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Alzheimer's disease (AD)-a complex disease showing multiple pathomechanistic alterations-is triggered by nonlinear dynamic interactions of genetic/epigenetic and environmental risk factors, which, ultimately, converge into a biologically heterogeneous disease. To tackle the burden of AD during early preclinical stages, accessible blood-based biomarkers are currently being developed. Specifically, next-generation clinical trials are expected to integrate positive and negative predictive blood-based biomarkers into study designs to evaluate, at the individual level, target druggability and potential drug resistance mechanisms. In this scenario, systems biology holds promise to accelerate validation and qualification for clinical trial contexts of use-including proof-of-mechanism, patient selection, assessment of treatment efficacy and safety rates, and prognostic evaluation. Albeit in their infancy, systems biology-based approaches are poised to identify relevant AD "signatures" through multifactorial and interindividual variability, allowing us to decipher disease pathophysiology and etiology. Hopefully, innovative biomarker-drug codevelopment strategies will be the road ahead towards effective disease-modifying drugs.
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Background: Elevated serum uric acid (sUA) is associated with heart failure (HF). Hypothesis: Urate‐lowering therapy (ULT) in HF is associated with lower risk of HF hospitalization (hHF) and mortality. Methods: Data on patients with HF and gout or hyperuricemia in the Clinical Practice Research Datalink database linked to the Hospital Episode Statistics and the Office for National Statistics in the United Kingdom were analyzed. Risks of hHF and all‐cause mortality or cardiovascular‐related mortality by ULT exposure (ULT initiated within ≤6 months of gout or hyperuricemia diagnosis) were analyzed in a propensity score‐matched cohort using adjusted Cox proportional hazards regression models. Results: Of 2174 propensity score‐matched pairs, patients were predominantly male, aged >70 years, with mean ± standard deviation sUA 9.3 ± 1.8 (ULT‐exposed) and 9.4 ± 1.9 mg/dL (ULT‐unexposed). At 5 years, ULT‐exposed patients had a 43% lower risk of hHF or all‐cause mortality (adjusted hazard ratio [HR]: 0.57; 95% confidence interval [CI]: 0.51–0.65) and a 19% lower risk of hHF or cardiovascular‐related mortality (adjusted HR: 0.81; 95% CI: 0.71–0.92) versus no ULT exposure. Conclusion: ULT was associated with reduced risk of adverse clinical outcomes in patients with HF and gout or hyperuricemia over 5 years. Practitioner points: Raised serum uric acid is strongly associated with heart failure (HF); however, it is unknown whether urate‐lowering therapy (ULT) could help patients with HF.We assessed the relationship between ULT and HF outcomes using UK patient data, and found that the risk of the composite of hospital admission for HF or death was lower with ULT than with no ULT.These results support further investigation into the potential benefit of ULT in HF. [ABSTRACT FROM AUTHOR]

BackgroundMeasures of neocortical amyloid burden (NAB) identify individuals who are at substantially greater risk of developing Alzheimer's disease (AD). Blood-based biomarkers predicting NAB would have great utility for the enrichment of AD clinical trials, including large-scale prevention trials.MethodsNontargeted proteomic discovery was applied to 78 subjects from the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing with a range of NAB values. Technical and independent replications were performed by immunoassay.ResultsSeventeen discovery candidates were selected for technical replication. α2-Macroglobulin, fibrinogen γ-chain (FGG), and complement factor H-related protein 1 were confirmed to be associated with NAB. In an independent cohort, FGG plasma levels combined with age predicted NAB had a sensitivity of 59% and specificity of 78%.ConclusionA single blood protein, FGG, combined with age, was shown to relate to NAB and therefore could have potential for enrichment of clinical trial populations.

