, the genetic basis of the ACE2 protein levels is not well understood.

METHODS

We have conducted the largest genome-wide association meta-analysis of plasma ACE2 levels in >28 000 individuals of the SCALLOP Consortium (Systematic and Combined Analysis of Olink Proteins). We summarize the cross-sectional epidemiological correlates of circulating ACE2. Using the summary statistics-based high-definition likelihood method, we estimate relevant genetic correlations with cardiometabolic phenotypes, COVID-19, and other human complex traits and diseases. We perform causal inference of soluble ACE2 on vascular disease outcomes and COVID-19 severity using mendelian randomization. We also perform in silico functional analysis by integrating with other types of omics data.

RESULTS

We identified 10 loci, including 8 novel, capturing 30% of the heritability of the protein. We detected that plasma ACE2 was genetically correlated with vascular diseases, severe COVID-19, and a wide range of human complex diseases and medications. An X-chromosome cis-protein quantitative trait loci-based mendelian randomization analysis suggested a causal effect of elevated ACE2 levels on COVID-19 severity (odds ratio, 1.63 [95% CI, 1.10-2.42]; P=0.01), hospitalization (odds ratio, 1.52 [95% CI, 1.05-2.21]; P=0.03), and infection (odds ratio, 1.60 [95% CI, 1.08-2.37]; P=0.02). Tissue- and cell type-specific transcriptomic and epigenomic analysis revealed that the ACE2 regulatory variants were enriched for DNA methylation sites in blood immune cells.

CONCLUSIONS

Human plasma ACE2 shares a genetic basis with cardiovascular disease, COVID-19, and other related diseases. The genetic architecture of the ACE2 protein is mapped, providing a useful resource for further biological and clinical studies on this coronavirus receptor.

Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer

Simple Summary

Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30–50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. The aim of our study was to broadly measure protein biomarkers to find tests for the early detection of ovarian cancer. We found that combinations of 4–7 protein biomarkers can provide highly accurate detection of early- and late-stage ovarian cancer compared to benign conditions. The performance of the tests was then validated in a second independent cohort.

Abstract

Background: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30–50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. Methods: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). Results: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. Conclusions: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.

Transcriptome Analysis of Post-Mortem Brain Tissue Reveals Up-Regulation of the Complement Cascade in a Subgroup of Schizophrenia Patients

Schizophrenia is a genetically complex neuropsychiatric disorder with largely unresolved mechanisms of pathology. Identification of genes and pathways associated with schizophrenia is important for understanding the development, progression and treatment of schizophrenia. In this study, pathways associated with schizophrenia were explored at the level of gene expression. The study included post-mortem brain tissue samples from 68 schizophrenia patients and 44 age and sex-matched control subjects. Whole transcriptome poly-A selected paired-end RNA sequencing was performed on tissue from the prefrontal cortex and orbitofrontal cortex. RNA expression differences were detected between case and control individuals, focusing both on single genes and pathways. The results were validated with RT-qPCR. Significant differential expression between patient and controls groups was found for 71 genes. Gene ontology analysis of differentially expressed genes revealed an up-regulation of multiple genes in immune response among the patients (corrected p-value = 0.004). Several genes in the category belong to the complement system, including C1R, C1S, C7, FCN3, SERPING1, C4A and CFI. The increased complement expression is primarily driven by a subgroup of patients with increased expression of immune/inflammatory response genes, pointing to important differences in disease etiology within the patient group. Weighted gene co-expression network analysis highlighted networks associated with both synaptic transmission and activation of the immune response. Our results demonstrate the importance of immune-related pathways in schizophrenia and provide evidence for elevated expression of the complement cascade as an important pathway in schizophrenia pathology.

Distinct genetic regions are associated with differential population susceptibility to chemical exposures

Interactions between environmental factors and genetics underlie the majority of chronic human diseases. Chemical exposures are likely an underestimated contributor, yet gene-environment (GxE) interaction studies rarely assess their modifying effects. Here, we describe a novel method to profile the human genome and identify regions associated with differential population susceptibility to chemical exposures. Single nucleotide polymorphisms (SNPs) implicated in enriched chemical-disease intersections were identified and validated for three chemical classes with expected GxE interaction potential (neuroactive, hepatoactive, and cardioactive compounds). The same approach was then used to characterize consumer product classes with unknown risk for GxE interactions (washing products, cosmetics, and adhesives). Additionally, high-risk variant sets that may confer differential population susceptibility were identified for these consumer product groups through frequent itemset mining and pathway analysis. A dataset of 2454 consumer product chemical-disease linkages, with risk values, SNPs, and pathways for each association was developed, describing the interplay between environmental factors and genetics in human disease progression. We found that genetic hotspots implicated in GxE interactions differ across chemical classes (e.g., washing products had high-risk SNPs implicated in nervous system disease) and illustrate how this approach can discover new associations (e.g., washing product n-butoxyethanol implicated SNPs in the PI3K-Akt signaling pathway for Alzheimer's disease). Hence, our approach can predict high-risk genetic regions for differential population susceptibility to chemical exposures and characterize chemical modifying factors in specific diseases. These methods show promise for describing how chemical exposures can lead to varied health outcomes in a population and for incorporating inter-individual variability into chemical risk assessment.

