Pfizer (Sweden)

Abstract The Pharma Proteomics Project is a precompetitive biopharmaceutical consortium characterizing the plasma proteomic profiles of 54,219 UK Biobank participants. Here we provide a detailed summary of this initiative, including technical and biological validations, insights into proteomic disease signatures, and prediction modelling for various demographic and health indicators. We present comprehensive protein quantitative trait locus (pQTL) mapping of 2,923 proteins that identifies 14,287 primary genetic associations, of which 81% are previously undescribed, alongside ancestry-specific pQTL mapping in non-European individuals. The study provides an updated characterization of the genetic architecture of the plasma proteome, contextualized with projected pQTL discovery rates as sample sizes and proteomic assay coverages increase over time. We offer extensive insights into trans pQTLs across multiple biological domains, highlight genetic influences on ligand–receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug discovery by extending the genetic proxied effects of protein targets, such as PCSK9, on additional endpoints, and disentangle specific genes and proteins perturbed at loci associated with COVID-19 susceptibility. This public–private partnership provides the scientific community with an open-access proteomics resource of considerable breadth and depth to help to elucidate the biological mechanisms underlying proteo-genomic discoveries and accelerate the development of biomarkers, predictive models and therapeutics 1 .

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.

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.

BACKGROUND: Hypopituitary patients with untreated GH deficiency and patients on inappropriately high doses of glucocorticoid (GC) share certain clinical features. OBJECTIVE: The aim of the study was to examine the influence of GC substitution on clinical characteristics in hypopituitary patients before and after GH replacement therapy. METHOD: A total of 2424 hypopituitary patients within the KIMS (Pfizer International Metabolic Database) were grouped according to ACTH status. Comparisons were performed between subjects on hydrocortisone (HC) (n = 1186), cortisone acetate (CA) (n = 487), and prednisolone/dexamethasone (n = 52), and ACTH-sufficient patients (AS) (n = 717) before and after 1 yr of GH treatment in terms of body mass index, waist and hip circumference, blood pressure, glucose, glycosylated hemoglobin (HbA1c), serum lipids, IGF-I, and comorbidity. Hydrocortisone equivalent (HCeq) doses were calculated, and measurements were adjusted for sex and age. RESULTS: At baseline, the HC group had increased total cholesterol, triglycerides, waist circumference, and HbA1c, and the prednisolone/dexamethasone group had increased waist/hip ratio as compared with AS. After HCeq dose adjustment, the HC group retained higher HbA1c than the CA group. GC-treated patients showed a dose-related increase in serum IGF-I, body mass index, triglycerides, low-density lipoprotein cholesterol and total cholesterol levels. Subjects with HCeq doses less than 20 mg/d (n = 328) at baseline did not differ from AS in metabolic endpoints. The 1-yr metabolic response to GH was similar in all GC groups and dose categories. All new cases of diabetes (n = 12), stroke (n = 8), and myocardial infarction (n = 3) during GH treatment occurred in GC-treated subjects. CONCLUSION: HCeq doses of at least 20 mg/d in adults with hypopituitarism are associated with an unfavorable metabolic profile. CA replacement may have metabolic advantages compared with other GCs.

CONTEXT: Pegvisomant is a GH receptor antagonist. The ACROSTUDY is a global safety surveillance study of long-term treatment of acromegaly with pegvisomant. OBJECTIVE: The objective of the study was to monitor long-term safety and treatment outcomes. DESIGN: ACROSTUDY is open to all patients with acromegaly who are treated with pegvisomant. We report an interim analysis of data captured from 1288 subjects enrolled before a database freeze of December 31, 2009. SETTING: This was a global noninterventional surveillance study. MAIN OUTCOME MEASURE(S): Long-term monitoring of safety, including central magnetic resonance imaging (MRI) reading and treatment outcomes, was measured. RESULTS: Subjects (n = 1288) were treated with pegvisomant for a mean of 3.7 yr and followed up in ACROSTUDY for a mean of 2.1 yr. A total of 1147 adverse events (AE) were recorded in 477 subjects (37%), among which 192 AE in 124 subjects (9.6%) were considered to be related to pegvisomant. Serious AE were recorded in 159 subjects (12.3%), whereas pegvisomant-related Serious AE were recorded in 26 subjects (2%). No deaths (15 subjects; 1.2%) were attributed to pegvisomant use. The incidence of increase in pituitary tumor size in the subset with confirmed MRI increases on central reading represented 3.2% of the overall cohort with at least two available MRI (n = 936). Injection-site reactions were reported in 28 cases (2.2%). In 30 patients (2.5%), an elevated aspartate aminotransferase or alanine aminotransferase of more than 3 times the upper level of normality was reported. There were no reports of liver failure. After 5 yr of pegvisomant treatment, 63.2% of subjects had normal IGF-I levels at a mean dose of 18 mg/d. CONCLUSIONS: Data entered and evaluated in ACROSTUDY indicate that pegvisomant is an effective and safe medical treatment in patients with acromegaly. The reported low incidence of pituitary tumor size increase, liver enzyme elevations, and lipodystrophy at the injection site are reassuring.