Background: Electronic healthcare records (EHR) are increasingly used in epidemiological studies but are often viewed as lacking quality compared to randomised control trials and prospective cohorts. Studies of patients with chronic obstructive pulmonary disease (COPD) often use the rate of forced expiratory volume in 1 second (FEV1) decline as an outcome; however, its definition and robustness in EHR have not been investigated. We aimed to investigate how the rate of FEV1 decline differs by the criteria used in an EHR database. Methods: Clinical Practice Research Datalink and Hospital Episode Statistics were used. Patient populations were defined using 8 sets of criteria around repeated FEV1 measurements. At a minimum, patients had a diagnosis of COPD, were ≥ 35 years old, were current or ex-smokers, and had data recorded from 2004. FEV1 measurements recorded during follow-up were identified. Thereafter, eight populations were defined based on criteria around: i) the exclusion of patients or individual measurements with potential measurement error; ii) minimum number of FEV1 measurements; iii) minimum time interval between measurements; iv) specific timing of measurements; v) minimum follow-up time; and vi) the use of linked data. For each population, the rate of FEV1 decline was estimated using mixed linear regression. Results: For 7/8 patient populations, rates of FEV1 decline (age and sex adjusted) were similar and ranged from − 18.7mL/year (95% CI − 19.2 to − 18.2) to − 16.5mL/year (95% CI − 17.3 to − 15.7). Rates of FEV1 decline in populations that excluded patients with potential measurement error ranged from − 79.4mL/year (95% CI − 80.7 to − 78.2) to − 46.8mL/year (95% CI − 47.6 to − 46.0). Conclusion: FEV1 decline remained similar in a COPD population regardless of number of FEV1 measurements, time intervals between measurements, follow-up period, exclusion of specific FEV1 measurements, and linkage to HES. However, exclusion of individuals with questionable data led to selection bias and faster rates of decline. [ABSTRACT FROM AUTHOR]

In this exploratory neuroimaging-proteomic study, we aimed to identify CSF proteins associated with AD and test their prognostic ability for disease classification and MCI to AD conversion prediction. Our study sample consisted of 295 subjects with CSF multi-analyte panel data and MRI at baseline downloaded from ADNI. Firstly, we tested the statistical effects of CSF proteins (n = 83) to measures of brain atrophy, CSF biomarkers, ApoE genotype and cognitive decline. We found that several proteins (primarily CgA and FABP) were related to either brain atrophy or CSF biomarkers. In relation to ApoE genotype, a unique biochemical profile characterised by low CSF levels of Apo E was evident in ε4 carriers compared to ε3 carriers. In an exploratory analysis, 3/83 proteins (SGOT, MCP-1, IL6r) were also found to be mildly associated with cognitive decline in MCI subjects over a 4-year period. Future studies are warranted to establish the validity of these proteins as prognostic factors for cognitive decline. For disease classification, a subset of proteins (n = 24) combined with MRI measurements and CSF biomarkers achieved an accuracy of 95.1% (Sensitivity 87.7%; Specificity 94.3%; AUC 0.95) and accurately detected 94.1% of MCI subjects progressing to AD at 12 months. The subset of proteins included FABP, CgA, MMP-2, and PPP as strong predictors in the model. Our findings suggest that the marker of panel of proteins identified here may be important candidates for improving the earlier detection of AD. Further targeted proteomic and longitudinal studies would be required to validate these findings with more generalisability. [ABSTRACT FROM AUTHOR]

