Citations

Intrathecal synthesis of central nervous system (CNS)-reactive autoantibodies is observed across patients with autoimmune encephalitis (AE), who show multiple residual neurobehavioral deficits and relapses despite immunotherapies. We leveraged two common forms of AE, mediated by leucine-rich glioma inactivated-1 (LGI1) and contactin-associated protein-like 2 (CASPR2) antibodies, as human models to comprehensively reconstruct and profile cerebrospinal fluid (CSF) B cell receptor (BCR) characteristics. We hypothesized that the resultant observations would both inform the observed therapeutic gap and determine the contribution of intrathecal maturation to pathogenic B cell lineages. From the CSF of three patients, 381 cognate-paired IgG BCRs were isolated by cell sorting and scRNA-seq, and 166 expressed as monoclonal antibodies (mAbs). Sixty-two percent of mAbs from singleton BCRs reacted with either LGI1 or CASPR2 and, strikingly, this rose to 100% of cells in clonal groups with ≥4 members. These autoantigen-reactivities were more concentrated within antibody-secreting cells (ASCs) versus B cells ( P < 0.0001), and both these cell types were more differentiated than LGI1- and CASPR2-unreactive counterparts. Despite greater differentiation, autoantigen-reactive cells had acquired few mutations intrathecally and showed minimal variation in autoantigen affinities within clonal expansions. Also, limited CSF T cell receptor clonality was observed. In contrast, a comparison of germline-encoded BCRs versus the founder intrathecal clone revealed marked gains in both affinity and mutational distances ( P = 0.004 and P < 0.0001, respectively). Taken together, in patients with LGI1 and CASPR2 antibody encephalitis, our results identify CSF as a compartment with a remarkably high frequency of clonally expanded autoantigen-reactive ASCs whose BCR maturity appears dominantly acquired outside the CNS.

OBJECTIVE Poor pain control has a negative impact on postoperative recovery and patient satisfaction. However, overzealous pain management, particularly with opioids, can confound serial neurological assessments, increase morbidity, and predispose patients to long-term dependence. Nonsteroidal anti-inflammatory drugs (NSAIDs) are effective in treating postoperative pain and can limit opioid intake, but their use has been limited in patients undergoing craniotomy for brain tumor resection due to concerns of an increased hemorrhage risk. Herein, the authors aim to 1) address the safety of NSAID use in the immediate postoperative setting and 2) determine whether NSAID administration decreases opioid use following craniotomy for tumor resection in adult patients. METHODS The authors conducted a retrospective cohort study of patients 18 years and older with an estimated glomerular filtration rate ≥ 60 ml/min/body surface area who had undergone craniotomy for tumor resection at their institution between 2019 and 2021. NSAID use in the first 48 hours following surgery was recorded. Primary outcomes were postoperative hemorrhage requiring a return to the operating room before hospital discharge and within 30 days of surgery. Secondary outcomes were more-than-minimal hemorrhage that did not require reoperation, acute kidney injury, and total opioid use within 48 hours after craniotomy. RESULTS Among 1765 reviewed patient records, 1182 were eligible for inclusion in this analysis. Amid these records were 114 patients (9.6%) who had received at least one dose of an NSAID within 48 hours of their craniotomy. Four (0.3%) patients experienced bleeding requiring a return to operating room, one of whom was from the NSAID-treated group (RR 3.12, 95% CI 0.33–29.77, p = 0.30). No significant difference in nonoperative intracranial hemorrhage (RR 1.34, 95% CI 0.54–3.35, p = 0.53), postoperative acute kidney injury, or clinically significant extracranial bleeding was found between the NSAID and no-NSAID groups. Patients in the NSAID group had significantly higher oral morphine equivalent use (median 68 vs 30, p < 0.001). CONCLUSIONS Postoperative NSAID use following craniotomy for tumor resection was not associated with an increased risk of hemorrhage requiring a return to the operating room. The authors noted higher opioid use in the patients treated with NSAIDs, which may reflect underlying reasons for the decision to treat patients with NSAIDs in the immediate postoperative period. These data warrant further investigation of NSAIDs as a safe, opioid-sparing postoperative pain management strategy in patients with normal kidney function who are undergoing intracranial tumor resection.