BACKGROUND: The secreted protein proprotein convertase subtilisin/kexin type 9 (PCSK9) is a promising new target for lowering plasma low-density lipoprotein cholesterol and preventing cardiovascular disease (CVD). The relationship between circulating PCSK9 and incident CVD in the general population is unknown. We investigated whether serum PCSK9 concentration is associated with incident CVD in a prospective cohort study of 4232 men and women 60 years of age at the time of recruitment. METHODS AND RESULTS: Incident CVD was recorded by matching to national registries. After 15 years of follow-up, a total of 491 incident events (fatal and nonfatal myocardial infarctions, unstable angina, deaths from coronary heart disease, fatal and nonfatal ischemic strokes) were recorded. Cox proportional hazards model was used to calculate hazard ratios with 95% confidence intervals. Baseline serum PCSK9 concentration predicted incident CVD; concentration in quartile 4 compared with quartile 1 was associated with a hazard ratio of 1.69 (95% confidence interval, 1.30-2.19) after adjustment for sex. Further adjustment for low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, lipoprotein(a), triglycerides, hypertension, diabetes mellitus, smoking, overweight, obesity, physical inactivity, and statin use resulted in a decrease in the hazard ratio to 1.48 (95% confidence interval, 1.12-1.95). CONCLUSIONS: Serum PCSK9 concentration is associated with future risk of CVD even after adjustments for established CVD risk factors. Further studies are needed to confirm this observation.

CONTEXT: Treatment with GH has been used to correct the growth deficit in children with GH deficiency (GHD). Although successful in increasing height velocity, such treatment often falls short of helping patients achieve full genetic height potential. OBJECTIVE: This study set out to analyze near-final height (FH) data from a cohort of GH-treated children with idiopathic GHD. DESIGN, SETTING, AND PARTICIPANTS: Of 1258 evaluable patients in the Pfizer International Growth Database (KIGS) with GHD, 980 were of Caucasian origin, and 278 were of Japanese origin; 747 had isolated GHD (IGHD), and 511 had multiple pituitary hormone deficiencies (MPHD). MAIN OUTCOME MEASURES: Near-FH, relation to midparental height, and factors predictive of growth outcomes were the main outcome measures. RESULTS: Median height sd scores (SDS) at the start of treatment were -2.4 (IGHD) and -2.9 (MPHD) for Caucasian males and -2.6 (IGHD) and -3.4 (MPHD) for females, respectively; comparable starting heights were -2.9 (IGHD) and -3.6 (MPHD) for Japanese males and -3.3 (IGHD) and -4.0 (MPHD) for females, respectively. Corresponding near-adult height SDS after GH treatment were -0.8 (IGHD) and -0.7 (MPHD) for Caucasian males and -1.0 (IGHD) and -1.1 (MPHD) for females, respectively; and -1.6 (IGHD) and -1.9 (MPHD) for Japanese males and -2.1 (IGHD) and -1.8 (MPHD) for females, respectively. Differences between near-adult height and midparental height ranged between -0.6 and +0.2 SDS for the various groups, with the closest approximation to MPH occurring in Japanese males with MPHD. The first-year increase in height SDS and prepubertal height gain was highly correlated with total height gain, confirming the importance of treatment before pubertal onset. CONCLUSIONS: It is possible to achieve FH within the midparental height range in patients with idiopathic GHD treated from an early age with GH, but absolute height outcomes remain in the lower part of the normal range. Patients with MPHD generally had a slightly better long-term height outcome.

CONTEXT: Patients with hypopituitarism have an increased standardized mortality rate. The basis for this has not been fully clarified. OBJECTIVE: To investigate in detail the cause of death in a large cohort of patients with hypopituitarism subjected to long-term follow-up. DESIGN AND METHODS: All-cause and cause-specific mortality in 1286 Swedish patients with hypopituitarism prospectively monitored in KIMS (Pfizer International Metabolic Database) 1995-2009 were compared to general population data in the Swedish National Cause of Death Registry. In addition, events reported in KIMS, medical records, and postmortem reports were reviewed. MAIN OUTCOME MEASURES: Standardized mortality ratios (SMR) were calculated, with stratification for gender, attained age, and calendar year during follow-up. RESULTS: An excess mortality was found, 120 deaths vs 84.3 expected, SMR 1.42 (95% confidence interval: 1.18-1.70). Infections, brain cancer, and sudden death were associated with significantly increased SMRs (6.32, 9.40, and 4.10, respectively). Fifteen patients, all ACTH-deficient, died from infections. Eight of these patients were considered to be in a state of adrenal crisis in connection with death (medical reports and post-mortem examinations). Another 8 patients died from de novo malignant brain tumors, 6 of which had had a benign pituitary lesion at baseline. Six of these 8 subjects had received prior radiation therapy. CONCLUSION: Two important causes of excess mortality were identified: first, adrenal crisis in response to acute stress and intercurrent illness; second, increased risk of a late appearance of de novo malignant brain tumors in patients who previously received radiotherapy. Both of these causes may be in part preventable by changes in the management of pituitary disease.

Delays in the diagnosis of Alzheimer's disease, and, therefore, delays in treatment, may have a detrimental effect on a patient's long-term well-being. This study assessed the effects of postponing donepezil treatment for 1 year by comparing patients treated continuously for 3 years with those who received placebo for 1 year followed by open-label donepezil for 2 years. Patients (n = 286) with possible or probable Alzheimer's disease (according to DSM-IV, NINCDS-ADRDA, and Mini-Mental State Examination criteria; see text) were randomized to receive donepezil (5 mg/day for 4 weeks, 10 mg/day thereafter) or placebo (delayed-start group) for 1 year. Of the 192 completers, 157 began a 2-year, open-label phase of donepezil treatment. Outcome measures were the Gottfries-Bråne-Steen scale, the Mini-Mental State Examination, the Global Deterioration Scale, the Progressive Deterioration Scale, the Neuropsychiatric Inventory, and safety (adverse events). Mixed regression analysis was used to compare changes between the groups over 3 years on the efficacy measures. There was a trend for patients receiving continuous therapy to have less global deterioration (Gottfries-Bråne-Steen scale) than those who had delayed treatment (p = 0.056). Small but statistically significant differences between the groups were observed for the secondary measures of cognitive function (Mini-Mental State Examination; p = 0.004) and cognitive and functional abilities (Global Deterioration Scale; p = 0.0231) in favor of continuous donepezil therapy. Over 90% of the patients in both cohorts experienced one treatment-emergent adverse event; most were considered mild or moderate. In conclusion, patients in whom the start of treatment is delayed may demonstrate slightly reduced benefits as compared with those seen in patients starting donepezil therapy early in the course of Alzheimer's disease. These data support the long-term efficacy and safety of donepezil.

The interdisciplinary Biofilm Nobel conference aimed not only to cover recent progress in this research area, but also to bridge basic science and clinical disciplines. As such, the conference gathered leading investigators who collectively covered the broad spectrum of biofilm research from the molecular analysis of basic phenomena to the clinical impact and the prevention of biofilm formation (http://biofilmnobelconference.org/). Broad scoping topics were thematically organized during the five keynote lectures, nine sessions, and 67 posters. From a medical perspective, these included the clinical problem of persistent infections by biofilm-forming microorganisms in device-related as well as soft tissue infection, the molecular basis of foreign body infections; biofilms and the immune system; and biofilms and cancer. Important fundamental discoveries made in basic biofilm research with respect to structure and regulation of biofilm formation were presented, along with biofilm diagnostics, bioinformatics of biofilm formation, the resistance phenotype, and prevention of biofilm formation. Various strategies to treat biofilm infections were also discussed. Although biofilm formation was observed as early as 1708 when Antonie van Leeuwenhoek investigated tissue colonized by microbes with his new, and at that time, highly powerful microscope, research on biofilm formation only began to make significant advances in the last 15–20 years with exponential growth (Table 1). It is recognized that the developmental process of biofilm formation (the association of bacteria into multicellular consortia, consisting of still autonomous cells connected by an extracellular matrix) is not only the natural mode of life of many microorganisms 1, 2, but also an important clinical pathogenic mechanism 3, 4 strengthened by the aging population, immunocompromised and olytraumatic patients, and modern medical instrumental intervention (Fig. 1). In the USA alone, it is estimated that 1.7 million hospital-acquired infections annually involve microorganisms in the biofilm state, incurring an additional $11 billion in healthcare costs (US CDC, 2007). The total annual cost for biofilm infections in the USA is unofficially estimated to be $94 billion with more than half a million deaths 5. The dimension of community acquired biofilm infections is also huge, with, e.g., US$105 billion spent on dental care alone, making dental caries and periodontitis the most prevalent biofilm-associated diseases 3. The spectrum of biofilm diseases is wide. While catheter-associated urinary tract infection (CAUTI) is the most common device-associated biofilm infection, central line-associated blood stream infections (CLABSI) and ventilator-associated pneumonia (VAP) are also of significant concern (Fig. 1). Although historically the most prominent biofilm-associated disease might be Pseudomonas aeruginosa-mediated lung infection in cystic fibrosis (CF) patients 6, soft tissue infections, e.g., diabetic foot ulcers and mucosal infections, including chronic and recurrent urinary tract infections, are main biofilm-associated diseases of today (Fig. 1). Basic science research has demonstrated that antibiotic resistance is transferred readily in biofilms. In line with this, Escherichia coli isolated from medical devices showed the highest incidence of resistance against cefuroxime and ciprofloxacin compared to isolates obtained from other body sites 7. CAUTI and prosthetic joint infections are two of the most relevant biofilm-associated foreign body infections, with great economical significance in health care 5. CAUTI, which accounts for 15% of all infections, is the second most common healthcare-associated infection in the USA, and virtually, all healthcare UTIs are associated with indwelling devices (http://www.cdc.gov/nhsn/pdfs/pscmanual/7psccauticurrent.pdf). The design of the Foley urinary tract catheter in use today has basically not changed since its invention in the 1930s. The probability that the catheter becomes infected is 1–5% per day, and after 4 weeks, nearly all patients will have high bacterial numbers in the urine 8. The high likelihood of microbial colonization arises as the Foley catheter undermines the local defense system in the urinary tract. Although there is an urgent need for catheter amelioration, until recently, there has been no development of catheters with novel design and material 8. Biofilm infections are costly. After hip or knee joint replacement, a prosthetic joint infection (PJI) with revision of the prosthesis is estimated to be $50–100 000 per patient. The PJI incidence within the first two postoperative years is 0.5–2%. As the number of arthroplasties in the USA is extrapolated to four million in 2030 from the one million in 2009 9, the incidence of PJIs will increase accordingly. Diagnosis of PJIs frequently requires approaches beyond standard microbiological tests 10. Biofilm infections are typically difficult to diagnose and recalcitrant to antimicrobial treatment. Suggested diagnostic guidelines to identify biofilm infections, therefore, consider several clinical criteria even in the presence of culture-negative samples 11, 12. The European Society for Clinical Microbiology and Infectious Diseases (ESCMID) is currently developing practical guidelines for clinical microbiologists and infectious disease specialists to diagnose some of the most common and prominent biofilm infections 13. Therefore, the identification of biological markers, which discriminate between biofilm and acute infections, will facilitate the choice of appropriate treatment including antibiotics. For example, transient lipopolysaccharide modifications are currently investigated as potential biofilm markers 14. Systematic analysis of the molecular mechanism of biofilm formation started as late as in the last 5 years of the nineteenth century (Table 1 gives a non-comprehensive overview over the milestones in biofilm research). Biofilm formation of microorganisms is now being recognized as an ancient developmental process towards multicellularity with common structural principles and regulation (Figs 2 and 3; 15, 16). With this recognition, facilitated by computer algorithms for aiding large-scale single-cell tracking and nano-resolution microscopy, biofilm formation can now be elucidated with previously unavailable temporal and spatial resolution 17, 18. The hallmarks of multicellularity, ubiquitous throughout the tree of life, include coordinated cellular behavior, division of labor between cells, and the protection from environmental stressors. Biofilm formation is characterized by the expression of an extracellular matrix, which has structural and physiological functions (Figs 2 and 3). Although differences in biofilm formation may exist even within a single strain grown under different environmental conditions, the structure and composition of the extracellular matrix follow common principles. Typically, a biofilm is composed of amyloid and adhesive fimbriae, non-fimbrial large surface proteins, exopolysaccharides, and extracellular DNA (eDNA) 19-21. Poly N-acetylglucosamine (PAG) and cellulose are common extracellular matrix polysaccharides in many phylogenetically diverse bacteria. Cellulose expression is common for gastrointestinal commensals and pathogens such as E. coli and Salmonella typhimurium, but cellulose is also a major matrix component in cyanobacterial mats and a cell wall component of some fungi 22. Identification of matrix polysaccharide composition, structure, and function is challenging. The structure of the Vibrio cholerae polysaccharide was only recently solved 22, 23, and the composition of P. aeruginosa's main matrix exopolysaccharides, Psl and Pel, is poorly understood and unknown, respectively. Structural and compositional information on biofilm matrix polysaccharides, once elucidated, can serve as targets for vaccination and biofilm infection diagnosis 25. Imprinting of the surface with exopolysaccharides before the establishment of microcolonies, the seeding units of mature biofilm structures 18, and cell differentiation, e.g., the development of hyper biofilm variants 26, 27 make biofilm formation analogous to tissue formation in higher organisms. The extracellular matrix of a biofilm features signaling properties similar to those of the multifunctional extracellular matrix of eukaryotic tissues, with extracellular molecules for communication (e.g., quorum sensing) and redox biology 20. These signaling events are continuous, bidirectional, and mediate interactions between cells in response to their immediate environment (a phenomenon known as dynamic reciprocity), just as tissue differentiation in higher organisms 28. Biofilm formation is regulated by the codon usage of biofilm genes 29, genetic factors including small RNAs 30, short secreted peptides 31, quorum sensing molecules 32, and by many environmental conditions. Although still controversial in the context of bacterial signaling 14, the presence of distinct genetic programs is required to coordinate the multicellular behavior. The most widespread globally occurring coordinated developmental program regulating biofilm formation in bacteria is the signaling network that involves the secondary messenger cyclic di-GMP 33. Cyclic di-GMP regulates the lifestyle transition between sessility and motility and, accordingly, also the transition between acute and chronic infections. This secondary messenger signaling system is very complex, involving a variety of cyclic di-GMP metabolizing enzymes and a diversity of physiological processes and reactions. These are regulated by cyclic di-GMP signaling directly and/or coupled through sophisticated molecular mechanisms that are mediated by a diversity of receptors to provide a fine-tuned output response 33-35. Cyclic di-GMP extensively crosstalks with other signaling systems such as the two-component systems 36. Cyclic di-AMP is another recently discovered novel secondary messenger molecule 37. It is responsible for coordinating stress responses and the peptidoglycan cell wall homeostasis and thereby affects biofilm formation and antibiotic resistance 38. Cyclic di-AMP has a phyletic distribution different from the cyclic di-GMP signaling system. Surprisingly, the presence of cyclic di-AMP is essential for some bacteria, although the molecular basis of cyclic di-AMP sensing molecules, proteins and RNA, is only beginning to be understood 39, 40. In summary, experimental studies of biofilms of various bacteria have revealed a great variety of signal transduction systems that control biofilm formation. At the same time, the availability of complete genome sequences allows prediction of all regulatory components in a given organism, and the subsequent identification of components that affect biofilm formation. An unexpected finding from such studies is that microbial signaling systems are far more diverse than previously thought and, furthermore, include a network of diverse sensors that transmit signals to a variety of regulatory mechanisms. One urgent task is to develop a system of genome-derived parameters that could serve as predictors of the organism's propensity to either stay motile or form a biofilm. Michael Galperin and colleagues have developed several metrics for genome comparisons, including signal protein family profiles, which reflect the abundance of each type of signal transduction protein and can be used to trace their evolution in the course of adaptation to specific ecological niches 41, 42. Besides being secondary messengers, the cyclic di-GMP and cyclic di-AMP secondary messenger molecules serve as (almost) unique microbial-associated molecular patterns (MAMPs) manipulating host responses and physiology. Listeria monocytogenes secretes cyclic di-AMP into the cytosol, triggering a type 1 interferon response that inhibits cell-mediated immunity 43. In eukaryotic cells, bacterial cyclic di-GMP and cyclic di-AMP are both sensed by the immune adaptor STING, which is not only a receptor for bacterial nucleotides, but also the intrinsic sensor of the non-canonical cyclic di-AGMP, the first and recently discovered eukaryotic cyclic di-nucleotide second messenger involved in innate immunity sensing 44, 45. Indeed, due to their unique immunostimulatory features, cyclic di-nucleotides are effective, non-toxic adjuvants 46. Cyclic di-GMP has been reported also to retard the growth of cancer cells 47. Thus, there is an immediate potential impact of biofilm research on seemingly remote research fields such as immunology and cancer biology. Biofilm formation is strongly dependent on environmental conditions. Historically, the relevance of structural and regulatory factors in biofilm formation during the infection processes has been derived from in vitro biofilm models such as adhesion to abiotic surfaces, colony morphology biofilm, pellicle formation and the widely used flow-cell system (Fig. 3). These factors are now being validated by relevant in vivo animal models, such as different foreign body infection models 48, 49. Certain bacteria selectively colonize cancer tissues 50. A surprising finding was the requirement of biofilm formation for the effective bacterial colonization of cancer tissue 51. Although the details of biofilm components required for effective tissue colonization are just emerging 52, the cancer biofilm model has the potential to serve as an in vivo model for routine screening of novel antimicrobial therapies. In addition, a determinative role of the immune response to bacterial biofilm formation in vivo has been observed 52. Current infectious diseases therapy is confronted by several challenges. Antibiotic resistance is rising rapidly, and there are relatively few novel compounds or strategies under development or under clinical testing. The intrinsic resistance of biofilm infections to antimicrobial treatment and even a competent immune system pose additional challenges. While some antibiotic agents such as rifampin have a reasonable activity against biofilm-forming cells 53, the majority of conventional antimicrobial treatment regimens are not effective against biofilms. Elucidation of the molecular mechanisms of antibiotic killing, on the one hand, and the developmental process of biofilm formation on the other have led to the identification of multiple novel points for targeted intervention strategies 121, 54. Strategies to prevent early onset of biofilm formation include manipulation of abiotic and biotic surfaces through rational surface design 55 and stimulation of the innate immune response 56, 57. Intensive screening activity for antibiofilm agents has identified compounds effective in diminishing the biofilm build-up or eradicating established biofilms. Promising antibiofilm agents include natural compounds that interfere with P. aeruginosa quorum sensing signaling 32. Pillicides and curlicides are novel compounds strategically developed against fimbriae involved in biofilm formation by E. coli causing UTIs 58. The latter compounds also reduce the formation of intracellular bacterial communities in the superficial epithelium 59 associated with chronic cystitis and recurrent infections. Lessons learned from those approaches and compounds identified might be useful also to fight biofilm formation in agricultural and technical settings, not the least derived from the fact that biofilm formation in medical settings, on plants and in technical domains shares, to some extent, common principles of adhesion and regulation [1, 33, 60, 61 ]. Systems analyses and network biology approaches have been used to study the actions of antibiotics and the mechanisms underlying the emergence of antibiotic resistance. Subsequently, different classes of bactericidal antibiotics were shown to induce alterations to central metabolism, cellular respiration, and iron homeostasis in Gram-negative and Gram-positive bacteria 62-64. These effects lead to the production of reactive oxygen species (ROS) and other damaging molecules, which ultimately contribute to antibiotic-induced cell death. Antibiotic-induced oxidative stress also causes DNA damage and can be enhanced by deletion of recA and disabling the SOS response, both involved in DNA repair. Further, engineered bacteriophages that overexpress the lexA3 allele, a non-cleavable variant of the repressor of the SOS response, enhance antibiotic-mediated killing by several orders of magnitude 65. The engineered bacteriophage can be used to restore antibiotic susceptibility to resistant strains and can be readily modified to target different gene networks. The contribution of the ROS pathway to antibiotic killing has been challenged 66; however, overall redox homeostasis is required for antibiotic resistance and cell viability 67, 68. The human innate immune system has an intrinsic capability to restrict the outgrowth of commensal and pathogenic microorganisms and, as such, is a rich source of antibiofilm agents 69. Based on observations that a cationic human host defense peptide LL-37 is able to inhibit biofilm formation and dissolve existing biofilms of P. aeruginosa 70, Hancock screened for and obtained small peptides 71, including protease-resistant variants, that have potent broad-spectrum antibiofilm properties. Importantly, antibiofilm activity was not correlative with antimicrobial activity versus planktonic (free swimming) cells 71. These novel peptides can kill multiple species of bacteria in biofilms (minimal biofilm inhibitory concentrations of >1–4 μg mL−1), including the so-called ESKAPE pathogens (multidrug-resistant strains of Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, P. aeruginosa, and Enterobacter spp.). Flow-cell biofilm observation demonstrated that these peptides can both prevent biofilm formation when added at the start of the biofilm development cycle and cause dispersal and/or death of bacteria in 2-day pre-formed biofilms. The novel peptides are able to work synergistically with several different antibiotics. Hancock proposed that these peptides work by a common mechanism in diverse bacteria and demonstrated that they are suppressing a stress response 72. While NO is a component of the innate immune system, it has also been demonstrated to act as a biofilm dispersal signal and is active against a wide range of biofilm-forming bacteria 73. NO is produced endogenously in mature biofilms and functions through the intracellular secondary messenger cyclic di-GMP, which in turn activates a range of effectors that result in biofilm dispersal 74, 75. Recently, the first cyclic di-GMP-specific phosphodiesterase was identified to be specifically involved in NO-induced dispersal in P. aeruginosa 76. Because NO induces dispersal at low, non-toxic concentrations, and its mechanism of action is broadly conserved across species, the use of NO signals represents a potentially promising strategy for biofilm control 77. NO can be delivered to biofilms by a range of means including the use of NO-donor compounds 78. NO can also be directly applied as a gas to infection sites exposed to air. Recently, the first clinical trial was conducted to evaluate the use of low-dose inhaled NO gas combined with standard intravenous antibiotic therapy for the disruption of P. aeruginosa biofilms in patients with CF. Patients who received NO gas at 10 ppm showed significant reductions in Pseudomonas biofilm aggregates and marginal improvement in lung function compared to patients who received a placebo. These results suggest that using NO as adjunctive therapy may be beneficial for the treatment of CF-related biofilm infections (Webb, Faust et al. in preparation). Due to the short half-life in biological systems, a preferred approach may be to deliver NO directly to the biofilm. An innovative new class of NO-donor prodrugs was described that can liberate NO upon specific activation by bacterial β-lactamase enzymes. These prodrugs enhance the efficacy of standard antibiotic therapies against in vitro biofilms and thus have significant clinical potential 79. Biofilms contain a high fraction of antibiotic tolerant quasi-dormant persister cells that are shielded from the immune system through the biofilm 80. Pathways leading to dormancy are highly redundant in E. coli and, potentially, in other bacteria. Induction of dormancy depends largely on the action of toxin/antitoxin modules 81, 82 where toxins function as protein synthesis inhibitors 83 and mRNA endonucleases 81, 82, 84. Further, damage of DNA induces expression of the TisB toxin 85, an endogenous antimicrobial peptide that opens an ion channel 86 causing decrease in the proton motive force (PMF) and ATP, resulting in antimicrobial target shutdown and consequently a dormant, drug-tolerant state. The multiplicity of dormancy pathways seemingly precludes development of drugs that could prevent persister formation 87, 88. However, Lewis reasoned that a compound capable of a unspecific corrupting action on a target in dormant, energy-deprived cells would kill persisters. The ClpP protease targeted by acyldepsipeptide (ADEP4) leads to non-specific activation of the enzyme independently of ATP in both growing and non-growing cells 89-91. Null clpP mutants are highly susceptible to killing by a variety of antibiotics, but resistant to ADEP4. As a consequence, the combination of ADEP4 with rifampicin eradicated persister cells in growing and biofilm populations of S. aureus in vitro. Importantly, a deep-seated biofilm infection in mice, not treatable with conventional antibiotics, could be cured. ADEP4 points to a general principle of killing by activation of a target with bacterial proteases such as Lon as additional candidate targets. Even in developing therapeutics to treat fungal infections and cancer this general principle of targeting might prove effective. Another global approach to eradicate persister cells is to target the aminoglycoside resistance of these cells. Aminoglycoside antibiotics require a threshold PMF and energy to be taken up by bacterial cells. The Collins group showed, using a network biology approach, that specific metabolic stimuli (e.g., sugars) enable the killing of Gram-negative and Gram-positive persisters with aminoglycosides 92. 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CONTEXT: Information about the expected growth response of children to GH therapy is currently inadequate. OBJECTIVES: The aim of the study was to compare observed and expected growth in response to GH in prepubertal children and to propose how these parameters can be used to optimize GH therapy. Indices considered were observed growth, observed growth relative to reference data [height sd score (Ht SDS), change in (Delta) Ht SDS, height velocity (HV)], and observed growth relative to growth predicted from prediction models [Studentized residual (SR)]. Design/Setting/Patients/Intervention: Growth data from KIGS-Pfizer International Growth Database-on prepubertal children aged 1-13 yr with severe GH deficiency (GHD; maxGH <5 microg/liter; n = 2129), with less-severe GHD (maxGH of 5-10 microg/liter; n = 3075), and with Turner syndrome (n = 2350), and short children born small for gestational age (n = 993) were analyzed before and during 2 yr of GH treatment. MAIN OUTCOME MEASURE: For each patient group, growth responses during the first 2 yr of GH treatment were established. The relationships of HV and DeltaHt SDS with SR were determined. RESULTS: Reference data were generated for assessing adequate individual responses. Responses to GH in terms of HV and DeltaHt SDS were greatest in children with severe GHD. HV and DeltaHt SDS were highly correlated with SR during only the first year of GH treatment (R approximately 0.7; P < 0.001). CONCLUSIONS: Decisions on GH therapy regimens should be made using both traditional (HV or DeltaHt SDS) and prediction model-derived (SR) indices of growth response.

OBJECTIVE: The aim of the present study was to clarify the relationship between GH deficiency (GHD) and some cardiovascular risk factors and to analyse the effect of GH replacement therapy in a large number of patients over a prolonged period of time. DESIGN: Data for analysis were retrieved from KIMS (Pfizer International Metabolic Database). Serum concentrations of total cholesterol, high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol and triglycerides were obtained from 2589 patients at baseline and from 1206 patients after 1 and 2 years of GH replacement therapy. Body mass index (BMI), waist and hip, resting blood pressure and body composition were also measured. RESULTS: At baseline, the unfavourable effects of GHD were most obvious in the lipid profile demonstrating elevated mean total and LDL-cholesterol, in the increased waist circumference and the elevated BMI. The cholesterol concentration, BMI and body composition were significantly adversely affected by a number of factors, including age, sex and the use of anti-epileptic drugs. The therapeutic effect of GH was essentially uniform across the whole population. GH replacement reduced significantly the mean total and LDL-cholesterol, the waist circumference and the fat mass and was maintained during 2 years. CONCLUSIONS: This analysis of a large number of patients confirmed that GHD adults present with an increased cardiovascular risk. The sustained improvement of the adverse lipid profile and body composition suggests that GH replacement therapy may reduce the risk of cardiovascular disease and the premature mortality seen in hypopituitary patients with untreated GHD.

OBJECTIVE: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome. We aimed to derive HFpEF phenotype-based groups ('phenogroups') based on clinical and echocardiogram data using machine learning, and to compare clinical characteristics, proteomics and outcomes across the phenogroups. METHODS: We applied model-based clustering to 32 echocardiogram and 11 clinical and laboratory variables collected in stable condition from 320 HFpEF outpatients in the Karolinska-Rennes cohort study (56% female, median 78 years (IQR: 71-83)). Baseline proteomics and the composite end point of all-cause mortality or heart failure (HF) hospitalisation were used in secondary analyses. RESULTS: We identified six phenogroups, for which significant differences in the prevalence of concomitant atrial fibrillation (AF), anaemia and kidney disease were observed (p<0.05). Fifteen out of 86 plasma proteins differed between phenogroups (false discovery rate, FDR<0.05), including biomarkers of HF, AF and kidney function. The composite end point was significantly different between phenogroups (log-rank p<0.001), at short-term (100 days), mid-term (18 months) and longer-term follow-up (1000 days). Phenogroup 2 was older, with poorer diastolic and right ventricular function and higher burden of risk factors as AF (85%), hypertension (83%) and chronic obstructive pulmonary disease (30%). In this group a third experienced the primary outcome to 100 days, and two-thirds to 18 months (HR (95% CI) versus phenogroups 1, 3, 4, 5, 6: 1.5 (0.8-2.9); 5.7 (2.6-12.8); 2.9 (1.5-5.6); 2.7 (1.6-4.6); 2.1 (1.2-3.9)). CONCLUSIONS: Using machine learning we identified distinct HFpEF phenogroups with differential characteristics and outcomes, as well as differential levels of inflammatory and cardiovascular proteins.

