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Most prior studies characterizing post-transplantation diabetes mellitus (PTDM) have been limited to single-cohort, single-organ studies. This retrospective study determined PTDM across organs by comparing incidence and risk factors among 346 liver and 407 kidney transplant recipients from a single center. Univariate and multivariate regression-based analyses were conducted to determine association of various risk factors and PTDM in the two cohorts, as well as differences in glucometrics and insulin use across time points. There was a higher incidence of PTDM among liver versus kidney transplant recipients (30% vs. 19%) at 1-year post-transplant. Liver transplant recipients demonstrated a 337% higher odds association to PTDM (OR 3.37, 95% CI (1.38-8.25), p<0.01). 1-month FBG was higher in kidney patients (135 mg/dL vs 104 mg/dL; p < .01), while 1-month insulin use was higher in liver patients (61% vs 27%, p < .01). Age, BMI, insulin use, and inpatient FBG were also significantly associated with differential PTDM risk. Kidney and liver transplant patients have different PTDM risk profiles, both in terms of absolute PTDM risk as well as time course of risk. Management of this population should better reflect risk heterogeneity to short-term need for insulin therapy and potentially long-term outcomes.

Hyperglycemia following solid organ transplant is common among patients without pre-existing diabetes mellitus (DM). Post-transplant hyperglycemia can occur once or multiple times, which if continued, causes new-onset diabetes after transplantation (NODAT). To study if the first and recurrent incidence of hyperglycemia are affected differently by immunosuppressive regimens, demographic and medical-related risk factors, and inpatient hyperglycemic conditions (i.e., an emphasis on the time course of post-transplant complications). We conducted a retrospective analysis of 407 patients who underwent kidney transplantation at Mayo Clinic Arizona. Among these, there were 292 patients with no signs of DM prior to transplant. For this category of patients, we evaluated the impact of (1) immunosuppressive drugs (e.g., tacrolimus, sirolimus, and steroid), (2) demographic and medical-related risk factors, and (3) inpatient hyperglycemic conditions on the first and recurrent incidence of hyperglycemia in one year post-transplant. We employed two versions of Cox regression analyses: (1) a time-dependent model to analyze the recurrent cases of hyperglycemia and (2) a time-independent model to analyze the first incidence of hyperglycemia. Age (P = 0.018), HDL cholesterol (P = 0.010), and the average trough level of tacrolimus (P<0.0001) are significant risk factors associated with the first incidence of hyperglycemia, while age (P<0.0001), non-White race (P = 0.002), BMI (P = 0.002), HDL cholesterol (P = 0.003), uric acid (P = 0.012), and using steroid (P = 0.007) are the significant risk factors for the recurrent cases of hyperglycemia. This study draws attention to the importance of analyzing the risk factors associated with a disease (specially a chronic one) with respect to both its first and recurrent incidence, as well as carefully differentiating these two perspectives: a fact that is currently overlooked in the literature.

This study developed a predictive model for Post-Transplant Diabetes Mellitus (PTDM) by integrating clinical and radiological data to identify at-risk kidney transplant recipients. In a retrospective analysis across three Mayo Clinic sites, clinical metrics were combined with deep learning analysis of pre-transplant CT images, focusing on body composition parameters like adipose tissue and muscle mass instead of BMI or other biomarkers. Among 2,005 nondiabetic kidney recipients, 335 (16.7%) developed PTDM within the first year. PTDM patients were older, had higher BMIs, elevated triglycerides, and were more likely to be male and non-White. They exhibited lower skeletal muscle area, greater visceral adipose tissue (VAT), more intermuscular fat, and higher subcutaneous fat (all p < 0.001). Multivariable analysis identified age (OR: 1.05, 95% CI: 1.03–1.08, p < 0.0001), family diabetes history (OR: 1.55, CI: 1.14–2.09, p = 0.0061), White race (OR: 0.43, CI: 0.28–0.66, p < 0.0001), and VAT area (OR: 1.37, CI: 1.14–1.64, p = 0.0009) as predictors. The combined model achieved C-statistic of 0.724 (CI: 0.692–0.757), outperforming the clinical-only model (C-statistic 0.68). Patients with PTDM in the first year had higher mortality than those without PTDM. This model improves predictive precision, enabling accurate identification and intervention for at risk patients.

