Impact of environmental factors on alloimmunity and transplant fate

Value of blood lipid in predicting graft dysfunction after organ and tissue transplantation: A study of Mendelian randomization

Background

While immunosuppressive regimens have improved outcomes in solid organ transplantation, non-immune factors have also been identified as contributors to graft prognosis. Age, gender, hormones, heredity, and other diseases have been recognized to affect organ transplantation. However, the causal relationship between blood lipids and graft dysfunction remains unverified in human clinical investigations. In this study, we employed two-sample Mendelian randomization (MR) to examine the causality between different types of blood lipids and graft dysfunction following organ and tissue transplantation.

Methods

We conducted a two-sample MR study using available genome-wide association summary data from the online database MRBASE (http://app.mrbase.org/), which encompasses over 11 billion associations between genetic factors and health-related outcomes, enabling researchers to explore various potential determinants of poor health. The exposure factors included four types of blood lipids: high-density lipoprotein, low-density lipoprotein, cholesterol, and triglycerides. For each exposure factor, three databases were selected for analysis. The outcome factor was the failure and rejection of transplanted organs and tissues. All databases consisted of European population samples, without specific subgroups. The related studies were conducted between 2016 and 2022, and the "TwoSampleMR" R package was employed for variant selection.

Results

A total of 13 sample groups were collected and analyzed. The results revealed a causal association between blood lipids and graft dysfunction following organ and tissue transplantation. Specifically, the two-sample MR analysis confirmed that low-density lipoprotein and cholesterol levels were significant risk factors for increased graft dysfunction risk after transplantation. Moreover, high-density lipoprotein potentially reduced the risk of allograft dysfunction, while triglycerides possibly elevated the risk.

Conclusions

Our recent study provides the initial confirmation that blood lipids may initiate causal pathological processes leading to graft dysfunction after organ and tissue transplantation.

Place-based heterogeneity in lung transplant recipient outcomes

Place is defined as a social or environmental area of residence with meaning to a patient. We hypothesize there is an association between place and the clinical outcomes of lung transplant recipients in the United States. In a retrospective cohort study of transplants between January 1, 2010, and December 31, 2019, in the Scientific Registry of Transplant Recipients, multivariable Cox regression models were used to test the association between place (through social and environmental factors) with readmission, lung rejection, and survival. Among 18,465 recipients, only 20% resided in the same county as the transplant center. Recipients from the most socially vulnerable counties when compared to the least vulnerable were more likely to have COPD as a native disease, Black or African American race, and travel long distances to reach a transplant center. Higher local life expectancy was associated with lower likelihood for readmission (odds ratio [OR] = 0.90, 95% confidence interval [CI]: 0.84, 0.98, p = .01). Higher social vulnerability was associated with a higher likelihood of lung rejection (OR = 1.37, [CI]: 1.07, 1.76, p = .01). There was no association of residence with posttransplant survival. Recipient place-based factors were associated with complications and processes of care after transplant and warrant further investigation.

Effect of the similarity of gut microbiota composition between donor and recipient on graft function after living donor kidney transplantation

Graft outcomes of unrelated donor kidney transplant are comparable with those of related donor kidney transplant despite their genetic distance. This study aimed to identify whether the similarity of donor–recipient gut microbiota composition affects early transplant outcomes. Stool samples from 67 pairs of kidney transplant recipients and donors were collected. Gut microbiota differences between donors and recipients were determined using weighted UniFrac distance. Among the donor–recipient pairs, 30 (44.8%) pairs were related, while 37 (55.2%) were unrelated. The unrelated pairs, especially spousal pairs, had similar microbial composition, and they more frequently shared their meals than related pairs did. The weighted UniFrac distance showed an inverse correlation with the 6-month allograft function (p = 0.034); the correlation was significant in the unrelated pairs (p = 0.003). In the unrelated pairs, the microbial distance showed an excellent accuracy in predicting the estimated glomerular filtration rate of < 60 mL/min/1.73 m² at 6-months post-transplantation and was better than human leukocyte antigen incompatibility and rejection. The incidence of infection within 6 months post-transplantation increased in the recipients having dissimilar microbiota with donors compared to the other recipients. Thus, pre-transplantation microbial similarity in unrelated donors and recipients may be associated with 6-month allograft function.

A simple segmentation and quantification method for numerical quantitative analysis of cells and tissues

BACKGROUND

Microscopic image analysis based on image processing is required for quantitative evaluation of decellularization. Existing methods are not widely used because of expensive commercial software, and machine learning-based techniques lack generality for decellularization because many high-resolution image data has to be processed.

