Decreased neutrophil function in newly diagnosed multiple myeloma patients is restored with lenalidomide therapy.

OBJECTIVES: Bacterial infections are common and a major cause of morbidity and mortality in multiple myeloma (MM). We have investigated the function of polymorphonuclear leukocyte (PMN), the immune system's first line of defense against bacteria, in peripheral blood (PB) and bone marrow (BM) samples from patients with newly diagnosed MM (NDMM), smoldering MM (SMM), monoclonal gammopathy of undetermined significance (MGUS) and healthy controls. METHODS: Phagocytosis and oxidative burst in PMN cells from patients and healthy donors were investigated using PhagoTest and PhagoBurst assay. RESULTS: PMN from NDMM, SMM, and MGUS patients had reduced phagocytosis and oxidative burst ability compared with healthy controls. The dysfunction was most prominent in BM samples from MM, SMM, and MGUS patients. Importantly the reduced phagocytosis in MM patients was restored in patients on lenalidomide therapy. Consistently the ability of Escherichia coli stimulated oxidative burst in BM was reduced for the MM, SMM, and MGUS cohort in contrast to the healthy controls and the patients on lenalidomide treatment. CONCLUSION: Our results show that MM patients have neutrophil dysfunction that could contribute to susceptibility for bacterial infections and that lenalidomide therapy was associated with restored PMN function.

Predictive and Prognostic Biomarkers in Patients With Mycosis Fungoides and Sézary Syndrome (BIO-MUSE): Protocol for a Translational Study.

BACKGROUND: Cutaneous T-cell lymphoma (CTCL) is a rare group of lymphomas that primarily affects the skin. Mycosis fungoides (MF) is the most common form of CTCL and Sézary syndrome (SS) is more infrequent. Early stages (IA-IIA) have a favorable prognosis, while advanced stages (IIB-IVB) have a worse prognosis. Around 25% of patients with early stages of the disease will progress to advanced stages. Malignant skin-infiltrating T-cells in CTCL are accompanied by infiltrates of nonmalignant T-cells and other immune cells that produce cytokines that modulate the inflammation. Skin infection, often with Staphylococcus aureus, is frequent in advanced stages and can lead to sepsis and death. S. aureus has also been reported to contribute to the progression of the disease. Previous reports indicate a shift from Th1 to Th2 cytokine production and dysfunction of the skin barrier in CTCL. Treatment response is highly variable and often unpredictable, and there is a need for new predictive and prognostic biomarkers. OBJECTIVE: This prospective translational study aims to identify prognostic biomarkers in the blood and skin of patients with MF and SS. METHODS: The Predictive and Prognostic Biomarkers in Patients With MF and SS (BIO-MUSE) study aims to recruit 120 adult patients with MF or SS and a control group of 20 healthy volunteers. The treatments will be given according to clinical routine. The sampling of each patient will be performed every 3 months for 3 years. The blood samples will be analyzed for lactate dehydrogenase, immunoglobulin E, interleukins, thymus and activation-regulated chemokine, and lymphocyte subpopulations. The lymphoma microenvironment will be investigated through digital spatial profiling and single-cell RNA sequencing. Microbiological sampling and analysis of skin barrier function will be performed. The life quality parameters will be evaluated. The results will be evaluated by the stage of the disease. RESULTS: Patient inclusion started in 2021 and is still ongoing in 2023, with 18 patients and 20 healthy controls enrolled. The publication of selected translational findings before the publication of the main results of the trial is accepted. CONCLUSIONS: This study aims to investigate blood and skin with a focus on immune cells and the microbiological environment to identify potential new prognostic biomarkers in MF and SS. TRIAL REGISTRATION: ClinicalTrials.gov NCT04904146; https://www.clinicaltrials.gov/study/NCT04904146. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55723.

Disease Activity and Tendency to Relapse in ANCA-Associated Vasculitis Are Reflected in Neutrophil and Intermediate Monocyte Frequencies.

Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a group of autoimmune diseases with inflammation affecting small blood vessels and includes granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA). In this study, we investigated granulocyte and monocyte subsets in a large cohort of AAV patients with emphasis on disease activity and tendency to relapse. A cohort of 105 patients with GPA or MPA and 126 healthy controls (HCs) were included. Clinical and laboratory data were collected for all patients, including disease activity, tendency to relapse, and pharmacological treatment. Using flow cytometry, circulating eosinophils, basophils, neutrophils, and monocytes were assessed. The monocytes were subdivided into classical (CD14++CD16-), intermediate (CD14++CD16+), and nonclassical (CD14-CD16+) monocytes. Mature (CD16high) or newly released (CD16dim) neutrophils were defined, as well as the frequency of CD177+ neutrophils. AAV patients displayed increased frequencies of intermediate monocytes, mature and newly released neutrophils, and an expanded population of CD177+ neutrophils compared to HC. MPA patients differed from GPA patients in terms of lower frequency of classical monocytes. No differences in cell frequencies regarding ANCA phenotype were observed. Paired data from 23 patients demonstrated that active disease was associated with an increased frequency of mature neutrophils and a decreased frequency of monocytes, in particular intermediate monocytes. Moreover, GPA patients with a tendency to relapse displayed an increased frequency of mature neutrophils with increased expression of CD177+. Relapsing MPA patients, on the other hand, showed decreased frequency of intermediate monocytes. Finally, rituximab treatment was associated with increased frequencies of classical and intermediate monocytes. In conclusion, AAV patients exhibit a skewing of different neutrophil and monocyte subpopulations that are associated with disease subtypes, disease activity, rituximab treatment, and propensity to relapse. These changes may contribute to the inflammatory process and could potentially be used as biomarkers for relapse prediction.

The risk of venous thromboembolism in oral contraceptive users: the role of genetic factors-a prospective cohort study of 240,000 women in the UK Biobank.

BACKGROUND: More than 150 million women worldwide use oral contraceptives. Women with inherited thrombophilia and carriers of certain thrombophilia gene variants, such as factor V Leiden and the prothrombin, are at an increased risk for venous thromboembolism, especially when combined with oral contraceptive use. Venous thromboembolism is a complex disorder involving many genetic risk factors, and recently, polygenic risk scores have been proposed to capture a significant proportion of the genetic risk of venous thromboembolism. OBJECTIVE: The aim of this study was to estimate the risk for developing venous thromboembolism when initiating oral contraceptive use (first 2 years) and during continued use among women with a high genetic liability. STUDY DESIGN: We used a prospective study design in which 244,420 participants from the UK Biobank were followed from birth. The effect of oral contraceptive use during the first 2 years and in the remaining years of oral contraceptive use on the risk of developing venous thromboembolism was estimated using a Cox regression with a time-dependent exposure variable. Women were stratified according to their polygenic risk scores and whether they were carriers of factor V Leiden and/or prothrombin variants. RESULTS: When genetic risk was not considered, an increased risk for venous thromboembolism was observed during the first 2 years of oral contraceptive use (hazard ratio, 3.09; 95% confidence interval, 3.00-3.20) but not during continued use (hazard ratio, 0.92; 95% confidence interval, 0.80-1.05). However, when genetic risk was considered, women in the highest polygenic risk score category had a more pronounced risk of developing a venous thromboembolism during the first 2 years of oral contraceptive use (hazard ratio, 6.35; 95% confidence interval, 4.98-8.09), and a high risk was also observed among factor V Leiden (hazard ratio, 5.73; 95% confidence interval, 5.31-6.17) and prothrombin variant carriers (hazard ratio, 5.23; 95% confidence interval, 4.67 - 5.87). A high polygenic risk score in combination with being a factor V Leiden and prothrombin variant carrier conferred the highest risk for developing a venous thromboembolism during the first 2 years of oral contraceptive use (hazard ratio, 14.8; 95% confidence interval, 9.28-23.6). Women with a high genetic liability also had an increased risk during continued use but it was less pronounced, and the highest risk was conferred to carriers of both factor V Leiden and the prothrombin variant (hazard ratio, 4.93; 95% confidence interval, 3.16-7.7). CONCLUSION: Evaluating polygenic risk can identify additional venous thromboembolism risk that is not captured in the commonly investigated genes for inherited thrombophilia. Our results indicate that oral contraceptive use is associated with an increased risk for developing a venous thromboembolism, particularly among women with a high genetic predisposition, and that oral contraceptive use dramatically increases the risk thereof short after initiation of use, which decreases with continued use. This suggests that the polygenic risk score could be used to identify women who are at high risk for developing a venous thromboembolism and advise them on alternative methods of contraception.

Copy number variations and their effect on the plasma proteome.

Structural variations, including copy number variations (CNVs), affect around 20 million bases in the human genome and are common causes of rare conditions. CNVs are rarely investigated in complex disease research because most CNVs are not targeted on the genotyping arrays or the reference panels for genetic imputation. In this study, we characterize CNVs in a Swedish cohort (N = 1,021) using short-read whole-genome sequencing (WGS) and use long-read WGS for validation in a subcohort (N = 15), and explore their effect on 438 plasma proteins. We detected 184,182 polymorphic CNVs and identified 15 CNVs to be associated with 16 proteins (P < 8.22×10-10). Of these, 5 CNVs could be perfectly validated using long-read sequencing, including a CNV which was associated with measurements of the osteoclast-associated immunoglobulin-like receptor (OSCAR) and located upstream of OSCAR, a gene important for bone health. Two other CNVs were identified to be clusters of many short repetitive elements and another represented a complex rearrangement including an inversion. Our findings provide insights into the structure of common CNVs and their effects on the plasma proteome, and highlights the importance of investigating common CNVs, also in relation to complex diseases.

