Institutional Special Needs Plans and Hospice Enrollment in Nursing Homes: A National Analysis.

BACKGROUND: Institutional Special Needs Plans (I-SNPs) in nursing homes could impact hospice use by residents with advanced illness. Little is known about their relationship. OBJECTIVE: To determine whether I-SNP availability has been associated with changes in hospice utilization. DESIGN: Federal data from 2011 and 2013 were extracted from the Minimum Data Set (MDS) and other sources. Multilevel models evaluated I-SNP-, resident-, and facility-related variables as predictors of hospice utilization. SETTING: All US nursing homes in 2011 (N = 15 750) and 2013 (N = 15 732). PARTICIPANTS: Nursing home residents enrolled in Medicare or in both Medicare and Medicaid. MEASUREMENTS: Nursing home and resident data were obtained from Centers for Medicare and Medicaid Services sources: the MDS 3.0, Master Summary Beneficiary File, and Special Needs Plan Comprehensive Report. RESULTS: The mean number of residents per nursing home was 210.9 (SD = 167.1) in 2011 and 217.2 (SD = 171.5) in 2013. The prevalence of I-SNP contracts in nursing homes increased between 2011 and 2013, from 55.2% (N = 8691) to 61.1% (N = 9605), respectively (P < .001). In multivariate analyses, greater hospice enrollment in nursing homes was associated with having at least one I-SNP enrollee per month; year (2013 higher than 2011); smaller facility size; urban (vs rural) setting; location in the Northeast (vs Midwest); lower average resident mental status; higher average resident mobility; younger residents, on average; and facilities with higher proportions of residents with specific diagnoses (cancer, cirrhosis, and dementia). After adjusting for resident and nursing home characteristics, the association between monthly I-SNP presence and hospice enrollment was found only in nursing homes with 50 or greater beds and there was a positive relationship with increasing size. CONCLUSIONS: Growth of I-SNPs has been associated with changes in hospice utilization, and the relationship varies by facility size. Studies are needed to clarify the nature of this association and determine whether care may be improved through coordination of these programs. J Am Geriatr Soc 67:2537-2544, 2019.

Species-level functional profiling of metagenomes and metatranscriptomes.

Functional profiles of microbial communities are typically generated using comprehensive metagenomic or metatranscriptomic sequence read searches, which are time-consuming, prone to spurious mapping, and often limited to community-level quantification. We developed HUMAnN2, a tiered search strategy that enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities. HUMAnN2 identifies a community's known species, aligns reads to their pangenomes, performs translated search on unclassified reads, and finally quantifies gene families and pathways. Relative to pure translated search, HUMAnN2 is faster and produces more accurate gene family profiles. We applied HUMAnN2 to study clinal variation in marine metabolism, ecological contribution patterns among human microbiome pathways, variation in species' genomic versus transcriptional contributions, and strain profiling. Further, we introduce 'contributional diversity' to explain patterns of ecological assembly across different microbial community types.

Multi-omics Analysis of Periodontal Pocket Microbial Communities Pre- and Posttreatment.

