Update on EPA's ToxCast program: providing high throughput decision support tools for chemical risk management

The field of toxicology is on the cusp of a major transformation in how the safety and hazard of chemicals are evaluated for potential effects on human health and the environment. Brought on by the recognition of the limitations of the current paradigm in terms of cost, time, and throughput, combined with the ever increasing power of modern biological tools to probe mechanisms of chemical-biological interactions at finer and finer resolutions, 21st century toxicology is rapidly taking shape. A key element of the new approach is a focus on the molecular and cellular pathways that are the targets of chemical interactions. By understanding toxicity in this manner, we begin to learn how chemicals cause toxicity, as opposed to merely what diseases or health effects they might cause. This deeper understanding leads to increasing confidence in identifying which populations might be at risk, significant susceptibility factors, and key influences on the shape of the dose-response curve. The U. S. Environmental Protection Agency (EPA) initiated the ToxCast, or "toxicity forecaster", program 5 years ago to gain understanding of the strengths and limitations of the new approach by starting to test relatively large numbers (hundreds) of chemicals against an equally large number of biological assays. Using computational approaches, the EPA is building decision support tools based on ToxCast in vitro screening results to help prioritize chemicals for further investigation, as well as developing predictive models for a number of health outcomes. This perspective provides a summary of the initial, proof of concept, Phase I of ToxCast that has laid the groundwork for the next phases and future directions of the program.

Editor's Highlight: Analysis of the Effects of Cell Stress and Cytotoxicity on In Vitro Assay Activity Across a Diverse Chemical and Assay Space

Chemical toxicity can arise from disruption of specific biomolecular functions or through more generalized cell stress and cytotoxicity-mediated processes. Here, responses of 1060 chemicals including pharmaceuticals, natural products, pesticidals, consumer, and industrial chemicals across a battery of 815 in vitro assay endpoints from 7 high-throughput assay technology platforms were analyzed in order to distinguish between these types of activities. Both cell-based and cell-free assays showed a rapid increase in the frequency of responses at concentrations where cell stress/cytotoxicity responses were observed in cell-based assays. Chemicals that were positive on at least 2 viability/cytotoxicity assays within the concentration range tested (typically up to 100 μM) activated a median of 12% of assay endpoints whereas those that were not cytotoxic in this concentration range activated 1.3% of the assays endpoints. The results suggest that activity can be broadly divided into: (1) specific biomolecular interactions against one or more targets (eg, receptors or enzymes) at concentrations below which overt cytotoxicity-associated activity is observed; and (2) activity associated with cell stress or cytotoxicity, which may result from triggering specific cell stress pathways, chemical reactivity, physico-chemical disruption of proteins or membranes, or broad low-affinity non-covalent interactions. Chemicals showing a greater number of specific biomolecular interactions are generally designed to be bioactive (pharmaceuticals or pesticidal active ingredients), whereas intentional food-use chemicals tended to show the fewest specific interactions. The analyses presented here provide context for use of these data in ongoing studies to predict in vivo toxicity from chemicals lacking extensive hazard assessment.

Continued muscle loss increases mortality in cirrhosis: Impact of aetiology of liver disease

BACKGROUND AND AIMS

Sarcopenia or skeletal muscle loss adversely affects outcomes in cirrhosis. The impact of aetiology of liver disease on the severity or the rate of muscle loss is not known.

METHODS

Consecutive, well-characterized adult patients with cirrhosis due to viral hepatitis (VH), alcoholic liver disease (ALD) or non-alcoholic fatty liver disease (NAFLD) and non-diseased controls with at least two temporally distinct abdominal CT (computed tomography) scans were evaluated. Psoas, paraspinal and abdominal wall muscle areas at the L3 vertebra level were quantified on the CT scans. Standardized rate of change in muscle area was expressed as change in area/100 days. Univariate and multivariable analyses were performed to identify contributors to rate of muscle loss and survival.

