Reducing diagnostic delays in acute hepatic porphyria using health records data and machine learning.

BACKGROUND: Acute hepatic porphyria (AHP) is a group of rare but treatable conditions associated with diagnostic delays of 15 years on average. The advent of electronic health records (EHR) data and machine learning (ML) may improve the timely recognition of rare diseases like AHP. However, prediction models can be difficult to train given the limited case numbers, unstructured EHR data, and selection biases intrinsic to healthcare delivery. We sought to train and characterize models for identifying patients with AHP. METHODS: This diagnostic study used structured and notes-based EHR data from 2 centers at the University of California, UCSF (2012-2022) and UCLA (2019-2022). The data were split into 2 cohorts (referral and diagnosis) and used to develop models that predict (1) who will be referred for testing of acute porphyria, among those who presented with abdominal pain (a cardinal symptom of AHP), and (2) who will test positive, among those referred. The referral cohort consisted of 747 patients referred for testing and 99 849 contemporaneous patients who were not. The diagnosis cohort consisted of 72 confirmed AHP cases and 347 patients who tested negative. The case cohort was 81% female and 6-75 years old at the time of diagnosis. Candidate models used a range of architectures. Feature selection was semi-automated and incorporated publicly available data from knowledge graphs. Our primary outcome was the F-score on an outcome-stratified test set. RESULTS: The best center-specific referral models achieved an F-score of 86%-91%. The best diagnosis model achieved an F-score of 92%. To further test our model, we contacted 372 current patients who lack an AHP diagnosis but were predicted by our models as potentially having it (≥10% probability of referral, ≥50% of testing positive). However, we were only able to recruit 10 of these patients for biochemical testing, all of whom were negative. Nonetheless, post hoc evaluations suggested that these models could identify 71% of cases earlier than their diagnosis date, saving 1.2 years. CONCLUSIONS: ML can reduce diagnostic delays in AHP and other rare diseases. Robust recruitment strategies and multicenter coordination will be needed to validate these models before they can be deployed.

Reducing diagnostic delays in Acute Hepatic Porphyria using electronic health records data and machine learning: a multicenter development and validation study.

Importance: Acute Hepatic Porphyria (AHP) is a group of rare but treatable conditions associated with diagnostic delays of fifteen years on average. The advent of electronic health records (EHR) data and machine learning (ML) may improve the timely recognition of rare diseases like AHP. However, prediction models can be difficult to train given the limited case numbers, unstructured EHR data, and selection biases intrinsic to healthcare delivery. Objective: To train and characterize models for identifying patients with AHP. Design Setting and Participants: This diagnostic study used structured and notes-based EHR data from two centers at the University of California, UCSF (2012-2022) and UCLA (2019-2022). The data were split into two cohorts (referral, diagnosis) and used to develop models that predict: 1) who will be referred for testing of acute porphyria, amongst those who presented with abdominal pain (a cardinal symptom of AHP), and 2) who will test positive, amongst those referred. The referral cohort consisted of 747 patients referred for testing and 99,849 contemporaneous patients who were not. The diagnosis cohort consisted of 72 confirmed AHP cases and 347 patients who tested negative. Cases were female predominant and 6-75 years old at the time of diagnosis. Candidate models used a range of architectures. Feature selection was semi-automated and incorporated publicly available data from knowledge graphs. Main Outcomes and Measures: F-score on an outcome-stratified test set. Results: The best center-specific referral models achieved an F-score of 86-91%. The best diagnosis model achieved an F-score of 92%. To further test our model, we contacted 372 current patients who lack an AHP diagnosis but were predicted by our models as potentially having it (≥ 10% probability of referral, ≥ 50% of testing positive). However, we were only able to recruit 10 of these patients for biochemical testing, all of whom were negative. Nonetheless, post hoc evaluations suggested that these models could identify 71% of cases earlier than their diagnosis date, saving 1.2 years. Conclusions and Relevance: ML can reduce diagnostic delays in AHP and other rare diseases. Robust recruitment strategies and multicenter coordination will be needed to validate these models before they can be deployed.