Effects of oral contraceptives and menopausal hormone therapy on the risk of rheumatoid arthritis: a prospective cohort study.

OBJECTIVES: Oral contraceptives (OC) and menopausal hormone therapy (MHT) contain exogenous sex hormones and are used by millions of women around the world. However, their effect on development of rheumatoid arthritis (RA) is still debated and the current literature suggests that they may exert opposite effects on the risk of RA. The present study aimed to estimate the effects of exogenous hormones on development of RA, both during the reproductive lifespan and later in life. METHODS: The association between OC and RA, as well as between MHT and late-onset RA (LORA), was investigated using time-dependent Cox regression modelling in white British women from the UK Biobank (N = 236 602 and N = 102 466, respectively) and replicated in women from all ethnic groups. RESULTS: OC use was associated with a decreased risk of RA in ever-users (hazard ratio [HR]=0.89; 95% CI = 0.82-0.96), as well as in current (HR = 0.81; 0.73-0.91) and former users (HR = 0.92; 0.84 -1.00), compared with never-users. In contrast, MHT use was associated with an increased risk of LORA in ever-users (HR = 1.16; 1.06-1.26) as well as in former users (HR = 1.13; 1.03-1.24) compared with never-users. CONCLUSION: OC use appears to protect against RA, while MHT may increase the risk of LORA. This study provides new insights into the possible inverse effect of exposure to different exogenous sex hormones on the risk of RA.

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.

Polygenic risk scores and risk stratification in deep vein thrombosis.

INTRODUCTION: Deep vein thrombosis (DVT) is a complex disease, where 60 % of risk is due to genetic factors, such as the Factor V Leiden (FVL) variant. DVT is either asymptomatic or manifests with unspecific symptoms and, if left untreated, DVT leads to severe complications. The impact is dramatic and currently, there is still a research gap in DVT prevention. We characterized the genetic contribution and stratified individuals based on genetic makeup to evaluate if it favorably impacts risk prediction. METHODS: In the UK Biobank (UKB), we performed gene-based association tests using exome sequencing data, as well as a genome-wide association study. We also constructed polygenic risk scores (PRS) in a subset of the cohort (Number of cases = 8231; Number of controls = 276,360) and calculated the impact on the prediction capacity of the PRS in a non-overlapping part of the cohort (Number of cases = 4342; Number of controls = 142,822). We generated additional PRSs that excluded the known causative variants. RESULTS: We discovered and replicated a novel common variant (rs11604583) near the region where are located the TRIM51 and LRRC55 genes and identified a novel rare variant (rs187725533) located near the CREB3L1 gene, associated with 2.5-fold higher risk of DVT. In one of the PRS models constructed, the top decile of risk is associated with 3.4-fold increased risk, an effect that is 2.3-fold when excluding FVL carriers. In the top PRS decile, the cumulative risk of DVT at the age of 80 years is 10 % for FVL carriers, contraposed to 5 % for non-carriers. The population attributable fractions of having a high polygenic risk on the rate of DVT was estimated to be around 20 % in our cohort. CONCLUSION: Individuals with a high polygenic risk of DVT, and not only carriers of well-studied variants such as FVL, may benefit from prevention strategies.

Adiposity and sex-specific cancer risk.

Obesity is associated with several types of cancer and fat distribution, which differs dramatically between sexes, has been suggested to be an independent risk factor. However, sex-specific effects on cancer risk have rarely been studied. Here we estimate the effects of fat accumulation and distribution on cancer risk in females and males. We performed a prospective study in 442,519 UK Biobank participants, for 19 cancer types and additional histological subtypes, with a mean follow-up time of 13.4 years. Cox proportional hazard models were used to estimate the effect of 14 different adiposity phenotypes on cancer rates, and a 5% false discovery rate was considered statistically significant. Adiposity-related traits are associated with all but three cancer types, and fat accumulation is associated with a larger number of cancers compared to fat distribution. In addition, fat accumulation or distribution exhibit differential effects between sexes on colorectal, esophageal, and liver cancer.

Body Mass Index and the Risk of Rheumatic Disease: Linear and Nonlinear Mendelian Randomization Analyses.