RESULTS

Among 83 cirrhotics (NAFLD n = 26, ALD n = 39, VH n = 18), there were 20 (24.1%) deaths over 62.7 ± 41.3 months. The mean percentage change in psoas area was -0.03 ± 0.05/100d in controls and -3.52 ± 0.45/100d in cirrhosis (P < .001). The mean percentage change in psoas area was -1.72 ± 0.27/100d in NAFLD, -5.28 ± 0.86/100d in ALD and -2.29 ± 0.28/100d in VH. Among cirrhotics, patients with ALD had the lowest initial muscle area and most rapid rate of reduction in muscle area. Aetiology of liver disease, model for end-stage liver disease (MELD) and the rate of loss of muscle area were independent risk factors for survival.

CONCLUSIONS

Aetiology of liver disease is an independent risk factor for sarcopenia with the greatest rate of muscle loss noted in ALD. Survival in cirrhosis was dependent on initial muscle mass, rate of muscle loss and MELD score.

Genome-wide assessment of recurrent genomic imbalances in canine leukemia identifies evolutionarily conserved regions for subtype differentiation

Leukemia in dogs is a heterogeneous disease with survival ranging from days to years, depending on the subtype. Strides have been made in both human and canine leukemia to improve classification and understanding of pathogenesis through immunophenotyping, yet classification and choosing appropriate therapy remains challenging. In this study, we assessed 123 cases of canine leukemia (28 ALLs, 24 AMLs, 25 B-CLLs, and 46 T-CLLs) using high-resolution oligonucleotide array comparative genomic hybridization (oaCGH) to detect DNA copy number alterations (CNAs). For the first time, such data were used to identify recurrent CNAs and inclusive genes that may be potential drivers of subtype-specific pathogenesis. We performed predictive modeling to identify CNAs that could reliably differentiate acute subtypes (ALL vs. AML) and chronic subtypes (B-CLL vs. T-CLL) and used this model to differentiate cases with up to 83.3 and 95.8 % precision, respectively, based on CNAs at only one to three genomic regions. In addition, CGH datasets for canine and human leukemia were compared to reveal evolutionarily conserved copy number changes between species, including the shared gain of HSA 21q in ALL and ∼25 Mb of shared gain of HSA 12 and loss of HSA 13q14 in CLL. These findings support the use of canine leukemia as a relevant in vivo model for human leukemia and justify the need to further explore the conserved genomic regions of interest for their clinical impact.

Immunoclassification characterized by CD8 and PD-L1 expression is associated with the clinical outcome of gastric cancer patients

Background

Gastric cancer (GC) is a major cause of cancer deaths, especially in Eastern Asia. Current classification systems, including the WHO, Lauren, and TCGA, have clarified the pathological and molecular profiles of GC. However, these classifications lack an association with clinical outcome and guidance for medication selection.

Objective

We aimed to identify a new immunoclassification for GC to better predict patient prognosis and aid in patient selection for immunotherapy.

Results

For all samples, 35 were EBV positive (+) and 112 were EBV negative (-). EBV infection was associated with the number of CD3+ T cells (OR = 2.91 95% CI 1.27-6.68, p = 0.012) and PD-L1 expression in TME (OR = 2.57, 95% CI 1.13–5.82, p = 0.024). EBV+ patients showed a poor overall survival (OS) compared with EBV- patients (HR = 2.37; 95% CI, 1.03–5.41; p = 0.011). Importantly, WIR patients lived significantly shorter than SIR patients with high CD8+ T cells and low PD-L1 expression (HR = 3.37; 95% CI, 1.63–6.97; p = 0.015).

Materials and Methods

147 formalin-fixed and paraffin-embedded (FFPE) samples of GC were obtained. Epstein-Barr virus (EBV) infection was measured. Immune markers including CD3, CD8 and PD-L1 were detected by immunohistochemistry (IHC) at tumor infiltration area (TI) and invasive margin area (IM) in tumor microenvironment (TME). PD-L1 expression was assessed by immunoreactive score (IRS) system. For immunoclassification, patients were classified into two subgroups: strong immunoreaction (SIR) and weak immunoreaction (WIR) defined by the number of CD8+ T cells and PD-L1 expression in TI.