Evidence-based consensus guidelines for the diagnosis and management of erythropoietic protoporphyria and X-linked protoporphyria.

Erythropoietic protoporphyria and X-linked protoporphyria are rare genetic photodermatoses. Limited expertise with these disorders among physicians leads to diagnostic delays. Here, we present evidence-based consensus guidelines for the diagnosis, monitoring, and management of erythropoietic protoporphyria and X-linked protoporphyria. A systematic literature review was conducted, and reviewed among subcommittees of experts, divided by topic. Consensus on guidelines was reached within each subcommittee and then among all members of the committee. The appropriate biochemical and genetic testing to establish the diagnosis is reviewed in addition to the interpretation of results. Prevention of symptoms, management of acute phototoxicity, and pharmacologic and nonpharmacologic treatment options are discussed. The importance of ongoing monitoring for liver disease, iron deficiency, and vitamin D deficiency is discussed with management guidance. Finally, management of pregnancy and surgery and the safety of other therapies are summarized. We emphasize that these are multisystemic disorders that require longitudinal monitoring. These guidelines provide a structure for evidence-based diagnosis and management for practicing physicians. Early diagnosis and management of these disorders are essential, particularly given the availability of new and emerging therapies.

Yield of Post-Acute Diverticulitis Colonoscopy for Ruling Out Colorectal Cancer.

Background and Aims: Colonoscopy is recommended post-acute diverticulitis (AD) to exclude underlying adenocarcinoma (CRC). However, post-AD colonoscopy utility remains controversial. We aimed to examine yield of post-AD colonoscopy in our majority-Hispanic patient population. Methods: Patients undergoing post-AD colonoscopy between 11/1/2015-7/31/2021 were identified from a prospectively maintained endoscopic database. AD cases without computed tomography confirmation were excluded. Pertinent data, including complicated vs uncomplicated AD, fecal immunochemical test (FIT) result post-AD/pre-colonoscopy, and number/type/location of non-advanced adenomas, advanced adenomas, and CRC, were abstracted. Analyses were conducted using two-sample Wilcoxon rank-sum and Fisher's exact tests. Results: 208 patients were included, of whom 62.0% had uncomplicated AD. Median age was 53, 54.3% were female, and 77.4% were Hispanic. Ninety non-advanced adenomas were detected in 45 patients (21.6%), in addition to advanced adenoma in eight patients (3.8%). Two patients (1.0%) had CRC, both of whom had complicated AD in the same location seen on imaging, and one of whom was FIT+ (the other had not undergone FIT). Patients with uncomplicated versus complicated AD had similarly low rates of advanced adenomas (4.7% vs. 2.5%, p=0.713). FIT data were available in 51 patients and positive in three (5.9%); non-advanced adenomas were found in all three FIT+ patients. No FIT- patient had an advanced adenoma or CRC. Conclusion: Colonoscopy post-AD is generally low yield, with CRC being rare and found only in those with complicated AD. Colonoscopy post-complicated AD appears advisable, whereas less invasive testing (e.g. FIT) may be considered post-uncomplicated AD to inform the need for colonoscopy.

Predictive Modeling of Colonoscopic Findings in a Fecal Immunochemical Test-Based Colorectal Cancer Screening Program.

