Transcriptome Analysis of Rheumatoid Arthritis Uncovers Genes Linked to Inflammation-Induced Pain.

Autoimmune diseases such as rheumatoid arthritis (RA) can promote states of chronic inflammation with accompanying tissue destruction and pain. RA can cause inflammatory synovitis in peripheral joints, particularly within the hands and feet, but can also sometimes trigger temporomandibular joint (TMJ) arthralgia. To better understand the effects of ongoing inflammation-induced pain signaling, dorsal root ganglia (DRGs) were acquired from individuals with RA for transcriptomic study. We conducted RNA sequencing from the L5 DRGs because it contains the soma of the sensory neurons that innervate the affected joints in the foot. DRGs from 5 RA patients were compared with 9 non-arthritic controls. RNA-seq of L5 DRGs identified 128 differentially expressed genes (DEGs) that were dysregulated in the RA subjects as compared to the non-arthritic controls. The DRG resides outside the blood brain barrier and, as such, our initial transcriptome analysis detected signs of an autoimmune disorder including the upregulated expression of immunoglobulins and other immunologically related genes within the DRGs of the RA donors. Additionally, we saw the upregulation in genes implicated in neurogenesis that could promote pain hypersensitivity. Overall, our DRG analysis suggests that there are upregulated inflammatory and pain signaling pathways that can contribute to chronic pain in RA.

Integrative multiomic analyses of dorsal root ganglia in diabetic neuropathic pain using proteomics, phospho-proteomics, and metabolomics.

Diabetic peripheral neuropathy (DPN) is characterized by spontaneous pain in the extremities. Incidence of DPN continues to rise with the global diabetes epidemic. However, there remains a lack of safe, effective analgesics to control this chronic painful condition. Dorsal root ganglia (DRG) contain soma of sensory neurons and modulate sensory signal transduction into the central nervous system. In this study, we aimed to gain a deeper understanding of changes in molecular pathways in the DRG of DPN patients with chronic pain. We recently reported transcriptomic changes in the DRG with DPN. Here, we expand upon those results with integrated metabolomic, proteomic, and phospho-proteomic analyses to compare the molecular profiles of DRG from DPN donors and DRG from control donors without diabetes or chronic pain. Our analyses identified decreases of select amino acids and phospholipid metabolites in the DRG from DPN donors, which are important for cellular maintenance. Additionally, our analyses revealed changes suggestive of extracellular matrix (ECM) remodeling and altered mRNA processing. These results reveal new insights into changes in the molecular profiles associated with DPN.

Multiomic Analyses of Nascent Preterm Infant Microbiomes Differentiation Suggest Opportunities for Targeted Intervention.

The first week after birth is a critical time for the establishment of microbial communities for infants. Preterm infants face unique environmental impacts on their newly acquired microbiomes, including increased incidence of cesarean section delivery and exposure to antibiotics as well as delayed enteral feeding and reduced human interaction during their intensive care unit stay. Using contextualized paired metabolomics and 16S sequencing data, the development of the gut, skin, and oral microbiomes of infants is profiled daily for the first week after birth, and it is found that the skin microbiome appears robust to early life perturbation, while direct exposure of infants to antibiotics, rather than presumed maternal transmission, delays microbiome development and prevents the early differentiation based on body site regardless of delivery mode. Metabolomic analyses identify the development of all gut metabolomes of preterm infants toward full-term infant profiles, but a significant increase of primary bile acid metabolism only in the non-antibiotic treated vaginally birthed late preterm infants. This study provides a framework for future multi-omic, multibody site analyses on these high-risk preterm infant populations and suggests opportunities for monitoring and intervention, with infant antibiotic exposure as the primary driver of delays in microbiome development.

Transcriptomic analysis of human sensory neurons in painful diabetic neuropathy reveals inflammation and neuronal loss.

Pathological sensations caused by peripheral painful neuropathy occurring in Type 2 diabetes mellitus (T2DM) are often described as 'sharp' and 'burning' and are commonly spontaneous in origin. Proposed etiologies implicate dysfunction of nociceptive sensory neurons in dorsal root ganglia (DRG) induced by generation of reactive oxygen species, microvascular defects, and ongoing axonal degeneration and regeneration. To investigate the molecular mechanisms contributing to diabetic pain, DRGs were acquired postmortem from patients who had been experiencing painful diabetic peripheral neuropathy (DPN) and subjected to transcriptome analyses to identify genes contributing to pathological processes and neuropathic pain. DPN occurs in distal extremities resulting in the characteristic "glove and stocking" pattern. Accordingly, the L4 and L5 DRGs, which contain the perikarya of primary afferent neurons innervating the foot, were analyzed from five DPN patients and compared with seven controls. Transcriptome analyses identified 844 differentially expressed genes. We observed increases in levels of inflammation-associated transcripts from macrophages in DPN patients that may contribute to pain hypersensitivity and, conversely, there were frequent decreases in neuronally-related genes. The elevated inflammatory gene profile and the accompanying downregulation of multiple neuronal genes provide new insights into intraganglionic pathology and mechanisms causing neuropathic pain in DPN patients with T2DM.

KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples.

Microbiome analyses of low-biomass samples are challenging because of contamination and inefficiencies, leading many investigators to employ low-throughput methods with minimal controls. We developed a new automated protocol, KatharoSeq (from the Greek katharos [clean]), that outperforms single-tube extractions while processing at least five times as fast. KatharoSeq incorporates positive and negative controls to reveal the whole bacterial community from inputs of as few as 50 cells and correctly identifies 90.6% (standard error, 0.013%) of the reads from 500 cells. To demonstrate the broad utility of KatharoSeq, we performed 16S rRNA amplicon and shotgun metagenome analyses of the Jet Propulsion Laboratory spacecraft assembly facility (SAF; n = 192, 96), 52 rooms of a neonatal intensive care unit (NICU; n = 388, 337), and an endangered-abalone-rearing facility (n = 192, 123), obtaining spatially resolved, unique microbiomes reproducible across hundreds of samples. The SAF, our primary focus, contains 32 sOTUs (sub-OTUs, defined as exact sequence matches) and their inferred variants identified by the deblur algorithm, with four (Acinetobacter lwoffii, Paracoccus marcusii, Mycobacterium sp., and Novosphingobium) being present in >75% of the samples. According to microbial spatial topography, the most abundant cleanroom contaminant, A. lwoffii, is related to human foot traffic exposure. In the NICU, we have been able to discriminate environmental exposure related to patient infectious disease, and in the abalone facility, we show that microbial communities reflect the marine environment rather than human input. Consequently, we demonstrate the feasibility and utility of large-scale, low-biomass metagenomic analyses using the KatharoSeq protocol. IMPORTANCE Various indoor, outdoor, and host-associated environments contain small quantities of microbial biomass and represent a niche that is often understudied because of technical constraints. Many studies that attempt to evaluate these low-biomass microbiome samples are riddled with erroneous results that are typically false positive signals obtained during the sampling process. We have investigated various low-biomass kits and methods to determine the limit of detection of these pipelines. Here we present KatharoSeq, a high-throughput protocol combining laboratory and bioinformatic methods that can differentiate a true positive signal in samples with as few as 50 to 500 cells. We demonstrate the application of this method in three unique low-biomass environments, including a SAF, a hospital NICU, and an abalone-rearing facility.

Feeding during Blood Transfusions and the Association with Necrotizing Enterocolitis.

Objective The aim of this study was to determine whether very low-birth-weight (VLBW) infants who had feedings withheld during all blood transfusions had a lower incidence of necrotizing enterocolitis (NEC) compared with infants who were fed during transfusions. Study Design A retrospective chart review over a 3-year period in a level-3 neonatal intensive care unit was conducted. A total of 108 inborn VLBW infants (weight range: 500-1,500 g) who had received a transfusion before 36 weeks were reviewed. Diagnosis of NEC (≥ Bell stage II), demographics, feeds, transfusions, outcomes, and variables associated with NEC were collected. Results The percentage of NEC cases was lower in infants who had feeds withheld during transfusions: 5/64 (7.8%) compared with 16/116 (13.8%) infants who were fed during transfusions. While potentially clinically important (6% absolute difference), this difference was not statistically significant (p = 0.33 by two-tailed Fisher exact test). Conclusions No significant decrease in the incidence of NEC was found when feeds were withheld during blood transfusions. Holding feeds during transfusions is not without consequences such as the need for intravenous access, additional fluids, and the disruption of optimum nutrition. Further studies are needed to establish the relationship between blood transfusions, feeds, and NEC.

An analysis of elder abuse rates in Milwaukee County.

INTRODUCTION: The elder abuse and neglect burden in Milwaukee County, Wisconsin, is substantial, with 3384 reports made from 2006 to 2009. Current prevalence estimates are determined from reported cases only and are likely underestimated. Provider awareness of victim and perpetrator characteristics is necessary to increase recognition and response. METHODS: A cross-sectional analysis of elder abuse and neglect cases reported to the Milwaukee County Department on Aging (MCDA) from 2006 to 2009 was performed to provide a profile of the county's elder abuse burden by victim, perpetrator, and reporter characteristics. Annual reporting trends were identified using Poisson regression analysis. RESULTS: Fifty-eight percent of MCDA reports of abuse were substantiated after investigation. Victims in Milwaukee County tended to be older than 75 (64%), female (64%), and white (62%). Reporting rates to the MCDA were significantly lower in 2009 than 2006. Perpetrators were often adult children (48%) or a spouse (14%). Forty percent of life-threatening cases of self-neglect were due to unfulfilled medical needs. Most reports were made by medical professionals (23%), relatives of the victim (21%), and community agencies (18%). Only 13% of elder abuse victims were placed in nursing homes and assisted living centers; many received services to assist independent living. DISCUSSION: Although this study is limited to reported cases only, it provides a valuable profile of pertinent elder abuse characteristics in Milwaukee County. CONCLUSION: Characteristics of vulnerable elders, potential abusers, and investigation outcomes are described to inform clinical practice about this important social issue.