Identification of Candidate Protein Biomarkers for CIN2+ Lesions from Self-Sampled, Dried Cervico-Vaginal Fluid Using LC-MS/MS

Simple Summary

Cervical cancer is the fourth most common cancer among women worldwide, and screening programs increase its detection rate and survivability. The molecular screening of the presence of human papilloma viruses (HPV) as alternatives to physical examinations offers cost-efficient solutions and can be performed on self-collected samples. A persistent infection with HPV is necessary (but not sufficient) to develop cancer, and additional biomarkers are needed to increase the precision. Here, we have analysed protein biomarkers found in self-collected dried cervico–vaginal fluid (CVF) from both controls and women with cervical cancer pre-stages. Our conclusion is that protein biomarkers can be robustly detected from dried CVF and that these can aid in the detection of cervical cancer pre-stages.

Abstract

Molecular screening programs for cervical cancer detect the presence of human papilloma virus (HPV) in cell material or vaginal fluids. Persistent infection with high-risk HPV is a necessary pre-requisite, but the majority of infections do not lead to pathological states. Additional biomarkers are needed to increase the specificity of the molecular tests. Here, we have investigated the possibility of detecting protein biomarkers using mass spectrometry from dried self-sampled cervico–vaginal fluid deposited on FTA cards. We found significant intra-individual correlations (p < 2.2 × 10⁻¹⁶), although heterogenous protein profiles were obtained between individuals. Out of 3699 proteins found in total, 169 were detected in at least 95% of the samples. Using a discovery/replication design, 18 proteins were found to be significant in the discovery cohort, with higher values in those cases compared to controls. All of these were found to also have higher levels among the cases in the replication cohort, with one protein (DEAD-Box Helicase) remaining statistically significant. Finally, a predictive 7-protein multivariate model was developed with a sensitivity and specificity of 0.90 and 0.55, respectively. Our results demonstrate that robust measurements of protein biomarkers can be obtained from self-sampled dried CVF and that these could be used to predict cervical cancer pre-stages.

Immune cells lacking Y chromosome show dysregulation of autosomal gene expression

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.

Mendelian randomisation identifies alternative splicing of the FAS death receptor as a mediator of severe COVID-19

Severe COVID-19 is characterised by immunopathology and epithelial injury. Proteomic studies have identified circulating proteins that are biomarkers of severe COVID-19, but cannot distinguish correlation from causation. To address this, we performed Mendelian randomisation (MR) to identify proteins that mediate severe COVID-19. Using protein quantitative trait loci (pQTL) data from the SCALLOP consortium, involving meta-analysis of up to 26,494 individuals, and COVID-19 genome-wide association data from the Host Genetics Initiative, we performed MR for 157 COVID-19 severity protein biomarkers. We identified significant MR results for five proteins: FAS, TNFRSF10A, CCL2, EPHB4 and LGALS9. Further evaluation of these candidates using sensitivity analyses and colocalization testing provided strong evidence to implicate the apoptosis-associated cytokine receptor FAS as a causal mediator of severe COVID-19. This effect was specific to severe disease. Using RNA-seq data from 4,778 individuals, we demonstrate that the pQTL at the FAS locus results from genetically influenced alternate splicing causing skipping of exon 6. We show that the risk allele for very severe COVID-19 increases the proportion of transcripts lacking exon 6, and thereby increases soluble FAS. Soluble FAS acts as a decoy receptor for FAS-ligand, inhibiting apoptosis induced through membrane-bound FAS. In summary, we demonstrate a novel genetic mechanism that contributes to risk of severe of COVID-19, highlighting a pathway that may be a promising therapeutic target.

Evaluation of 92 cardiovascular proteins in dried blood spots collected under field-conditions: Off-the-shelf affinity-based multiplexed assays work well, allowing for simplified sample collection

Workplace-collected blood spots deposited on filter paper were analysed with multiplexed affinity-based protein assays and found to be suitable for proteomics analysis. The protein extension assay (PEA) was used to characterize 92 proteins using 1.2 mm punches in repeated samples collected from 20 workers. Overall, 97.8% of the samples and 91.3% of the analysed proteins passed quality control. Both within and between spot correlations using six replicates from the same individual were above 0.99, suggesting that comparable levels are obtained from multiple punches from the same spot and from consecutive spots. Protein levels from dried blood and wet serum from the same individuals were compared and the majority of the analysed proteins were found to be significantly correlated. These results open up for simplified sample collection of blood in field conditions for proteomic analysis, but also highlight that not all proteins can be robustly measured from dried whole blood.

Temporal changes in the vaginal microbiota in self-samples and its association with persistent HPV16 infection and CIN2

Background

The vaginal microbiota has been reported to be associated with HPV infection and cervical cancer. This study was performed to compare the vaginal microbiota at two timepoints in women performing self-sampling and had a persistent or transient HPV16 infection. The women were tested for 12 high-risk HPV (hrHPV) types but only women with single type (HPV16) were included to reduce confounding variables.

Methods

In total 96 women were included in this study. Of these, 26 were single positive for HPV16 in the baseline test and HPV negative in the follow-up test and 38 were single positive for HPV16 in both tests and diagnosed with CIN2+ in histology. In addition, 32 women that were negative for all 12 HPV tested were included. The samples of vaginal fluid were analyzed with the Ion 16S™ Metagenomics Kit and Ion 16S™ metagenomics module within the Ion Reporter™ software.

Results

K-means clustering resulted in two Lactobacillus-dominated groups, one with Lactobacillus sp. and the other specifically with Lactobacillus iners. The two remaining clusters were dominated by a mixed non-Lactobacillus microbiota. HPV negative women had lower prevalence (28%) of the non-Lactobacill dominant cluster in the baseline test, as compared to women with HPV16 infection (42%) (p value = 0.0173). Transition between clusters were more frequent in women with persistent HPV16 infection (34%) as compared in women who cleared the HPV16 infection (19%) (p value = 0.036).