385 Background: Tyrosine kinase inhibitors (TKI) and immuno-oncology (IO) agents alone or in combination have revolutionized the landscape of management for untreated metastatic renal cell carcinoma (mRCC). Baseline quality of life (QOL) outside of interventional clinical trials and rationale for management decisions in mRCC are poorly understood. Methods: In this prospective observational study of 800 mRCC pts in the US, pts must: have a diagnosis of mRCC (any histology) with no prior systemic therapy (ST) for mRCC; be age ≥19 at informed consent; be able to comply with completion of PROs. Exclusion criteria include being treated for active malignancy other than mRCC or not intending to follow up at a study site within PCORnet. Pts undergo consent and baseline assessments by the study site team, with subsequent follow up by the central coordinating center. The primary objective is to determine distinct patterns of change in QOL and symptom burden of mRCC pts. A key secondary objective is to identify patterns of clinical management in the real world setting of mRCC across treatment regimens. Minimally important differences are defined as 3- and 7-points for FKSI-19 and FACT-G respectively. ClinicalTrials.gov ID: NCT04919122. Results: As of 9/1/2023, 173 pts have been enrolled (126 ST, 47 no ST [NST]): 75% male, 87% white, 73% clear cell, 52% intermediate risk and 47% poor risk. 47% had radical nephrectomy and 22% another solid tumor. ST pts as compared to NST pts were more likely to be poor risk (52% vs 16%); but differences in baseline pain were not significant. Of ST pts, 44 were treated with IO-IO (ipilimumab + nivolumab), 50 with IO-TKI (cabozantinib + nivolumab 38%, axitinib + pembrolizumab 38%, lenvatinib + pembrolizumab 24%) and 32 other (IO alone 34%, TKI alone 31%, investigational drug 25%). Reasons for NST included active surveillance (AS, 50%), other (21%), local therapy (13%). Mean differences between ST and NST for baseline FKSI-19 and FACT-G were 5.7 (95% CI: 1.2 – 10.2) and 3.3 (-2.6 – 9.3). There were no differences in pain or PROs between IO-IO and IO-TKI pts. Mean differences in FKSI-19 and FACT-G between AS vs IO-IO were 10.6 (4.8 – 16.4) and 8.6 (1.1 – 16.0); and vs IO-TKI were 11.0 (4.9 – 17.0) and 10.3 (3.5 – 17.1). On physician surveys, primary reasons for treatment selection were (in order of % selected): complete response (CR), prolonged survival (OS), prognostic factors (Px), treatment-free interval for IO-IO; versus delaying progression (PFS), OS, CR, Px for IO-TKI. Conclusions: Our data suggest differences in baseline QoL in pts treated with ST vs NST, as well as AS vs IO-IO or IO-TKI, in the real world. Reasons for selection of ST regimen differed among combination regimen classes. Completion of ODYSSEY will clarify baseline and longitudinal differences in pain and PROs among management strategies and give novel insights into the rationale for real world management of untreated pts with mRCC. Clinical trial information: NCT04919122 .

Abstract Background: The genotoxin colibactin causes a tumor single-base substitution (SBS) mutational signature, SBS88. It is unknown whether epidemiologic factors’ association with colorectal cancer risk and survival differs by SBS88. Methods: Within the Genetic Epidemiology of Colorectal Cancer Consortium and Colon Cancer Family Registry, we measured SBS88 in 4,308 microsatellite stable/microsatellite instability low tumors. Associations of epidemiologic factors with colorectal cancer risk by SBS88 were assessed using multinomial regression (N = 4,308 cases, 14,192 controls; cohort-only cases N = 1,911), and with colorectal cancer–specific survival using Cox proportional hazards regression (N = 3,465 cases). Results: 392 (9%) tumors were SBS88 positive. Among all cases, the highest quartile of fruit intake was associated with lower risk of SBS88-positive colorectal cancer than SBS88-negative colorectal cancer [odds ratio (OR) = 0.53, 95% confidence interval (CI) 0.37-0.76; OR = 0.75, 95% CI 0.66–0.85, respectively, Pheterogeneity = 0.047]. Among cohort studies, associations of body mass index (BMI), alcohol, and fruit intake with colorectal cancer risk differed by SBS88. BMI ≥30 kg/m2 was associated with worse colorectal cancer–specific survival among those SBS88-positive [hazard ratio (HR) = 3.40, 95% CI 1.47–7.84], but not among those SBS88-negative (HR = 0.97, 95% CI 0.78–1.21, Pheterogeneity = 0.066). Conclusions: Most epidemiologic factors did not differ by SBS88 for colorectal cancer risk or survival. Higher BMI may be associated with worse colorectal cancer–specific survival among those SBS88-positive; however, validation is needed in samples with whole-genome or whole-exome sequencing available. Impact: This study highlights the importance of identification of tumor phenotypes related to colorectal cancer and understanding potential heterogeneity for risk and survival.

