Washington University School Of Medicine Research Articles

Abstract PO3-09-01: Integrating pathomic and radiomic images to classify risk of subsequent events among women with DCIS

Abstract Background Multiple sources of ~omic data can be generated from women at different stages of developing breast cancer, the leading cancer diagnosed in women worldwide. Traditionally interrogation of risk factors to study associations and develop prediction models for future breast events has been limited to one or few risk factors, or summary scores of clinical and tumor characteristics. Methods to bring mammography images and breast biopsies of precancer lesions together to summarize risk of cancer developing in the breast are urgently needed. Integration of these two sources has not been performed to date, but has potential to increase accuracy of risk prediction. Approach The Repository of Archival Human Breast Tissue (RAHBT) was established in 2007 at Washington University School of Medicine (WUSM) and maintains biospecimens and medical record data of women treated with breast-conserving surgery (BCS) or mastectomy for breast cancer at WUSM and six other St Louis metropolitan hospitals between 1981-2016. Prospective follow-up of cases is achieved through health records and Siteman tumor registry. Among 1831 patients with pathologically confirmed DCIS who had no prior cancer, 174 developed breast events at least six months after initial DCIS diagnosis. For each case diagnosed between January 1998 and March 2016 with subsequent breast events, two DCIS controls were matched on race, year of diagnosis (±5 years), age (±5 years), and type of surgery. Tissue micro arrays (TMAs) are constructed after breast pathology review and processed for H&E and imaged. Breast cancer risk factor data are uniformly retrieved form the medical records at time of processing cases of DCIS. Mammogram images are retrieved for all women. Full-field digital mammograms (FFDM) are all using the same technology (Hologic). Risk factors and outcome variables: ipsilateral breast events (IBE) was defined as the development of invasive cancer or DCIS in the treated breast at least 6 months post-diagnosis. Follow-up time was calculated from the date of DCIS diagnosis to the date of first IBE, death, or last follow-up, whichever occurred first. The predictors included commonly used clinicopathological factors: age, tumor grade (high vs. low/intermediate), comedonecrosis, surgical margins (close (≤2mm) vs. negative ( >2mm)), local treatment (BCS only and mastectomy vs. BCS+radiation), and endocrine therapy. BMI, menopausal status, and ER were also available for evaluation as predictors. We limited this analysis to women with digital mammograms immediately prior to diagnosis and include 128 cases and controls. Validation cohort As the RAHBT cohort continues to be followed additional second breast events have been documented after the cut off for events identified through March 2016, and the identical procedures used to review/confirm DCIS and subsequent breast events, construct TMAs, process H&E and images, and assemble risk factor data, and the associated digital mammograms. We have 13 additional ipsilateral breast events with complete data and their controls for independently testing the model performance. Statistical methods Propose novel supervised learning approach to integrate image data from mammograms and TMA slides that accommodates agreement between multi-omics. Results 128 (cases and controls, 21.9% ipsilateral subsequent events) identified for development and internal cross validation. Median age at diagnosis was 52 and median time to subsequent breast event was 63 mo. Controlling for the clinical/pathologic risk factors (age, BMI, BI-RADs density, treatment, tumor grade, parous, menopausal status, ER status, and race) and integrating the whole mammogram and TMA pathology images, we observe a 5-yr ipsilateral AUC = 0.74; 10-yr AUC 0.75. The independent validation is ongoing. Conclusions Integrating heterogeneous multiomic data sources can generate significant improvement in long term risk prediction after initial DCIS diagnosis. Citation Format: Shih-Ting Huang, Debbie Bennett, Robert West, Graham Colditz, Shu Jiang. Integrating pathomic and radiomic images to classify risk of subsequent events among women with DCIS [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-09-01.

Abstract PO5-05-05: Clinical outcomes of CDK4/6 inhibitors in patients with bone only metastatic breast cancer