Conclusions

The vaginal microbiota showed a higher rate of transitioning between bacterial profiles in women with persistent HPV16 infection as compared to women with transient infection. This indicate an instability in the microenvironment in women with persistent HPV infection and development of CIN2+.

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.

Preoperative Fasting and General Anaesthesia Alter the Plasma Proteome

Background: Blood plasma collected at time of surgery is an excellent source of patient material for investigations into disease aetiology and for the discovery of novel biomarkers. Previous studies on limited sets of proteins and patients have indicated that pre-operative fasting and anaesthesia can affect protein levels, but this has not been investigated on a larger scale. These effects could produce erroneous results in case-control studies if samples are not carefully matched. Methods: The proximity extension assay (PEA) was used to characterize 983 unique proteins in a total of 327 patients diagnosed with ovarian cancer and 50 age-matched healthy women. The samples were collected either at time of initial diagnosis or before surgery under general anaesthesia. Results: 421 of the investigated proteins (42.8%) showed statistically significant differences in plasma abundance levels comparing samples collected at time of diagnosis or just before surgery under anaesthesia. Conclusions: The abundance levels of the plasma proteome in samples collected before incision, i.e., after short-time fasting and under general anaesthesia differs greatly from levels in samples from awake patients. This emphasizes the need for careful matching of the pre-analytical conditions of samples collected from controls to cases at time of surgery in the discovery as well as clinical use of protein biomarkers.

Invasive cervical tumors with high and low HPV titer represent molecular subgroups with different disease etiology

Invasive cervical cancer (ICC) with very low titer of high-risk human papillomavirus (HPV) has worse clinical outcome than cases with high titer, indicating a difference in molecular etiology. Fresh-frozen ICC tumors (n = 49) were classified into high- and low-HPV-titer cases using real-time PCR-based HPV genotyping. The mutation spectra were studied using the AmpliSeq Comprehensive Cancer Panel and the expression profiles using total RNA sequencing, and the results were validated using the AmpliSeq Transcriptome assay. HPV DNA genotyping and RNA sequencing showed that 16.6% of ICC tumors contained very low levels of HPV DNA and HPV transcripts. Tumors with low HPV levels had more mutations with a high allele frequency and fewer mutations with low allele frequency relative to tumors with high HPV titer. A number of genes showed significant expression differences between HPV titer groups, including genes with somatic mutations. Gene ontology and pathway analyses implicated the enrichment of genes involved in DNA replication, cell cycle control and extracellular matrix in tumors with low HPV titer. The results indicate that in low titer tumors, HPVs act as trigger of cancer development whereas somatic mutations are clonally selected and become drivers of the tumor development process. In contrast, in tumors with high HPV titer the expression of HPV oncoproteins plays a major role in tumor development and the many low frequency somatic mutations represent passengers. This putative subdivision of invasive cervical tumors may explain the higher radiosensitivity of ICC tumors with high HPV titer and thereby have consequences for clinical management.

HPV viral load in self-collected vaginal fluid samples as predictor for presence of cervical intraepithelial neoplasia

Objective

This study was performed to evaluate the use of high-risk HPV (hrHPV) viral load in screening tests for cervical cancer to predict persistent infection and presence of cervical intraepithelial neoplasia grade 2 or worse (CIN2+).

Methods

We followed women between 30 and 60 years of age who performed self-sampling of vaginal fluid and subsequently a hrHPV test. Women who were hrHPV positive in their screening test repeated the hrHPV test 3–6 months later and were included in the present study.

Results

Our results show that women with a persistent HPV16 infection had higher HPV viral load in their primary screening test than women with transient infections (p = 5.33e-03). This was also true for sum of viral load for all hrHPV types in the primary screening test (p = 3.88e-07). 48% of women with persistent HPV16 infection and CIN2+ had an increase in HPV16 titer in the follow-up test, as compared to only 20% of women with persistent infection but without CIN2+ lesions. For the sum of all hrHPV types, 41% of women with persistent infection and CIN2+ had an increase in titer as compared to 26% of women without CIN2 + .

Conclusions

The results show that hrHPV viral load in the primary screening HPV test is associated with the presence of CIN2+ and could be used in triaging hrHPV positive women for different follow-up strategies or recall times. Serial testing of hrHPV viral load has the potential to distinguish women with CIN2+ lesions from women with persistent infection but without CIN2+ lesions.

Clinical validation of the HPVIR high-risk HPV test on cervical samples according to the international guidelines for human papillomavirus DNA test requirements for cervical cancer screening

Background

The indicating FTA card is a dry medium used for collection of cervical samples. HPVIR is a multiplex real-time PCR test that detects 12 high-risk human papillomavirus types (hrHPV) and provides single genotype information for HPV16, − 31, − 35, − 39, − 51, − 56, and − 59 and pooled type information for HPV18/45 and HPV33/52/58. The aim of this study was to evaluate whether a strategy with cervical samples collected on the FTA card and subsequently analysed with the HPVIR test complies with the criteria of the international guidelines for a clinically validated method for cervical screening.

Methods

We performed a non-inferiority test comparing the clinical sensitivity and specificity of the candidate test (FTA card and HPVIR) with a clinically validated reference test (Cobas^® HPV test) based on liquid-based cytology (LBC) samples. Two clinical samples (LBC and FTA) were collected from 896 participants in population-based screening. For evaluation of the specificity we used 799 women without ≥ CIN2, and for clinical sensitivity we used 67 women with histologically confirmed ≥ CIN2. The reproducibility was studied by performing inter- and intra-laboratory tests of 558 additional clinical samples.

Results

The clinical sensitivity and specificity for samples collected on the FTA card and analysed using the HPVIR test were non-inferior to samples analysed with the Cobas® HPV test based on LBC samples (non-inferiority test score, p = 1.0 × 10^− 2 and p = 1.89 × 10^− 9, respectively). Adequate agreement of > 87% was seen in both the intra- and inter-laboratory comparisons.

Conclusions

Samples collected on the indicating FTA card and analysed with HPVIR test fulfil the requirements of the international guidelines and can therefore be used in primary cervical cancer screening.

High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer

Ovarian cancer is usually detected at a late stage and the overall 5-year survival is only 30-40%. Additional means for early detection and improved diagnosis are acutely needed. To search for novel biomarkers, we compared circulating plasma levels of 593 proteins in three cohorts of patients with ovarian cancer and benign tumors, using the proximity extension assay (PEA). A combinatorial strategy was developed for identification of different multivariate biomarker signatures. A final model consisting of 11 biomarkers plus age was developed into a multiplex PEA test reporting in absolute concentrations. The final model was evaluated in a fourth independent cohort and has an AUC = 0.94, PPV = 0.92, sensitivity = 0.85 and specificity = 0.93 for detection of ovarian cancer stages I-IV. The novel plasma protein signature could be used to improve the diagnosis of women with adnexal ovarian mass or in screening to identify women that should be referred to specialized examination.

Author Correction: New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Identification of Candidate Plasma Protein Biomarkers for Cervical Cancer Using the Multiplex Proximity Extension Assay

Human papillomavirus (HPV) is recommended as the primary test in cervical cancer screening, with co-testing by cytology for HPV-positive women to identify cervical lesions. Cytology has low sensitivity and there is a need to identify biomarkers that could identify dysplasia that are likely to progress to cancer. We searched for plasma proteins that could identify women with cervical cancer using the multiplex proximity extension assay (PEA). The abundance of 100 proteins were measured in plasma collected at the time of diagnosis of patients with invasive cervical cancer and in population controls using the Olink Multiplex panels CVD II, INF I, and ONC II. Eighty proteins showed increased levels in cases compared with controls. We identified a signature of 11 proteins (PTX3, ITGB1BP2, AXIN1, STAMPB, SRC, SIRT2, 4E-BP1, PAPPA, HB-EGF, NEMO and IL27) that distinguished cases and controls with a sensitivity of 0.96 at a specificity of 1.0. This signature was evaluated in a prospective replication cohort with samples collected before, at or after diagnosis and achieved a sensitivity of 0.78 and a specificity 0.56 separating samples collected at the time of diagnosis of invasive cancer from samples collected prior to diagnosis. No difference in abundance was seen between samples collected prior to diagnosis or after treatment as compared with population controls, indicating that this protein signature is mainly informative close to time of diagnosis. Further studies are needed to determine the optimal window in time prior to diagnosis for these biomarker candidates.

New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries

Reduced lung function predicts mortality and is key to the diagnosis of chronic obstructive pulmonary disease (COPD). In a genome-wide association study in 400,102 individuals of European ancestry, we define 279 lung function signals, 139 of which are new. In combination, these variants strongly predict COPD in independent populations. Furthermore, the combined effect of these variants showed generalizability across smokers and never smokers, and across ancestral groups. We highlight biological pathways, known and potential drug targets for COPD and, in phenome-wide association studies, autoimmune-related and other pleiotropic effects of lung function-associated variants. This new genetic evidence has potential to improve future preventive and therapeutic strategies for COPD.

Genetic variants influencing phenotypic variance heterogeneity

Most genetic studies identify genetic variants associated with disease risk or with the mean value of a quantitative trait. More rarely, genetic variants associated with variance heterogeneity are considered. In this study, we have identified such variance single-nucleotide polymorphisms (vSNPs) and examined if these represent biological gene × gene or gene × environment interactions or statistical artifacts caused by multiple linked genetic variants influencing the same phenotype. We have performed a genome-wide study, to identify vSNPs associated with variance heterogeneity in DNA methylation levels. Genotype data from over 10 million single-nucleotide polymorphisms (SNPs), and DNA methylation levels at over 430 000 CpG sites, were analyzed in 729 individuals. We identified vSNPs for 7195 CpG sites (P < 9.4 × 10-11). This is a relatively low number compared to 52 335 CpG sites for which SNPs were associated with mean DNA methylation levels. We further showed that variance heterogeneity between genotypes mainly represents additional, often rare, SNPs in linkage disequilibrium (LD) with the respective vSNP and for some vSNPs, multiple low frequency variants co-segregating with one of the vSNP alleles. Therefore, our results suggest that variance heterogeneity of DNA methylation mainly represents phenotypic effects by multiple SNPs, rather than biological interactions. Such effects may also be important for interpreting variance heterogeneity of more complex clinical phenotypes.

Publisher Correction: Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits

In the version of this article originally published, the name of author Martin H. de Borst was coded incorrectly in the XML. The error has now been corrected in the HTML version of the paper.

A two-step strategy for identification of plasma protein biomarkers for endometrial and ovarian cancer

Background

Over 500,000 women worldwide are diagnosed with ovarian or endometrial cancer each year. We have used a two-step strategy to identify plasma proteins that could be used to improve the diagnosis of women with an indication of gynecologic tumor and in population screening.