OBJECTIVE

In this study, we developed an image processing algorithm for quantitative analysis of tissues and cells in a general microscopic image.

METHODS

The proposed method extracts the color images obtained by the microscope into reference images consisting of grayscale, red (R), green (G), and blue (B) information and transforms each into a binary image. The transformed images were extracted by separating the cells and tissues through outlier noise elimination, logical multiplication and labeling. In order to verify the method, decellularization of porcine arotic valve was performed by the electrical method. Slice samples were obtained by time and the proposed method was applied.

RESULTS

The experimental results show that the segmentation of cells and tissues, and quantitative analysis of the number of cells and changes in tissue area during the decellularization process was possible.

CONCLUSIONS

The proposed method shows that cell and tissue extraction and quantitative numerical analysis were possible in different brightness of microscopic images.

Hyperlipidemia and Allograft Rejection

Purpose of review

Advances in the development of immunosuppressive drug regimens have led to impressive survival rates in the year following organ transplantation. However rates of long-term graft dysfunction remain undesirably high. Recently it has been shown that co-morbidities in the patient population may affect graft survival. In mouse models, hyperlipidemia, a co-morbidity present in the majority of cardiac transplant patients, can significantly alter T cell responses to cardiac and skin allografts, and accelerate graft rejection. Here we review recent advances in our understanding of how alterations in lipids affect immune function and graft survival.

Recent Findings

Recent work in humans has highlighted the importance of controlling low density lipoprotein (LDL) levels in transplant recipients to reduce the development of chronic allograft vasculopathy (CAV). High serum levels of cholesterol containing particles leads to extensive immune system changes to T cell proliferation, differentiation and suppression. Changes in B cell subsets, and the ability of antigen presenting cells to stimulate T cells in hyperlipidemic animals may also contribute to increased organ allograft rejection.

Summary

Cholesterol metabolism is a critical cellular pathway for proper control of immune cell homeostasis and activation. Increasing evidence in both human, and in mouse models shows that elevated levels of serum cholesterol can have profound impact on the immune system. Hyperlipidemia has been shown to increase T cell activation, alter the development of T helper subsets, increase the inflammatory capacity of antigen presenting cells (APC) and significantly accelerate graft rejection in several models.

A large, international study on post-transplant glomerular diseases: the TANGO project

Background

Long-term outcomes in kidney transplantation (KT) have not significantly improved during the past twenty years. Despite being a leading cause of graft failure, glomerular disease (GD) recurrence remains poorly understood, due to heterogeneity in disease pathogenesis and clinical presentation, reliance on histopathology to confirm disease recurrence, and the low incidence of individual GD subtypes. Large, international cohorts of patients with GD are urgently needed to better understand the disease pathophysiology, predictors of recurrence, and response to therapy.

Methods

The Post-TrANsplant GlOmerular Disease (TANGO) study is an observational, multicenter cohort study initiated in January 2017 that aims to: 1) characterize the natural history of GD after KT, 2) create a biorepository of saliva, blood, urine, stools and kidney tissue samples, and 3) establish a network of patients and centers to support novel therapeutic trials. The study includes 15 centers in America and Europe. Enrollment is open to patients with biopsy-proven GD prior to transplantation, including IgA nephropathy, membranous nephropathy, focal and segmental glomerulosclerosis, atypical hemolytic uremic syndrome, dense-deposit disease, C3 glomerulopathy, complement- and IgG-positive membranoproliferative glomerulonephritis or membranoproliferative glomerulonephritis type I-III (old classification). During phase 1, patient data will be collected in an online database. The biorepository (phase 2) will involve collection of samples from patients for identification of predictors of recurrence, biomarkers of disease activity or response to therapy, and novel pathogenic mechanisms. Finally, through phase 3, we will use our multicenter network of patients and centers to launch interventional studies.

Discussion

Most prior studies of post-transplant GD recurrence are single-center and retrospective, or rely upon registry data that frequently misclassify the cause of kidney disease. Systematically determining GD recurrence rates and predictors of clinical outcomes is essential to improving post-transplant outcomes. Furthermore, accurate molecular phenotyping and biomarker development will allow better understanding of individual GD pathogenesis, and potentially identify novel drug targets for GD in both native and transplanted kidneys. The TANGO study has the potential to tackle GD recurrence through a multicenter design and a comprehensive biorepository.