SeroNet Pooling Project of immunocompromised populations

Introduction: COVID-19 vaccination substantially reduces morbidity and mortality associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severe illness. However, despite effective COVID-19 vaccines many questions remain about the efficacy of vaccines and the durability and robustness of immune responses, especially in immunocompromised persons. The NCI-funded Serological Sciences Network (SeroNet) is a coordinated effort including 11 sites to advance research on the immune response to SARS-CoV-2 infection and COVID-19 vaccination among diverse and vulnerable populations. The goals of the Pooling Project are: (1) to conduct real-world data (RWD) analyses using electronic medical records (EMR) data from four health care systems (Kaiser Permanente Northern California, Northwell Health, Veterans Affairs-Case Western, and Cedars-Sinai) to determine vaccine effectiveness in (a) cancer patients;(b) autoimmune diseases and (c) solid organ transplant recipients (SOTR);(2) to conduct meta-analyses of prospective cohort studies from eight SeroNet institutions (Cedars-Sinai, Johns Hopkins, Northwell Health, Emory University, University of Minnesota, Mount Sinai, Yale University) to determine post-vaccine immune responses in (a) lung cancer patients;(b) hematologic cancers/hematopoietic stem cell transplant (HSCT) recipients;(c) SOTR;(d) lupus. Method(s): For our RWD analyses, data is extracted from EMR using standardized algorithms using ICD-10 codes to identify immunocompromised persons (hematologic and solid organ malignancy;SOTR;autoimmune disease, including inflammatory bowel disease, rheumatoid arthritis, and SLE). We use common case definitions to extract data on demographic, laboratory values, clinical co morbidity, COVID-19 vaccination, SARS-CoV-2 infection and severe COVID-19, and diseasespecific variables. In addition, we pool individual-level data from prospective cohorts enrolling patients with cancer and other immunosuppressed conditions from across network. Surveys and biospecimens from serology and immune profiling are collected at pre-specified timepoints across longitudinal cohorts. Result(s): Currently, we have EMR data extracted from 4 health systems including >715,000 cancer patients, >9,500 SOTR and >180,000 with autoimmune conditions. Prospective cohorts across the network have longitudinal data on >450 patients with lung cancer, >1,200 patients with hematologic malignancies, >400 SOTR and >400 patients with lupus. We will report results examining vaccine effectiveness for prevention of SARS-CoV-2 infection, severe COVID-19 and post-acute sequelae of COVID-19 (PAS-C or long COVID) in cancer patients compared to other immunocompromised conditions. Conclusion(s): Our goal is to inform public health guidelines on COVID-19 vaccine and boosters to reduce SARS-CoV-2 infection and severe illness in immunocompromised populations.

Social isolation and cognitive function in middle aged and older adults in the Wisconsin Alzheimer's Disease Research Center: Implications for the pandemic

Background: Social isolation and loneliness contribute to cognitive decline, and social isolation represents a key modifiable risk factor for dementia. Substantial interruptions in social engagement due to the COVID-19 pandemic have heightened awareness of this issue, but common later-life events may also reduce social connectedness. The neurocognitive impacts of such disruptions are unclear. Using the validated NIH Emotion Toolbox, we examined perceived social support and changes in perceived support as predictors of cognitive function in a sample of middle aged and older adults. Method(s): 672 participants from the Wisconsin Alzheimer's Disease Research Center (ADRC) completed cognitive tests and Emotion Toolbox questionnaires at 2+ visits between 2017 and 2021 (mean interim = 1.7 years). Predictors comprised t-scores on three perceived social support scales: Emotional Support, Instrumental Support, and Loneliness. Cross-sectional analyses examined associations between social support and cognitive outcomes including memory (RAVLT Immediate and Delayed Recall) and processing speed/executive function (Trails A&B times). Using median t scores from the first and last available visit to categorize social support as high or low (for Loneliness, low loneliness was categorized as "high" social support), support over time was classified as stable-high, stable-low, or "change" (high-low or low-high). Mixed-effects regression models examined the demographic-adjusted predictor-outcome relationships between social support and cognition across visits. Result(s): In this ADRC sample (mean age 65.2, SD = 9.2;Table 1), all three social support scores associated cross-sectionally (Table 2) with Trails A and B performance. Relative to stable-high participants, those reporting either stable-low or declines from high to low social support exhibited poorer performance on measures of processing speed/executive function. Conversely, participants in the low-high group performed comparably on cognitive tests to those in the stable-high group (Table 3;Figure 1). Conclusion(s): Social support associated with processing speed/executive function in this sample. Participants who reported a change in social support performed comparably to those with either stable high or stable low support, suggesting that processing speed/executive function associated with social support may be modifiable in the shorter term. These findings underscore the cognitive cost of social isolation and highlight the substantial benefits of maintaining - and improving - social connections among middle aged and older adults. Copyright © 2022 the Alzheimer's Association.