Methods

In the discovery step we screened 441 proteins in plasma using the proximity extension assay (PEA) and five Olink Multiplex assays (CVD II, CVD III, INF I, ONC II, NEU I) in women with ovarian cancer (n = 106), endometrial cancer (n = 74), benign ovarian tumors (n = 150) and healthy population controls (n = 399). Based on the discovery analyses a set of 27 proteins were selected and two focused multiplex PEA assays were developed. In a replication step the focused assays were used to study an independent set of cases with ovarian cancer (n = 280), endometrial cancer (n = 228), women with benign ovarian tumors (n = 76) and healthy controls (n = 57).

Results

In the discovery step, 27 proteins that showed an association to cancer status were identified. In the replication analyses, the focused assays distinguished benign tumors from ovarian cancer stage III-IV with a sensitivity of 0.88 and specificity of 0.92 (AUC = 0.92). The assays had a significantly higher AUC for distinguishing benign tumors from late stage ovarian cancer than using CA125 and HE4 (p = 9.56e-22). Also, population controls could be distinguished from ovarian cancer stage III-IV with a sensitivity of 0.85 and a specificity of 0.92 (AUC = 0.89).

Conclusion

The PEA assays represent useful tools for identification of new biomarkers for gynecologic cancers. The selected protein assays could be used to distinguish benign tumors from ovarian and endometrial cancer in women diagnosed with an unknown suspicious pelvic mass. The panels could also be used in population screening, for identification of women in need of specialized gynecologic transvaginal ultrasound examination.

Funding

The Swedish Cancer Foundation, Vinnova (SWELIFE), The Foundation for Strategic Research (SSF), Assar Gabrielsson Foundation.

Randomised study of HPV prevalence and detection of CIN2+ in vaginal self-sampling compared to cervical specimens collected by medical personnel

We conducted a randomised study to compare vaginal self-sampling with assisted sampling by medical personnel on the cervix for HPV testing in primary screening. The first aim was to determine if the HPV prevalence is independent of sampling location (vagina versus cervix) and the person performing the sampling. The second aim was to evaluate if the two sampling strategies differed in the detection rate of CIN2+. In total, 19,523 women were randomised into two groups, with 9926 invited to perform self-sampling (SS arm) using the Rover VIBA-brush and 9597 offered assisted sampling using the cytobrush (AS arm). All samples were applied to the indicating FTA elute card and analysed for high-risk HPV using the hpVIR real-time PCR assay. The outcome for the first aim was HPV prevalence and for the second aim the number of CIN2+ based on histology. In the SS arm, 52.7% of invited women participated in the study, as compared to 34.2% in the AS arm. All samples contained sufficient amount of nuclear DNA for a valid HPV result, with vaginal samples having a higher DNA amount than cervical samples (p < 4.62 × 10^-11 ). HPV prevalence was 4.6% in the SS arm and 4.1% in the AS arm (p = 5.5 × 10^-2 ), and the distribution of HPV types similar between arms. There was no difference in the prevalence of CIN2+ per 1000 women screened between arms (p = 0.86). The results show that vaginal self-sampling is an equivalent alternative to sampling by medical personnel for HPV typing and identification of CIN2+.

Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

Meta-analysis of exome array data identifies six novel genetic loci for lung function

Background: Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. Methods: We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV ₁), forced vital capacity (FVC) and the ratio of FEV ₁ to FVC (FEV ₁/FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. Results: We identified significant (P<2·8x10 ^-7) associations with six SNPs: a nonsynonymous variant in RPAP1, which is predicted to be damaging, three intronic SNPs ( SEC24C, CASC17 and UQCC1) and two intergenic SNPs near to LY86 and FGF10. Expression quantitative trait loci analyses found evidence for regulation of gene expression at three signals and implicated several genes, including TYRO3 and PLAU. Conclusions: Further interrogation of these loci could provide greater understanding of the determinants of lung function and pulmonary disease.

Genomewide binding of transcription factor Snail1 in triple-negative breast cancer cells

Transcriptional regulation mediated by the zinc finger protein Snail1 controls early embryogenesis. By binding to the epithelial tumor suppressor CDH1 gene, Snail1 initiates the epithelial–mesenchymal transition (EMT). The EMT generates stem‐like cells and promotes invasiveness during cancer progression. Accordingly, Snail1 mRNA and protein is abundantly expressed in triple‐negative breast cancers with enhanced metastatic potential and phenotypic signs of the EMT. Such high endogenous Snail1 protein levels permit quantitative chromatin immunoprecipitation‐sequencing (ChIP‐seq) analysis. Snail1 associated with 185 genes at cis regulatory regions in the Hs578T triple‐negative breast cancer cell model. These genes include morphogenetic regulators and signaling components that control polarized differentiation. Using the CRISPR/Cas9 system in Hs578T cells, a double deletion of 10 bp each was engineered into the first exon and into the second exon–intron junction of Snail1, suppressing Snail1 expression and causing misregulation of several hundred genes. Specific attention to regulators of chromatin organization provides a possible link to new phenotypes uncovered by the Snail1 loss‐of‐function mutation. On the other hand, genetic inactivation of Snail1 was not sufficient to establish a full epithelial transition to these tumor cells. Thus, Snail1 contributes to the malignant phenotype of breast cancer cells via diverse new mechanisms.