Conclusions

In this study, we suggest a new immunoclassification for gastric cancer which is associated with patient outcome and may provide a way to guide immunotherapy in the future.

Bile acids targeted metabolomics and medication classification data in the ADNI1 and ADNIGO/2 cohorts

Alzheimer's disease (AD) is the most common cause of dementia. The mechanism of disease development and progression is not well understood, but increasing evidence suggests multifactorial etiology, with a number of genetic, environmental, and aging-related factors. There is a growing body of evidence that metabolic defects may contribute to this complex disease. To interrogate the relationship between system level metabolites and disease susceptibility and progression, the AD Metabolomics Consortium (ADMC) in partnership with AD Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for patients in the ADNI1 cohort. We used the Biocrates Bile Acids platform to evaluate the association of metabolic levels with disease risk and progression. We detail the quantitative metabolomics data generated on the baseline samples from ADNI1 and ADNIGO/2 (370 cognitively normal, 887 mild cognitive impairment, and 305 AD). Similar to our previous reports on ADNI1, we present the tools for data quality control and initial analysis. This data descriptor represents the third in a series of comprehensive metabolomics datasets from the ADMC on the ADNI.

Lymphoblastoid cell lines models of drug response: successes and lessons from this pharmacogenomic model

A new standard for medicine is emerging that aims to improve individual drug responses through studying associations with genetic variations. This field, pharmacogenomics, is undergoing a rapid expansion due to a variety of technological advancements that are enabling higher throughput with reductions in cost. Here we review the advantages, limitations, and opportunities for using lymphoblastoid cell lines (LCL) as a model system for human pharmacogenomic studies. There are a wide range of publicly available resources with genome-wide data available for LCLs from both related and unrelated populations, removing the cost of genotyping the data for drug response studies. Furthermore, in contrast to human clinical trials or in vivo model systems, with high-throughput in vitro screening technologies, pharmacogenomics studies can easily be scaled to accommodate large sample sizes. An important component to leveraging genome-wide data in LCL models is association mapping. Several methods are discussed herein, and include multivariate concentration response modeling, issues with multiple testing, and successful examples of the 'triangle model' to identify candidate variants. Once candidate gene variants have been determined, their biological roles can be elucidated using pathway analyses and functionally confirmed using siRNA knockdown experiments. The wealth of genomics data being produced using related and unrelated populations is creating many exciting opportunities leading to new insights into the genetic contribution and heritability of drug response.

EBV infection and MSI status significantly influence the clinical outcomes of gastric cancer patients

BACKGROUND

Epstein-Barr virus (EBV) and microsatellite instability (MSI) are associated with the carcinogenesis of many kinds of tumors, including gastric cancer (GC). However, the impact of EBV and MSI status on the prognosis of stage II and III GC is still unclear. The aim of this study was to find out the prognostic value of EBV and MSI status in a population of GC patients from Southern China.

METHODS

Patients were genotyped for EBV infection based on the detection of EBV DNA from the formalin-fixed paraffin-embedded (FFPE) specimens. Sequentially, MSI status was measured by direct sequencing. Clinical characteristics and overall survival (OS) were analyzed in 202 GC patients. Additionally, the association of EBV and MSI status with chemotherapy-based toxicity was analyzed in 324 GC patients.

RESULTS

The survival analysis revealed EBV+ patients had a poorer OS than EBV- patients (HR=1.75, 95% CI: 1.08-2.82, FDR p=0.04). This survival advantage for EBV- patients was also found in patients <60y (FDR p=0.04) and patient with stage III disease (FDR p=0.04).

CONCLUSIONS

EBV infection and MSI status are associated with overall survival of gastric cancer patients. However, traditional chemotherapy showed no difference on outcome of patients in EBV and MSI subgroups.

