Acute Kidney Injury, Systemic Inflammation and Long-term Cognitive Function: ASSESS-AKI.

BACKGROUND: Cognitive dysfunction is a well-known complication of chronic kidney disease, but it is less known whether cognitive decline occurs in survivors after acute kidney injury (AKI). We hypothesized that an episode of AKI is associated with poorer cognitive function, mediated, at least in part, by persistent systemic inflammation. METHODS: ASSESS-AKI enrolled patients surviving three months after hospitalization with and without AKI matched based on demographics, comorbidities, and baseline kidney function. A subset underwent cognitive testing using the modified mini-mental status examination (3MS) at 3, 12, and 36 months. We examined the association of AKI with 3MS scores using mixed linear models and assessed the proportion of risk mediated by systemic inflammatory biomarkers. RESULTS: Among 1538 participants in ASSESS-AKI, 1420 (92%) completed the 3MS assessment at 3 months and had a corresponding matched participant. Participants with AKI had lower 3MS scores at three years (difference -1.1 (95% CI: -2.0, -0.3) P=0.009) compared to participants without AKI. A higher proportion of AKI participants had a clinically meaningful (≥ 5 point) reduction in 3MS scores at three years compared to participants without AKI (14% vs. 10%, P=0.04). In mediation analyses, plasma soluble tumor necrosis factor receptor-1 (sTNFR-1) at three months after AKI mediated 35% (P=0.02) of the AKI related risk for 3MS scores at three years. CONCLUSIONS: AKI was associated with lower 3MS scores and sTNFR-1 concentrations appeared to mediate a significant proportion of the risk of long-term cognitive impairment. Further work is needed to determine if AKI is causal or a marker for cognitive impairment.

The costs of curiosity and creativity: Minimizing the downsides while maximizing the upsides.

The unbridled positivity toward curiosity and creativity may be excessive. Both aid species survival through exploration and advancement. These beneficial effects are well documented. What remains is to understand their optimal levels and contexts for maximal achievement, health, and well-being. Every beneficial element to individuals and groups carries the potential for harm - curiosity and creativity included.

A Retrospective Cohort Study That Examined the Impact of Cannabis Consumption on Long-Term Kidney Outcomes.

Background: Cannabis consumption for recreational and medical use is increasing worldwide. However, the long-term effects on kidney health and disease are largely unknown. Materials and Methods: Post hoc analysis of cannabis use as a risk factor for kidney disease was performed using data from the Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) study that enrolled hospitalized adults with and without acute kidney injury from four U.S. centers during 2009-2015. Associations between self-reported cannabis consumption and the categorical and continuous outcomes were determined using multivariable Cox regression and linear mixed models, respectively. Results: Over a mean follow-up of 4.5±1.8 years, 94 participants without chronic kidney disease (CKD) (estimated glomerular filtration rate [eGFR] >60 mL/min/1.73 m2) who consumed cannabis had similar rates of annual eGFR decline versus 889 nonconsumers (mean difference=-0.02 mL/min/1.73 m2/year, p=0.9) and incident CKD (≥25% reduction in eGFR compared with the 3-month post-hospitalization measured eGFR and achieving CKD stage 3 or higher) (adjusted hazard ratio [aHR]=1.2; 95% confidence interval [CI]=0.7-2.0). Nineteen participants with CKD (eGFR <60 mL/min/1.73 m2) who consumed cannabis had more rapid eGFR decline versus 597 nonconsumers (mean difference=-1.3 mL/min/1.73 m2/year; p=0.02) that was not independently associated with an increased risk of CKD progression (≥50% reduction in eGFR compared with the 3-month post-hospitalization eGFR, reaching CKD stage 5, or receiving kidney replacement therapy) (aHR=1.6; 95% CI=0.7-3.5). Cannabis consumption was not associated with the rate of change in urine albumin to creatinine ratio (UACR) over time among those with (p=0.7) or without CKD (p=0.4). Conclusions: Cannabis consumption did not adversely affect the kidney function of participants without CKD but was associated with a faster annual eGFR decline among participants with CKD. Cannabis consumption was not associated with changes in UACR over time, incident CKD, or progressive CKD regardless of baseline kidney function. Additional research is needed to investigate the kidney endocannabinoid system and the impact of cannabis use on kidney disease outcomes.