Genome-wide binding of transcription factor ZEB1 in triple-negative breast cancer cells

Zinc finger E-box binding homeobox 1 (ZEB1) is a transcriptional regulator involved in embryonic development and cancer progression. ZEB1 induces epithelial-mesenchymal transition (EMT). Triple-negative human breast cancers express high ZEB1 mRNA levels and exhibit features of EMT. In the human triple-negative breast cancer cell model Hs578T, ZEB1 associates with almost 2,000 genes, representing many cellular functions, including cell polarity regulation (DLG2 and FAT3). By introducing a CRISPR-Cas9-mediated 30 bp deletion into the ZEB1 second exon, we observed reduced migratory and anchorage-independent growth capacity of these tumor cells. Transcriptomic analysis of control and ZEB1 knockout cells, revealed 1,372 differentially expressed genes. The TIMP metallopeptidase inhibitor 3 and the teneurin transmembrane protein 2 genes showed increased expression upon loss of ZEB1, possibly mediating pro-tumorigenic actions of ZEB1. This work provides a resource for regulators of cancer progression that function under the transcriptional control of ZEB1. The data confirm that removing a single EMT transcription factor, such as ZEB1, is not sufficient for reverting the triple-negative mesenchymal breast cancer cells into more differentiated, epithelial-like clones, but can reduce tumorigenic potential, suggesting that not all pro-tumorigenic actions of ZEB1 are linked to the EMT.

A Meta-Analysis of Genome-Wide Association Studies of Growth Differentiation Factor-15 Concentration in Blood

Blood levels of growth differentiation factor-15 (GDF-15), also known as macrophage inhibitory cytokine-1 (MIC-1), have been associated with various pathological processes and diseases, including cardiovascular disease and cancer. Prior studies suggest genetic factors play a role in regulating blood MIC-1/GDF-15 concentration. In the current study, we conducted the largest genome-wide association study (GWAS) to date using a sample of ∼5,400 community-based Caucasian participants, to determine the genetic variants associated with MIC-1/GDF-15 blood concentration. Conditional and joint (COJO), gene-based association, and gene-set enrichment analyses were also carried out to identify novel loci, genes, and pathways. Consistent with prior results, a locus on chromosome 19, which includes nine single nucleotide polymorphisms (SNPs) (top SNP, rs888663, p = 1.690 × 10^-35), was significantly associated with blood MIC-1/GDF-15 concentration, and explained 21.47% of its variance. COJO analysis showed evidence for two independent signals within this locus. Gene-based analysis confirmed the chromosome 19 locus association and in addition, a putative locus on chromosome 1. Gene-set enrichment analyses showed that the“COPI-mediated anterograde transport” gene-set was associated with MIC-1/GDF15 blood concentration with marginal significance after FDR correction (p = 0.067). In conclusion, a locus on chromosome 19 was associated with MIC-1/GDF-15 blood concentration with genome-wide significance, with evidence for a new locus (chromosome 1). Future studies using independent cohorts are needed to confirm the observed associations especially for the chromosomes 1 locus, and to further investigate and identify the causal SNPs that contribute to MIC-1/GDF-15 levels.

Targeted plasma proteomics identifies a novel, robust association between cornulin and Swedish moist snuff

Lifestyle behaviors are believed to influence the body’s inflammatory state. Chronic low-grade inflammation contributes to the development of major non-communicable diseases such as diabetes, cardiovascular disease and cancer. Inflammation may thus be an important link between lifestyle and disease. We evaluated self-reported physical activity, tobacco use and alcohol consumption in relation to plasma levels of 160 validated inflammatory and cancer biomarkers. The study included 138 participants from a population-based cohort, all with repeated sampling of plasma and data ten years apart, allowing consideration of both intra- and inter-individual variation. Of 17 relationships identified, the strongest was an independent, positive association between cornulin (CRNN) and Swedish moist snuff (snus) use. We replicated the finding in a second cohort of 501 individuals, in which a dose-response relationship was also observed. Snus explained approximately one fifth of the variance in CRNN levels in both sample sets (18% and 23%). In conclusion, we identified a novel, independent, dose-dependent association between CRNN and snus use. Further study is warranted, to evaluate the performance of CRNN as a potential snus biomarker. The putative importance of lifestyle behaviors on a wide range of protein biomarkers illustrates the need for more personalized biomarker cut-offs.

Epigenome-wide association study reveals differential DNA methylation in individuals with a history of myocardial infarction

Cardiovascular diseases (CVDs) are the leading causes of death worldwide and represent a substantial economic burden on public health care systems. Epigenetic markers have potential as diagnostic markers before clinical symptoms have emerged, and as prognostic markers to inform the choice of clinical intervention. In this study, we performed an epigenome-wide association study (EWAS) for CVDs, to identify disease-specific alterations in DNA methylation. CpG methylation in blood samples from the northern Sweden population health study (NSPHS) (n = 729) was assayed on the Illumina Infinium HumanMethylation450 BeadChip. Individuals with a history of a CVD were identified in the cohort. It included individuals with hypertension (N = 147), myocardial infarction (MI) (N = 48), stroke (N = 27), thrombosis (N = 22) and cardiac arrhythmia (N = 5). Differential DNA methylation was observed at 211 CpG-sites in individuals with a history of MI (q <0.05). These sites represent 196 genes, of which 42 have been described in the scientific literature to be related to cardiac function, cardiovascular disease, cardiogenesis and recovery after ischemic injury. We have shown that individuals with a history of MI have a deviating pattern of DNA methylation at many genomic loci of which a large fraction has previously been linked to CVD. Our results highlight genes that might be important in the pathogenesis of MI or in recovery. In addition, the sites pointed out in this study can serve as candidates for further evaluation as potential biomarkers for MI.

