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Abstract Introduction Chimeric antigen receptor (CAR) T-cell therapy and bispecific antibodies have emerged as transformative options for patients with relapsed or refractory multiple myeloma (MM). Both modalities commonly target B-cell maturation antigen (BCMA) and have demonstrated high overall response rates in pretreated populations ranging from 65-83%. However, the optimal sequencing and comparative effectiveness of these two novel therapies remain unclear. Understanding their treatment outcomes is critical to inform treatment decisions in this rapidly evolving therapeutic landscape. Method A retrospective cohort study was conducted using TriNetX, a global federated health research network that provides access to electronic medical records from approximately 132 million patients, primarily in the United States. Adult patients (≥18 years) diagnosed with relapsed or refractory MM between January 1, 2022, and January 1, 2024, were identified using ICD-10-CM codes. Patients were categorized into two cohorts: those who received CAR T-cell therapy including idecabtagene vicleucel and ciltacabtagene autoleucel and those who received bispecific antibodies including teclistamab and elranatamab. Propensity score matching (1:1) using nearest neighbor matching with a 0.1 pooled standard deviation caliper was performed for demographics, comorbidities, prior stem cell transplantation, medications, and performance status. Study outcomes included 1-year rates of all-cause mortality, all-cause hospitalization, cytokine release syndrome (CRS), immune effector cell-associated neurotoxicity syndrome (ICANS), anemia, neutropenia, thrombocytopenia, sepsis, and pneumonia. Statistical analyses were conducted on the TriNetX platform, with significance set at P<0.05 (two-sided). TriNetX calculates hazard ratios (HRs) and cumulative incidences (CIs) using R survival package version 3.2-3 with the proportional hazard assumption tested using Schoenfeld residuals. This study does not require Institutional Review Board review or informed consent due to the use of de-identified data. Results Our study identified 2,023 patients, including 911 patients who received CAR T-cell therapy and 1,112 who received bispecific antibiotics. After propensity score matching (PSM), each cohort included 649 patients. The CAR T-cell therapy group had a mean age of 66.8 ± 8.4 years, with 41.4% female, 68.0% White, 20.6% African American, and 2.3% Asian. The bispecific antibody group had a mean age of 66.3 ± 9.3 years, with 41.1% female, 67.3% White, 21.1% African American, and 2.2% Asian. CAR T-cell therapy group experienced a 64% lower risk of all-cause mortality (HR 0.36; 95% CI, 0.26–0.48) and a 44% lower risk of all-cause ICU admission (HR 0.56; 95% CI, 0.42–0.75) compared with bispecific antibodies group. However, CAR T-cell therapy group was associated with higher risk of CRS (HR: 1.91; 95% CI: 1.57–2.31), ICANS (HR: 1.50; 95% CI: 1.12–2.01), neutropenia (HR: 2.32; 95% CI: 1.96–2.76), and thrombocytopenia (HR: 1.80; 95% CI: 1.43–2.28) compared to bispecific antibodies group. There was no significant difference observed in anemia (HR: 0.96; 95% CI: 0.82–1.13) between these two treatment groups. Additionally, CAR T-cell therapy group was associated with 46% lower risk of sepsis (HR: 0.54; 95% CI: 0.39–0.75) and 68% lower risk of pneumonia (HR: 0.32; 95% CI: 0.17–0.61) compared to bispecific antibodies group. ConclusionIn this real-world analysis, CAR T-cell therapy demonstrated a substantial lower mortality and reduced ICU utilization compared with bispecific antibodies in patients with relapsed or refractory MM, despite its higher risks of CRS, ICANS, and hematologic toxicities. An important limitation of our study is the lack of data on the number of prior lines of therapy, which likely differed between groups, as bispecific antibodies are typically used in the fourth line or beyond, while CAR T-cell therapies are approved to be used as the second line. This discrepancy may have influenced both mortality and infection rates. Despite the limitation, our findings underscore the need for prospective clinical trials directly comparing CAR T-cell therapy and bispecific antibodies to validate these observations and define the optimal sequencing of these modalities. Furthermore, research into predictive biomarkers and personalized selection algorithms will be crucial to optimize treatment decisions in this rapidly evolving therapeutic landscape.

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS