Analysis of MRI-derived spleen iron in the UK Biobank identifies genetic variation linked to iron homeostasis and hemolysis

Tissue Iron Distribution in Anemic Patients with End-Stage Kidney Disease: Results of a Pilot Study

Background/Objectives: Anemia is a frequent multifactorial co-morbidity in end-stage kidney disease (ESKD) associated with morbidity and poor QoL. Apart from insufficient erythropoietin formation, iron deficiency (ID) contributes to anemia development. Identifying patients in need of iron supplementation with current ID definitions is difficult since no good biomarker is available to detect actual iron needs. Therefore, new diagnostic tools to guide therapy are needed. Methods: We performed a prospective cohort study analyzing tissue iron content with MRI-based R2*-relaxometry in 20 anemic ESKD patients and linked it with iron biomarkers in comparison to 20 otherwise healthy individuals. Results: ESKD patients had significantly higher liver (90.1 s-1 vs. 36.1 s-1, p < 0.001) and spleen R2* values (119.8 s-1 vs. 19.3 s-1, p < 0.001) compared to otherwise healthy individuals, while their pancreas and heart R2* values did not significantly differ. Out of the 20 ESKD patients, 17 had elevated spleen and 12 had elevated liver R2* values. KDIGO guidelines (focusing on serum iron parameters) would recommend iron supplementation in seven patients with elevated spleen and four patients with elevated liver R2* values. Conclusions: These findings highlight that liver and especially spleen iron concentrations are significantly higher in ESKD patients compared to controls. Tissue iron overload diverged from classical iron parameters suggesting need of iron supplementation. Measurement of MRI-guided tissue iron distribution might help guide treatment of anemic ESKD patients.

Multi-organ imaging-derived polygenic indexes for brain and body health

The UK Biobank (UKB) imaging project is a crucial resource for biomedical research, but is limited to 100,000 participants due to cost and accessibility barriers. Here we used genetic data to predict heritable imaging-derived phenotypes (IDPs) for a larger cohort. We developed and evaluated 4,375 IDP genetic scores (IGS) derived from UKB brain and body images. When applied to UKB participants who were not imaged, IGS revealed links to numerous phenotypes and stratified participants at increased risk for both brain and somatic diseases. For example, IGS identified individuals at higher risk for Alzheimer's disease and multiple sclerosis, offering additional insights beyond traditional polygenic risk scores of these diseases. When applied to independent external cohorts, IGS also stratified those at high disease risk in the All of Us Research Program and the Alzheimer's Disease Neuroimaging Initiative study. Our results demonstrate that, while the UKB imaging cohort is largely healthy and may not be the most enriched for disease risk management, it holds immense potential for stratifying the risk of various brain and body diseases in broader external genetic cohorts.

Spleen volume is independently associated with non-alcoholic fatty liver disease, liver volume and liver fibrosis

Non-alcoholic fatty liver disease (NAFLD) can lead to irreversible liver damage manifesting in systemic effects (e.g., elevated portal vein pressure and splenomegaly) with increased risk of deadly outcomes. However, the association of spleen volume with NAFLD and related type 2-diabetes (T2D) is not fully understood. The UK Biobank contains comprehensive health-data of 500,000 participants, including clinical data and MR images of >40,000 individuals. The present study estimated the spleen volume of 37,066 participants through automated deep learning-based image segmentation of neck-to-knee MR images. The aim was to investigate the associations of spleen volume with NAFLD, T2D and liver fibrosis, while adjusting for natural confounders. The recent redefinition and new designation of NAFLD to metabolic dysfunction-associated steatotic liver disease (MASLD), promoted by major organisations of studies on liver disease, was not employed as introduced after the conduct of this study. The results showed that spleen volume decreased with age, correlated positively with body size and was smaller in females compared to males. Larger spleens were observed in subjects with NAFLD and T2D compared to controls. Spleen volume was also positively and independently associated with liver fat fraction, liver volume and the fibrosis-4 score, with notable volumetric increases already at low liver fat fractions and volumes, but not independently associated with T2D. These results suggest a link between spleen volume and NAFLD already at an early stage of the disease, potentially due to initial rise in portal vein pressure.

Combined metabolomic and proteomic analysis of sepsis related acute liver injury and its pathogenesis research

BACKGROUND

Sepsis-induced acute liver injury is common in patients in intensive care units. However, the exact mechanism of this condition remains unclear. The purpose of this study was to investigate the roles and mechanisms of proteins and metabolites in the liver tissue of mice after sepsis and elucidate the molecular biological mechanisms of sepsis-related liver injury.

METHODS

First, a lipopolysaccharide (LPS)-induced sepsis mouse model was established. Then, according to alanine aminotransferase (ALT) and aspartate aminotransferase (AST) detection in mouse serum and liver histopathological examination (HE) staining, the septic mice were divided into two groups: acute liver injury after sepsis and nonacute liver injury after sepsis. Metabolomics and proteomic analyses were performed on the liver tissues of the two groups of mice to identify significantly different metabolites and proteins. The metabolomics and proteomics results were further analysed to identify the biological indicators and pathogenesis related to the occurrence and development of sepsis-related acute liver injury at the protein and metabolite levels.

