Identifying therapeutic targets for cancer among 2074 circulating proteins and risk of nine cancers.

Circulating proteins can reveal key pathways to cancer and identify therapeutic targets for cancer prevention. We investigate 2,074 circulating proteins and risk of nine common cancers (bladder, breast, endometrium, head and neck, lung, ovary, pancreas, kidney, and malignant non-melanoma) using cis protein Mendelian randomisation and colocalization. We conduct additional analyses to identify adverse side-effects of altering risk proteins and map cancer risk proteins to drug targets. Here we find 40 proteins associated with common cancers, such as PLAUR and risk of breast cancer [odds ratio per standard deviation increment: 2.27, 1.88-2.74], and with high-mortality cancers, such as CTRB1 and pancreatic cancer [0.79, 0.73-0.85]. We also identify potential adverse effects of protein-altering interventions to reduce cancer risk, such as hypertension. Additionally, we report 18 proteins associated with cancer risk that map to existing drugs and 15 that are not currently under clinical investigation. In sum, we identify protein-cancer links that improve our understanding of cancer aetiology. We also demonstrate that the wider consequence of any protein-altering intervention on well-being and morbidity is required to interpret any utility of proteins as potential future targets for therapeutic prevention.

Proteomic characterization of acute kidney injury in patients hospitalized with SARS-CoV2 infection.

BACKGROUND: Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms. METHODS: Using measurements of ~4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N = 437), we identified 413 higher plasma abundances of protein targets and 30 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p < 0.05). Of these, 62 proteins were validated in an external cohort (p < 0.05, N = 261). RESULTS: We demonstrate that COVID-AKI is associated with increased markers of tubular injury (NGAL) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p < 0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2, trefoil factor 3, transmembrane emp24 domain-containing protein 10, and cystatin-C indicating tubular dysfunction and injury. CONCLUSIONS: Using clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage.

Acute kidney injury (AKI) is a sudden, sometimes fatal, episode of kidney failure or damage. It is a known complication of COVID-19, albeit through unclear mechanisms. COVID-19 is also associated with kidney dysfunction in the long term, or chronic kidney disease (CKD). There is a need to better understand which patients with COVID-19 are at risk of AKI or CKD. We measure levels of several thousand proteins in the blood of hospitalized COVID-19 patients. We discover and validate sets of proteins associated with severe AKI and CKD in these patients. The markers identified suggest that kidney injury in COVID-19 patients involves damage to kidney cells that reabsorb fluid from urine and reduced blood flow to the heart, causing damage to heart muscles. Our findings might help clinicians to predict kidney injury in patients with COVID-19, and to understand its mechanisms.

Proteomic Characterization of Acute Kidney Injury in Patients Hospitalized with SARS-CoV2 Infection.

Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms. Using measurements of ∼4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N= 437), we identified 413 higher plasma abundances of protein targets and 40 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p <0.05). Of these, 62 proteins were validated in an external cohort (p <0.05, N =261). We demonstrate that COVID-AKI is associated with increased markers of tubular injury (NGAL) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p <0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2, trefoil factor 3, transmembrane emp24 domain-containing protein 10, and cystatin-C indicating tubular dysfunction and injury. Using clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage.

Going digital: a narrative overview of the effects, quality and utility of mobile apps in chronic disease self-management.