The ASSESS-AKI Study found urinary epidermal growth factor is associated with reduced risk of major adverse kidney events.

Biomarkers of tubular function such as epidermal growth factor (EGF) may improve prognostication of participants at highest risk for chronic kidney disease (CKD) after hospitalization. To examine this, we measured urinary EGF (uEGF) from samples collected in the Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Study, a multi-center, prospective, observational cohort of hospitalized participants with and without AKI. Cox proportional hazards regression was used to investigate the association of uEGF/Cr at hospitalization, three months post-discharge, and the change between these time points with major adverse kidney events (MAKE): CKD incidence, progression, or development of kidney failure. Clinical findings were paired with mechanistic studies comparing relative Egf expression in mouse models of kidney atrophy or repair after ischemia-reperfusion injury. MAKE was observed in 20% of 1,509 participants over 4.3 years of follow-up. Each 2-fold higher level of uEGF/Cr at three months was associated with decreased risk of MAKE (adjusted hazards ratio 0.46, 95% confidence interval: 0.39-0.55). Participants with the highest increase in uEGF/Cr from hospitalization to three-month follow-up had a lower risk of MAKE (adjusted hazards ratio 0.52; 95% confidence interval: 0.36-0.74) compared to those with the least change in uEGF/Cr. A model using uEGF/Cr at three months combined with clinical variables yielded moderate discrimination for MAKE (area under the curve 0.73; 95% confidence interval: 0.69-0.77) and strong discrimination for kidney failure at four years (area under the curve 0.96; 95% confidence interval: 0.92-1.00). Accelerated restoration of Egf expression in mice was seen in the model of adaptive repair after injury, compared to a model of progressive atrophy. Thus, urinary EGF/Cr may be a biomarker of distal tubular health, with higher concentrations and increased uEGF/Cr post-discharge independently associated with reduced risk of MAKE in hospitalized patients.

Integrated Analysis of Blood and Urine Biomarkers to Identify Acute Kidney Injury Subphenotypes and Associations With Long-term Outcomes.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) is a heterogeneous clinical syndrome with varying causes, pathophysiology, and outcomes. We incorporated plasma and urine biomarker measurements to identify AKI subgroups (subphenotypes) more tightly linked to underlying pathophysiology and long-term clinical outcomes. STUDY DESIGN: Multicenter cohort study. SETTING & PARTICIPANTS: 769 hospitalized adults with AKI matched with 769 without AKI, enrolled from December 2009 to February 2015 in the ASSESS-AKI Study. PREDICTORS: 29 clinical, plasma, and urinary biomarker parameters used to identify AKI subphenotypes. OUTCOME: Composite of major adverse kidney events (MAKE) with a median follow-up period of 4.7 years. ANALYTICAL APPROACH: Latent class analysis (LCA) and k-means clustering were applied to 29 clinical, plasma, and urinary biomarker parameters. Associations between AKI subphenotypes and MAKE were analyzed using Kaplan-Meier curves and Cox proportional hazard models. RESULTS: Among 769 AKI patients both LCA and k-means identified 2 distinct AKI subphenotypes (classes 1 and 2). The long-term risk for MAKE was higher with class 2 (adjusted HR, 1.41 [95% CI, 1.08-1.84]; P=0.01) compared with class 1, adjusting for demographics, hospital level factors, and KDIGO stage of AKI. The higher risk of MAKE among class 2 was explained by a higher risk of long-term chronic kidney disease progression and dialysis. The top variables that were different between classes 1 and 2 included plasma and urinary biomarkers of inflammation and epithelial cell injury; serum creatinine ranked 20th out of the 29 variables for differentiating classes. LIMITATIONS: A replication cohort with simultaneously collected blood and urine sampling in hospitalized adults with AKI and long-term outcomes was unavailable. CONCLUSIONS: We identify 2 molecularly distinct AKI subphenotypes with differing risk of long-term outcomes, independent of the current criteria to risk stratify AKI. Future identification of AKI subphenotypes may facilitate linking therapies to underlying pathophysiology to prevent long-term sequalae after AKI. PLAIN-LANGUAGE SUMMARY: Acute kidney injury (AKI) occurs commonly in hospitalized patients and is associated with high morbidity and mortality. The AKI definition lumps many different types of AKI together, but subgroups of AKI may be more tightly linked to the underlying biology and clinical outcomes. We used 29 different clinical, blood, and urinary biomarkers and applied 2 different statistical algorithms to identify AKI subtypes and their association with long-term outcomes. Both clustering algorithms identified 2 AKI subtypes with different risk of chronic kidney disease, independent of the serum creatinine concentrations (the current gold standard to determine severity of AKI). Identification of AKI subtypes may facilitate linking therapies to underlying biology to prevent long-term consequences after AKI.