Background: Approximately 30% of renal cell carcinoma (RCC) cases present with de novo metastatic disease, while 20% to 30% of those with localized disease will develop metastases following surgical resection. Various drug classes have been investigated to treat RCC, including cytokine-based therapies, small molecule Vascular Endothelial Growth Factor (VEGF) tyrosine kinase inhibitors (TKIs) and antibody-based therapies. Up to 58% of patients fail to respond to primary immune checkpoint inhibitor (ICI) therapy, and nearly all initial responders experience disease progression due to the development of secondary resistance. Consequently, novel treatment options are being investigated. Objective: Review the rapidly evolving ADC therapeutic landscape in metastatic RCC including recent trials, emerging ADCs targets, and future directions for ADCs in the treatment of advanced RCC. Methods: Literature review using the MEDLINE database on important trials and presentations from the American Society of Clinical Oncology (ASCO), and the European Society for Medical Oncology (ESMO) conferences. Key words used included “renal cell carcinoma,” “RCC,” “metastatic RCC,” “advanced RCC,” “antibody-based therapies,” “immunotherapy,” “clinical trials,” and “emerging drugs.” Specifically for review of ADCs in RCC, the following search string was used with additional review of bibliographies from retrieved papers: “((antibody drug conjugate) OR (antibody-dependent cellular cytotoxicity) OR (chimeric antigen receptor)) AND ((kidney cancer) OR (renal cell carcinoma))”. Results: Several promising targets including MMP14, EGFR, MCT4, CA9, MET, CDH13, B7-H3, and PSMA were identified with relevant preclinical and clinical studies reviewed. Conclusions: While ADCs therapeutics have not shown benefit to date for renal cell carcinoma, there are ample promising candidates and targets for future research.

AbstractBackgroundThe U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is a two‐year randomized controlled trial designed to evaluate the effects of lifestyle interventions on older adults aged 60‐79 years. The POINTER Imaging ancillary study employs arterial spin labeling (ASL) magnetic resonance imaging (MRI) with two inversion times, enabling the mapping of arterial transit time (ATT) and the investigation of its relationship with dementia risk factors. This study examines the effect of the Framingham Risk Score (FRS) on ATT, which provides hemodynamic information on the cerebral vasculature.MethodA subset of POINTER Imaging participants (n = 134; F/M = 81/53; age = 68.1±5.1; FRS = 11.3±10.4) from two imaging sites underwent two ASL MRI scans during the baseline session. Two 3D Pulsed ASL scans were obtained with TI1 of 790ms and TI2 values of 2000ms or 2750ms, providing delay times (between labeling and imaging) of 1210ms or 1960ms. ATT, the time required for blood to travel from the neck to the tissue, was estimated in the range of 1210ms and 1960ms using a kinetic model (Figure 1). ATT maps were normalized to a standard space, and a voxel‐wise linear regression (ATT∼age+sex+log(FRS)) was performed on ATT maps in gray matter to assess the effect of FRS on ATT. To control false positives, clusters smaller than 1.4ml were removed based on a simulation with α = 0.05.ResultFigure 2 depicts three clusters found in the occipital, precuneus and frontal gray matter regions, all of which demonstrate a positive relationship between ATT and log(FRS). Participants with higher FRS exhibit prolonged mean ATT values in the clusters as shown in Figure 3. After stratifying into sex groups, both groups show the same direction.ConclusionAlthough the detectable range of ATT with two ASL scans was limited, the analysis suggests that an increased risk of cardiovascular disease, as quantified by the Framingham Risk Score, can serve as an indicator of potential cerebrovascular disease leading to prolonged ATT, which is associated with arterial stiffness, and vascular resistance. The clusters demonstrating the association between FRS and ATT are the brain regions that may have heightened vulnerability to vascular risk factors, according to previous studies.

