De-escalation of Disease-Modifying Therapy for People with Multiple Sclerosis Due to Safety Considerations: Characterizing 1-Year Outcomes in 25 People Who Switched from Ocrelizumab to Diroximel Fumarate.

INTRODUCTION: Switching disease-modifying therapy (DMT) may be considered for relapsing-remitting multiple sclerosis (RRMS) if a patient's current therapy is no longer optimal. This was particularly important during the recent COVID-19 pandemic because of considerations around immune deficiency and impaired vaccine response associated with B cell-depleting DMTs. This real-world, single-center study aimed to evaluate change or decline in functional ability and overall disease stability in people with RRMS who were switched from B cell-depleting ocrelizumab (OCRE) to diroximel fumarate (DRF) because of safety concern related to the COVID-19 pandemic. METHODS: Adults with RRMS were included if they had been clinically stable for ≥ 1 year on OCRE. Data collected at baseline and 1 year post switch included relapse rate, magnetic resonance imaging (MRI), blood work for assessment of peripheral immune parameters, the Cognitive Assessment Battery (CAB), optical coherence tomography (OCT), and patient-reported outcomes (PROs). RESULTS: Participants (N = 25) had a mean (SD) age of 52 (9) years, and a mean (SD) duration of 26 (8) months' treatment with OCRE before the switch to DRF. Median washout duration since the last OCRE infusion was 7 months (range 4-18 months). No participants relapsed on DRF during follow-up, and all remained persistent on DRF after 1 year. There were no significant changes in peripheral immune parameters, other than an increase in the percentage of CD19+ cells 1 year after switching (p < 0.05). Similarly, there were no significant changes in CAB, OCT, and PROs. CONCLUSION: These preliminary findings suggest that transition to DRF from OCRE may be an effective treatment option for people with RRMS who are clinically stable but may need to switch for reasons unrelated to effectiveness. Longer follow-up times on larger samples are needed to confirm these observations.

Characterizing opioid overdose hotspots for place-based overdose prevention and treatment interventions: A geo-spatial analysis of Rhode Island, USA.

OBJECTIVE: Examine differences in neighborhood characteristics and services between overdose hotspot and non-hotspot neighborhoods and identify neighborhood-level population factors associated with increased overdose incidence. METHODS: We conducted a population-based retrospective analysis of Rhode Island, USA residents who had a fatal or non-fatal overdose from 2016 to 2020 using an environmental scan and data from Rhode Island emergency medical services, State Unintentional Drug Overdose Reporting System, and the American Community Survey. We conducted a spatial scan via SaTScan to identify non-fatal and fatal overdose hotspots and compared the characteristics of hotspot and non-hotspot neighborhoods. We identified associations between census block group-level characteristics using a Besag-York-Mollié model specification with a conditional autoregressive spatial random effect. RESULTS: We identified 7 non-fatal and 3 fatal overdose hotspots in Rhode Island during the study period. Hotspot neighborhoods had higher proportions of Black and Latino/a residents, renter-occupied housing, vacant housing, unemployment, and cost-burdened households. A higher proportion of hotspot neighborhoods had a religious organization, a health center, or a police station. Non-fatal overdose risk increased in a dose responsive manner with increasing proportions of residents living in poverty. There was increased relative risk of non-fatal and fatal overdoses in neighborhoods with crowded housing above the mean (RR 1.19 [95 % CI 1.05, 1.34]; RR 1.21 [95 % CI 1.18, 1.38], respectively). CONCLUSION: Neighborhoods with increased prevalence of housing instability and poverty are at highest risk of overdose. The high availability of social services in overdose hotspots presents an opportunity to work with established organizations to prevent overdose deaths.

Current challenges and future of agricultural genomes to phenomes in the USA.

Dramatic improvements in measuring genetic variation across agriculturally relevant populations (genomics) must be matched by improvements in identifying and measuring relevant trait variation in such populations across many environments (phenomics). Identifying the most critical opportunities and challenges in genome to phenome (G2P) research is the focus of this paper. Previously (Genome Biol, 23(1):1-11, 2022), we laid out how Agricultural Genome to Phenome Initiative (AG2PI) will coordinate activities with USA federal government agencies expand public-private partnerships, and engage with external stakeholders to achieve a shared vision of future the AG2PI. Acting on this latter step, AG2PI organized the "Thinking Big: Visualizing the Future of AG2PI" two-day workshop held September 9-10, 2022, in Ames, Iowa, co-hosted with the United State Department of Agriculture's National Institute of Food and Agriculture (USDA NIFA). During the meeting, attendees were asked to use their experience and curiosity to review the current status of agricultural genome to phenome (AG2P) work and envision the future of the AG2P field. The topic summaries composing this paper are distilled from two 1.5-h small group discussions. Challenges and solutions identified across multiple topics at the workshop were explored. We end our discussion with a vision for the future of agricultural progress, identifying two areas of innovation needed: (1) innovate in genetic improvement methods development and evaluation and (2) innovate in agricultural research processes to solve societal problems. To address these needs, we then provide six specific goals that we recommend be implemented immediately in support of advancing AG2P research.