Joint Modeling of Clinical and Biomarker Data in Acute Kidney Injury Defines Unique Subphenotypes with Differing Outcomes.

BACKGROUND: AKI is a heterogeneous syndrome. Current subphenotyping approaches have only used limited laboratory data to understand a much more complex condition. METHODS: We focused on patients with AKI from the Assessment, Serial Evaluation, and Subsequent Sequelae in AKI (ASSESS-AKI). We used hierarchical clustering with Ward linkage on biomarkers of inflammation, injury, and repair/health. We then evaluated clinical differences between subphenotypes and examined their associations with cardiorenal events and death using Cox proportional hazard models. RESULTS: We included 748 patients with AKI: 543 (73%) of them had AKI stage 1, 112 (15%) had AKI stage 2, and 93 (12%) had AKI stage 3. The mean age (±SD) was 64 (13) years; 508 (68%) were men; and the median follow-up was 4.7 (Q1: 2.9, Q3: 5.7) years. Patients with AKI subphenotype 1 ( N =181) had the highest kidney injury molecule (KIM-1) and troponin T levels. Subphenotype 2 ( N =250) had the highest levels of uromodulin. AKI subphenotype 3 ( N =159) comprised patients with markedly high pro-brain natriuretic peptide and plasma tumor necrosis factor receptor-1 and -2 and low concentrations of KIM-1 and neutrophil gelatinase-associated lipocalin. Finally, patients with subphenotype 4 ( N =158) predominantly had sepsis-AKI and the highest levels of vascular/kidney inflammation (YKL-40, MCP-1) and injury (neutrophil gelatinase-associated lipocalin, KIM-1). AKI subphenotypes 3 and 4 were independently associated with a higher risk of death compared with subphenotype 2 and had adjusted hazard ratios of 2.9 (95% confidence interval, 1.8 to 4.6) and 1.6 (95% confidence interval, 1.01 to 2.6, P = 0.04), respectively. Subphenotype 3 was also independently associated with a three-fold risk of CKD and cardiovascular events. CONCLUSIONS: We discovered four AKI subphenotypes with differing clinical features and biomarker profiles that are associated with longitudinal clinical outcomes.

Longitudinal biomarkers and kidney disease progression after acute kidney injury.