BACKGROUND: The fecal immunochemical test (FIT) is the primary modality used by the Los Angeles County Department of Health Services (LADHS) for colorectal cancer (CRC) screening in average-risk patients. Some patients referred for FIT-positive diagnostic colonoscopy have neither adenomas nor more advanced pathology. We aimed to identify predictors of false-positive FIT (FP-FIT) results in our largely disenfranchised, low socioeconomic status population. METHODS: We conducted a retrospective study of 596 patients who underwent diagnostic colonoscopy following a positive screening FIT. Colonoscopies showing adenomas (or more advanced pathology) were considered positive. We employed multiple logistic and linear regression as well as machine learning models (MLMs) to identify clinical predictors of FP-FIT (primary outcome) and the presence of advanced adenomas (secondary outcome). RESULTS: Overall, 268 patients (45.0%) had a FP-FIT. Female sex and hemorrhoids (odds ratios [ORs] 1.59 and 1.89, respectively) were associated with increased odds of FP-FIT and fewer advanced adenomas (ß = - 0.658 and - 0.516, respectively). Conversely, increasing age and BMI (ORs 0.94 and 0.96, respectively) were associated with decreased odds of FP-FIT and a greater number of advanced adenomas (ß = 0.073 and 0.041, respectively). MLMs predicted FP-FIT with high specificity (93.8%) and presence of advanced adenoma with high sensitivity (94.4%). CONCLUSION: Increasing age and BMI are associated with lower odds of FP-FIT and greater number of advanced adenomas, while female sex and hemorrhoids are associated with higher odds of FP-FIT and fewer advanced adenomas. The presence of the aforementioned predictors may inform the decision to proceed with diagnostic colonoscopy in FIT-positive patients.

The Genetic Architecture of Carbon Tetrachloride-Induced Liver Fibrosis in Mice.

BACKGROUND & AIMS: Liver fibrosis is a multifactorial trait that develops in response to chronic liver injury. Our aim was to characterize the genetic architecture of carbon tetrachloride (CCl4)-induced liver fibrosis using the Hybrid Mouse Diversity Panel, a panel of more than 100 genetically distinct mouse strains optimized for genome-wide association studies and systems genetics. METHODS: Chronic liver injury was induced by CCl4 injections twice weekly for 6 weeks. Four hundred thirty-seven mice received CCl4 and 256 received vehicle, after which animals were euthanized for liver histology and gene expression. Using automated digital image analysis, we quantified fibrosis as the collagen proportionate area of the whole section, excluding normal collagen. RESULTS: We discovered broad variation in fibrosis among the Hybrid Mouse Diversity Panel strains, demonstrating a significant genetic influence. Genome-wide association analyses revealed significant and suggestive loci underlying susceptibility to fibrosis, some of which overlapped with loci identified in mouse crosses and human population studies. Liver global gene expression was assessed by RNA sequencing across the strains, and candidate genes were identified using differential expression and expression quantitative trait locus analyses. Gene set enrichment analyses identified the underlying pathways, of which stellate cell involvement was prominent, and coexpression network modeling identified modules associated with fibrosis. CONCLUSIONS: Our results provide a rich resource for the design of experiments to understand mechanisms underlying fibrosis and for rational strain selection when testing antifibrotic drugs.

Reactivation of Hepatitis B Virus: A Review of Clinical Guidelines.

http://aasldpubs.onlinelibrary.wiley.com/hub/journal/10.1002/(ISSN)2046-2484/video/15-4-reading-myint a video presentation of this article https://www.wileyhealthlearning.com/Activity/7088610/disclaimerspopup.aspx questions and earn CME.

Diesel Exhaust Induces Mitochondrial Dysfunction, Hyperlipidemia, and Liver Steatosis.