OBJECTIVE: Although the association between obesity and risk of rheumatic disease is well established, the precise causal relation has not been conclusively proven. Here, we estimate the causal effect of body mass index (BMI) on the risk of developing 5 different rheumatic diseases. METHODS: Linear and nonlinear mendelian randomization (MR) were used to estimate the effect of BMI on risk of rheumatic disease, and sex-specific effects were identified. Analyses were performed in 361,952 participants from the UK Biobank cohort for 5 rheumatic diseases: rheumatoid arthritis (n = 8,381 cases), osteoarthritis (n = 87,430), psoriatic arthropathy (n = 933), gout (n = 13,638), and inflammatory spondylitis (n = 4,328). RESULTS: Using linear MR, we found that 1 SD increase in BMI increases the incidence rate for rheumatoid arthritis (incidence rate ratio [IRR] 1.52 [95% confidence interval (95% CI) 1.36-1.69]), osteoarthritis (IRR 1.49 [95% CI 1.43-1.55]), psoriatic arthropathy (IRR 1.80 [95% CI 1.31-2.48]), gout (IRR 1.73 [95% CI 1.56-1.92]), and inflammatory spondylitis (IRR 1.34 [95% CI 1.14-1.57]) in all individuals. BMI was found to be a stronger risk factor in women compared to men for psoriatic arthropathy (P for sex interaction = 3.3 × 10-4 ) and gout (P for sex interaction = 4.3 × 10-3 ), and the effect on osteoarthritis was stronger in premenopausal compared to postmenopausal women (P = 1.8 × 10-3 ). Nonlinear effects of BMI were identified for osteoarthritis and gout in men, and for gout in women. The nonlinearity for gout was also more extreme in men compared to women (P = 0.03). CONCLUSION: Higher BMI causes an increased risk for rheumatic disease, an effect that is more pronounced in women for both gout and psoriatic arthropathy. The novel sex- and BMI-specific causal effects identified here provide further insight into rheumatic disease etiology and mark an important step toward personalized medicine.

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.

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.

Precision medicine in complex diseases-Molecular subgrouping for improved prediction and treatment stratification.

Complex diseases are caused by a combination of genetic, lifestyle, and environmental factors and comprise common noncommunicable diseases, including allergies, cardiovascular disease, and psychiatric and metabolic disorders. More than 25% of Europeans suffer from a complex disease, and together these diseases account for 70% of all deaths. The use of genomic, molecular, or imaging data to develop accurate diagnostic tools for treatment recommendations and preventive strategies, and for disease prognosis and prediction, is an important step toward precision medicine. However, for complex diseases, precision medicine is associated with several challenges. There is a significant heterogeneity between patients of a specific disease-both with regards to symptoms and underlying causal mechanisms-and the number of underlying genetic and nongenetic risk factors is often high. Here, we summarize precision medicine approaches for complex diseases and highlight the current breakthroughs as well as the challenges. We conclude that genomic-based precision medicine has been used mainly for patients with highly penetrant monogenic disease forms, such as cardiomyopathies. However, for most complex diseases-including psychiatric disorders and allergies-available polygenic risk scores are more probabilistic than deterministic and have not yet been validated for clinical utility. However, subclassifying patients of a specific disease into discrete homogenous subtypes based on molecular or phenotypic data is a promising strategy for improving diagnosis, prediction, treatment, prevention, and prognosis. The availability of high-throughput molecular technologies, together with large collections of health data and novel data-driven approaches, offers promise toward improved individual health through precision medicine.

An atlas of genetic scores to predict multi-omic traits.

The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics1. Here we examine a large cohort (the INTERVAL study2; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores.

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.

Building a precision medicine infrastructure at a national level: The Swedish experience.

Precision medicine has the potential to transform healthcare by moving from one-size-fits-all to personalised treatment and care. This transition has been greatly facilitated through new high-throughput sequencing technologies that can provide the unique molecular profile of each individual patient, along with the rapid development of targeted therapies directed to the Achilles heels of each disease. To implement precision medicine approaches in healthcare, many countries have adopted national strategies and initiated genomic/precision medicine initiatives to provide equal access to all citizens. In other countries, such as Sweden, this has proven more difficult due to regionally organised healthcare. Using a bottom-up approach, key stakeholders from academia, healthcare, industry and patient organisations joined forces and formed Genomic Medicine Sweden (GMS), a national infrastructure for the implementation of precision medicine across the country. To achieve this, Genomic Medicine Centres have been established to provide regionally distributed genomic services, and a national informatics infrastructure has been built to allow secure data handling and sharing. GMS has a broad scope focusing on rare diseases, cancer, pharmacogenomics, infectious diseases and complex diseases, while also providing expertise in informatics, ethical and legal issues, health economy, industry collaboration and education. In this review, we summarise our experience in building a national infrastructure for precision medicine. We also provide key examples how precision medicine already has been successfully implemented within our focus areas. Finally, we bring up challenges and opportunities associated with precision medicine implementation, the importance of international collaboration, as well as the future perspective in the field of precision medicine.