BACKGROUNDLongitudinal investigations of murine acute kidney injury (AKI) suggest that injury and inflammation may persist long after the initial insult. However, the evolution of these processes and their prognostic values are unknown in patients with AKI.METHODSIn a prospective cohort of 656 participants hospitalized with AKI, we measured 7 urine and 2 plasma biomarkers of kidney injury, inflammation, and tubular health at multiple time points from the diagnosis to 12 months after AKI. We used linear mixed-effect models to estimate biomarker changes over time, and we used Cox proportional hazard regressions to determine their associations with a composite outcome of chronic kidney disease (CKD) incidence and progression. We compared the gene expression kinetics of biomarkers in murine models of repair and atrophy after ischemic reperfusion injury (IRI).RESULTSAfter 4.3 years, 106 and 52 participants developed incident CKD and CKD progression, respectively. Each SD increase in the change of urine KIM-1, MCP-1, and plasma TNFR1 from baseline to 12 months was associated with 2- to 3-fold increased risk for CKD, while the increase in urine uromodulin was associated with 40% reduced risk for CKD. The trajectories of these biological processes were associated with progression to kidney atrophy in mice after IRI.CONCLUSIONSustained tissue injury and inflammation, and slower restoration of tubular health, are associated with higher risk of kidney disease progression. Further investigation into these ongoing biological processes may help researchers understand and prevent the AKI-to-CKD transition.FUNDINGNIH and NIDDK (grants U01DK082223, U01DK082185, U01DK082192, U01DK082183, R01DK098233, R01DK101507, R01DK114014, K23DK100468, R03DK111881, K01DK120783, and R01DK093771).

Biomarkers of eGFR decline after cardiac surgery in children: findings from the ASSESS-AKI study.

BACKGROUND: Children who require surgery for congenital heart disease have increased risk for long-term chronic kidney disease (CKD). Clinical factors as well as urine biomarkers of tubular health and injury may help improve the prognostication of estimated glomerular filtration rate (eGFR) decline. METHODS: We enrolled children from 1 month to 18 years old undergoing cardiac surgery in the ASSESS-AKI cohort. We used mixed-effect models to assess the association between urinary biomarkers (log2-transformed uromodulin, NGAL, KIM-1, IL-18, L-FABP) measured 3 months after cardiac surgery and cyanotic heart disease with the rate of eGFR decline at annual in-person visits over 4 years. RESULTS: Of the 117 children enrolled, 30 (24%) had cyanotic heart disease. During 48 months of follow-up, the median eGFR in the subgroup of children with cyanotic heart disease was lower at all study visits as compared with children with acyanotic heart disease (p = 0.01). In the overall cohort, lower levels of both urine uromodulin and IL-18 after discharge were associated with eGFR decline. After adjustment for age, RACHS-1 surgical complexity score, proteinuria, and eGFR at the 3-month study visit, lower concentrations of urine uromodulin and IL-18 were associated with a monthly decline in eGFR (uromodulin ß = 0.04 (95% CI: 0.00-0.09; p = 0.07) IL-18 ß = 0.07 (95% CI: 0.01-0.13; p = 0.04), ml/min/1.73 m2 per month). CONCLUSIONS: At 3 months after cardiac surgery, children with lower urine uromodulin and IL-18 concentrations experienced a significantly faster decline in eGFR. Children with cyanotic heart disease had a lower median eGFR at all time points but did not experience faster eGFR decline. A higher-resolution version of the Graphical abstract is available as Supplementary information.

Divergent semantic integration (DSI): Extracting creativity from narratives with distributional semantic modeling.

We developed a novel conceptualization of one component of creativity in narratives by integrating creativity theory and distributional semantics theory. We termed the new construct divergent semantic integration (DSI), defined as the extent to which a narrative connects divergent ideas. Across nine studies, 27 different narrative prompts, and over 3500 short narratives, we compared six models of DSI that varied in their computational architecture. The best-performing model employed Bidirectional Encoder Representations from Transformers (BERT), which generates context-dependent numerical representations of words (i.e., embeddings). BERT DSI scores demonstrated impressive predictive power, explaining up to 72% of the variance in human creativity ratings, even approaching human inter-rater reliability for some tasks. BERT DSI scores showed equivalently high predictive power for expert and nonexpert human ratings of creativity in narratives. Critically, DSI scores generalized across ethnicity and English language proficiency, including individuals identifying as Hispanic and L2 English speakers. The integration of creativity and distributional semantics theory has substantial potential to generate novel hypotheses about creativity and novel operationalizations of its underlying processes and components. To facilitate new discoveries across diverse disciplines, we provide a tutorial with code (osf.io/ath2s) on how to compute DSI and a web app ( osf.io/ath2s ) to freely retrieve DSI scores.