Abstract Background: CDK4/6 inhibitors (CDK 4/6i) have significantly advanced the treatment of hormone receptor-positive (HR+) metastatic breast cancer in the last decade. Several clinical trials including PALOMA, MONALEESA, and MONARCH have shown improved progression-free survival (PFS) rates when CDK4/6i were combined with endocrine therapy (ET). These results led to recommending their use in combination with ET as the first line of therapy in the metastatic settings. Bone metastasis is the most common site of disease in patients with HR+ metastatic breast cancer, about 40% of whom have bone as the only site of metastasis (bone-only disease [BoD]). While previous studies have shown that BoD can have a unique clinical course and a more favorable prognosis compared to non-BoD metastasis, most of the aforementioned CDK 4/6i clinical trials have not shown significant improvements in PFS in BoD subset of patients. Here we aimed to investigate the survival outcomes of BoD patients at a single institution center and evaluate CDK 4/6i activity in preclinical models of bone metastasis in breast cancer. Patients and methods: Patients with HR+, HER2-negative metastatic breast cancer from a retrospective CDK4/6i study at Washington University School of Medicine were included in this analysis. We selected all the patients who received CDK4/6i in the first- or second-line settings from June 2014 to March 2020. Outcomes were collected through June 10, 2023. The Kaplan-Meier method with log rank test and multivariable cox model were used for survival analysis. Results: 114 female patients (n=75 first line, n=39 second line, n=20 African American, n=94 Caucasian) were included in this study. All patients received Palbociclib as the first exposure to CDK4/6 inhibitor in combination with ET for at least two months. Median age was 60 years (range, 28-87) and forty-seven patients (41%) were in the BoD group. Survival outcomes for BoD group were compared to the rest of patients who had either bone and visceral or visceral only metastatic lesions (BV group). Our results demonstrated a significantly reduced median PFS in BoD group compared to BV group (13.1 months [95%CI:8-18.2] vs 19.6 months [95%CI:6.8-32.4], p=0.01) respectively. There was no significant difference in overall survival between BoD and BV groups (36.6 months [95%CI:32.2-41] vs 41.7 months [95%CI 36.1-47.2] p=0.74) respectively. In multivariate analysis regarding the associated risk factors with PFS, after adjusting for age and race, BoD had a HR of 1.62 (95%CI:1.04-2.54) for PFS. Among the 75 patients who received CDK4/6i as their first line of therapy, BoD (n=32 patients [42.7%]) also showed an inferior (p=0.05) median PFS (20 months [95%CI 12.9-27]) compared to BV group (n=43 patients [57.3%], median PFS=28.4 months [95%CI: 16.3-40.4]). To investigate potential treatment resistance mechanisms in bone metastases, we used the triple negative 4T1 and the ER+ luminal B PyMT Bo1 breast tumor cell line derived mammary gland models in immunocompetent mice. Single agent CDK4/6i, ribociclib, decreased primary mammary gland tumor burden. This effect was abrogated when CD8+ T-cells were depleted. In the bone colonization model using these cell lines, ribociclib had little effect on bone tumor burden. Arg1+ immune suppressive macrophages were significantly decreased in the primary mammary tumor but not in the bone tumor after ribociclib administration, suggesting a relative treatment resistance and immune suppression in the bone tumor microenvironment compared to the primary mammary gland. Conclusion: CDK4/6i play a significant role in the treatment of patients with HR+ metastatic breast cancer. Our single institution, retrospective study and preclinical data suggests that CDK4/6i may not be as effective for the treatment of tumors residing in the bone microenvironment, warranting future studies to understand the mechanisms of CDK4/6 inhibitors action in bone versus visceral metastases. Citation Format: Mahta Mardani, Suleyman Noordeen, Katherine Clifton, Cynthia Ma, Jingqin Luo, Jing Xi, Nusayba Bagegni, Foluso Ademuyiwa, Rama Suresh, Ashley Frith, Andrew Davis, Ron Bose, Lindsay Peterson, Shana Thomas, Yu Tao, Takayuki Kobayashi, Jingyu Xiang, Yalin Xu, Xinming Su, Katherine Weilbaecher. Clinical outcomes of CDK4/6 inhibitors in patients with bone only metastatic breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-05-05.

The people behind the papers - Yongjun Yin and David Ornitz.

During alveologenesis, multiple mesenchymal cell types play crucial roles in maximising the lung surface area. In their study, David Ornitz and colleagues define the repertoire of lung fibroblasts, with a particular focus on alveolar myofibroblasts. To know more about their work, we spoke to the first author, Yongjun Yin, and the corresponding author, David Ornitz, Alumni Endowed Professor at the Department of Developmental Biology, Washington University School of Medicine, St. Louis.

Abstract 4431: Steroid hormone metabolites and mammographic breast density in premenopausal women