Rate of FEV1 decline in COPD is heterogeneous and the extent to which inhaled corticosteroids (ICS) influence the rate of decline is unclear. The majority of previous reviews have investigated specific ICS and non-ICS inhalers and have consisted of randomised control trials (RCTs), which have specific inclusion and exclusion criteria and short follow up times. We aimed to investigate the association between change in FEV1 and ICS-containing medications in COPD patients over longer follow up times.MEDLINE and EMBASE were searched and literature comparing change in FEV1 in COPD patients taking ICS-containing medications with patients taking non-ICS-containing medications were identified. Titles, abstract, and full texts were screened and information extracted using the PICO checklist. Risk of bias was assessed using the Cochrane Risk of Bias tool and a descriptive synthesis of the literature was carried out due to high heterogeneity of included studies.Seventeen studies met our inclusion criteria. We found that the difference in change in FEV1 in people using ICS and non-ICS containing medications depended on the study follow-up time. Shorter follow-up studies (1 year or less) were more likely to report an increase in FEV1 from baseline in both patients on ICS and in patients on non-ICS-containing medications, with the majority of these studies showing a greater increase in FEV1 in patients on ICS-containing medications. Longer follow-up studies (greater than 1 year) were more likely to report a decline in FEV1 from baseline in patients on ICS and in patients on non-ICS containing medications but rates of FEV1 decline were similar.Further studies are needed to better understand changes in FEV1 when ICS-containing medications are prescribed and to determine whether ICS-containing medications influence rate of decline in FEV1 in the long term. Results from inclusive trials and observational patient cohorts may provide information more generalisable to a population of COPD patients. [ABSTRACT FROM AUTHOR]

Background: Electronic healthcare records (EHR) are increasingly used in epidemiological studies but are often viewed as lacking quality compared to randomised control trials and prospective cohorts. Studies of patients with chronic obstructive pulmonary disease (COPD) often use the rate of forced expiratory volume in 1 second (FEV 1 ) decline as an outcome; however, its definition and robustness in EHR have not been investigated. We aimed to investigate how the rate of FEV 1 decline differs by the criteria used in an EHR database., Methods: Clinical Practice Research Datalink and Hospital Episode Statistics were used. Patient populations were defined using 8 sets of criteria around repeated FEV 1 measurements. At a minimum, patients had a diagnosis of COPD, were ≥35 years old, were current or ex-smokers, and had data recorded from 2004. FEV 1 measurements recorded during follow-up were identified. Thereafter, eight populations were defined based on criteria around: i) the exclusion of patients or individual measurements with potential measurement error; ii) minimum number of FEV 1 measurements; iii) minimum time interval between measurements; iv) specific timing of measurements; v) minimum follow-up time; and vi) the use of linked data. For each population, the rate of FEV 1 decline was estimated using mixed linear regression., Results: For 7/8 patient populations, rates of FEV 1 decline (age and sex adjusted) were similar and ranged from -18.7mL/year (95% CI -19.2 to -18.2) to -16.5mL/year (95% CI -17.3 to -15.7). Rates of FEV 1 decline in populations that excluded patients with potential measurement error ranged from -79.4mL/year (95% CI -80.7 to -78.2) to -46.8mL/year (95% CI -47.6 to -46.0)., Conclusion: FEV 1 decline remained similar in a COPD population regardless of number of FEV 1 measurements, time intervals between measurements, follow-up period, exclusion of specific FEV 1 measurements, and linkage to HES. However, exclusion of individuals with questionable data led to selection bias and faster rates of decline., Competing Interests: HW reports grants from GSK, AZ, and BI, outside the submitted work; SK reports grants from Medical Research Council, during the conduct of the study; personal fees from Roche Diagnostics, personal fees from DIADEM, personal fees from AstraZeneca, outside the submitted work; JQ reports grants from British Lung Foundation and personal fees from AZ, Asthma UK, BI, Bayer, GSK, MRC, and Chiesi, outside the submitted work. The authors report no other conflicts of interest in this work., (© 2021 Whittaker et al.)