Plasma Soluble Tumor Necrosis Factor Receptor Concentrations and Clinical Events After Hospitalization: Findings From the ASSESS-AKI and ARID Studies.

RATIONALE & OBJECTIVE: The role of plasma soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 in the prognosis of clinical events after hospitalization with or without acute kidney injury (AKI) is unknown. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: Hospital survivors from the ASSESS-AKI (Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury) and ARID (AKI Risk in Derby) studies with and without AKI during the index hospitalization who had baseline serum samples for biomarker measurements. PREDICTORS: We measured sTNFR1 and sTNFR2 from plasma samples obtained 3 months after discharge. OUTCOMES: The associations of biomarkers with longitudinal kidney disease incidence and progression, heart failure, and death were evaluated. ANALYTICAL APPROACH: Cox proportional hazard models. RESULTS: Among 1,474 participants with plasma biomarker measurements, 19% had kidney disease progression, 14% had later heart failure, and 21% died during a median follow-up of 4.4 years. For the kidney outcome, the adjusted HRs (AHRs) per doubling in concentration were 2.9 (95% CI, 2.2-3.9) for sTNFR1 and 1.9 (95% CI, 1.5-2.5) for sTNFR2. AKI during the index hospitalization did not modify the association between biomarkers and kidney events. For heart failure, the AHRs per doubling in concentration were 1.9 (95% CI, 1.4-2.5) for sTNFR1 and 1.5 (95% CI, 1.2-2.0) for sTNFR2. For mortality, the AHRs were 3.3 (95% CI, 2.5-4.3) for sTNFR1 and 2.5 (95% CI, 2.0-3.1) for sTNFR2. The findings in ARID were qualitatively similar in terms of the magnitude of association between biomarkers and outcomes. LIMITATIONS: Different biomarker platforms and AKI definitions; limited generalizability to other ethnic groups. CONCLUSIONS: Plasma sTNFR1 and sTNFR2 measured 3 months after hospital discharge were independently associated with clinical events regardless of AKI status during the index admission. sTNFR1 and sTNFR2 may assist with the risk stratification of patients during follow-up.

ggMOB: Elucidation of genomic conjugative features and associated cargo genes across bacterial genera using genus-genus mobilization networks.

Horizontal gene transfer mediated by conjugation is considered an important evolutionary mechanism of bacteria. It allows organisms to quickly evolve new phenotypic properties including antimicrobial resistance (AMR) and virulence. The frequency of conjugation-mediated cargo gene exchange has not yet been comprehensively studied within and between bacterial taxa. We developed a frequency-based network of genus-genus conjugation features and candidate cargo genes from whole-genome sequence data of over 180,000 bacterial genomes, representing 1,345 genera. Using our method, which we refer to as ggMOB, we revealed that over half of the bacterial genomes contained one or more known conjugation features that matched exactly to at least one other genome. Moreover, the proportion of genomes containing these conjugation features varied substantially by genus and conjugation feature. These results and the genus-level network structure can be viewed interactively in the ggMOB interface, which allows for user-defined filtering of conjugation features and candidate cargo genes. Using the network data, we observed that the ratio of AMR gene representation in conjugative versus non-conjugative genomes exceeded 5:1, confirming that conjugation is a critical force for AMR spread across genera. Finally, we demonstrated that clustering genomes by conjugation profile sometimes correlated well with classical phylogenetic structuring; but that in some cases the clustering was highly discordant, suggesting that the importance of the accessory genome in driving bacterial evolution may be highly variable across both time and taxonomy. These results can advance scientific understanding of bacterial evolution, and can be used as a starting point for probing genus-genus gene exchange within complex microbial communities that include unculturable bacteria. ggMOB is publicly available under the GNU licence at https://ruiz-hci-lab.github.io/ggMOB/.