Cheminformatics approach to exploring and modeling trait-associated metabolite profiles

Developing predictive and transparent approaches to the analysis of metabolite profiles across patient cohorts is of critical importance for understanding the events that trigger or modulate traits of interest (e.g., disease progression, drug metabolism, chemical risk assessment). However, metabolites’ chemical structures are still rarely used in the statistical modeling workflows that establish these trait-metabolite relationships. Herein, we present a novel cheminformatics-based approach capable of identifying predictive, interpretable, and reproducible trait-metabolite relationships. As a proof-of-concept, we utilize a previously published case study consisting of metabolite profiles from non-small-cell lung cancer (NSCLC) adenocarcinoma patients and healthy controls. By characterizing each structurally annotated metabolite using both computed molecular descriptors and patient metabolite concentration profiles, we show that these complementary features enhance the identification and understanding of key metabolites associated with cancer. Ultimately, we built multi-metabolite classification models for assessing patients’ cancer status using specific groups of metabolites identified based on high structural similarity through chemical clustering. We subsequently performed a metabolic pathway enrichment analysis to identify potential mechanistic relationships between metabolites and NSCLC adenocarcinoma. This cheminformatics-inspired approach relies on the metabolites’ structural features and chemical properties to provide critical information about metabolite-trait associations. This method could ultimately facilitate biological understanding and advance research based on metabolomics data, especially with respect to the identification of novel biomarkers.

Comprehensive genomic characterization of five canine lymphoid tumor cell lines

BACKGROUND

Leukemia/lymphoma cell lines have been critical in the investigation of the pathogenesis and therapy of hematological malignancies. While human LL cell lines have generally been found to recapitulate the primary tumors from which they were derived, appropriate characterization including cytogenetic and transcriptional assessment is crucial for assessing their clinical predictive value.

RESULTS

In the following study, five canine LL cell lines, CLBL-1, Ema, TL-1 (Nody-1), UL-1, and 3132, were characterized using extensive immunophenotyping, karyotypic analysis, oligonucleotide array comparative genomic hybridization (oaCGH), and gene expression profiling. Genome-wide DNA copy number data from the cell lines were also directly compared with 299 primary canine round cell tumors to determine whether the cell lines represent primary tumors, and, if so, what subtype each most closely resembled.

CONCLUSIONS

Based on integrated analyses, CLBL-1 was classified as B-cell lymphoma, Ema and TL-1 as T-cell lymphoma, and UL-1 as T-cell acute lymphoblastic leukemia. 3132, originally classified as a B-cell lymphoma, was reclassified as a histiocytic sarcoma based on characteristic cytogenomic properties. In combination, these data begin to elucidate the clinical predictive value of these cell lines which will enhance the appropriate selection of in vitro models for future studies of canine hematological malignancies.

The AGMK1-9T7 cell model of neoplasia: Evolution of DNA copy-number aberrations and miRNA expression during transition from normal to metastatic cancer cells

To study neoplasia in tissue culture, cell lines representing the evolution of normal cells to tumor cells are needed. To produce such cells, we developed the AGMK1-9T7 cell line, established cell banks at 10-passage intervals, and characterized their biological properties. Here we examine the evolution of chromosomal DNA copy-number aberrations and miRNA expression in this cell line from passage 1 to the acquisition of a tumorigenic phenotype at passage 40. We demonstrated the use of a human microarray platform for DNA copy-number profiling of AGMK1-9T7 cells using knowledge of synteny to 'recode' data from human chromosome coordinates to those of the African green monkey. This approach revealed the accumulation of DNA copy-number gains and losses in AGMK1-9T7 cells from passage 3 to passage 40, which spans the period in which neoplastic transformation occurred. These alterations occurred in the sequences of genes regulating DNA copy-number imbalance of several genes that regulate endothelial cell angiogenesis, survival, migration, and proliferation. Regarding miRNA expression, 195 miRNAs were up- or down-regulated at passage 1 at levels that appear to be biologically relevant (i.e., log2 fold change >2.0 (q<0.05)). At passage 10, the number of up/down-regulated miRNAs fell to 63; this number increased to 93 at passage 40. Principal-component analysis grouped these miRNAs into 3 clusters; miRNAs in sub-clusters of these groups could be correlated with initiation, promotion, and progression, stages that have been described for neoplastic development. Thirty-four of the AGMK1-9T7 miRNAs have been associated with these stages in human cancer. Based on these data, we propose that the evolution of AGMK1-9T7 cells represents a detailed model of neoplasia in vitro.