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. A machine learning approach is used to analyse multi-omics (proteomics, metabolomics and transcriptomics) data, producing genetic scores for more than 17,000 biomolecular traits in human blood, and identifying possible associations with disease.

OBJECTIVE: Hypopituitarism is associated with an increased mortality rate but the reasons underlying this have not been fully elucidated. The purpose of this study was to evaluate mortality and associated factors within a large GH-replaced population of hypopituitary patients. DESIGN: In KIMS (Pfizer International Metabolic Database) 13,983 GH-deficient patients with 69,056 patient-years of follow-up were available. METHODS: This study analysed standardised mortality ratios (SMRs) by Poisson regression. IGF1 SDS was used as an indicator of adequacy of GH replacement. Statistical significance was set to P<0.05. RESULTS: All-cause mortality was 13% higher compared with normal population rates (SMR, 1.13; 95% confidence interval, 1.04-1.24). Significant associations were female gender, younger age at follow-up, underlying diagnosis of Cushing's disease, craniopharyngioma and aggressive tumour and presence of diabetes insipidus. After controlling for confounding factors, there were statistically significant negative associations between IGF1 SDS after 1, 2 and 3 years of GH replacement and SMR. For cause-specific mortality there was a negative association between 1-year IGF1 SDS and SMR for deaths from cardiovascular diseases (P=0.017) and malignancies (P=0.044). CONCLUSIONS: GH-replaced patients with hypopituitarism demonstrated a modest increase in mortality rate; this appears lower than that previously published in GH-deficient patients. Factors associated with increased mortality included female gender, younger attained age, aetiology and lower IGF1 SDS during therapy. These data indicate that GH replacement in hypopituitary adults with GH deficiency may be considered a safe treatment.

Abstract The UK Biobank Pharma Proteomics Project (UKB-PPP) is a collaboration between the UK Biobank (UKB) and thirteen biopharmaceutical companies characterising the plasma proteomic profiles of 54,306 UKB participants. Here, we describe results from the first phase of UKB-PPP, including protein quantitative trait loci (pQTL) mapping of 1,463 proteins that identifies 10,248 primary genetic associations, of which 85% are newly discovered. We also identify independent secondary associations in 92% of cis and 29% of trans loci, expanding the catalogue of genetic instruments for downstream analyses. The study provides an updated characterisation of the genetic architecture of the plasma proteome, leveraging population-scale proteomics to provide novel, extensive insights into trans pQTLs across multiple biological domains. We highlight genetic influences on ligand-receptor interactions and pathway perturbations across a diverse collection of cytokines and complement proteins, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug target discovery by extending the genetic proxied effect of PCSK9 levels on lipid concentrations, cardio- and cerebro-vascular diseases, and additionally disentangle specific genes and proteins perturbed at COVID-19 susceptibility loci. This public-private partnership provides the scientific community with an open-access proteomics resource of unprecedented breadth and depth to help elucidate biological mechanisms underlying genetic discoveries and accelerate the development of novel biomarkers and therapeutics.