Predicting Epitope Candidates for SARS-CoV-2.

Epitopes are short amino acid sequences that define the antigen signature to which an antibody or T cell receptor binds. In light of the current pandemic, epitope analysis and prediction are paramount to improving serological testing and developing vaccines. In this paper, known epitope sequences from SARS-CoV, SARS-CoV-2, and other Coronaviridae were leveraged to identify additional antigen regions in 62K SARS-CoV-2 genomes. Additionally, we present epitope distribution across SARS-CoV-2 genomes, locate the most commonly found epitopes, and discuss where epitopes are located on proteins and how epitopes can be grouped into classes. The mutation density of different protein regions is presented using a big data approach. It was observed that there are 112 B cell and 279 T cell conserved epitopes between SARS-CoV-2 and SARS-CoV, with more diverse sequences found in Nucleoprotein and Spike glycoprotein.

The Relationship between Rate and Volume of Intravenous Fluid Administration and Kidney Outcomes after Angiography.

BACKGROUND AND OBJECTIVES: Contrast-associated AKI may result in higher morbidity and mortality. Intravenous fluid administration remains the mainstay for prevention. There is a lack of consensus on the optimal administration strategy. We studied the association of periprocedure fluid administration with contrast-associated AKI, defined as an increase in serum creatinine of at least 25% or 0.5 mg/dl from baseline at 3-5 days after angiography, and 90-day need for dialysis, death, or a 50% increase in serum creatinine. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We conducted a secondary analysis of 4671 PRESERVE participants who underwent angiographic procedures. Although fluid type was randomized, strategy of administration was at the discretion of the clinician. We divided the study cohort into quartiles by total fluid volume. We performed multivariable logistic regression, adjusting for clinically important covariates. We tested for the interaction between fluid volume and duration of fluid administration, categorized as <6 or ≥6 hours. RESULTS: The mean (SD) age was 70 (8) years, 94% of participants were male, and median (interquartile range) eGFR was 60 (41-60) ml/min per 1.73 m2. The range of fluid administered was 89-882 ml in quartile 1 and 1258-2790 ml in quartile 4. Compared with the highest quartile (quartile 4) of fluid volume, we found a significantly higher risk of the primary outcome in quartile 1 (adjusted odds ratio, 1.58; 95% confidence interval, 1.06 to 2.38) but not in quartiles 2 and 3 compared with quartile 4. There was no difference in the incidence of contrast-associated AKI across the quartiles. The interaction between volume and duration was not significant for any of the outcomes. CONCLUSIONS: We found that administration of a total volume of 1000 ml, starting at least 1 hour before contrast injection and continuing postcontrast for a total of 6 hours, is associated with a similar risk of adverse outcomes as larger volumes of intravenous fluids administered for periods >6 hours. Mean fluid volumes <964 ml may be associated with a higher risk for the primary outcome, although residual confounding cannot be excluded.

Considerations in Controlling for Urine Concentration for Biomarkers of Kidney Disease Progression After Acute Kidney Injury.

Introduction: Biomarkers of acute kidney injury (AKI) are often indexed to urine creatinine (UCr) or urine osmolarity (UOsm) to control for urine concentration. We evaluated how these approaches affect the biomarker-outcome association in patients with AKI. Methods: The Assessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury Study was a cohort of hospitalized patients with and without AKI between 2009 and 2015. Using Cox proportional hazards regression, we assessed the associations and predictions (C-statistics) of urine biomarkers with a composite outcome of incident chronic kidney disease (CKD) and CKD progression. We used 4 approaches to account for urine concentration: indexing and adjusting for UCr and UOsm. Results: Among 1538 participants, 769 (50%) had AKI and 300 (19.5%) developed composite CKD outcome at median follow-up of 4.7 years. UCr and UOsm during hospitalization were inversely associated with the composite CKD outcome. The associations and predictions with CKD were significantly strengthened after indexing or adjusting for UCr or UOsm for urine kidney injury molecule-1 (KIM-1), interleukin-18 (IL-18), and monocyte chemoattractant protein-1 (MCP-1) in patients with AKI. There was no significant improvement with indexing or adjusting UCr or UOsm for albumin, neutrophil gelatinase-associated lipocalin (NGAL), and chitinase 3-like 1 (YKL-40). Uromodulin's (UMOD) inverse association with the outcome was significantly blunted after indexing but not adjusting for UCr or UOsm. Conclusion: UCr and UOsm during hospitalization are inversely associated with development and progression of CKD. Indexing or adjusting for UCr or UOsm strengthened associations and improved predictions for CKD for only some biomarkers. Incorporating urinary concentration should be individualized for each biomarker in research and clinical applications.