Periodontitis is a polymicrobial infectious disease that causes breakdown of the periodontal ligament and alveolar bone. We employed a meta-omics approach that included microbial 16S rRNA amplicon sequencing, shotgun metagenomics, and tandem mass spectrometry to analyze sub- and supragingival biofilms in adults with chronic periodontitis pre- and posttreatment with 0.25% sodium hypochlorite. Microbial samples were collected with periodontal curettes from 3- to 12-mm-deep periodontal pockets at the baseline and at 2 weeks and 3 months. All data types showed high interpersonal variability, and there was a significant correlation between phylogenetic diversity and pocket depth at the baseline and a strong correlation (rho = 0.21; P = 0.008) between metabolite diversity and maximum pocket depth (MPD). Analysis of subgingival baseline samples (16S rRNA and shotgun metagenomics) found positive correlations between abundances of particular bacterial genera and MPD, including Porphyromonas, Treponema, Tannerella, and Desulfovibrio species and unknown taxon SHD-231. At 2 weeks posttreatment, we observed an almost complete turnover in the bacterial genera (16S rRNA) and species (shotgun metagenomics) correlated with MPD. Among the metabolites detected, the medians of the 20 most abundant metabolites were significantly correlated with MPD pre- and posttreatment. Finally, tests of periodontal biofilm community instability found markedly higher taxonomic instability in patients who did not improve posttreatment than in patients who did improve (UniFrac distances; t = -3.59; P = 0.002). Interestingly, the opposite pattern occurred in the metabolic profiles (Bray-Curtis; t = 2.42; P = 0.02). Our results suggested that multi-omics approaches, and metabolomics analysis in particular, could enhance treatment prediction and reveal patients most likely to improve posttreatment. IMPORTANCE Periodontal disease affects the majority of adults worldwide and has been linked to numerous systemic diseases. Despite decades of research, the reasons for the substantial differences among periodontitis patients in disease incidence, progressivity, and response to treatment remain poorly understood. While deep sequencing of oral bacterial communities has greatly expanded our comprehension of the microbial diversity of periodontal disease and identified associations with healthy and disease states, predicting treatment outcomes remains elusive. Our results suggest that combining multiple omics approaches enhances the ability to differentiate among disease states and determine differential effects of treatment, particularly with the addition of metabolomic information. Furthermore, multi-omics analysis of biofilm community instability indicated that these approaches provide new tools for investigating the ecological dynamics underlying the progressive periodontal disease process.

Microbiota Transfer Therapy alters gut ecosystem and improves gastrointestinal and autism symptoms: an open-label study.

BACKGROUND: Autism spectrum disorders (ASD) are complex neurobiological disorders that impair social interactions and communication and lead to restricted, repetitive, and stereotyped patterns of behavior, interests, and activities. The causes of these disorders remain poorly understood, but gut microbiota, the 1013 bacteria in the human intestines, have been implicated because children with ASD often suffer gastrointestinal (GI) problems that correlate with ASD severity. Several previous studies have reported abnormal gut bacteria in children with ASD. The gut microbiome-ASD connection has been tested in a mouse model of ASD, where the microbiome was mechanistically linked to abnormal metabolites and behavior. Similarly, a study of children with ASD found that oral non-absorbable antibiotic treatment improved GI and ASD symptoms, albeit temporarily. Here, a small open-label clinical trial evaluated the impact of Microbiota Transfer Therapy (MTT) on gut microbiota composition and GI and ASD symptoms of 18 ASD-diagnosed children. RESULTS: MTT involved a 2-week antibiotic treatment, a bowel cleanse, and then an extended fecal microbiota transplant (FMT) using a high initial dose followed by daily and lower maintenance doses for 7-8 weeks. The Gastrointestinal Symptom Rating Scale revealed an approximately 80% reduction of GI symptoms at the end of treatment, including significant improvements in symptoms of constipation, diarrhea, indigestion, and abdominal pain. Improvements persisted 8 weeks after treatment. Similarly, clinical assessments showed that behavioral ASD symptoms improved significantly and remained improved 8 weeks after treatment ended. Bacterial and phagedeep sequencing analyses revealed successful partial engraftment of donor microbiota and beneficial changes in the gut environment. Specifically, overall bacterial diversity and the abundance of Bifidobacterium, Prevotella, and Desulfovibrio among other taxa increased following MTT, and these changes persisted after treatment stopped (followed for 8 weeks). CONCLUSIONS: This exploratory, extended-duration treatment protocol thus appears to be a promising approach to alter the gut microbiome and virome and improve GI and behavioral symptoms of ASD. Improvements in GI symptoms, ASD symptoms, and the microbiome all persisted for at least 8 weeks after treatment ended, suggesting a long-term impact. TRIAL REGISTRATION: This trial was registered on the ClinicalTrials.gov, with the registration number  NCT02504554.