Abstract Background: Steroid hormones influence breast tissue development and play a role in breast carcinogenesis. Their associations with mammographic breast density (MBD), an established risk factor for breast cancer, are less clear. We, therefore, investigated the associations of steroid hormone metabolites with MBD in premenopausal women. Methods: Our study population consists of 705 premenopausal women recruited during their annual screening mammogram at the Washington University School of Medicine, St. Louis, MO. We assessed volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV) using Volpara. We assayed 54 steroid hormone metabolites from fasting blood samples at Metabolon. Linear regression models were used, after adjusting for covariates, to estimate the least square means of VPD, DV, and NDV across tertiles (T) of each metabolite. Sensitivity analysis was performed among the subset of participants with a history of oral contraceptive use (OCP). We used the Benjamini-Hochberg procedure to correct for multiple tests to control the false discovery rate (FDR) at a 5% level. Results: Five androgen metabolites (androstenediol (3beta,17beta) monosulfate 2, androstenediol (3beta,17beta) disulfate 1, 5alpha-androstan-3alpha,17beta-diol monosulfate 2, 5alpha-androstan-3alpha,17beta-diol disulfate, and 5alpha-androstan-3beta,17beta-diol disulfate) and two corticosteroid metabolites (tetrahydrocortisone glucuronide 5, and cortolone glucuronide 1) were inversely associated with VPD. Androstenediol (3beta,17beta) disulfate 1, and 5alpha-androstan-3alpha,17beta-diol disulfate displayed the strongest associations with VPD. The mean VPD decreased across tertiles of androstenediol (3beta,17beta) disulfate 1 from 9.0% in T1 to 8.5% in T2, and 7.5% in T3 (FDR p-value=0.02). Similarly, the mean VPD decreased from 8.8% in T1 to 8.4% in T2, and 7.6% in T3 of 5alpha-androstan-3alpha,17beta-diol disulfate (FDR p-value=0.03). Progestin steroid metabolites appeared to be positively associated with VPD but only 5alpha-pregnan-3beta,20alpha-diol monosulfate 2 was marginally significant after FDR correction (7.5% in T1, 8.3% in T2, and 8.8% in T3; FDR p-value=0.06). Four metabolites (three corticosteroids and one androgenic steroid) were positively associated with NDV. No metabolite was associated with DV. In sensitivity analysis limited to OCP users, mean VPDs were lower but the directions of associations were similar to those observed in the overall analysis. Conclusion: We report novel associations of corticosteroids and androgen metabolites with breast density in premenopausal women. Our findings shed important new insights into hormonal biomarkers and MBD. Citation Format: Kayode A. Matthew, Girish K. Vanapali, Kayla R. Getz, Myung S. Jeon, Chongliang Luo, Xingyi Guo, Jingqin Luo, Adetunji T. Toriola. Steroid hormone metabolites and mammographic breast density in premenopausal women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4431.

Abstract 6255: Personalized medicine for DCIS

Abstract Background: In 2023, 55,720 women will be diagnosed with non-invasive ductal carcinoma in situ (DCIS) in the United States. We evaluated RNA sequencing (RNA-Seq), clinical and social factors that drive subsequent breast events in a DCIS study population enriched for Black women (30%). Methods: RNA was extracted from macrosections of archival formalin-fixed paraffin-embedded (FFPE) DCIS tissue from Resource Archival Human Breast Tissue (RAHBT) from the St. Louis Breast Tissue Registry at Washington University School of Medicine and the Dana Farber Cancer Institute patient cohorts. Tissues were prepared by microsection of 5 uM whole section from unstained slides (Fisher). RNA was extracted using Qiagen RNeasy FFPE Kits from macrosectioned DCIS specimens. Purified total RNA was evaluated for quality and quantity using the Agilent Fragment Analyzer RNA assay. Bulk RNA sequencing was piloted in DCIS case-control samples using the SMART-seq and Hybrid Capture platforms at the DFCI Molecular Biology Core Facilities. Raw reads were aligned to the GRCh38/hg38 reference genome using STAR. Preliminary quality control analysis of a curated gene list showed higher quality data using the Hybrid Capture technology. Libraries for Hybrid Capture were pooled in 8plex reactions and hybridized to Twist Exome 2.0 probes for target enrichment. The final library pools were sequenced on an Illumina NovaSeq. Cases were defined as women diagnosed with DCIS in 1999 or later with subsequent invasive breast cancer, local DCIS recurrence, or lobular CIS recurrence. Controls were defined as women diagnosed with DCIS in 1999 or later without subsequent breast events during a similar follow-up time. The R package DESeq2 was used for data analysis. Results: The mean age at DCIS diagnosis was 56.3 (Std Dev 10.23). The mean follow-up time was 147.8 months. Hybrid Capture RNA-Seq files are stored and analyzed from the Harvard Medical School O2 Cluster using R programming (version 4.2.2, DEGreport). Quality control analyses demonstrated that the majority of the samples sequenced by Hybrid Capture had over 20 million total reads. Principal Component Analyses (PCA) and hierarchical clustering analyses of 19,821 protein-coding genes were conducted on the 143 DCIS samples sequenced using Hybrid Capture. PC1 was race (9%). A significant association was observed for follow-up time (PC3, 4.03%). First, we explored the association of the candidate gene ERBB2. The mean transcript abundance for ERBB2 was 11784.37 (case-control p-value=0.08). Preliminary analysis of selected genes of interest did not show statistically significant differences between cases and controls after FDR p-value adjustment. Differential gene expression analyses are ongoing. Conclusion: This study demonstrates the feasibility of generating high-quality RNA-seq data from diverse, archival DCIS samples. Citation Format: Aditi Hazra. Personalized medicine for DCIS [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6255.