Diet quality indices and changes in cognition during chemotherapy

PURPOSE

No evidence-based prevention strategies currently exist for cancer-related cognitive decline (CRCD). Although patients are often advised to engage in healthy lifestyle activities (e.g., nutritious diet), little is known about the impact of diet on preventing CRCD. This secondary analysis evaluated the association of pre-treatment diet quality indices on change in self-reported cognition during chemotherapy.

METHODS

Study participants (n = 96) completed the Block Brief Food Frequency Questionnaire (FFQ) before receiving their first infusion and the PROMIS cognitive function and cognitive abilities questionnaires before infusion and again 5 days later (i.e., when symptoms were expected to be their worst). Diet quality indices included the Dietary Approaches to Stop Hypertension (DASH), Alternate Mediterranean Diet (aMED), and a low carbohydrate diet index and their components. Descriptive statistics were generated for demographic and clinical variables and diet indices. Residualized change models were computed to examine whether diet was associated with change in cognitive function and cognitive abilities, controlling for age, sex, cancer type, treatment type, depression, and fatigue.

RESULTS

Study participants had a mean age of 59 ± 10.8 years and 69% were female. Although total diet index scores did not predict change in cognitive function or cognitive abilities, higher pre-treatment ratio of aMED monounsaturated/saturated fat was associated with less decline in cognitive function and cognitive abilities at 5-day post-infusion (P ≤ .001).

CONCLUSIONS

Higher pre-treatment ratio of monounsaturated/saturated fat intake was associated with less CRCD early in chemotherapy. Results suggest greater monounsaturated fat and less saturated fat intake could be protective against CRCD during chemotherapy.

Peri-operative anti-inflammatory drug use and seizure recurrence after resective epilepsy surgery: Target trials emulation

We conducted a retrospective observational study to examine whether anti-inflammatory medications prescribed peri-operatively of resective brain surgery can reduce long-term seizure recurrence for individuals with drug-resistant focal epilepsy. We used insurance-claims data from across the United States to screen medications prescribed to 1,993 individuals undergoing epilepsy. We then validated the results in a well-characterized cohort of 671 epilepsy patients from a major surgical center. Twelve medications met the screening criteria and were evaluated, identifying dexamethasone and zonisamide as potentially beneficial. Dexamethasone reduced seizure recurrence by 42% over 9 years of follow-up (hazard-ratio = 0.742; 95% CI = 0.662, 0.831), and zonisamide reduced recurrence by 33% (HR = 0.782; 95% CI = 0.667, 0.917). While dexamethasone could not be validated, analysis of zonisamide in the clinical cohort corroborated the beneficial effect (HR = 0.828; 95% CI = 0.706, 0.971). If prospectively validated, this study suggests surgeons could improve long-term outcomes of epilepsy surgery by medically reducing neuro-inflammation in the surgical bed.

Evidence that extracellular HSPB1 contributes to inflammation in alcohol-associated hepatitis

Background and aims

Alcohol-associated hepatitis (AH) is the most life-threatening form of alcohol-associated liver disease (ALD). AH is characterized by severe inflammation attributed to increased levels of ethanol, microbes or microbial components, and damage-associated molecular pattern (DAMP) molecules in the liver. HSPB1 (Heat Shock Protein Family B (Small) Member 1; also known as Hsp25/27) is a DAMP that is rapidly increased in and released from cells experiencing stress, including hepatocytes. The goal of this study was to define the role of HSPB1 in AH pathophysiology.

Methods

Serum HSPB1 was measured in a retrospective study of 184 heathy controls (HC), heavy alcohol consumers (HA), patients with alcohol-associated cirrhosis (AC), and patients with AH recruited from major hospital centers. HSPB1 was also retrospectively evaluated in liver tissue from 10 HC and AH patients and an existing liver RNA-seq dataset. Finally, HSPB1 was investigated in a murine Lieber-DeCarli diet model of early ALD as well as cellular models of ethanol stress in hepatocytes and hepatocyte-macrophage communication during ethanol stress.