Pooled analysis of genome-wide association studies of cervical intraepithelial neoplasia 3 (CIN3) identifies a new susceptibility locus

Recent genome-wide association studies (GWASs) in subjects of European descent have identified associations between cervical cancer risk and three independent loci as well as multiple classical human leukocyte antigen (HLA) alleles at 6p21.3. To search for novel loci associated with development of cervical cancer, we performed a pooled analysis of data from two GWASs by imputing over 10 million genetic variants and 424 classical HLA alleles, for 1,553 intraepithelial neoplasia 3 (CIN3), 81 cervical cancer and 4,442 controls from the Swedish population. Notable findings were validated in an independent study of 961 patients (827 with CIN3 and 123 with cervical cancer) and 1,725 controls. Our data provided increased support for previously identified loci at 6p21.3 (rs9271898, P = 1.2 × 10⁻²⁴; rs2516448, 1.1 × 10⁻¹⁵; and rs3130196, 2.3 × 10⁻⁹, respectively) and also confirmed associations with reported classical HLA alleles including HLA-B*07:02, -B*15:01, -DRB1*13:01, -DRB1*15:01, -DQA1*01:03, -DQB1*06:03 and -DQB1*06:02. In addition, we identified and subsequently replicated an independent signal at rs73730372 at 6p21.3 (odds ratio = 0.60, 95% confidence interval = 0.54–0.67, P = 3.0 × 10⁻¹⁹), which was found to be an expression quantitative trait locus (eQTL) of both HLA-DQA1 and HLA-DQB1. This is one of the strongest common genetic protective variants identified so far for CIN3. We also found HLA-C*07:02 to be associated with risk of CIN3. The present study provides new insights into pathogenesis of CIN3.

Meta-analysis of exome array data identifies six novel genetic loci for lung function

Background: Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. Methods: We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV ₁), forced vital capacity (FVC) and the ratio of FEV ₁ to FVC (FEV ₁/FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. Results: We identified significant (P<2·8x10 ^-7) associations with six SNPs: a nonsynonymous variant in RPAP1, which is predicted to be damaging, three intronic SNPs ( SEC24C, CASC17 and UQCC1) and two intergenic SNPs near to LY86 and FGF10. Expression quantitative trait loci analyses found evidence for regulation of gene expression at three signals and implicated several genes, including TYRO3 and PLAU. Conclusions: Further interrogation of these loci could provide greater understanding of the determinants of lung function and pulmonary disease.

Meta-analysis of exome array data identifies six novel genetic loci for lung function

Background: Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. Methods: We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV 1), forced vital capacity (FVC) and the ratio of FEV 1 to FVC (FEV 1/FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. Results: We identified significant (P<2·8x10 -7) associations with six SNPs: a nonsynonymous variant in RPAP1, which is predicted to be damaging, three intronic SNPs ( SEC24C, CASC17 and UQCC1) and two intergenic SNPs near to LY86 and FGF10. Expression quantitative trait loci analyses found evidence for regulation of gene expression at three signals and implicated several genes, including TYRO3 and PLAU. Conclusions: Further interrogation of these loci could provide greater understanding of the determinants of lung function and pulmonary disease.

The relative contribution of DNA methylation and genetic variants on protein biomarkers for human diseases

Associations between epigenetic alterations and disease status have been identified for many diseases. However, there is no strong evidence that epigenetic alterations are directly causal for disease pathogenesis. In this study, we combined SNP and DNA methylation data with measurements of protein biomarkers for cancer, inflammation or cardiovascular disease, to investigate the relative contribution of genetic and epigenetic variation on biomarker levels. A total of 121 protein biomarkers were measured and analyzed in relation to DNA methylation at 470,000 genomic positions and to over 10 million SNPs. We performed epigenome-wide association study (EWAS) and genome-wide association study (GWAS) analyses, and integrated biomarker, DNA methylation and SNP data using between 698 and 1033 samples depending on data availability for the different analyses. We identified 124 and 45 loci (Bonferroni adjusted P < 0.05) with effect sizes up to 0.22 standard units' change per 1% change in DNA methylation levels and up to four standard units' change per copy of the effective allele in the EWAS and GWAS respectively. Most GWAS loci were cis-regulatory whereas most EWAS loci were located in trans. Eleven EWAS loci were associated with multiple biomarkers, including one in NLRC5 associated with CXCL11, CXCL9, IL-12, and IL-18 levels. All EWAS signals that overlapped with a GWAS locus were driven by underlying genetic variants and three EWAS signals were confounded by smoking. While some cis-regulatory SNPs for biomarkers appeared to have an effect also on DNA methylation levels, cis-regulatory SNPs for DNA methylation were not observed to affect biomarker levels. We present associations between protein biomarker and DNA methylation levels at numerous loci in the genome. The associations are likely to reflect the underlying pattern of genetic variants, specific environmental exposures, or represent secondary effects to the pathogenesis of disease.

Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA. Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation.

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 FEV 1 (forced expiratory volume in 1 second) or FEV 1 /FVC (FEV 1 /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 FEV 1 or FEV 1 /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 ( βint  = -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 FEV 1 /FVC ratio. In interpreting this interaction, we showed that the genetic risk of falling below the FEV /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 FEV 1 /FVC may be more susceptible to the deleterious effects of smoking.