AbstractBackgroundA key focus of the U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is recruitment of unimpaired older individuals at risk for cognitive decline with heterogeneous characteristics (under‐represented racial and ethnicity groups (URG), family history of cognitive decline, hypertension, geographic diversity), and a subset of individuals undergo PET and MRI.MethodTo examine effects of heterogeneity on relationships between risk factors, AD biomarkers (Aβ and entorhinal tau PET, hippocampal volume (HV)) and cognition (global, executive function, and memory) were examined from U.S. POINTER neuroimaging participants (N = 602, about 65% of the anticipated total sample) and a subset of Alzheimer’s Disease Neuroimaging Initiative participants (N = 503). Neuroimaging data were processed and analyzed using harmonized methods across studies. Some cohort‐specific measurements were standardized using a within‐cohort reference group (Aβ‐negative individuals <70yrs and with global CDR = 0).ResultU.S. POINTER imaging participants are younger than those in ADNI (68.6+/‐5.0yrs vs 70.7+/‐4.4yrs), more likely to be female (65% vs 58%) and from URG (27% vs 15%), and had lower education (14.7+/‐3.3yrs vs 16.7+/‐2.3yrs) and higher Framingham Cardiovascular Risk scores (9.9+/‐8.3 vs 7.7+/‐5.3). The groups differed on several AD biomarkers and cognitive measures (Table). In regression models, AD biomarkers were stronger predictors of cognitive performance in ADNI compared to POINTER. Specifically, Aβ+ individuals with elevated tau had disproportionately poorer cognitive performance in ADNI, and this relationship remained consistent across cognitive measures (Figure). Conversely, demographic/risk variables were stronger predictors in POINTER. Demographic/risk predictors (age, sex, education, race, and FRS) together explained twice as much variance in global cognition in POINTER compared to ADNI (Adjusted R2 = 29% vs 14%). The addition of AD biomarkers to the model further increased the amount of variance in global cognition explained from 14% to 34% in ADNI, but addition of AD biomarkers did not increase variance explained in the POINTER model.ConclusionHeterogeneity among study participants appears to influence baseline biomarker‐cognition relationships such that AD biomarkers explain more variability in cognitive performance in ADNI than POINTER. These findings further suggest that cohort characteristics may affect the potential influence of amyloid‐ and tau‐modifying treatments on cognition.

AbstractBackgroundThe Standardized Centralized Alzheimer’s & related dementias Neuroimaging (SCAN) project harmonizes processing of prospectively acquired PET and MRI scans from Alzheimer’s disease research centers (ADRCs) across the USA. SCAN data will be integrated with other ADRC data streams within the National Alzheimer’s Coordinating Center (NACC), including the Uniform Data Set which includes rich longitudinal demographic, cognitive, and neuropathological data, resulting in a large, potentially representative cohort. The project has sought to accommodate site‐to‐site variation in image acquisition while permitting harmonization of imaging data, necessitating new analytic approaches for different PET tracers and PET scans without MRIs.MethodPET scans underwent preprocessing for quality control and smoothing to a uniform resolution. MRI‐free processing pipelines and positivity thresholds were developed for each beta‐amyloid (Aβ)‐PET tracer: [11C]PiB, [18F]florbetaben (FBB), [18F]florbetapir (FBP) and [18F]flutafuranol (NAV). A generic Aβ‐PET template was used for spatial normalization and cortical summary SUVRs were calculated in template space. Aβ‐positivity thresholds were determined by examining both MRI‐dependent thresholds transformed into MRI‐free units and a young control mean+2SD. Centiloid (CL) conversions were completed for each Aβ‐PET tracer. Tau‐PET tracers ([18F]flortaucipir (FTP) and [18F]MK‐6240) required tracer‐specific warping templates for best performance relative to gold‐standard MRI‐dependent processing. Demographic and clinical data were obtained from NACC.Result15 ADRCs have contributed data to SCAN as of January 2023. 477 participants had preprocessed, SCAN‐compliant (https://scan.naccdata.org/) Aβ‐PET scans and NACC data; 219 of these participants (46%) also had tau‐PET scans (Table 1). This cohort included 18% of individuals from underrepresented groups. Clinical diagnostic groups ranged from cognitively unimpaired to MCI and dementia (74% of whom had AD dementia). Using pooled Aβ‐PET data across 4 tracers in CLs, there were expected differences in Aβ burden by diagnosis group (Fig. 1) and positive associations with tau (Fig. 2).ConclusionSCAN has successfully harmonized PET data from more than a dozen US ADRCs yielding a large, clinically heterogeneous cohort of deeply phenotyped research participants. SCAN data will be compatible with ADNI data allowing for further pooling of data and greater statistical power to drive critical questions in AD and related dementias research.