Antibody Responses to an Additional Dose of SARS-CoV-2 mRNA Vaccine in Solid Organ Transplant Recipients with and without HIV

Purpose: Solid organ transplant (SOT) recipients mount suboptimal immune responses to a two-dose SARS-CoV-2 mRNA vaccine series. Data regarding antibody responses in HIV and SOT remains limited. We characterized spike binding antibody responses before and after an additional mRNA vaccine dose in SOT recipients, including in people with HIV (PWH). Method(s): Spike binding antibody titers were assessed before and one month after an additional vaccine dose using a quantitative ELISA. An additional vaccine dose was defined as a third dose of a mRNA vaccine primary series, as recommended by the CDC. Result(s): Antibody titers were assessed in 64 SOT recipients (58% kidney, 34% liver, 8% other). Participants had a median age of 57 and 47% were women. PWH comprised 14% of the cohort (9/64, 78% kidney). 70% (45/64) of SOT recipients developed antibodies after a two-dose vaccine series (62% kidney, 33% liver). The additional dose was given a median of 169 days (IQR 144.75-185.75 days) after the second vaccine dose, and 72% received three doses of BNT162b2 (Pfizer-BioNTech) while 28% received three doses of mRNA-1273 vaccine (Moderna). The median time between transplantation and an additional vaccine dose was 2.8 years (IQR, 0.6-8.9). 32% (6/19) of SOT recipients who had no detectable antibody seroconverted after receiving an additional vaccine dose. The 45 participants who were seropositive prior to the third dose displayed a median 4.4-fold increase in antibody titers. SOT recipients with HIV had comparable antibody responses to those without HIV. Conclusion(s): Our data indicate that SOT recipients benefit from an additional SARS-CoV-2 mRNA vaccine dose. SOT recipients with and without HIV appear to mount comparable antibody responses upon vaccination, although larger numbers are needed.

Suboptimal Humoral and Cellular Immune Response to SARS-CoV-2 RNA Vaccination in Myeloma Patients Is Associated with Anti-CD38 and BCMA-Targeted Treatment