Abstract 2140: Untargeted lipidomics reveals racial differences in lipid species among women

Abstract Introduction: Lipids are important for many cellular processes and have been implicated in cancer development. Adopting a lipidomic approach has revealed sex-specific differences in lipid species but whether there are racial differences in lipid profiles remain unexplored. As a result, we investigated differences in lipid species between Non-Hispanic Black (NHB) vs Non-Hispanic White (NHW) women. Methods: We performed lipidomic profiling on 705 premenopausal women who were recruited during their annual screening mammogram at Washington University School of Medicine, St. Louis, MO. A total of 982 lipid species were profiled at Metabolon (Durham, NC®). 125 lipid species missing in 300 or more women were excluded from the analysis. For the remaining missing values, we employed the nearest neighbor method for imputation. We investigated the race-differentiating lipid species concentrations using linear regression models, adjusting for age and body mass index (BMI). To satisfy the assumptions of normality and homoscedasticity, we log-transformed the lipid concentrations before performing regression analyses. The linear regression coefficients were then back-transformed as percentage differences. We accounted for multiple testings by applying the Bonferroni correction. Statistical significance was defined as a Bonferroni-adjusted p-value < 10−5. Pathway enrichment analyses was conducted for differential lipid species for each sub pathway. Results: Of the 705 women, 506 were NHW and 163 were NHB. In analysis adjusted for age and BMI, 278 lipid species were significantly lower in NHB, and one lipid specie (TAG58:10-FA20:4) was higher in NHB. These species belonged to triacylglycerols (TAG, n=213), phosphatidylcholines (PC, n=25), diacylglycerols (DAG, n=22), cholesteryl esters (CE, n=4), phosphatidylethanolamines (PE, n=4), lysophosphatidylcholines (LPC, n=3), lysophosphatidylethanolamines (LPE, n=3), sphingomyelins (SM, n=2), ceramides (CER, n=1), lactosylceramides (LCER, n=1) and phosphatidylinositols (PI, n=1) sub-pathways. The TAG sub-pathway was enriched with differential lipid species (213 significant out of 518 species, p = 1.26 × 10−11). Forty-three lipid species (42 TAGs and one DAG) exhibited an absolute percentage difference > 50% between NHB and NHW women. The top 3 TAG species with the largest absolute percentage differences were TAG44:0-FA14:0 (60.6% lower in NHB women, p = 6.25 × 10−8), TAG46:2-FA16:1 (59.8% lower in NHB women, p = 1.11 × 10−14) and TAG47:2-FA16:1 (59.4% lower in NHB women, p = 8.66 × 10−20). Conversely, TAG58:10-FA20:4 was 47.1% (p = 5.79 × 10−8) higher in NHB women. Conclusions: Our study reveals novel substantial racial differences in lipid species among women, mostly in the TAG sub-pathway, highlighting the influence of race on the lipidome. Validation in a different study population is needed. Citation Format: ang Li, Ghazaleh Pourali, Kayla R. Getz, Myung Sik Jeon, Jingqin Luo, Chongliang Luo, Adetunji T. Toriola. Untargeted lipidomics reveals racial differences in lipid species among women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2140.

Associations of Vitamins and Related Cofactor Metabolites with Mammographic Breast Density in Premenopausal Women

BackgroundIdentifying biological drivers of mammographic breast density (MBD), a strong risk factor for breast cancer, could provide insight into breast cancer etiology and prevention. Studies on dietary factors and MBD have yielded conflicting results. There are, however, very limited data on the associations of dietary biomarkers and MBD. ObjectiveWe aimed to investigate the associations of vitamins and related cofactor metabolites with MBD in premenopausal women. MethodsWe measured 37 vitamins and related cofactor metabolites in fasting plasma samples of 705 premenopausal women recruited during their annual screening mammogram at the Washington University School of Medicine, St. Louis, MO. Volpara was used to assess volumetric percent density (VPD), dense volume (DV), and nondense volume (NDV). We estimated the least square means of VPD, DV, and NDV across quartiles of each metabolite, as well as the regression coefficient of a metabolite in continuous scale from multiple covariate-adjusted linear regression. We corrected for multiple testing using the Benjamini–Hochberg procedure to control the false discover rate (FDR) at a 5% level. ResultsParticipants’ mean VPD was 10.5%. Two vitamin A metabolites (β-cryptoxanthin and carotene diol 2) were positively associated, and one vitamin E metabolite (γ-tocopherol) was inversely associated with VPD. The mean VPD increased across quartiles of β-cryptoxanthin (Q1 = 7.2%, Q2 = 7.7%, Q3 = 8.4%%, Q4 = 9.2%; P-trend = 1.77E-05, FDR P value = 1.18E-03). There was a decrease in the mean VPD across quartiles of γ-tocopherol (Q1 = 9.4%, Q2 = 8.1%, Q3 = 8.0%, Q4 = 7.8%; P -trend = 4.01E-03, FDR P value = 0.04). Seven metabolites were associated with NDV: 3 vitamin E (γ-CEHC glucuronide, δ-CEHC, and γ-tocopherol) and 1 vitamin C (gulonate) were positively associated, whereas 2 vitamin A (carotene diol 2 and β-cryptoxanthin) and 1 vitamin C (threonate) were inversely associated with NDV. No metabolite was significantly associated with DV. ConclusionWe report novel associations of vitamins and related cofactor metabolites with MBD in premenopausal women.

