Owens, S. | bioRxiv Science

bioRxiv2017

Perimenstrual Symptom Exacerbation in Borderline Personality Disorder: Evidence from Multilevel Models and the Carolina Premenstrual Assessment Scoring System

BackgroundIndividuals with borderline personality disorder (BPD) suffer from a constellation of rapidly shifting emotional, interpersonal, and behavioral symptoms. The menstrual cycle may contribute to symptom instability among females with this disorder.\n\nMethodsFifteen healthy, unmedicated females with BPD and without dysmenorrhea reported daily symptoms across 35 days. Urine luteinizing hormone (LH) and salivary progesterone (P4) were used to confirm ovulation and cycle phase. Cyclical worsening of symptoms was evaluated using (1) phase contrasts in multilevel models and (2) the Carolina Premenstrual Assessment Scoring System (C-PASS; Eisenlohr-Moul et al., 2017b), a protocol for evaluating clinically significant cycle effects on symptoms.\n\nResultsMost symptoms demonstrated midluteal worsening, a perimenstrual peak, and resolution of symptoms in the follicular or ovulatory phase. Post-hoc correlations with person-centered progesterone revealed negative correlations with most symptoms. Depressive symptoms showed an unexpected delayed pattern in which baseline levels of symptoms were observed in the ovulatory and midluteal phases, and exacerbations were observed during both the perimenstrual and follicular phases. The majority of participants met C-PASS criteria for clinically significant (>=30%) symptom exacerbation. All participants met the emotional instability criterion of BPD, and no participant met DSM-5 criteria for premenstrual dysphoric disorder (PMDD).\n\nConclusionsFemales with BPD may be at elevated risk for perimenstrual worsening of emotional symptoms. Longitudinal studies with fine-grained hormonal measurement as well as hormonal experiments are needed to determine the pathophysiology of perimenstrual exacerbation in BPD.

neuroscience↗

bioRxiv2017

Bacterial community composition and dynamics spanning five years in freshwater bog lakes

Bacteria play a key role in freshwater biogeochemical cycling, but long-term trends in freshwater bacterial community composition and dynamics are not yet well characterized. We used a multi-year time series of 16S rRNA gene amplicon sequencing data from eight bog lakes to census the freshwater bacterial community and observe annual and seasonal trends in abundance. Multiple sites and sampling events were necessary to begin to fully describe the bacterial communities. Each lake and layer contained a distinct bacterial community, with distinct levels of richness and indicator taxa that likely reflected the environmental conditions of each site. The community present in each year and site was also unique. Despite high interannual variability in community composition, we detected a core community of ubiquitous freshwater taxa. Although trends in abundance did not repeat annually, each freshwater lineage within the communities had a consistent lifestyle, defined by persistence, abundance, and variability. The results of our analysis emphasize the importance of long-term observations, as analyzing only a single year of data would not have allowed us to describe the dynamics and composition of these freshwater bacterial communities to the extent presented here.\n\nImportanceLakes are excellent systems for investigating bacterial community dynamics because they have clear boundaries and strong environmental gradients. The results of our research demonstrate that bacterial community dynamics operate on multi-year timescales, a finding which likely applies to other ecosystems, with implications for study design and interpretation. Understanding the drivers and controls of bacterial communities on long time scales would improve both our knowledge of fundamental properties of bacterial communities, and our ability to predict community states. In this specific ecosystem, bog lakes play a disproportionately large role in global carbon cycling, and the information presented here may ultimately help refine carbon budgets for these lakes. Finally, all data and code in this study are publicly available. We hope that this will serve as a resource to anyone seeking to answer their own microbial ecology questions using a multi-year time series.

microbiology↗