Background: Multiple myeloma (MM) patients are immunocompromised due to defects in humoral/cellular immunity and immunosuppressive therapy. Reports indicate that the antibody (Ab) response in MM after 1 dose of SARS-CoV-2 RNA vaccine is attenuated. The impact of treatment on cellular immunity after vaccination remains unknown. Methods: We analyzed SARS-CoV-2 spike-binding (anti-S) IgG level in 320 MM patients receiving SARS-CoV-2 RNA vaccination. Blood and saliva were taken at multiple time points and compared with serology data of 69 age-matched vaccinated healthcare workers. We profiled SARS-CoV-2-specific T cell responses in a subset of 45 MM patients and 12 age-matched healthy controls by flow cytometry and ELIspot. All subjects were enrolled in studies approved by the Institutional Review Board at the Icahn School of Medicine at Mount Sinai. Results: The 320 patients (median age 68 year) received two-dose RNA vaccines (69.1% BNT162b2, 27.2% mRNA-1273). Median time to diagnosis was 60 months with a median of 2 prior treatment lines (range 0-16). We included 23 patients with smoldering MM. Patients received various treatments at vaccination with 148 (43.8%) on anti-CD38-containing treatment, 36 (11.3%) on BCMA-targeted therapy and 59 (18.4%) not on active treatment (incl. SMM patients). At the last available evaluation prior to vaccination, 131 (40.9%) exhibited a complete response. At data cutoff, a total of 260 patients (81.3%) had anti-S IgG measured >10 days after the second vaccine (median 51 days). Of these, 84.2% mounted measurable anti-S IgG levels (median 149 AU/mL). In the control group, Ab levels were significantly higher (median 300 AU/mL). Ab levels in the vaccinated MM patients with prior COVID-19 were 10-fold higher than those of patients without prior COVID-19 (p<0.001). Repeat Ab measurements up to 60 days after second vaccination confirm delayed and suboptimal IgG kinetics, particularly in patients receiving anti-MM treatment compared to controls (Figure 1). MM patients on active treatment had lower anti-S IgG levels (p=0.004) compared to patients not on therapy (median 70 vs 183 AU/mL). Notably, 41 patients (15.8%) failed to develop detectable anti-S IgG: 24/41 (58.5%) were on anti-CD38, 13/41 (31.7%) on anti-BCMA bispecific Ab therapy and 4/41 (9.8%) >3 months after CAR T. Univariate analysis showed an association of disease-related factors with absence of anti-S IgG: more previous lines of treatment (>3 lines, p=0.035;>5 lines, p=0.009), receiving active MM treatment (p=0.005), grade 3 lymphopenia (p=0.018), receiving anti-CD38 therapy (p=0.042) and receiving BCMA-targeted therapy (p<0.001). Multivariate analysis (corrected for age, vaccine type, lines of treatment, time since diagnosis, response status and lymphopenia) confirmed that anti-CD38 (p=0.005) and BCMA-targeted treatment (p<0.001) are associated with not developing detectable anti-S IgG. Clinical relevance is emphasized by 10 cases of COVID-19 after 1 (n=7) or 2 vaccine doses (n=3, all without anti-S IgG) with 1 patient passing due to respiratory failure. We studied SARS-CoV-2-specific T cell responses >2 weeks after the second vaccine in 18 MM patients with undetectable anti-S IgG (seronegative), 27 with detectable anti-S IgG (seropositive) and 12 healthy seropositive controls. We found that seropositive MM patients had CD4+CD154+ T cells producing IFNg, TNFa and IL-2 at similar levels as controls, whereas in the seronegative MM cohort CD4 T cell responses were significantly reduced (p<0.005). SARS-CoV-2-specific CD8 T cell responses were overall weaker and not different across cohorts. This data suggests that absence of detectable IgG is associated with suboptimal response of humoral and cellular immunity. Conclusion: MM patients mount a suboptimal IgG response after SARS-CoV-2 vaccination, with 15.8% of patients without detectable anti-S IgG. Ongoing analyses will highlight durability of serological protection against COVID-19. Additional data on T cell responses and immunophenotyping in the context of vaccination will be upda ed at the meeting. Implications are continuation of non-pharmacological interventions, e.g. masking/social distancing, for vulnerable patients. The findings underscore a need for serological monitoring of MM patients after vaccination and for trials assessing use of prophylactic strategies or studies exploring additional immunization strategies. [Formula presented] Disclosures: Wang: Sanofi Genzyme: Consultancy. Chari: Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees;Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding;Millenium/Takeda: Consultancy, Research Funding;Sanofi Genzyme: Consultancy, Membership on an entity's Board of Directors or advisory committees;Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees;Pharmacyclics: Research Funding;GlaxoSmithKline: Consultancy, Membership on an entity's Board of Directors or advisory committees;Secura Bio: Consultancy, Membership on an entity's Board of Directors or advisory committees;Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding;Antengene: Consultancy, Membership on an entity's Board of Directors or advisory committees;Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees;Novartis: Consultancy, Research Funding;Janssen Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding;Shattuck Labs: Consultancy, Membership on an entity's Board of Directors or advisory committees;BMS/Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding;Takeda: Consultancy, Research Funding;AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Cordon-Cardo: Kantaro: Patents & Royalties. Krammer: Kantaro: Patents & Royalties;Merck: Consultancy;Pfizer: Consultancy;Avimex: Consultancy;Seqirus: Consultancy. Jagannath: Legend Biotech: Consultancy;Karyopharm Therapeutics: Consultancy;Janssen Pharmaceuticals: Consultancy;Bristol Myers Squibb: Consultancy;Sanofi: Consultancy;Takeda: Consultancy. Simon: Kantaro: Patents & Royalties. Parekh: Foundation Medicine Inc: Consultancy;Amgen: Research Funding;PFIZER: Research Funding;CELGENE: Research Funding;Karyopharm Inv: Research Funding.

Disability and the COVID-19 Pandemic: Using Twitter to Understand Accessibility during Rapid Societal Transition

The COVID-19 pandemic has forced institutions to rapidly alter their behavior, which typically has disproportionate negative effects on people with disabilities as accessibility is overlooked. To investigate these issues, we analyzed Twitter data to examine accessibility problems surfaced by the crisis. We identified three key domains at the intersection of accessibility and technology: (i) the allocation of product delivery services, (ii) the transition to remote education, and (iii) the dissemination of public health information. We found that essential retailers expanded their high-risk customer shopping hours and pick-up and delivery services, but individuals with disabilities still lacked necessary access to goods and services. Long-experienced access barriers to online education were exacerbated by the abrupt transition of in-person to remote instruction. Finally, public health messaging has been inconsistent and inaccessible, which is unacceptable during a rapidly-evolving crisis. We argue that organizations should create flexible, accessible technology and policies in calm times to be adaptable in times of crisis to serve individuals with diverse needs. © 2020 Owner/Author.