OBJECTIVE: Air pollution is associated with increased cardiovascular morbidity and mortality, as well as dyslipidemia and metabolic syndrome. Our goal was to dissect the mechanisms involved. Approach and Results: We assessed the effects of exposure to air pollution on lipid metabolism in mice through assessment of plasma lipids and lipoproteins, oxidized fatty acids 9-HODE (9-hydroxyoctadecadienoic) and 13-HODE (13-hydroxyoctadecadienoic), lipid, and carbohydrate metabolism. Findings were corroborated, and mechanisms were further assessed in HepG2 hepatocytes in culture. ApoE knockout mice exposed to inhaled diesel exhaust (DE, 6 h/d, 5 days/wk for 16 weeks) exhibited elevated plasma cholesterol and triglyceride levels, increased hepatic triglyceride content, and higher hepatic levels of 9-HODE and 13-HODE, as compared to control mice exposed to filtered air. A direct effect of DE exposure on hepatocytes was demonstrated by treatment of HepG2 cells with a methanol extract of DE particles followed by loading with oleic acid. As observed in vivo, this led to increased triglyceride content and significant downregulation of ACAD9 mRNA expression. Treatment of HepG2 cells with DE particles and oleic acid did not alter de novo lipogenesis but inhibited total, mitochondrial, and ATP-linked oxygen consumption rate, indicative of mitochondrial dysfunction. Treatment of isolated mitochondria, prepared from mouse liver, with DE particles and oleic acid also inhibited mitochondrial complex activity and ß-oxidation. CONCLUSIONS: DE exposure leads to dyslipidemia and liver steatosis in ApoE knockout mice, likely due to mitochondrial dysfunction and decreased lipid catabolism.

The Genetic Architecture of Diet-Induced Hepatic Fibrosis in Mice.

We report the genetic analysis of a "humanized" hyperlipidemic mouse model for progressive nonalcoholic steatohepatitis (NASH) and fibrosis. Mice carrying transgenes for human apolipoprotein E*3-Leiden and cholesteryl ester transfer protein and fed a "Western" diet were studied on the genetic backgrounds of over 100 inbred mouse strains. The mice developed hepatic inflammation and fibrosis that was highly dependent on genetic background, with vast differences in the degree of fibrosis. Histological analysis showed features characteristic of human NASH, including macrovesicular steatosis, hepatocellular ballooning, inflammatory foci, and pericellular collagen deposition. Time course experiments indicated that while hepatic triglyceride levels increased steadily on the diet, hepatic fibrosis occurred at about 12 weeks. We found that the genetic variation predisposing to NASH and fibrosis differs markedly from that predisposing to simple steatosis, consistent with a multistep model in which distinct genetic factors are involved. Moreover, genome-wide association identified distinct genetic loci contributing to steatosis and NASH. Finally, we used hepatic expression data from the mouse panel and from 68 bariatric surgery patients with normal liver, steatosis, or NASH to identify enriched biological pathways. Conclusion: The pathways showed substantial overlap between our mouse model and the human disease.

Skeletal muscle action of estrogen receptor α is critical for the maintenance of mitochondrial function and metabolic homeostasis in females.

Impaired estrogen receptor α (ERα) action promotes obesity and metabolic dysfunction in humans and mice; however, the mechanisms underlying these phenotypes remain unknown. Considering that skeletal muscle is a primary tissue responsible for glucose disposal and oxidative metabolism, we established that reduced ERα expression in muscle is associated with glucose intolerance and adiposity in women and female mice. To test this relationship, we generated muscle-specific ERα knockout (MERKO) mice. Impaired glucose homeostasis and increased adiposity were paralleled by diminished muscle oxidative metabolism and bioactive lipid accumulation in MERKO mice. Aberrant mitochondrial morphology, overproduction of reactive oxygen species, and impairment in basal and stress-induced mitochondrial fission dynamics, driven by imbalanced protein kinase A-regulator of calcineurin 1-calcineurin signaling through dynamin-related protein 1, tracked with reduced oxidative metabolism in MERKO muscle. Although muscle mitochondrial DNA (mtDNA) abundance was similar between the genotypes, ERα deficiency diminished mtDNA turnover by a balanced reduction in mtDNA replication and degradation. Our findings indicate the retention of dysfunctional mitochondria in MERKO muscle and implicate ERα in the preservation of mitochondrial health and insulin sensitivity as a defense against metabolic disease in women.

Liver X receptors balance lipid stores in hepatic stellate cells through Rab18, a retinoid responsive lipid droplet protein.