In Case You Haven't Heard…

Children diagnosed with major depressive disorder between the ages of 3 and 6 — known as preschool‐onset MDD — are more likely than their peers to express suicidal thoughts and behaviors before the age of 13, a report in the Journal of the American Academy of Child and Adolescent Psychiatry suggests, according to an American Psychiatric Association news release. “While general [suicidal thoughts and behaviors] screening is not indicated for children under age 8, suicide assessment should be conducted if warning signs such as mood disturbances are present,” wrote Laura Hennefield, Ph.D., of the Washington University School of Medicine and colleagues. “Children with [preschool‐onset] MDD would likely benefit from increased suicide screening, proactive safety planning, and early interventions.” The study included 137 children aged 8 to 12 who met the criteria for preschool‐onset MDD, and 53 children aged 8 to 12 with no history of depression. The researchers found that 67.9% of 8 to 12‐year‐old children who had preschool‐onset MDD expressed suicidal thoughts and behaviors by preadolescence, including 26.3% over the prior month. In contrast, 22.6% of children without a history of depression endorsed suicidal thoughts and behaviors by preadolescence, including 3.8% over the prior month. The children with preschool‐onset MDD were also significantly more likely to have made a suicide attempt by age 12 compared with peers without depression history.

Are Digital Markers of Everyday Driving Comparable to Fluid Biomarkers in Identifying Preclinical Alzheimer Disease?

AbstractBackgroundPreclinical Alzheimer’s disease (AD) may have a subtle functional signature reflected in changes in everyday driving behaviour. Driving has the potential to serve as a digital marker for AD when captured continuously and characterized accurately. This study directly compares the diagnostic performance of digital markers of everyday driving, cerebrospinal fluid (CSF), and blood biomarkers in detecting amyloid deposition in AD, using amyloid positron emission tomography (PET) as the “gold standard”.MethodParticipants were enrolled in a longitudinal study on driving and preclinical AD biomarkers at Washington University School of Medicine. The Driving Real‐World In‐Vehicle Evaluation System (DRIVES) Project uses in‐vehicle GPS dataloggers to collect daily driving among cognitive normal drivers. This study included 121 drivers (aged 65+) with complete blood, CSF, and PET biomarker data. We employed three artificial neural network (ANN) to examine the relationship between everyday driving and PET‐amyloid status. The first model solely included driving features. The second ANN model (i.e., “non‐intrusive” model) added age and education level as additional features. The third model included all of the previous features plus APOE e4 status. Plasma Aß42/Aß40<0.1013 and CSF Aß42/Aß40<0.0673 were used to detect PET‐amyloid positivity. To compare the performance of the ANN models and the CSF and plasma biomarkers, area under the receiver operating curve (AUC) from 5‐fold cross‐validation were calculated.ResultIndividuals who were PET‐amyloid positive (n = 46) were more likely to be older (p<.05) and carry an APOE e4 allele (p<.0001). The two groups did not differ in sex or education. In predicting PET‐amyloid positivity, the five most important driving features were the number of left turns per mile, 80th percentile of jerk, minimum vehicle speed, speed variability, and the number of speeding incidents. The CSF biomarker achieved the highest performance (AUC = 0.96±0.04), followed by the model with driving, age, education and APOE e4 status (AUC = 0.88±0.05). The model with only driving features achieved lower performance (AUC = 0.74±0.07), while the non‐intrusive ANN model achieved comparable performance to the plasma biomarker (AUC: 0.82±0.11vs.0.83±0.12).ConclusionDigital markers of everyday driving along with age and education level offer a non‐intrusive and scalable diagnostic tool for preclinical AD that provides ongoing assessments.

Navigational Decision‐Making Among Older Drivers: An Analysis of Real‐World Driving Patterns