Accelerated lung function decline has been associated with increased risk of cardiovascular disease (CVD) in a general population, but little is known about this association in chronic obstructive pulmonary disease (COPD). We investigated the association between accelerated lung function decline and CVD outcomes and mortality in a primary care COPD population.COPD patients without a history of CVD were identified in the Clinical Practice Research Datalink (CPRD)-GOLD primary care dataset (n=36 382). Accelerated decline in forced expiratory volume in 1 s (FEV 1 ) was defined using the fastest quartile of the COPD population's decline. A Cox regression was used to assess the association between baseline accelerated FEV 1 decline and a composite CVD outcome over follow-up (myocardial infarction, ischaemic stroke, heart failure, atrial fibrillation, coronary artery disease and CVD mortality). The model was adjusted for age, sex, smoking status, body mass index, history of asthma, hypertension, diabetes, statin use, Modified Medical Research Council (mMRC) dyspnoea score, exacerbation frequency and baseline FEV 1 % predicted.6110 COPD patients (16.8%) had a CVD event during follow-up; median length of follow-up was 3.6 years (interquartile range (IQR) 1.7-6.1 years). Median rate of FEV 1 decline was -19.4 mL·year -1 (IQR -40.5-1.9); 9095 patients (25%) had accelerated FEV 1 decline (> -40.5 mL·year -1 ), 27 287 (75%) did not (≤ -40.5 mL·year -1 ). Risk of CVD and mortality was similar between patients with and without accelerated FEV 1 decline (HR adj 0.98, 95% CI 0.90-1.06). Corresponding risk estimates were 0.99 (95% CI 0.83-1.20) for heart failure, 0.89 (95% CI 0.70-1.12) for myocardial infarction, 1.01 (95% CI 0.82-1.23) for stroke, 0.97 (95% CI 0.81-1.15) for atrial fibrillation, 1.02 (95% CI 0.87-1.19) for coronary artery disease and 0.94 (95% CI 0.71-1.25) for CVD mortality. Rather, risk of CVD was associated with a mMRC score ≤2 and two or more exacerbations in the year prior.CVD outcomes and mortality were associated with exacerbation frequency and severity and increased mMRC dyspnoea score but not with accelerated FEV 1 decline., Competing Interests: Conflict of interest: H.R. Whittaker reports grants from GSK, AstraZeneca and BI, outside the submitted work. Conflict of interest: C. Bloom reports funding from AstraZeneca, Chiesi and Asthma UK, outside the submitted work. Conflict of interest: A. Morgan has nothing to disclose. Conflict of interest: D. Jarvis reports grants from the European Union and Cystic Fibrosis Trust, outside the submitted work. Conflict of interest: S.J. Kiddle reports grants from the Medical Research Council (grant number MR/P021573/1), during the conduct of the study; and personal fees from Roche Diagnostics and DIADEM, outside the submitted work. Conflict of interest: J.K. Quint reports grants from the British Lung Foundation, during the conduct of the study; grants and personal fees from AstraZeneca, BI, Bayer and GSK, and grants from Asthma UK, the Medical Research Council and Chiesi, outside the submitted work., (Copyright ©ERS 2021.)

Background: Inhaled corticosteroid (ICS)-containing medications slow rate of decline of FEV 1 . Blood eosinophil (EOS) levels are associated with the degree of exacerbation reduction with ICS. Purpose: We investigated whether FEV 1 decline differs between patients with and without ICS, stratified by blood EOS level. Patients and methods: The UK Clinical Practice Research Datalink (primary care records) and Hospital Episode Statistics (hospital records) were used to identify COPD patients aged 35 years or older, who were current or ex-smokers with ≥2 FEV 1 measurements ≥6 months apart. Prevalent ICS use and the nearest EOS count to start of follow-up were identified. Patients were classified at baseline as higher stratum EOS (≥150 cell/µL) on ICS; higher stratum EOS not on ICS; lower stratum EOS (<150 cells/µL) on ICS; and lower stratum EOS not on ICS. In addition, an incident ICS cohort was used to investigate the rate of FEV 1 change by EOS and incident ICS use. Mixed-effects linear regression was used to compare rates of FEV 1 change in mL/year. Results: A total of 26,675 COPD patients met our inclusion criteria (median age 69, 46% female). The median duration of follow up was 4.2 years. The rate of FEV 1 change in