Peritoneal dialysis (PD) and in-center hemodialysis (HD) are accepted as clinically equivalent dialysis modalities, yet in-center HD is the predominant renal replacement therapy (RRT) modality offered to new end-stage renal disease (ESRD) patients in the United States and most other industrialized nations. This predominance has little to do with clinical outcomes, patient choice, cost, or quality of life. It has been driven by ease of HD initiation, physician experience and training, inadequate pre-ESRD patient education, ample in-center HD capacity, and lack of adequate infrastructure for PD-related care. As compared with in-center HD, PD is a widely applicable, yet underutilized modality of RRT that provides comparable clinical outcomes, superior quality of life measures, significant cost savings, and many other unmeasured advantages. A "PD First" approach not only has advantages for patients but also physicians, healthcare systems, and society. In this review, we will summarize evidence demonstrating that PD should be the default modality when new ESRD patients are transitioning to dialysis therapy when preemptive transplantation is not an option and highlight the essential infrastructural requirements to allow for a "PD First" model.

Background

Serum albumin level predicts mortality in dialysis patients and is used to assess their health status and the quality of delivered care. Whether the threshold level of serum albumin at which mortality risk increases in peritoneal dialysis (PD) patients is the same as for hemodialysis (HD) patients has not been studied.

Study design

Observational cohort study of dialysis patients undertaken to determine the survival-predictability of serum albumin level in PD patients and compare it with that in HD patients.

Setting & participants

130,052 dialysis patients (PD, 12,171; HD, 117,851) who received treatment in any of the 580 dialysis units owned by DaVita Inc between July 1, 2001, through June 30, 2006, followed up through June 30, 2007.

Predictor

Baseline and time-averaged serum albumin level (assayed using bromcresol green) and change in serum albumin level over 6 months.

Outcome measures

All-cause, cardiovascular, and infection-related mortality.

Results

PD patients with baseline serum albumin level <3.0 g/dL had a more than 3-fold higher adjusted risk of all-cause and cardiovascular mortality and 3.4-fold higher risk of infection-related mortality (reference group: serum albumin, 4.00-4.19 g/dL). Adjusted all-cause mortality was significantly lower in PD patients with a ≥0.3-g/dL increase in serum albumin level over 6 months and significantly higher in those for whom it decreased by ≥0.2 g/dL (reference group: serum albumin change, +0.1 to -0.1 g/dL). A significant increase in death risk was evident for HD patients with serum albumin level <4.0 g/dL, but at <3.8 g/dL for PD patients. For each albumin category, overall death risk for PD patients was lower than for HD patients (reference group: HD patients with serum albumin of 4.00-4.19 g/dL).

Limitations

Study can identify associations only without attribution of causality and residual confounding cannot be excluded.

Conclusions

Serum albumin predicts all-cause, cardiovascular, and infection-related mortality in both PD and HD patients. However, the threshold at which risk of death increases varies by dialysis modality, and this difference should be considered by agencies or organizations that set quality standards.

Somatic mosaicism is defined as an occurrence of two or more populations of cells having genomic sequences differing at given loci in an individual who is derived from a single zygote. It is a characteristic of multicellular organisms that plays a crucial role in normal development and disease. To study the nature and extent of somatic mosaicism in autism spectrum disorder, bipolar disorder, focal cortical dysplasia, schizophrenia, and Tourette syndrome, a multi-institutional consortium called the Brain Somatic Mosaicism Network (BSMN) was formed through the National Institute of Mental Health (NIMH). In addition to genomic data of affected and neurotypical brains, the BSMN also developed and validated a best practices somatic single nucleotide variant calling workflow through the analysis of reference brain tissue. These resources, which include >400 terabytes of data from 1087 subjects, are now available to the research community via the NIMH Data Archive (NDA) and are described here.

Background

Post-zygotic mutations incurred during DNA replication, DNA repair, and other cellular processes lead to somatic mosaicism. Somatic mosaicism is an established cause of various diseases, including cancers. However, detecting mosaic variants in DNA from non-cancerous somatic tissues poses significant challenges, particularly if the variants only are present in a small fraction of cells.

Results

Here, the Brain Somatic Mosaicism Network conducts a coordinated, multi-institutional study to examine the ability of existing methods to detect simulated somatic single-nucleotide variants (SNVs) in DNA mixing experiments, generate multiple replicates of whole-genome sequencing data from the dorsolateral prefrontal cortex, other brain regions, dura mater, and dural fibroblasts of a single neurotypical individual, devise strategies to discover somatic SNVs, and apply various approaches to validate somatic SNVs. These efforts lead to the identification of 43 bona fide somatic SNVs that range in variant allele fractions from ~ 0.005 to ~ 0.28. Guided by these results, we devise best practices for calling mosaic SNVs from 250× whole-genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrate that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees.

Conclusions

This study provides a unified set of best practices to detect somatic SNVs in non-cancerous tissues. The data and methods are freely available to the scientific community and should serve as a guide to assess the contributions of somatic SNVs to neuropsychiatric diseases.

We analyzed 131 human brains (44 neurotypical, 19 with Tourette syndrome, 9 with schizophrenia, and 59 with autism) for somatic mutations after whole genome sequencing to a depth of more than 200×. Typically, brains had 20 to 60 detectable single-nucleotide mutations, but ~6% of brains harbored hundreds of somatic mutations. Hypermutability was associated with age and damaging mutations in genes implicated in cancers and, in some brains, reflected in vivo clonal expansions. Somatic duplications, likely arising during development, were found in ~5% of normal and diseased brains, reflecting background mutagenesis. Brains with autism were associated with mutations creating putative transcription factor binding motifs in enhancer-like regions in the developing brain. The top-ranked affected motifs corresponded to MEIS (myeloid ectopic viral integration site) transcription factors, suggesting a potential link between their involvement in gene regulation and autism.

H3Africa is developing capacity for health-related genomics research in Africa

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.