Early Detection of Breast Cancer-Related Lymphedema: Accuracy of Indocyanine Green Lymphography Compared with Bioimpedance Spectroscopy and Subclinical Lymphedema Symptoms.

Introduction: The reported incidences of breast cancer-related lymphedema (LE) affecting the arms vary greatly. Reason for this variability includes different diagnostic techniques used across studies. In the current study, we compared the accuracy of indocyanine green lymphography (ICG_L) and bioimpedance spectroscopy (BIS) in detecting LE before presentation of clinical signs. Methods and Results: Patients with no initial detectable signs of clinical LE of their arms after axillary lymph node dissection or removal of >5 lymph nodes on sentinel lymph node biopsy were included. Subclinical LE was defined as BIS values outside the normal range [(≥7 units (or >10 units)] or a 7-unit (or 10 unit) change between two measurements. We tracked ICG_L and BIS measurements for 133 potentially affected arms (n = 123). ICG_L detected signs of lymphatic flow disruption in 63 arms (47%). Based on the BIS value of 7 units, 60 arms (45%) had values outside the normal range. When using ICG_L-identified LE cases as true positives, BIS had a 54% accuracy (area under the curve [AUC] = 0.54) in detecting LE. Accuracy was 61% for subclinical LE symptoms when compared with ICG_L (AUC = 0.62). Both BIS and subclinical LE symptoms had <0.70 AUC-receiver characteristic operator curve, suggesting that BIS and development of subclinical LE symptoms are not adequate for identifying patients with subclinical LE. Conclusion: ICG_L is a reliable diagnostic tool for detecting early signs of lymphatic flow disruption in subclinical LE. Utilizing ICG_L to diagnose subclinical LE followed by a personalized treatment plan may provide patients the best chance of preventing disease progression.

Associations between stool micro-transcriptome, gut microbiota, and infant growth.

Rapid infant growth increases the risk for adult obesity. The gut microbiome is associated with early weight status; however, no study has examined how interactions between microbial and host ribonucleic acid (RNA) expression influence infant growth. We hypothesized that dynamics in infant stool micro-ribonucleic acids (miRNAs) would be associated with both microbial activity and infant growth via putative metabolic targets. Stool was collected twice from 30 full-term infants, at 1 month and again between 6 and 12 months. Stool RNA were measured with high-throughput sequencing and aligned to human and microbial databases. Infant growth was measured by weight-for-length z-score at birth and 12 months. Increased RNA transcriptional activity of Clostridia (R = 0.55; Adj p = 3.7E-2) and Burkholderia (R = -0.820, Adj p = 2.62E-3) were associated with infant growth. Of the 25 human RNAs associated with growth, 16 were miRNAs. The miRNAs demonstrated significant target enrichment (Adj p < 0.05) for four metabolic pathways. There were four associations between growth-related miRNAs and growth-related phyla. We have shown that longitudinal trends in gut microbiota activity and human miRNA levels are associated with infant growth and the metabolic targets of miRNAs suggest these molecules may regulate the biosynthetic landscape of the gut and influence microbial activity.

Oral microbiome activity in children with autism spectrum disorder.

Autism spectrum disorder (ASD) is associated with several oropharyngeal abnormalities, including buccal sensory sensitivity, taste and texture aversions, speech apraxia, and salivary transcriptome alterations. Furthermore, the oropharynx represents the sole entry point to the gastrointestinal (GI) tract. GI disturbances and alterations in the GI microbiome are established features of ASD, and may impact behavior through the "microbial-gut-brain axis." Most studies of the ASD microbiome have used fecal samples. Here, we identified changes in the salivary microbiome of children aged 2-6 years across three developmental profiles: ASD (n = 180), nonautistic developmental delay (DD; n = 60), and typically developing (TD; n = 106) children. After RNA extraction and shotgun sequencing, actively transcribing taxa were quantified and tested for differences between groups and within ASD endophenotypes. A total of 12 taxa were altered between the developmental groups and 28 taxa were identified that distinguished ASD patients with and without GI disturbance, providing further evidence for the role of the gut-brain axis in ASD. Group classification accuracy was visualized with receiver operating characteristic curves and validated using a 50/50 hold-out procedure. Five microbial ratios distinguished ASD from TD participants (79.5% accuracy), three distinguished ASD from DD (76.5%), and three distinguished ASD children with/without GI disturbance (85.7%). Taxonomic pathways were assessed using the Kyoto Encyclopedia of Genes and Genomes microbial database and compared with one-way analysis of variance, revealing significant differences within energy metabolism and lysine degradation. Together, these results indicate that GI microbiome disruption in ASD extends to the oropharynx, and suggests oral microbiome profiling as a potential tool to evaluate ASD status. Autism Res 2018, 11: 1286-1299. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Previous research suggests that the bacteria living in the human gut may influence autistic behavior. This study examined genetic activity of microbes living in the mouth of over 300 children. The microbes with differences in children with autism were involved in energy processing and showed potential for identifying autism status.