AbstractBackgroundDriving is an important aspect of independence for older adults. However, cognitive decline may impair driving abilities and safety. A deeper understanding of the impact of cognitive impairment on driving behaviours in older adults can inform public health strategies to support maintaining their ability to drive safely. This study investigates how older adults with and without cognitive impairment make navigational decisions (e.g., route choice) while driving in real‐world settings.MethodParticipants were enrolled in longitudinal driving studies at Washington University School of Medicine. GPS dataloggers tracked the daily driving patterns of 246 older drivers (aged 65+), including 230 cognitively normal older adults (CTL; Clinical Dementia Rating [CDR] = 0) and 16 older adults with cognitive impairment (DEM; CDR>0). Spatial clustering and hashing algorithms were employed to analyze each participant’s destinations and route choices. Trips with hard‐braking, sudden‐acceleration, and over‐speeding were considered “adverse behavior.” The Mann‐Whitney U‐test was performed to identify significant differences between the two groups.ResultThe CTL group had an average age of 68.2 ± 5.7 years and was composed of 46% females, while the DEM group had an average age of 69.2 ± 6.8 years and had 36% females. Additionally, the CTL group had a mean of 16.5 ± 2.3 years of education, while the DEM group had a mean of 16.0 ± 2.3 years of education. The results indicated that drivers with cognitive impairment had fewer full‐cycle trips (i.e., trips with the same start point and destination; p = 0.0165), visited fewer new destinations (p = 0.0210), used fewer distinct routes to reach their most common destination (p = 0.0174), and took fewer distinct routes to reach their most common destination when normalized by the average monthly frequency of this trip (p = 0.0062). No significant differences were observed in the other driving measures.ConclusionThis study reveals significant differences in driving patterns between cognitively normal older adults and those with cognitive impairment. Older adults with cognitive impairment exhibited more conservative driving behaviors, such as taking fewer full‐cycle trips and having less variety in their daily driving routes. These findings have important implications for designing interventions to improve mobility for older adults.

Longitudinal changes in driving behaviours among older adults with different A/T/N biomarker profiles

AbstractBackgroundThe pathophysiological process of Alzheimer’s disease (AD) spans approximately 10‐15 years. To define AD by its pathologic processes, the A/T/N classification framework was proposed constituting ß‐amyloid (A), tau (T), and neurodegeneration (N) biomarkers derived from cerebrospinal fluid (CSF) or imaging. With these biomarkers, individuals can be divided into four categories: normal (A‐T‐N‐), AD pathologic change (A+T‐N‐), AD (A+T+N‐, A+T‐N+, A+T+N+), and suspected non‐AD pathology (SNAP) (A‐T+N‐, A‐T‐N+, A‐T+N+). Recent evidence indicates that daily driving behaviours can identify preclinical AD, solely based on CSF ß‐amyloid (A), with high accuracy. This study aims to determine the extent to which longitudinal changes in driving behaviour vary between individuals with different A/T/N profile categories.MethodParticipants were enrolled in a longitudinal study on driving and preclinical AD biomarkers from Washington University School of Medicine. Temporospatial driving behaviours were collected with a data logger installed in participant vehicles over a period between January 2015 and March 2020. CSF collected within three years of each driving event was used to assign A/T/N categories. The cohort included 132 cognitively normal (Clinical Dementia Rating of 0) older adults (>65). Changes in driving behaviours over time were modelled for each group using linear mixed‐effects models. A Z‐test was used to determine if the slopes significantly differed between individuals with normal biomarkers and the remaining groups.ResultParticipants were classified as 59 individuals with normal biomarkers, 9 with AD pathologic change biomarkers, 45 with AD biomarkers, and 19 with SNAP biomarkers. Compared to normal aging, the AD pathology group had a statistically significantly higher increase in average occurrences of under‐speeding (p = 0.001), a significant decrease in average trip duration (p = 0.021), and a significant decrease in the average standard deviation of vehicle speed (p = 0.029). The AD group had no significant differences from the normally aging group. The SNAP group showed a significantly higher increase in the average occurrences of over‐speeding (p<0.001) than normal aging.ConclusionDriving behaviours and their rate of change over time vary between individuals with different A/T/N profile categories. These differences provide an opportunity to strengthen our understanding of the disease trajectory.

Longitudinal changes in driving behaviours among older adults with different A/T/N biomarker profiles

AbstractBackgroundThe pathophysiological process of Alzheimer’s disease (AD) spans approximately 10‐15 years. To define AD by its pathologic processes, the A/T/N classification framework was proposed constituting β‐amyloid (A), tau (T), and neurodegeneration (N) biomarkers derived from cerebrospinal fluid (CSF) or imaging. With these biomarkers, individuals can be divided into four categories: normal (A‐T‐N‐), AD pathologic change (A+T‐N‐), AD (A+T+N‐, A+T‐N+, A+T+N+), and suspected non‐AD pathology (SNAP) (A‐T+N‐, A‐T‐N+, A‐T+N+). Recent evidence indicates that daily driving behaviours can identify preclinical AD, solely based on CSF β‐amyloid (A), with high accuracy. This study aims to determine the extent to which longitudinal changes in driving behaviour vary between individuals with different A/T/N profile categories.MethodParticipants were enrolled in a longitudinal study on driving and preclinical AD biomarkers from Washington University School of Medicine. Temporospatial driving behaviours were collected with a data logger installed in participant vehicles over a period between January 2015 and March 2020. CSF collected within three years of each driving event was used to assign A/T/N categories. The cohort included 132 cognitively normal (Clinical Dementia Rating of 0) older adults (>65). Changes in driving behaviours over time were modelled for each group using linear mixed‐effects models. A Z‐test was used to determine if the slopes significantly differed between individuals with normal biomarkers and the remaining groups.ResultParticipants were classified as 59 individuals with normal biomarkers, 9 with AD pathologic change biomarkers, 45 with AD biomarkers, and 19 with SNAP biomarkers. Compared to normal aging, the AD pathology group had a statistically significantly higher increase in average occurrences of under‐speeding (p = 0.001), a significant decrease in average trip duration (p = 0.021), and a significant decrease in the average standard deviation of vehicle speed (p = 0.029). The AD group had no significant differences from the normally aging group. The SNAP group showed a significantly higher increase in the average occurrences of over‐speeding (p<0.001) than normal aging.ConclusionDriving behaviours and their rate of change over time vary between individuals with different A/T/N profile categories. These differences provide an opportunity to strengthen our understanding of the disease trajectory.