Objective Smartphone health applications (apps) are being increasingly used to assist patients in chronic disease self-management. The effects of such apps on patient outcomes are uncertain, as are design features that maximise usability and efficacy, and the best methods for evaluating app quality and utility. Methods In assessing efficacy, PubMed, Cochrane Library and EMBASE were searched for systematic reviews (and single studies if no systematic review was available) published between January 2007 and January 2018 using search terms (and synonyms) of 'smartphone' and 'mobile applications', and terms for each of 11 chronic diseases: asthma, chronic obstructive lung disease (COPD), diabetes, chronic pain, serious mental health disorders, alcohol and substance addiction, heart failure, ischaemic heart disease, cancer, cognitive impairment, chronic kidney disease (CKD). With regard to design features and evaluation methods, additional reviews were sought using search terms 'design', 'quality,' 'usability', 'functionality,' 'adherence', 'evaluation' and related synonyms. Results Of 13 reviews and six single studies assessing efficacy, consistent evidence of benefit was seen only with apps for diabetes, as measured by decreased glycosylated haemoglobin levels (HbA1c). Some, but not all, studies showed benefit in asthma, low back pain, alcohol addiction, heart failure, ischaemic heart disease and cancer. There was no evidence of benefit in COPD, cognitive impairment or CKD. In all studies, benefits were clinically marginal and none related to morbid events or hospitalisation. Twelve design features were identified as enhancing usability. An evaluation framework comprising 32 items was formulated. Conclusion Evidence of clinical benefit of most available apps is very limited. Design features that enhance usability and maximise efficacy were identified. A provisional 'first-pass' evaluation framework is proposed that can help decide which apps should be endorsed by government agencies following more detailed technical assessments and which could then be recommended with confidence by clinicians to their patients. What is known about the topic? Smartphone health apps have attracted considerable interest from patients and health managers as a means of promoting more effective self-management of chronic diseases, which leads to better health outcomes. However, most commercially available apps have never been evaluated for benefits or harms in clinical trials, and there are currently no agreed quality criteria, standards or regulations to ensure health apps are user-friendly, accurate in content, evidence based or efficacious. What does this paper add? This paper presents a comprehensive review of evidence relating to the efficacy, usability and evaluation of apps for 11 common diseases aimed at assisting patients in self-management. Consistent evidence of benefit was only seen for diabetes apps; there was absent or conflicting evidence of benefit for apps for the remaining 10 diseases. Benefits that were detected were of marginal clinical importance, with no reporting of hard clinical end-points, such as mortality or hospitalisations. Only a minority of studies explicitly reported using behaviour change theories to underpin the app intervention. Many apps lacked design features that the literature identified as enhancing usability and potential to confer benefit. Despite a plethora of published evaluation tools, there is no universal framework that covers all relevant clinical and technical attributes. An inclusive list of evaluation criteria is proposed that may overcome this shortcoming. What are the implications for practitioners? The number of smartphone apps will continue to grow, as will the appetite for patients and clinicians to use them in chronic disease self-management. However, the evidence to date of clinical benefit of most apps already available is very limited. Design features that enhance usability and clinical efficacy need to be considered. In making decisions about which apps should be endorsed by government agencies and recommended with confidence by clinicians to their patients, a comprehensive but workable evaluation framework needs to be used by bodies assuming the roles of setting and applying standards.

Making sense of intratumor genetic heterogeneity: altered frequency of androgen receptor CAG repeat length variants in breast cancer tissues.

To examine the significance of intratumor genetic heterogeneity (ITGH) of the androgen receptor (AR) gene in breast cancer, patient-matched samples of laser capture microdissected breast tumor cells, adjacent normal breast epithelia cells, and peripheral blood leukocytes were sequenced using a novel next generation sequencing protocol. This protocol measured the frequency of distribution of a variable AR CAG repeat length, a functional polymorphism associated with breast cancer risk. All samples exhibited some degree of ITGH with up to 30 CAG repeat length variants identified. Each type of tissue exhibited a different distribution profile of CAG repeat lengths with substantial differences in the frequencies of zero and 18-25 CAG AR variants. Tissue differences in the frequency of ARs with each of these CAG repeat lengths were significant as measured by paired, twin t-tests. These results suggest that preferential selection of 18-25 CAG repeat length variants in breast tumors may be associated with breast cancer, and support the observation that shorter CAG repeats may protect against breast cancer. They also suggest that merely identifying variant genes will be insufficient to determine the critical mutational events of oncogenesis, which will require measuring the frequency of distribution of mutations within cancerous and matching normal tissues.

Genetic regulation of vitamin D levels.