UNLABELLED: Liver X receptors (LXRs) are determinants of hepatic stellate cell (HSC) activation and liver fibrosis. Freshly isolated HSCs from Lxrαß(-/-) mice have increased lipid droplet (LD) size, but the functional consequences of this are unknown. Our aim was to determine whether LXRs link cholesterol to retinoid storage in HSCs and how this impacts activation. Primary HSCs from Lxrαß(-/-) and wild-type mice were profiled by gene array during in vitro activation. Lipid content was quantified by high-performance liquid chromatography and mass spectroscopy. Primary HSCs were treated with nuclear receptor ligands, transfected with small interfering RNA and plasmid constructs, and analyzed by immunocytochemistry. Lxrαß(-/-) HSCs have increased cholesterol and retinyl esters. The retinoid increase drives intrinsic retinoic acid receptor signaling, and activation occurs more rapidly in Lxrαß(-/-) HSCs. We identify Rab18 as a novel retinoic acid-responsive, LD-associated protein that helps mediate stellate cell activation. Rab18 mRNA, protein, and membrane insertion increase during activation. Both Rab18 guanosine triphosphatase activity and isoprenylation are required for stellate cell LD loss and induction of activation markers. These phenomena are accelerated in Lxrαß(-/-) HSCs, where there is greater retinoic acid flux. Conversely, Rab18 knockdown retards LD loss in culture and blocks activation, just like the functional mutants. Rab18 is also induced with acute liver injury in vivo. CONCLUSION: Retinoid and cholesterol metabolism are linked in stellate cells by the LD-associated protein Rab18. Retinoid overload helps explain the profibrotic phenotype of Lxrαß(-/-) mice, and we establish a pivotal role for Rab18 GTPase activity and membrane insertion in wild-type stellate cell activation. Interference with Rab18 may have significant therapeutic benefit in ameliorating liver fibrosis.

Positron emission tomography probe demonstrates a striking concentration of ribose salvage in the liver.

PET is a powerful technique for quantifying and visualizing biochemical pathways in vivo. Here, we develop and validate a novel PET probe, [(18)F]-2-deoxy-2-fluoroarabinose ([(18)F]DFA), for in vivo imaging of ribose salvage. DFA mimics ribose in vivo and accumulates in cells following phosphorylation by ribokinase and further metabolism by transketolase. We use [(18)F]DFA to show that ribose preferentially accumulates in the liver, suggesting a striking tissue specificity for ribose metabolism. We demonstrate that solute carrier family 2, member 2 (also known as GLUT2), a glucose transporter expressed in the liver, is one ribose transporter, but we do not know if others exist. [(18)F]DFA accumulation is attenuated in several mouse models of metabolic syndrome, suggesting an association between ribose salvage and glucose and lipid metabolism. These results describe a tool for studying ribose salvage and suggest that plasma ribose is preferentially metabolized in the liver.

Reciprocal regulation of hepatic and adipose lipogenesis by liver X receptors in obesity and insulin resistance.

Liver X receptors (LXRs) regulate lipogenesis and inflammation, but their contribution to the metabolic syndrome is unclear. We show that LXRs modulate key aspects of the metabolic syndrome in mice. LXRαß-deficient-ob/ob (LOKO) mice remain obese but show reduced hepatic steatosis and improved insulin sensitivity compared to ob/ob mice. Impaired hepatic lipogenesis in LOKO mice is accompanied by reciprocal increases in adipose lipid storage, reflecting tissue-selective effects on the SREBP, PPARγ, and ChREBP lipogenic pathways. LXRs are essential for obesity-driven SREBP-1c and ChREBP activity in liver, but not fat. Furthermore, loss of LXRs in obesity promotes adipose PPARγ and ChREBP-ß activity, leading to improved insulin sensitivity. LOKO mice also exhibit defects in ß cell mass and proliferation despite improved insulin sensitivity. Our data suggest that sterol sensing by LXRs in obesity is critically linked with lipid and glucose homeostasis and provide insight into the complex relationships between LXR and insulin signaling.