Decreased insulin sensitivity blunts the normal increase in gene expression from skeletal muscle after exercise. In addition, chronic inflammation decreases insulin sensitivity. Chronic kidney disease (CKD) is an inflammatory state. How CKD and, subsequently, kidney transplantation affects skeletal muscle gene expression after exercise are unknown. Study cohort: non-diabetic male/female 4/1, age 52±2 years, with end-stage CKD who underwent successful kidney transplantation. The following were measured both pre-transplant and post-transplant and compared to normals: Inflammatory markers, euglycemic insulin clamp studies determine insulin sensitivity, and skeletal muscle biopsies performed before and within 30 minutes after an acute exercise protocol. Microarray analyses were performed on the skeletal muscle using the 4x44K Whole Human Genome Microarrays. Since nuclear factor of activated T cells (NFAT) plays an important role in T cell activation and calcineurin inhibitors are mainstay immunosuppression, calcineurin/NFAT pathway gene expression was compared at rest and after exercise. Log transformation was performed to prevent skewing of data and regression analyses comparing measures pre- and post-transplant performed. Markers of inflammation significantly improved post-transplantation. Insulin infusion raised glucose disposal slightly lower post-transplant compared to pre-transplant, but not significantly, thus concluding differences in insulin sensitivity were similar. The overall pattern of gene expression in response to exercise was reduced both pre-and post-transplant compared to healthy volunteers. Although significant changes were observed among NFAT/Calcineurin gene at rest and after exercise in normal cohort, there were no significant differences comparing NFAT/calcineurin pathway gene expression pre- and post-transplant. Despite an improvement in serum inflammatory markers, no significant differences in glucose disposal were observed post-transplant. The reduced skeletal muscle gene expression, including NFAT/calcineurin gene expression, in response to a single bout of exercise was not improved post-transplant. This study suggests that the improvements in inflammatory mediators post-transplant are unrelated to changes of NFAT/calcineurin gene expression.

OBJECTIVE: New-onset diabetes after kidney transplantation (NODAT) has adverse clinical and economic implications. A risk score for NODAT could help identify research subjects for intervention studies. RESEARCH DESIGN AND METHODS: We conducted a single-center retrospective cohort study using pretransplant clinical and laboratory measurements to construct a risk score for NODAT. NODAT was defined by hemoglobin A1c (HbA1c) ≥6.5%, fasting serum glucose ≥126 mg/dL, or prescribed therapy for diabetes within 1 year posttransplant. Three multivariate logistic regression models were constructed: 1) standard model, with both continuous and discrete variables; 2) dichotomous model, with continuous variables dichotomized at clinically relevant cut points; and 3) summary score defined as the sum of the points accrued using the terms from the dichotomous model. RESULTS: A total of 316 subjects had seven pretransplant variables with P < 0.10 in univariate logistic regression analyses (age, planned corticosteroid therapy posttransplant, prescription for gout medicine, BMI, fasting glucose and triglycerides, and family history of type 2 diabetes) that were selected for multivariate models. Areas under receiver operating curves for all three models were similar (0.72, 0.71, and 0.70). A simple risk score calculated as the sum of points from the seven variables performed as well as the other two models in identifying risk of NODAT. CONCLUSIONS: A risk score computed from seven simple pretransplant variables can identify risk of NODAT.

The kidney atrophies in patients with advanced chronic kidney disease (CKD) but factors influencing kidney size in normal adults are less clear. To help define this, we measured kidney volumes on contrast-enhanced computed tomographic images from 1344 potential kidney donors (aged 18–75 years). Cortical volume per body surface area progressively declined in both genders with increased age. Statistically, this was primarily dependent on the age-related decline in glomerular filtration rate (GFR). Independent predictors of increased cortical volume per body surface area were male gender, increased GFR, increased 24-h urine albumin, current smoker, and decreased high-density lipid cholesterol. Medullary volume per body surface area increased with age in men, while it increased with age in women until the age of 50 years followed by a subsequent decline. Independent predictors of increased medullary volume per body surface area were older age, male gender, increased GFR, increased 24-h urine albumin, increased serum glucose, and decreased serum uric acid. Thus, while cortical volume declines with age along the same biological pathway as the age-related decline in GFR, albuminuria and some risk factors are actually associated with increased cortical or medullary volume among relatively healthy adults. Underlying hypertrophy or atrophy of different nephron regions may explain these findings.