Data-efficient resting-state functional magnetic resonance imaging brain mapping with deep learning.

Resting-state functional MRI (RS-fMRI) enables the mapping of function within the brain and is emerging as an efficient tool for the presurgical evaluation of eloquent cortex. Models capable of reliable and precise mapping of resting-state networks (RSNs) with a reduced scanning time would lead to improved patient comfort while reducing the cost per scan. The aims of the present study were to develop a deep 3D convolutional neural network (3DCNN) capable of voxel-wise mapping of language (LAN) and motor (MOT) RSNs with minimal quantities of RS-fMRI data. Imaging data were gathered from multiple ongoing studies at Washington University School of Medicine and other thoroughly characterized, publicly available data sets. All study participants (n = 2252 healthy adults) were cognitively screened and completed structural neuroimaging and RS-fMRI. Random permutations of RS-fMRI regions of interest were used to train a 3DCNN. After training, model inferences were compared using varying amounts of RS-fMRI data from the control data set as well as 5 patients with glioblastoma multiforme. The trained model achieved 96% out-of-sample validation accuracy on data encompassing a large age range collected on multiple scanner types and varying sequence parameters. Testing on out-of-sample control data showed 97.9% similarity between results generated using either 50 or 200 RS-fMRI time points, corresponding to approximately 2.5 and 10 minutes, respectively (96.9% LAN, 96.3% MOT true-positive rate). In evaluating data from patients with brain tumors, the 3DCNN was able to accurately map LAN and MOT networks despite structural and functional alterations. Functional maps produced by the 3DCNN can inform surgical planning in patients with brain tumors in a time-efficient manner. The authors present a highly efficient method for presurgical functional mapping and thus improved functional preservation in patients with brain tumors.

Glutamate excitotoxicity in the cochlea

Glutamate excitotoxicity in the cochlea Mark Rutherford, Associate Professor at Washington University School of Medicine, discusses the burden and causes of hearing dysfunction, as well as the possible solutions for mitigating glutamate excitotoxicity. The cochlea, the snail-shaped organ of the inner ear located deep in the skull, contains approximately 15,000 sound receptors called sensory ‘hair cells’ and approximately 50,000 nerve fibers sending sound information to the brain. Although that may seem like a lot, it is not compared to the approximately 100 billion neurons in the brain. These hair cells and nerve fibers are all we get for life, and they are gradually lost over time due to aging. Unfortunately, environmental factors accelerate cochlear decline over time. One of those environmental factors is loud sounds.Today, we live in an environment of sound at levels that far exceed those under which our species evolved, especially those of us with noisy occupations or recreational activities. For example, military personnel are particularly vulnerable to hearing loss, making hearing disorders (including tinnitus) the number one disability claim of the U.S. Veterans Administration.

Cell-specific Systemic Immune Signatures Associated with Treatment Burden in Neovascular Age-related Macular Degeneration

Choroidal neovascularization (CNV) accounts for the majority of severe vision loss in neovascular age-related macular degeneration (AMD). Despite therapies that target VEGF, patients are often under-responsive, require frequent eye injections to control disease, and eventually lose some vision despite chronic therapy implicating a multifactorial etiology in treatment response. Genetic studies implicate systemic immunity in AMD and systemic immune cells accumulate within CNV lesions, yet a role for these cells in anti-VEGF response remains undetermined. The purpose of this study was to identify transcriptional signatures of circulating immune cells that are associated with high anti-VEGF treatment burden. Experimental pilot study. Patients with neovascular AMD seen at Washington University School of Medicine in St. Louis and BJC Health System. We profiled by single cell RNA sequencing the peripheral blood mononuclear cells of 27 treatment-experienced patients with wet AMD. We stratified this cohort into 2 groups with low and high treatment burden (≤5 or ≥ 6 injections in the past 12 months, respectively). Identification of immune cells associated with high treatment burden. Gene expression signature of CD16+ monocytes may be associated with high treatment burden. These studies delineate potential signatures of circulating immune cells that may be associated with high treatment burden in neovascular AMD, potentially informing the development of diagnostic predictors of anti-VEGF response and new precision medicine-based approaches to complement anti-VEGF therapies. Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Lipidome of mammographic breast density in premenopausal women