RESULTS

A total of 14 differentially expressed proteins and 46 differentially expressed metabolites were identified. Recombinant Erythrocyte Membrane Protein Band 4.2 (Epb42) and adenosine diphosphate (ADP) may be the key proteins and metabolites responsible for sepsis-related acute liver injury, according to the correlation analysis of proteomics and metabolomics. The expression of the differential protein Epb42 was further verified by western blot (WB) detection.

CONCLUSIONS

Our study suggests that the differential protein Epb42 may be key proteins causing sepsis-associated acute liver injury, providing new and valuable information on the possible mechanism of sepsis-associated acute liver injury.

Survival analysis of patients with extrahepatic cholangiocarcinoma: a nomogram for clinical and MRI features

BACKGROUND

This study aimed to establish a predictive model to estimate the postoperative prognosis of patients with extrahepatic cholangiocarcinoma (ECC) based on preoperative clinical and MRI features.

METHODS

A total of 104 patients with ECC confirmed by surgery and pathology were enrolled from January 2013 to July 2021, whose preoperative clinical, laboratory, and MRI data were retrospectively collected and examined, and the effects of clinical and imaging characteristics on overall survival (OS) were analyzed by constructing Cox proportional hazard regression models. A nomogram was constructed to predict OS, and calibration curves and time-dependent receiver operating characteristic (ROC) curves were employed to assess OS accuracy.

RESULTS

Multivariate regression analyses revealed that gender, DBIL, ALT, GGT, tumor size, lesion's position, the signal intensity ratio of liver to paraspinal muscle (SIRLiver/Muscle), and the signal intensity ratio of spleen to paraspinal muscle (SIRSpleen/Muscle) on T2WI sequences were significantly associated with OS, and these variables were included in a nomogram. The concordance index of nomogram for predicting OS was 0.766, and the AUC values of the nomogram predicting 1-year and 2-year OS rates were 0.838 and 0.863, respectively. The calibration curve demonstrated good agreement between predicted and observed OS. 5-fold and 10-fold cross-validation show good stability of nomogram predictions.

CONCLUSIONS

Our nomogram based on clinical, laboratory, and MRI features well predicted OS of ECC patients, and could be considered as a convenient and personalized prediction tool for clinicians to make decisions.

Using artificial intelligence to improve body iron quantification: A scoping review

This scoping review explores the potential of artificial intelligence (AI) in enhancing the screening, diagnosis, and monitoring of disorders related to body iron levels. A systematic search was performed to identify studies that utilize machine learning in iron-related disorders. The search revealed a wide range of machine learning algorithms used by different studies. Notably, most studies used a single data type. The studies varied in terms of sample sizes, participant ages, and geographical locations. AI's role in quantifying iron concentration is still in its early stages, yet its potential is significant. The question is whether AI-based diagnostic biomarkers can offer innovative approaches for screening, diagnosing, and monitoring of iron overload and anemia.

Tissue iron distribution in patients with anemia of inflammation: Results of a pilot study

Anemia of inflammation (AI) is frequently present in subjects with inflammatory disorders, primarily caused by inflammation-driven iron retention in macrophages. So far, only limited data on qualitative and quantitative estimates of tissue iron retention in AI patients exist. We performed a prospective cohort study analyzing splenic, hepatic, pancreatic, and cardiac iron content with MRI-based R2*-relaxometry in AI patients, including subjects with concomitant true iron deficiency (AI+IDA) hospitalized between 05/2020-01/2022. Control groups were individuals without inflammation. Spleen R2* values in AI patients with ferritin ≤200 μg/L (AI+IDA) were comparable with those found in controls. In AI patients with ferritin >200 μg/L, spleen (47.6 s^-1 vs. 19.3 s^-1 , p < .001) and pancreatic R2* values (32.5 s^-1 vs. 24.9 s^-1 , p = .011) were significantly higher compared with controls, while liver and heart R2*-values did not differ. Higher spleen R2* values were associated with higher ferritin, hepcidin, CRP, and IL-6 concentrations. Spleen R2* values normalized in AI patients after recovery (23.6 s^-1 vs. 47.6 s^-1 , p = .008), while no changes were found in patients with baseline AI+IDA. This is the first study investigating tissue iron distribution in patients with inflammatory anemia and AI with concomitant true iron deficiency. The results support the findings in animal models demonstrating iron retention in macrophages, which are primarily accumulating in the spleen under inflammatory conditions. MRI-related iron measurement may help to better characterize actual iron needs and to define better biomarker thresholds in the diagnosis of true ID in patients with AI. It may qualify as a useful diagnostic method to estimate the need for iron supplementation and to guide therapy.