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Individual bacteria and shifts in the composition of the microbiome have been associated with human diseases including cancer. To investigate changes in the microbiome associated with oral cancers, we profiled cancers and anatomically matched contralateral normal tissue from the same patient by sequencing 16S rDNA hypervariable region amplicons. In cancer samples from both a discovery and a subsequent confirmation cohort, abundance of Firmicutes (especially Streptococcus) and Actinobacteria (especially Rothia) was significantly decreased relative to contralateral normal samples from the same patient. Significant decreases in abundance of these phyla were observed for pre-cancers, but not when comparing samples from contralateral sites (tongue and floor of mouth) from healthy individuals. Weighted UniFrac principal coordinates analysis based on 12 taxa separated most cancers from other samples with greatest separation of node positive cases. These studies begin to develop a framework for exploiting the oral microbiome for monitoring oral cancer development, progression and recurrence. [ABSTRACT FROM AUTHOR]

Introduction: Periodontal disease is a chronic, inflammatory bacterial dysbiosis that is associated with both Alzheimer's disease (AD) and Down syndrome., Methods: A total of 48 elderly cognitively normal subjects were evaluated for differences in subgingival periodontal bacteria (assayed by 16S rRNA sequencing) between cerebrospinal fluid (CSF) biomarker groups of amyloid and neurofibrillary pathology. A dysbiotic index (DI) was defined at the genus level as the abundance ratio of known periodontal bacteria to healthy bacteria. Analysis of variance/analysis of covariance (ANOVA/ANCOVA), linear discriminant effect-size analyses (LEfSe) were used to determine the bacterial genera and species differences between the CSF biomarker groups., Results: At genera and species levels, higher subgingival periodontal dysbiosis was associated with reduced CSF amyloid beta (Aβ)42 ( P  = 0.02 and 0.01) but not with P-tau., Discussion: We show a selective relationship between periodontal disease bacterial dysbiosis and CSF biomarkers of amyloidosis, but not for tau. Further modeling is needed to establish the direct link between oral bacteria and Aβ., Competing Interests: Kaj Blennow has served as a consultant, at advisory boards, or at data monitoring committees for Abcam, Axon, Biogen, JOMDD/Shimadzu. Julius Clinical, Lilly, MagQu, Novartis, Roche Diagnostics, and Siemens Healthineers, and is a co‐founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program. Henrik Zetterberg has served at scientific advisory boards for Denali, Roche Diagnostics, Wave, Samumed, Siemens Healthineers, Pinteon Therapeutics and CogRx, has given lectures in symposia sponsored by Fujirebio, Alzecure and Biogen, and is a co‐founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program (outside submitted work). No conflict of interest is reported for any of the other authors., (© 2021 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Background: Patients with head and neck cancer (HNC) experience painful, debilitating symptoms and functional limitations that can interrupt cancer treatment, and decrease their health-related quality of life (HRQoL). The Electronic Patient Visit Assessment (ePVA) for head and neck is a web-based mHealth patient-reported measure that asks questions about 21 categories of symptoms and functional limitations common to HNC. This article presents the development and usefulness of the ePVA as a clinical support tool for real-time interventions for patient-reported symptoms and functional limitations in HNC., Methods: Between January 2018 and August 2019, 75 participants were enrolled in a clinical usefulness study of the ePVA. Upon signing informed consent, participants completed the ePVA and the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire (QLQ) general (C30) questionnaire v3.0 (scores range from 0 to 100 with 100 representing best HRQoL). Clinical usefulness of the ePVA was defined as demonstration of reliability, convergent validity with HRQoL, and acceptability of the ePVA (i.e., >70% of eligible participants complete the ePVA at two or more visits and >70% of ePVA reports are read by providers). Formal focus group discussions with the interdisciplinary team that cared for patients with HNC guided the development of the ePVA as a clinical support tool. Qualitative and quantitative methods were used throughout the study. Descriptive statistics consisting of means and frequencies, Pearson correlation coefficient, and Student's t-tests were calculated using SAS 9.4 and STATA., Results: The participants were primarily male (71%), White (76%), diagnosed with oropharyngeal or oral cavity cancers (53%), and undergoing treatment for HNC (69%). Data analyses supported the reliability (alpha =0.85), convergent validity with HRQoL scores, and acceptability of the ePVA. Participants with the highest number of symptoms and functional limitations reported significantly worse HRQoL (sum of symptoms: r=-0.50, P<0.0001; sum of function limitations: r=-0.56, P<0.0001). Ninety-two percent of participants (59 of 64) who had follow-up visits within the 6-month study period completed the ePVA at two or more visits and providers read 89% (169 of 189) of automated ePVA reports. The use of the ePVA as a clinical support tool for real-time interventions for symptoms and functional limitations reported by patients is described in a clinical exemplar., Conclusions: This research indicates that the ePVA may be a useful mHealth tool as a clinical support tool for real-time interventions for patient-reported symptoms and functional limitations in HNC. The study findings support future translational research to enhance the usefulness of the ePVA in real world settings for early interventions that decrease symptom burden and improve the QoL of patients with HNC., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/mhealth-19-250). The series “Real-Time Detection and Management of Chronic Illnesses” was commissioned by the editorial office without any funding or sponsorship. MRF serves as an unpaid Guest Editor of the series and serves as an unpaid editorial board member of mHealth from Aug 2018 to Jul 2020. MRF reports grants from Louis and Rachel Rudin Foundation Interdisciplinary Pilot Project Award, from NIH/2017 Palliative Care Research Cooperative Group Investigator Development Pilot Award (funded by National Institute of Nursing Research U24NR014637); from New York University Research Challenge Fund, and from John A. Harford Foundation Change AGEnts Action Award, during the conduct of the study. BLE reports grants from USA. National Institutes of Health/National Cancer Institute (P30CA006927 Fox Chase Cancer Center Support Grant), during the conduct of the study. JHVC reports grants from Louis and Rachel Rudin Foundation Interdisciplinary Pilot Project, from 2017 Palliative Care Research Cooperative Group Investigator Development Pilot (funded by National Institute of Nursing Research U24NR014637), grants from NYU University Research Challenge Fund, grants from John A. Harford Foundation Change AGEnts Action Award, during the conduct of the study. The authors have no other conflicts of interest to declare., (2021 mHealth. All rights reserved.)