Next-generation sequencing of the mitochondrial genome and association with IgA nephropathy in a renal transplant population

Kidneys are highly aerobic organs that are critically dependent on the normal functioning of mitochondria. Genetic variations disrupting mitochondrial function are associated with multifactorial disorders including kidney disease. This study sequenced the entire mitochondrial genome in a renal transplant cohort of 64 individuals, using next-generation sequencing, to evaluate the association of genetic variants with IgA nephropathy and end-stage renal disease (ESRD, n = 100).

Understanding coronary heart disease-related disability in older adults in the Republic of Ireland and Northern Ireland in 2010/2011

Background

Although life expectancy continues to increase in the Republic of Ireland (ROI) and Northern Ireland (NI), coronary heart disease (CHD) remains a leading cause of death and disability in older adults. Some, but not all, of the socioeconomic inequality in cardiovascular disability can be explained by a social gradient in conventional risk factors. The aims of the research were to assess CHD-related disability, and to establish the prevalence and population attributable fractions (PAFs) of risk factors for CHD-related disability across gender and socioeconomic groups in older adults in NI and ROI.

Factors influencing survival after kidney transplant failure

BACKGROUND: The failure of a kidney transplant is now a common reason for initiation of dialysis therapy. Kidney transplant recipients commencing dialysis have greater morbidity and mortality than transplant-naïve, incident dialysis patients. This study aimed to identify variables associated with survival after graft failure.

METHODS: All recipients of first, deceased donor kidney transplants performed in Northern Ireland between 1986 and 2005 who had a functioning graft at 12 months were included (n = 585). Clinical and blood-derived variables (age, gender, primary renal disease, diabetic status, smoking status, human leukocyte antigen (HLA) mismatch, acute rejection episodes, immunosuppression, cardiovascular disease, graft survival, haemoglobin, albumin, phosphate, C reactive protein, estimated glomerular filtration rate (eGFR), rate of eGFR decline, dialysis modality, and access) were collected prospectively and investigated for association with re-transplantation and survival. The association between re-transplantation and survival was explored by modelling re-transplantation as a time-dependent covariate.

RESULTS: Median follow-up time was 12.1 years. Recipients with a failing graft (158/585) demonstrated rapid loss of eGFR prior to graft failure, reducing the time available to plan for alternative renal replacement therapy. Median survival after graft failure was 3.0 years. In multivariate analysis, age and re-transplantation were associated with survival after graft failure. Re-transplantation was associated with an 88% reduction in mortality.

CONCLUSIONS: Optimal management of kidney transplant recipients with failing grafts requires early recognition of declining function and proactive preparation for re-transplantation given the substantial survival benefit this confers. The survival benefit associated with re-transplantation persists after prolonged exposure to immunosuppressive therapy.

Estimated Glomerular Filtration Rate Decline as a Predictor of Dialysis in Kidney Transplant Recipients

BACKGROUND: It is now common for individuals to require dialysis following the failure of a kidney transplant. Management of complications and preparation for dialysis are suboptimal in this group. To aid planning, it is desirable to estimate the time to dialysis requirement. The rate of decline in the estimated glomerular filtration rate (eGFR) may be used to this end.

METHODS: This study compared the rate of eGFR decline prior to dialysis commencement between individuals with failing transplants and transplant-naïve patients. The rate of eGFR decline was also compared between transplant recipients with and without graft failure. eGFR was calculated using the four-variable MDRD equation with rate of decline calculated by least squares linear regression.

RESULTS: The annual rate of eGFR decline in incident dialysis patients with graft failure exceeded that of the transplant-naïve incident dialysis patients. In the transplant cohort, the mean annual rate of eGFR decline prior to graft failure was 7.3 ml/min/1.73 m(2) compared to 4.8 ml/min/1.73 m(2) in the transplant-naïve group (p < 0.001) and 0.35 ml/min/1.73 m(2) in recipients without graft failure (p < 0.001). Factors associated with eGFR decline were recipient age, decade of transplantation, HLA mismatch and histological evidence of chronic immunological injury.

CONCLUSIONS: Individuals with graft failure have a rapid decline in eGFR prior to dialysis commencement. To improve outcomes, dialysis planning and management of chronic kidney disease complications should be initiated earlier than in the transplant-naïve population.

A quality-scalable and energy-efficient approach for spectral analysis of heart rate variability

Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case.