Vitamin D plays several roles in the body, influencing bone health as well as serum calcium and phosphate levels. Further, vitamin D may modify immune function, cell proliferation, differentiation, and apoptosis. Vitamin D deficiency has been associated with numerous health outcomes, including bone disease, cancer, autoimmune disease, infectious disease, type 1 and type 2 diabetes, hypertension, and heart disease, although it is unclear whether or not these associations are causal. Various twin and family studies have demonstrated moderate to high heritability for circulating vitamin D levels. Accordingly, many studies have investigated the genetic determinants of this hormone. Recent advances in the methodology of large-scale genetic association studies, including coordinated international collaboration, have identified associations of CG, DHCR1, CYP2R1, VDR, and CYP24A1 with serum levels of vitamin D. Here, we review the genetic determinants of vitamin D levels by focusing on new findings arising from candidate gene and genomewide association studies.

Genetic polymorphisms of innate immunity-related inflammatory pathways and their association with factors related to type 2 diabetes.

BACKGROUND: Type 2 diabetes mellitus (T2DM) has been linked to a state of pre-clinical chronic inflammation resulting from abnormalities in the innate immune pathway. Serum levels of pro-inflammatory cytokines and acute-phase proteins, collectively known as 'inflammatory network', are elevated in the pre-, or early, stages of T2DM and increase with disease progression. Genetic variation can affect the innate immune response to certain environmental factors, and may, therefore, determine an individual's lifetime risk of disease. METHODS: We conducted a cross-sectional study in 6,720 subjects from the Twins UK Registry to evaluate the association between 18 single nucleotide polymorphisms (SNPs) in five genes (TLR4, IL1A, IL6, TNFA, and CRP) along the innate immunity-related inflammatory pathway and biomarkers of predisposition to T2DM [fasting insulin and glucose, HDL- and LDL- cholesterols, triglycerides (TGs), amyloid-A, sensitive C-reactive protein (sCRP) and vitamin D binding protein (VDBP) and body mass index (BMI)]. RESULTS: Of 18 the SNPs examined for their association with nine metabolic phenotypes of interest, six were significantly associated with five metabolic phenotypes (Bonferroni correction, P ≤ 0.0027). Fasting insulin was associated with SNPs in IL6 and TNFA, serum HDL-C with variants of TNFA and CRP and serum sCRP level with SNPs in CRP. Cross-correlation analysis among the different metabolic factors related to risk of T2DM showed several significant associations. For example, BMI was directly correlated with glucose (r = 0.11), insulin (r = 0.15), sCRP (r = 0.23), LDL-C (r = 0.067) and TGs (r = 0.18) but inversely with HDL-C (r = -0.14). sCRP was also positively correlated (P < 0.0001) with insulin (r = 0.17), amyloid-A (r = 0.39), TGs (r = 0.26), and VDBP (r = 0.36) but inversely with HDL-C (r = -0.12). CONCLUSION: Genetic variants in the innate immunity pathway and its related inflammatory cascade is associated with some metabolic risk factors for T2DM; an observation that may provide a rationale for further studying their role as biomarkers for disease early risk prediction.

Glutamine-, glutamine synthetase-, glutamate dehydrogenase- and pyruvate carboxylase-immunoreactivities in the rat dorsal root ganglion and peripheral nerve.

Supporting glial cells of the peripheral nervous system include satellite cells of dorsal root ganglia and Schwann cells of peripheral nerves. In the central nervous system, glial cells contain enzymes related to the tricarboxylic acid and glutamine cycles: pyruvate carboxylase, glutamate dehydrogenase, and glutamine synthetase. The present study used immunohistochemistry in the rat peripheral nervous system to determine the cellular distribution of these enzymes along with glutamine. In dorsal root ganglia and peripheral nerves, glutamine and glutamine related enzymes were enriched in satellite and Schwann cells. In the dorsal root ganglia, immunoreactive satellite cells surrounded neurons of all sizes. In peripheral nerve, immunoreactive Schwann cells were most easily observed surrounding large diameter, myelinated axons. These Schwann cells contained immunoreactivity in their cell bodies, nodes of Ranvier, and the rim of cytoplasm outside the myelin sheath. Myelin sheaths were non-immunoreactive. The peripheral glial tricarboxylic and glutamine cycles may be used to produce glutamine for neuronal cell uptake and conversion to glutamate for synaptic transmission. Alternatively, these cycles may function in peripheral glia similar to central nervous system astrocytes for supporting the energy demands of neurons.