prevalent ICS users was slower than non-ICS users (-12.6 mL/year vs -21.1 mL/year; P  =0.001). The rate of FEV 1 change was not significantly different when stratified by EOS level. The rate of FEV 1 change in incident ICS users increased (+4.2 mL/year) vs -21.2 mL/year loss in non-ICS users; P <0.001. In patients with high EOS, incident ICS patients showed an increase in FEV 1 (+12 mL/year) compared to non-ICS users whose FEV 1 decreased (-20.8 mL/year); P <0.001. No statistical difference was seen in low EOS patients. Incident ICS use is associated with an improvement in FEV 1 change, however, over time this association is lost. Conclusion: Regardless of blood EOS level, prevalent ICS use is associated with slower rates of FEV 1 decline in COPD., Competing Interests: Miss Whittaker reports grants from GlaxoSmithKline, during the conduct of the study; Dr Müllerova was employed by and reported personal fees from GlaxoSmithKline, during the conduct of the study; Dr Jarvis reports grants from European Union and Cystic Fibrosis Trust, outside the submitted work; she also reports grants from GlaxoSmithKline, during the conduct of the study. Dr Barnes is employed, holds shares and reports personal fees from GlaxoSmithKline, outside the submitted work; he also received grants from GlaxoSmithKline, during the conduct of the study. Dr Jones is employed by and reports personal fees from GlaxoSmithKline, during the conduct of the study; Dr Compton is employed, holds shares and reports personal fees from GlaxoSmithKline, during the conduct of the study; Dr Kiddle reports grants from MRC, during the conduct of the study; grants from Roche Diagnostics, Engineering and Physical Sciences Research Council, Biotechnology and Biological Sciences Research Council, National Institute for Health Research, Alzheimer’s Society, Eli Lily, and Jannsen, outside the submitted work; Dr Kiddle was supported by a MRC Career Development Award (MR/PO21573/1). Dr Quint reports grants from GlaxoSmithKline, during the conduct of the study; grants from The Health Foundation, MRC, Wellcome Trust, British Lung Foundation, Insmed, AstraZeneca, Bayer, Boehringer Ingelheim, Chiesi, Teva, and GlaxoSmithKline, outside the submitted work. The authors report no other conflicts of interest in this work.

Background: Blood biomarkers may aid in recruitment to clinical trials of Alzheimer's disease (AD) modifying therapeutics by triaging potential trials participants for amyloid positron emission tomography (PET) or cerebrospinal fluid (CSF) Aβ and tau tests. Objective: To discover a plasma proteomic signature associated with CSF and PET measures of AD pathology. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) based proteomics were performed in plasma from participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD, recruited to the Amsterdam Dementia Cohort, stratified by CSF Tau/Aβ 42 ( n = 50). Technical replication and independent validation were performed by immunoassay in plasma from SCD, MCI, and AD participants recruited to the Amsterdam Dementia Cohort with CSF measures ( n = 100), MCI participants enrolled in the GE067-005 study with [ 18 F]-Flutemetamol PET amyloid measures ( n = 173), and AD, MCI and cognitively healthy participants from the EMIF 500 study with CSF Aβ 42 measurements ( n = 494). Results: 25 discovery proteins were nominally associated with CSF Tau/Aβ 42 ( P < 0.05) with associations of ficolin-2 (FCN2), apolipoprotein C-IV and fibrinogen β chain confirmed by immunoassay ( P < 0.05). In the GE067-005 cohort, FCN2 was nominally associated with PET amyloid ( P < 0.05) replicating the association with CSF Tau/Aβ 42 . There were nominally significant associations of complement component 3 with PET amyloid, and apolipoprotein(a), apolipoprotein A-I, ceruloplasmin, and PPY with MCI conversion to AD (all P < 0.05). In the EMIF 500 cohort FCN2 was trending toward a significant relationship with CSF Aβ 42 ( P ≈ 0.05), while both A1AT and clusterin were nominally significantly associated with CSF Aβ 42 (both P < 0.05). Conclusion: Associations of plasma proteins with multiple measures of AD pathology and progression are demonstrated. To our knowledge this is the first study to report an association of FCN2 with AD pathology. Further testing of the proteins in larger independent cohorts will be important.