Growth signals employ CGGBP1 to suppress transcription of Alu-SINEs

CGGBP1 (CGG triplet repeat-binding protein 1) regulates cell proliferation, stress response, cytokinesis, telomeric integrity and transcription. It could affect these processes by modulating target gene expression under different conditions. Identification of CGGBP1-target genes and their regulation could reveal how a transcription regulator affects such diverse cellular processes. Here we describe the mechanisms of differential gene expression regulation by CGGBP1 in quiescent or growing cells. By studying global gene expression patterns and genome-wide DNA-binding patterns of CGGBP1, we show that a possible mechanism through which it affects the expression of RNA Pol II-transcribed genes in trans depends on Alu RNA. We also show that it regulates Alu transcription in cis by binding to Alu promoter. Our results also indicate that potential phosphorylation of CGGBP1 upon growth stimulation facilitates its nuclear retention, Alu-binding and dislodging of RNA Pol III therefrom. These findings provide insights into how Alu transcription is regulated in response to growth signals.

Stability of Proteins in Dried Blood Spot Biobanks

An important motivation for the construction of biobanks is to discover biomarkers that identify diseases at early, potentially curable stages. This will require biobanks from large numbers of individuals, preferably sampled repeatedly, where the samples are collected and stored under conditions that preserve potential biomarkers. Dried blood samples are attractive for biobanking because of the ease and low cost of collection and storage. Here we have investigated their suitability for protein measurements. Ninety-two proteins with relevance for oncology were analyzed using multiplex proximity extension assays (PEA) in dried blood spots collected on paper and stored for up to 30 years at either +4 °C or −24 °C.

Our main findings were that (1) the act of drying only slightly influenced detection of blood proteins (average correlation of 0.970), and in a reproducible manner (correlation of 0.999), (2) detection of some proteins was not significantly affected by storage over the full range of three decades (34 and 76% of the analyzed proteins at +4 °C and −24 °C, respectively), whereas levels of others decreased slowly during storage with half-lives in the range of 10 to 50 years, and (3) detectability of proteins was less affected in dried samples stored at −24 °C compared with at +4 °C, as the median protein abundance had decreased to 80 and 93% of starting levels after 10 years of storage at +4 °C or −24 °C, respectively. The results of our study are encouraging as they suggest an inexpensive means to collect large numbers of blood samples, even by the donors themselves, and to transport, and store biobanked samples as spots of whole blood dried on paper. Combined with emerging means to measure hundreds or thousands of protein, such biobanks could prove of great medical value by greatly enhancing discovery as well as routine analysis of blood biomarkers.

Mapping of 79 loci for 83 plasma protein biomarkers in cardiovascular disease

Recent advances in highly multiplexed immunoassays have allowed systematic large-scale measurement of hundreds of plasma proteins in large cohort studies. In combination with genotyping, such studies offer the prospect to 1) identify mechanisms involved with regulation of protein expression in plasma, and 2) determine whether the plasma proteins are likely to be causally implicated in disease. We report here the results of genome-wide association (GWA) studies of 83 proteins considered relevant to cardiovascular disease (CVD), measured in 3,394 individuals with multiple CVD risk factors. We identified 79 genome-wide significant (p<5e-8) association signals, 55 of which replicated at P<0.0007 in separate validation studies (n = 2,639 individuals). Using automated text mining, manual curation, and network-based methods incorporating information on expression quantitative trait loci (eQTL), we propose plausible causal mechanisms for 25 trans-acting loci, including a potential post-translational regulation of stem cell factor by matrix metalloproteinase 9 and receptor-ligand pairs such as RANK-RANK ligand. Using public GWA study data, we further evaluate all 79 loci for their causal effect on coronary artery disease, and highlight several potentially causal associations. Overall, a majority of the plasma proteins studied showed evidence of regulation at the genetic level. Our results enable future studies of the causal architecture of human disease, which in turn should aid discovery of new drug targets.

Several proteins that circulate in blood have been linked to cardiovascular disease through the use of classic epidemiology and correlation studies. If individuals with higher risk of disease have higher levels of a protein, the protein may be associated with disease. However, this does not necessarily mean that the protein causes disease; it may merely be an innocent bystander or a consequence of the disease process. To establish whether a protein causes disease, a genetic approach, insensitive to reverse causation, can be used. Instead of correlating the levels of the protein itself, gene variants that regulate the protein levels are used in the analysis. This approach requires prior knowledge of which genetic variants are linked to individual proteins. Therefore we completed a map of how common genetic variants affect the blood concentration levels of 83 proteins that have been implicated in cardiovascular disease. By using this map of cause-to-effect findings, we gained insights into the regulation of a majority of the proteins under study and how they relate to risk of coronary artery disease. This study provides a map of genetic regulation of important cardiovascular plasma proteins, insights into their upstream regulatory environment, as well as novel leads for cardiovascular drug development.

PATZ1 down-regulates FADS1 by binding to rs174557 and is opposed by SP1/SREBP1c

The FADS1 and FADS2 genes in the FADS cluster encode the rate-limiting enzymes in the synthesis of long-chain polyunsaturated fatty acids (LC-PUFAs). Genetic variation in this region has been associated with a large number of diseases and traits many of them correlated to differences in metabolism of PUFAs. However, the causative variants leading to these associations have not been identified. Here we find that the multiallelic rs174557 located in an AluYe5 element in intron 1 of FADS1 is functional and lies within a PATZ1 binding site. The derived allele of rs174557, which is the common variant in most populations, diminishes binding of PATZ1, a transcription factor conferring allele-specific downregulation of FADS1. The PATZ1 binding site overlaps with a SP1 site. The competitive binding between the suppressive PATZ1 and the activating complex of SP1 and SREBP1c determines the enhancer activity of this region, which regulates expression of FADS1.