BACKGROUND: Several uncommon adverse effects may be related to growth hormone (GH) treatment. Three potential side effects, headache, idiopathic intracranial hypertension (IIH) and slipped capital femoral epiphysis (SCFE), will be discussed. Data from 57,968 children in the KIGS (Pfizer International Growth Study database) were analyzed to determine the effects of recombinant human GH (Genotropin) on these side effects. The diagnostic groups were idiopathic GH deficiency (IGHD) (n = 27,690), congenital GHD (CGHD) (n = 2,547), craniopharyngioma (n = 1,155), cranial tumours (n = 2,203), Turner syndrome (TS) (n = 6,092), idiopathic short stature (ISS) (n = 5,286), small for gestational age (SGA) (n = 2,973), chronic renal insufficiency (CRI) (n = 1,753) and Prader-Willi syndrome (PWS) (n = 1,368). RESULTS: Total incidence (per 100,000 treatment years) of headache was 793.5 (n = 569). The incidence was significantly higher in the groups of patients with craniopharyngiomas, CGHD and cranial tumours than in the other diagnostic groups (p < 0.05 for all). IIH occurred in 41 children resulting in a total incidence (per 100,000 treatment years) of 27.7. The incidence (per 100,000 treatment years) was significantly lower in patients with IGHD (12.2) than in those with TS (56.4) (p = 0.0004), CGHD (54.5) (p = 0.0064), PWS (68.3) (p = 0.0263) and CRI (147.8) (p < 0.001). No cases of IIH were reported in the ISS group of patients. The median duration from onset of GH therapy to IIH ranged from 0.01 to 1.3 years in various diagnostic groups. SCFE was observed in a total of 52 children resulting in a total incidence (per 100,000 treatment years) of 73.4. The incidence (per 100,000 treatment years) was significantly lower in patients with IGHD (18.3) and in those children with ISS (14.5) than in the TS (84.5), cranial tumours (86.1) and craniopharyngioma groups (120.5) (p < 0.05 for all). No cases of SCFE were reported in the SGA and PWS groups. The median duration from onset of GH therapy to SCFE ranged from 0.4 to 2.5 years. CONCLUSIONS: The incidences of IIH and SCFE in this analysis are lower than the values reported in previous KIGS analyses and comparable to other databases. Patients with TS, organic GHD, PWS and CRI seem to be more prone to these side effects.

AIM: To develop methods to identify factors associated with a favorable outcome in GH-treated children with idiopathic short stature (ISS). METHODS: From 4,685 children listed as having ISS within KIGS (Pfizer International Growth Database), we studied (a) the prediction model group (n = 657) to develop the first-year prediction model, and (b) the near adult height group (NAH; n = 256) which received GH for >4 years to develop descriptive models for adult height and overall height gain. RESULTS: NAH group at GH start: age was 10.0 years, height -2.5 SD score (SDS), weight -2.3 SDS, height minus mid-parental height (MPH) -1.5 SDS; GH dose 0.19 mg/kg/week. Height gain was 1.1 SDS at a median age of 17.2 years. Growth response correlated positively with GH dose and weight at the start of GH treatment, and negatively with age and height SDS minus MPH SDS. The model explains 39% (error SD 1.2 cm) of the variability. Adult height correlated (R(2) = 0.64) positively with height at GH start, MPH and the first-year responsiveness to GH, and negatively with age. CONCLUSIONS: Prepubertal children with ISS who show an appropriate first-year response to GH are likely to benefit from long-term treatment, even on low GH dosages.

The costs and consequences of donepezil versus placebo treatment in patients with mild to moderate Alzheimer's disease (AD) were evaluated as part of a 1-year prospective, double-blind, randomized, multinational clinical trial. Patients received either donepezil (n = 142; 5 mg/day for 28 days followed by 10 mg/day according to the clinician's judgement) or placebo (n = 144). Unit costs were assessed in 1999 Swedish kronas (SEK) and converted to US dollars (USD). Donepezil-treated patients gained functional benefits relative to placebo on the Progressive Deterioration Scale (p = 0.042) and Instrumental Activities of Daily Living scale (p = 0.025) at week 52. Caregivers of donepezil-treated patients spent an average of 400 h less annually providing care than caregivers of placebo-treated patients. Mean annual healthcare costs were SEK 137,752 (USD 16,438) per patient for the donepezil group and SEK 135,314 (USD 16,147) in the placebo group. With the average annual cost of donepezil at SEK 10,723 (USD 1,280) per patient, the SEK 2,438 (USD 291) cost difference represented a 77% cost offset. When caregiver time and healthcare costs were included, mean annual costs were SEK 209,244 (USD 24,969) per patient in the donepezil group and SEK 218,434 (USD 26,066) in the placebo group, a total saving associated with donepezil treatment of SEK 9,190 (USD 1,097) per patient [95% CI of SEK -43,959 (USD -5,246), SEK 25,581 (USD 3,053); p = 0.6]. The positive effects on the efficacy outcome measures combined with no additional costs from a societal perspective indicate that donepezil is a cost-effective treatment, representing an improved strategy for the management of patients with AD.

BACKGROUND: This retrospective register study assessed overall survival (OS) and influential factors on OS in Swedish renal cell carcinoma (RCC) patients. METHODS: Using three merged national health registers, Cox proportional-hazards analysis was conducted and, in three models, it was used to assess the impact of cytokine (interferon-α and tyrosine kinase inhibitor (TKI; sunitinib or sorafenib) treatment on OS in metastatic (m)RCC. RESULTS: From 2000 to 2008, 8009 patients were diagnosed with RCC and 2753 with mRCC (2002-2008). Median OS in RCC patients diagnosed from 2006 to 2008 compared with 2000-2005 was not reached vs 47.9 months (P<0.001), and in mRCC patients diagnosed from 2006 to 2008 compared with 2002-2005, was 12.4 vs 9.6 months, respectively (P=0.004). Factors associated with significantly improved OS in RCC were female gender, lower age, and previous nephrectomy, and, in mRCC female gender, previous nephrectomy, and any TKI prescription (Model 1: median-adjusted OS, 19.4 months (TKI patients) vs 9.7 months (non-TKI patients); hazard ratio, 0.621; P<0.001). CONCLUSION: OS was improved in Swedish patients diagnosed with RCC and mRCC in the period 2006-2008 compared with 2000-2005 (RCC) and 2002-2005 (mRCC). Although multifactorial in origin, results suggest that increased nephrectomy rates and the use of TKIs contributed to the improvement seen in mRCC patients.