AbstractBackgroundThe U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is a 2‐year randomized controlled trial to evaluate the effect of lifestyle interventions in cognitively unimpaired older adults (60‐79 years) at risk for decline/dementia. Here, using data from the POINTER Imaging ancillary substudy, we explore how Alzheimer’s disease pathology and cardiovascular risk influence brain structure, cognition and their relationship.MethodPOINTER Imaging participants underwent cross‐sectional MRI, [18F]Florbetaben (FBB) Aβ‐PET and [18F]MK6240 tau‐PET. FBB and MK6240 data were processed using previously validated methods. MRIs were processed with voxel‐based morphometry. To quantify cardiovascular risk, the Framingham risk score (FRS) was calculated for each participant. We used linear regression models in the whole sample as well as in Aβ status subgroups to evaluate voxel‐wise associations of brain structure, measured using voxel‐based morphometry, with age, FRS, AD pathology (cortical summary Aβ and entorhinal cortex (ERC) tau burden), and a global cognition composite score.ResultAcross all 624 participants (Table 1), cognition (age‐adjusted) was positively related to brain structure across temporal, frontal and medial parietal cortices (Fig. 1A). ERC tau‐PET was negatively associated with brain structure in bilateral medial temporal lobes (MTL) and, notably, in bilateral basal forebrain (Fig. 1B). FRS showed significant negative associations in superior temporal gyrus and occipital cortex (Fig. 1C), but tau‐PET associations remained similar when adjusting for FRS. In Aβ+ participants, cognition‐ and FRS‐structure relationships were weaker but tau‐PET‐structure associations were stronger and extended outside the MTL. In Aβ‐ participants, cognition‐ and FRS‐structure relationships were similar to those observed in the whole cohort and tau‐PET associations were no longer significant.ConclusionIn this heterogeneous cohort of older adults, tau was associated with brain structure in strikingly specific patterns that were related to Aβ but not to cardiovascular risk as measured by the FRS. Tau‐structure associations were restricted to temporal lobes and basal forebrain and were independent of more widespread cognition‐structure associations, indicating that factors other than tau may play a critical role. Our next steps include comparing the current cohort to others with different at‐risk characteristics (e.g., ADNI, Berkeley Aging Cohort Study).

AbstractBackgroundStructural variants range from simple loss or gain of genetic material to complex events that restructure entire chromosomes. This heterogeneity coupled with variant size greater than sequencing read‐length makes structural variant mapping from short‐read sequencing data difficult and error‐prone. Consequently, the role of structural variants is poorly explored in many phenotypes, including dementia.MethodWe used the GATK‐SV pipeline that combines four external structural variant mapping algorithms with machine‐learning to build high‐quality consensus structural variant calls. We applied GATK‐SV to short‐read whole‐genome sequencing data of 2,601 frontotemporal dementia‐amyotrophic lateral sclerosis spectrum (FTD/ALS) patients, 2,612 Lewy body dementia (LBD) patients, and 4,132 neurologically unaffected participants.ResultAfter stringent quality‐control, we performed genome‐wide association studies on 2,307 ALS/FTD patients versus 3,677 controls with 4,699 common structural variants and 2,355 LBD patients versus 3,700 controls with 4,889 common structural variants. In the FTD/ALS cohort, we identified well‐known risk variants at the C9orf72 (p‐value = 4.99×10‐18, OR = 14.47, 95% CI = 7.90–26.49) and MAPT loci (p‐value = 3.48×10‐6, OR = 0.77, 95% CI = 0.68–0.86) corroborating the ability of our pipeline to identify disease‐associated structural variants. Moreover, we discovered, replicated, and validated TPCN1 as a novel risk locus for LBD (p‐value = 9.18×10‐6, OR = 1.43, 95% CI = 1.22–1.67). Further, we identified rare exonic variants with known pathogenic or likely pathogenic effects, such as an SNCA gene duplication in LBD and a deletion of exons 1 and 2 in CHCHD10 in FTD/ALS. We additionally observed structural variants in regulatory regions, e.g. a deletion of a key PSEN2 enhancer, which resulted in an approximate 0.70 fold‐change in PSEN2 expression in LBD. Finally, we built an interactive web app where structural variants can be visualized and explored (https://ndru-ndrs-lng-nih.shinyapps.io/non_ad_dementias_sv_app/).ConclusionCommon and rare structural variants play a role in LBD and FTD/ALS. Our structural variant resource is publicly available and can be used to further explore the role of structural variants in LBD and FTD/ALS.