Results

Circulating HSPB1 was significantly increased in AH patients and levels positively correlated with disease-severity scores. Likewise, HSPB1 was increased in the liver of patients with severe AH and in the liver of ethanol-fed mice. In vitro , ethanol-stressed hepatocytes released HSPB1, which then triggered TNFα-mediated inflammation in macrophages. Anti-HSPB1 antibody prevented TNFα release from macrophages exposed to media conditioned by ethanol-stressed hepatocytes.

Conclusions

Our findings support investigation of HSPB1 as both a biomarker and therapeutic target in ALD. Furthermore, this work demonstrates that anti-HSPB1 antibody is a rational approach to targeting HSPB1 with the potential to block inflammation and protect hepatocytes, without inactivating host defense.

GRAPHICAL ABSTRACT

HIGHLIGHTS

HSPB1 is significantly increased in serum and liver of patients with alcohol-associated hepatitis.Ethanol consumption leads to early increases in HSPB1 in the mouse liver.Hepatocytes subjected to ethanol stress release HSPB1 into the extracellular environment where it activates TNFα-mediated inflammation in macrophages.Anti-HSPB1 antibody blocks hepatocyte-triggered TNFα in a model of hepatocyte-macrophage communication during ethanol stress.

Genomic approaches to explore susceptibility and pathogenesis of alcohol use disorder and alcohol-associated liver disease

Excessive alcohol use is a major risk factor for the development of an alcohol use disorder (AUD) and contributes to a wide variety of other medical illnesses, including alcohol-associated liver disease (ALD). Both AUD and ALD are complex and causally interrelated diseases, and multiple factors other than alcohol consumption are implicated in the disease pathogenesis. While the underlying pathophysiology of AUD and ALD is complex, there is substantial evidence for a genetic susceptibility of both diseases. Current genome-wide association studies indicate that the genes associated with clinical AUD only poorly overlap with the genes identified for heavy drinking and, in turn, neither overlap with the genes identified for ALD. Uncovering the main genetic factors will enable us to identify molecular drivers underlying the pathogenesis, discover potential targets for therapy, and implement patient care early in disease progression. In this review, we described multiple genomic approaches and their implications to investigate the susceptibility and pathogenesis of both AUD and ALD. We concluded our review with a discussion of the knowledge gaps and future research on genomic studies in these 2 diseases.

Abstract LB-177: Novel approaches for improving interpretation and predictive models of comparative genomic hybridization data

As costs of genome wide analyses decline and become more accessible, their use in both human and animal cancer studies are generating increasing information regarding underlying cancer etiology. Comparative genomic hybridization (CGH) is providing valuable information relating copy number aberrations (CNAs) to cancer mechanisms and clinical outcomes. However, challenges exist to interpreting and fully utilizing these data. First, without matched tumor and healthy tissue samples from individuals, distinguishing naturally occurring copy number variations (CNVs) from CNAs is difficult. Second, the large search space of genome wide analyses makes finding combinations of CNAs with improved predictive potential compared to single CNAs challenging. Here we provide novel methods to address these challenges associated with CGH data. Many new resources (e.g. The Cancer Genome Atlas (TCGA)), are making large volumes of genomic data publically accessible. However, most datasets do not have matched normal and tumor tissue samples between subjects. We tested matched normal and tissue samples from 30 patients with colorectal, lung, and pancreatic cancer and compared CNVs and CNAs to findings in larger, non-matched samples in TCGA. Even with limited matched samples, this approach allows for the differentiation of CNVs from CNAs discovered in analyses of non-matched samples.

In some cases, combinations of CNAs can provide improved predictive capability compared to any single CNA. However, it is computationally intractable to exhaustively test combinations of CNAs in a genome-wide study. To address this limitation, we use a novel approach for CNA feature reduction that minimizes the variance within CNA segments across subjects, and Random Forest Ensemble Classification. This approach provides CNA combinations with balanced accuracies of 83.5% and 94.9% for distinguishing 52 cases of canine ALL/AML and 71 cases of B-CLL/T-CLL, respectively. These two approaches address frequent limitations in the interpretation CGH data. Better distinguishing CNVs and interrogating CNA combinations, can provide additional information about the role of CNAs in disease mechanisms and improve treatment decisions.

Citation Format: Daniel Rotroff, Matthew Breen, Alison Motsinger-Reif. Novel approaches for improving interpretation and predictive models of comparative genomic hybridization data. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr LB-177. doi:10.1158/1538-7445.AM2015-LB-177

GLI1+ perivascular, renal, progenitor cells: The likely source of spontaneous neoplasia that created the AGMK1-9T7 cell line

The AGMK1-9T7 cell line has been used to study neoplasia in tissue culture. By passage in cell culture, these cells evolved to become tumorigenic and metastatic in immunodeficient mice at passage 40. Of the 20 x 106 kidney cells originally plated, less than 2% formed the colonies that evolved to create this cell line. These cells could be the progeny of some type of kidney progenitor cells. To characterize these cells, we documented their renal lineage by their expression of PAX-2 and MIOX, detected by indirect immunofluorescence. These cells assessed by flow-cytometry expressed high levels of CD44, CD73, CD105, Sca-1, and GLI1 across all passages tested; these markers have been reported to be expressed by renal progenitor cells. The expression of GLI1 was confirmed by immunofluorescence and western blot analysis. Cells from passages 13 to 23 possessed the ability to differentiate into adipocytes, osteoblasts, and chondrocytes; after passage 23, their ability to form these cell types was lost. These data indicate that the cells that formed the AGMK1-9T7 cell line were GLI1+ perivascular, kidney, progenitor cells.

Combined Liver Transplant and Cardiac Surgery: Long-term Outcomes and Predictors of Success

OBJECTIVE

We aim to report our institutional outcomes of single-staged combined liver transplantation (LT) and cardiac surgery (CS).

BACKGROUND

Concurrent LT and CS is a potential treatment for combined cardiac dysfunction and end-stage liver disease, yet only 54 cases have been previously reported in the literature. Thus, the outcomes of this approach are relatively unknown, and this approach has been previously regarded as extremely risky.

METHODS

Thirty-one patients at our institution underwent combined CS and liver transplant. Patients with at least 1-year follow-up were included. The Leave-One-Out Cross-Validation machine-learning approach was used to generate a model for mortality.

RESULTS

Median follow-up was 8.2 years (IQR: 4.6-13.6 years). One- and 5-year survival was 74.2% (N=23) and 55% (N=17), respectively. Negative predictive factors of survival included recipient age >60 years ( P =0.036), nonalcoholic steatohepatitis-cirrhosis ( P =0.031), coronary artery bypass-graft (CABG)-based CS ( P =0.046), and preoperative renal dysfunction ( P =0.024). The final model demonstrated that renal dysfunction had a relative weighted impact of 3.2 versus CABG (1.7), age ≥60 years (1.7), or nonalcoholic steatohepatitis (1.3). Elevated LT+CS risk score was associated with an increased 5-year mortality after surgery (area under the curve=0.731, P =<0.001). Conversely, the widely accepted The Society of Thoracic Surgeons Predicted Risk of Mortality calculator was unable to successfully stratify patients according to 1-year ( P >0.99) or 5-year ( P =0.695) survival rates.

CONCLUSIONS

This is the largest series describing combined LT+CS, with joint surgical management appearing feasible in highly selected patients. CABG and preoperative renal dysfunction are important negative predictors of mortality. The 4-variable LT+CS score may help predict patients at high risk for postoperative mortality.

A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity

Introduction

We investigated the genetic determinants of variation in the hemoglobin glycation index (HGI), an emerging biomarker for the risk of diabetes complications.

Methods

We conducted a genome-wide association study (GWAS) for HGI in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (N = 7,913) using linear regression and additive genotype encoding on variants with minor allele frequency greater than 3%. We conducted replication analyses of top findings in the Atherosclerosis Risk in Communities (ARIC) study with inverse variance-weighted meta-analysis. We followed up with stratified GWAS analyses by sex and self-reported race.