This retrospective study analyzed glycemic trends, incidence of post-transplant diabetes mellitus (PTDM) incidence and associated risk factors in a cohort of patients who underwent first-time heart transplantation (HT). Univariate analyses compared patient with and without pretransplant diabetes mellitus (DM). Multivariate regression analyses were conducted to determine association between PTDM and different risk factors. Finally, trends in glucometrics and other outcomes are described across follow-up time points. There were 152 patients who underwent HT between 2010 and 2015, 109 of whom had no pretransplant history of DM. PTDM incidence was 38% by the 1-year follow-up. Pretransplant body mass index (odds ratio [OR] 1.12, 95% confidence interval [CI] 1.01 to 1.23, p = 0.03), insulin use during the final 24 hours of inpatient stay (OR 4.26, 95% CI 1.72 to 10.56, p <0.01), mean inpatient glucose (OR 2.21, 95% CI 1.33 to 3.69, p <0.01), and mean glucose in the final 24 hours before discharge (OR 1.29, 95% CI 1.03 to 1.60, p = 0.03) were associated with increased odds of PTDM at 1 year. In patients on insulin before discharge, blood glucose values were significantly higher compared with those who were not (136 mg/dl vs 114 mg/dl at 1 to 3 months, 112 vs 100 at 4 to 6 months, 109 vs 98 at 8 to 12 months, all p <0.01). This analysis improves understanding of PTDM incidence, glucometric trends, and risk differences by DM status in the HT population. Similar to liver and kidney patients, inpatient glucometrics may be informative of PTDM risk in HT patients. Guidelines for this population should be developed to account for risk heterogeneity and need for differential management.

Because the negative consequences of new-onset diabetes mellitus after transplantation (NODAT) diminish the significant gains of kidney transplantation, it is imperative to develop clinical interventions to reduce the incidence of NODAT. In this review, we discuss whether intensive lifestyle interventions that delay or prevent type 2 diabetes mellitus may decrease the incidence of NODAT. We examine the literature pertaining to incidence and timing of onset of NODAT, as well as the risk factors and pathophysiology that NODAT shares with type 2 diabetes mellitus, namely pathways related to increased insulin resistance and decreased insulin secretion. Our central hypothesis is that NODAT results from the same metabolic risk factors that underlie type 2 diabetes mellitus. These risk factors are altered and enhanced by transplantation, \"tipping\" some transplant recipients with seemingly normal glucose homeostasis before transplant toward the development of NODAT. We describe the diabetogenic properties of transplant immunosuppressive drugs. We describe novel methods of prevention that are being explored, including resting the pancreatic β-cells by administration of basal insulin during the period immediately after transplant. On the basis of the current evidence, we propose that intensive lifestyle modification, adapted for individuals with chronic kidney disease or end-stage renal disease, as well as resting pancreatic β-cells during the immediate postoperative period, may lower the incidence of NODAT.

New-onset diabetes after kidney transplant (NODAT) adversely impacts kidney allograft and patient survival. Epigenetic alterations in adipose tissue like DNA methylation may play a contributory role. Adipose tissue DNA of the patients with NODAT and their age, sex and BMI matched controls (nine each) were sequenced by reduced representation bisulfite sequencing. Differentially methylated CpGs (DMCs) and differentially methylated regions (DMRs) were studied. Adipose tissue from the patients had reduced DNA methylation in intergenic and intronic regions. DMCs were found to be more hypomethylated in repeat regions and hypermethylated in CGIs and promoter region. About 900 DMRs were found and their associated genes were significantly enriched in 32 pathways, the top ones of which were associated with insulin resistance and inflammation. Some DMR or DMC genes have known T2DM associations. Changes in DNA methylation in adipose tissue may be suggestive of future NODAT.

A 37-year-old African-American woman with end-stage renal disease presumed to be secondary to diabetes mellitus type 2, on daily peritoneal dialysis, was admitted for a painful left lower extremity lesion. Examination revealed a large, dusky, tender region over the left lateral thigh. She was on warfarin for mechanical heart valves. Despite discontinuation of warfarin and placement on heparin, the lesion progressed to extend to the medial left thigh and medial and lateral right thigh. CT scan demonstrated arteriolar medial calcification and vascular calcification of the small subcutaneous vessels, without evidence of abscess or haematoma. The patient declined punch biopsy. Given the known risk factors of high calcium-phosphate and radiological findings, a diagnosis of calcific uraemic arteriolopathy was made. Phosphate-binder therapy was optimised. She was transitioned to daily haemodialysis, and sodium thiosulfate was initiated. Skin lesions demonstrated improvement at her 5 weeks posthospitalisation follow-up.