Angiopoietins as Prognostic Markers for Future Kidney Disease and Heart Failure Events after Acute Kidney Injury.

BACKGROUND: The mechanisms underlying long-term sequelae after AKI remain unclear. Vessel instability, an early response to endothelial injury, may reflect a shared mechanism and early trigger for CKD and heart failure. METHODS: To investigate whether plasma angiopoietins, markers of vessel homeostasis, are associated with CKD progression and heart failure admissions after hospitalization in patients with and without AKI, we conducted a prospective cohort study to analyze the balance between angiopoietin-1 (Angpt-1), which maintains vessel stability, and angiopoietin-2 (Angpt-2), which increases vessel destabilization. Three months after discharge, we evaluated the associations between angiopoietins and development of the primary outcomes of CKD progression and heart failure and the secondary outcome of all-cause mortality 3 months after discharge or later. RESULTS: Median age for the 1503 participants was 65.8 years; 746 (50%) had AKI. Compared with the lowest quartile, the highest quartile of the Angpt-1:Angpt-2 ratio was associated with 72% lower risk of CKD progression (adjusted hazard ratio [aHR], 0.28; 95% confidence interval [CI], 0.15 to 0.51), 94% lower risk of heart failure (aHR, 0.06; 95% CI, 0.02 to 0.15), and 82% lower risk of mortality (aHR, 0.18; 95% CI, 0.09 to 0.35) for those with AKI. Among those without AKI, the highest quartile of Angpt-1:Angpt-2 ratio was associated with 71% lower risk of heart failure (aHR, 0.29; 95% CI, 0.12 to 0.69) and 68% less mortality (aHR, 0.32; 95% CI, 0.15 to 0.68). There were no associations with CKD progression. CONCLUSIONS: A higher Angpt-1:Angpt-2 ratio was strongly associated with less CKD progression, heart failure, and mortality in the setting of AKI.

Functional Genomics Platform, A Cloud-Based Platform for Studying Microbial Life at Scale.

The rapid growth in biological sequence data is revolutionizing our understanding of genotypic diversity and challenging conventional approaches to informatics. With the increasing availability of genomic data, traditional bioinformatic tools require substantial computational time and the creation of ever-larger indices each time a researcher seeks to gain insight from the data. To address these challenges, we pre-computed important relationships between biological entities spanning the Central Dogma of Molecular Biology and captured this information in a relational database. The database can be queried across hundreds of millions of entities and returns results in a fraction of the time required by traditional methods. In this paper, we describe Functional Genomics Platform (formerly known as OMXWare), a comprehensive database relating genotype to phenotype for bacterial life. Continually updated, the Functional Genomics Platform today contains data derived from 200,000 curated, self-consistently assembled genomes. The database stores functional data for over 68 million genes, 52 million proteins, and 239 million domains with associated biological activity annotations from Gene Ontology, KEGG, MetaCyc, and Reactome. The Functional Genomics Platform maps all of the many-to-many connections between each biological entity including the originating genome, gene, protein, and protein domain. Various microbial studies, from infectious disease to environmental health, can benefit from the rich data and connections. We describe the data selection, the pipeline to create and update the Functional Genomics Platform, and the developer tools (Python SDK and REST APIs)which allow researchers to efficiently study microbial life at scale.