Results

In ACCORD, we identified single nucleotide polymorphisms (SNPs) associated with HGI, including a peak with the strongest association at the intergenic SNP rs73407935 (7q11.22) (P = 5.8e-10) with a local replication in ARIC. In black individuals, the variant rs10739419 on chromosome 9 in the Whirlin (WHRN) gene formally replicated (meta-P = 2.2e-9). The SNP-based heritability of HGI was 0.39 (P< 1e-10). HGI had significant sex-specific associations with SNPs in or near GALNT11 in women and HECW2 in men. Finally, in Hispanic participants, we observed genome-wide significant associations with variants near USF1 and NXNL2/SPIN1.

Discussion

Many HGI-associated SNPs were distinct from those associated with fasting plasma glucose or HbA1c, lending further support for HGI as a distinct biomarker of diabetes complications. The results of this first evaluation of the genetic etiology of HGI indicate that it is highly heritable and point to heterogeneity by sex and race.

Pain Assessment in Osteoarthritis: Present Practices and Future Prospects Including the Use of Biomarkers and Wearable Technologies, and AI-Driven Personalized Medicine

Osteoarthritis (OA) is a highly prevalent chronic joint disorder affecting ~600 million individuals worldwide and is characterized by complex pain mechanisms that significantly impair patient quality of life. Challenges exist in accurately assessing and measuring pain in OA due to variations in pain perception among individuals and the heterogeneous nature of the disease. Conventional pain assessment methods, such as patient-reported outcome measures and clinical evaluations, often fail to fully capture the heterogeneity of pain experiences among individuals with OA. This review will summarize and evaluate current methods of pain assessment in OA and highlight future directions for standardized pain assessment. We discuss the role of animal models in enhancing our understanding of OA pain pathophysiology and highlight the necessity of translational research to advance pain assessment strategies. Key challenges explored include identifying phenotypes of pain susceptibility, integrating biomarkers into clinical practice, and adopting personalized pain management approaches through the incorporation of multi-modal data and multilevel analysis. We underscore the imperative for continued innovation in pain assessment and management to improve outcomes for patients with OA.

Macrovascular and microvascular complications in US Medicare enrollees with type 2 diabetes with and without atherosclerotic cardiovascular disease

AIMS

To assess the incidence of macrovascular and microvascular complications in US Medicare enrollees diagnosed with T2D with and without established ASCVD.

MATERIALS AND METHODS

We conducted a retrospective cohort study using Medicare fee-for-service claims data from 1 January 2006, through 31 December 2021. Baseline demographic and clinical characteristics were assessed in the 1-year prior to indexing. Cumulative incidences of various diabetes complications were assessed until the first microvascular or macrovascular complication of interest, the end of the study period or death.

RESULTS

A total of 2 326 726 patients and 640 666 patients met study inclusion/exclusion criteria for the T2D cohort and T2D + ASCVD sub-cohort, respectively. The incidence rate of any macrovascular event was 483.34 per 10 000 person-years in the T2D cohort. Overall, the 1-year cumulative incidence rate of any macrovascular event was 3.90%. Coronary heart disease (T2D, 3.24%; T2D + ASCVD, 8.10%) and peripheral artery disease (T2D, 1.97%; T2D + ASCVD, 7.33%) were the macrovascular events with the greatest 1-year cumulative incidence. Patients developed microvascular complications at a rate of 1569.28 per 10 000 person-years in the T2D cohort and 1859.80 per 10 000 person-years in the T2D + ASCVD sub-cohort. The 1-year cumulative incidence of any microvascular event was 16.88% in the T2D cohort and 21.16% in the T2D + ASCVD sub-cohort. Neuropathy and nephropathy were the microvascular events with the greatest 1-year cumulative incidence in both cohorts: T2D, 8.34% and 7.02%; T2D + ASCVD, 10.65% and 9.12%, respectively.

CONCLUSIONS

The frequencies of macrovascular and microvascular complications highlight the importance of annual cardiovascular risk assessment in patients with T2D, especially those with established ASCVD.