Hybrid mouse diversity panel: a panel of inbred mouse strains suitable for analysis of complex genetic traits.

We have developed an association-based approach using classical inbred strains of mice in which we correct for population structure, which is very extensive in mice, using an efficient mixed-model algorithm. Our approach includes inbred parental strains as well as recombinant inbred strains in order to capture loci with effect sizes typical of complex traits in mice (in the range of 5% of total trait variance). Over the last few years, we have typed the hybrid mouse diversity panel (HMDP) strains for a variety of clinical traits as well as intermediate phenotypes and have shown that the HMDP has sufficient power to map genes for highly complex traits with resolution that is in most cases less than a megabase. In this essay, we review our experience with the HMDP, describe various ongoing projects, and discuss how the HMDP may fit into the larger picture of common diseases and different approaches.

The number of x chromosomes causes sex differences in adiposity in mice.

Sexual dimorphism in body weight, fat distribution, and metabolic disease has been attributed largely to differential effects of male and female gonadal hormones. Here, we report that the number of X chromosomes within cells also contributes to these sex differences. We employed a unique mouse model, known as the "four core genotypes," to distinguish between effects of gonadal sex (testes or ovaries) and sex chromosomes (XX or XY). With this model, we produced gonadal male and female mice carrying XX or XY sex chromosome complements. Mice were gonadectomized to remove the acute effects of gonadal hormones and to uncover effects of sex chromosome complement on obesity. Mice with XX sex chromosomes (relative to XY), regardless of their type of gonad, had up to 2-fold increased adiposity and greater food intake during daylight hours, when mice are normally inactive. Mice with two X chromosomes also had accelerated weight gain on a high fat diet and developed fatty liver and elevated lipid and insulin levels. Further genetic studies with mice carrying XO and XXY chromosome complements revealed that the differences between XX and XY mice are attributable to dosage of the X chromosome, rather than effects of the Y chromosome. A subset of genes that escape X chromosome inactivation exhibited higher expression levels in adipose tissue and liver of XX compared to XY mice, and may contribute to the sex differences in obesity. Overall, our study is the first to identify sex chromosome complement, a factor distinguishing all male and female cells, as a cause of sex differences in obesity and metabolism.

Coordinate regulation of neutrophil homeostasis by liver X receptors in mice.

The most abundant immune cell type is the neutrophil, a key first responder after pathogen invasion. Neutrophil numbers in the periphery are tightly regulated to prevent opportunistic infections and aberrant inflammation. In healthy individuals, more than 1 × 109 neutrophils per kilogram body weight are released from the bone marrow every 24 hours. To maintain homeostatic levels, an equivalent number of senescent cells must be cleared from circulation. Recent studies indicate that clearance of senescent neutrophils by resident tissue macrophages and DCs helps to set homeostatic levels of neutrophils via effects on the IL-23/IL-17/G-CSF cytokine axis, which stimulates neutrophil production in the bone marrow. However, the molecular events in phagocytes underlying this feedback loop have remained indeterminate. Liver X receptors (LXRs) are members of the nuclear receptor superfamily that regulate both lipid metabolic and inflammatory gene expression. Here, we demonstrate that LXRs contribute to the control of neutrophil homeostasis. Using gain- and loss-of-function models, we found that LXR signaling regulated the efficient clearance of senescent neutrophils by peripheral tissue APCs in a Mer-dependent manner. Furthermore, activation of LXR by engulfed neutrophils directly repressed the IL-23/IL-17/G-CSF granulopoietic cytokine cascade. These results provide mechanistic insight into the molecular events orchestrating neutrophil homeostasis and advance our understanding of LXRs as integrators of phagocyte function, lipid metabolism, and cytokine gene expression.