BackgroundHigh mammographic breast density (MBD) is a strong risk factor for breast cancer development, but the biological mechanisms underlying MBD are unclear. Lipids play important roles in cell differentiation, and perturbations in lipid metabolism are implicated in cancer development. Nevertheless, no study has applied untargeted lipidomics to profile the lipidome of MBD. Through this study, our goal is to characterize the lipidome of MBD in premenopausal women.MethodsPremenopausal women were recruited during their annual screening mammogram at the Washington University School of Medicine in St. Louis, MO. Untargeted lipidomic profiling for 982 lipid species was performed at Metabolon (Durham, NC®), and volumetric measures of MBD (volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV)) was assessed using Volpara 1.5 (Volpara Health®). We performed multivariable linear regression models to investigate the associations of lipid species with MBD and calculated the covariate-adjusted least square mean of MBD by quartiles of lipid species. MBD measures were log10 transformed, and lipid species were standardized. Linear coefficients of MBD were back-transformed and considered significant if the Bonferroni corrected p-value was < 0.05.ResultsOf the 705 premenopausal women, 72% were non-Hispanic white, and 23% were non-Hispanic black. Mean age, and BMI were 46 years and 30 kg/m2, respectively. Fifty-six lipid species were significantly associated with VPD (52 inversely and 4 positively). The lipid species with positive associations were phosphatidylcholine (PC)(18:1/18:1), lysophosphatidylcholine (LPC)(18:1), lactosylceramide (LCER)(14:0), and phosphatidylinositol (PI)(18:1/18:1). VPD increased across quartiles of PI(18:1/18:1): (Q1 = 7.5%, Q2 = 7.7%, Q3 = 8.4%, Q4 = 9.4%, Bonferroni p-trend = 0.02). The lipid species that were inversely associated with VPD were mostly from the triacylglycerol (N = 43) and diacylglycerol (N = 7) sub-pathways. Lipid species explained some of the variation in VPD. The inclusion of lipid species increased the adjusted R2 from 0.45, for a model that includes known determinants of VPD, to 0.59.ConclusionsWe report novel lipid species that are associated with MBD in premenopausal women. Studies are needed to validate our results and the translational potential.

Association of Systemic Lupus Erythematosus Disease Activity With Choroidal Thickness.

To determine the association between disease activity and choroidal thickness in patients with systemic lupus erythematosus (SLE). We conducted a cohort study of 24 SLE patients and 13 healthy controls recruited at Washington University School of Medicine between June 2019 and November 2021. SLE disease activity was assessed using the SLE Disease Activity Index-2000 Responder Index-50 (S2K RI-50). Patients were divided into four groups: high disease activity/no lupus nephritis (HDA/no LN; S2K RI-50 > 4), HDA/active LN (HDA/active LN; S2K RI-50 > 4), low disease activity/inactive LN (LDA/inactive LN; S2K RI-50 ≤ 4), and LDA/no LN (LDA/no LN; S2K RI-50 ≤ 4). LDA/no LN patients were age-, sex-, and race-matched to healthy controls and patients in other SLE groups. Choroidal thickness of the right eye was measured blinded to disease activity on a horizontal section through the fovea on optical coherence tomography images taken within a week of disease assessment. Patients with HDA had choroidal thickening compared with matched patients with LDA. After controlling for multiplicity, choroidal thinning remained statistically significant at 1000 μm nasal to the fovea (308 ± 68 vs 228 ± 64 μm, p = 0.001). Choroidal thickness was not different between LDA/no LN and LDA/inactive LN or healthy controls. HDA in patient with SLE is associated with increased choroidal thickness whereas comorbid inactive LN did not affect choroidal thickness. Additional studies in a larger longitudinal cohort are needed to study whether choroidal thickness may be used as a noninvasive, adjunctive measure for disease activity in SLE.

Efficacy of Gabapentin For Post–COVID-19 Olfactory Dysfunction

The COVID-19 pandemic affected millions of people and has become a dominant etiology of olfactory dysfunction (OD). No interventions with definitive clinical utility exist. Gabapentin represents a potential therapy for COVID-19-induced OD. To evaluate the efficacy of oral gabapentin on olfactory function and olfaction-related quality of life in patients with COVID-19-induced OD. This pilot double-blinded, placebo-controlled randomized clinical trial (RCT) was conducted at Washington University School of Medicine in St Louis from January 7, 2022, to February 3, 2023. Adults with at least 3 months of OD after COVID-19 infection were eligible for inclusion. Participants with a history of other causes of OD or contraindications to gabapentin were excluded. Patients were randomized 1:1 to oral gabapentin or placebo. All patients underwent titration to a maximum tolerable dose, which was maintained during an 8-week fixed-dose (FD) phase then tapered off. Participants were monitored for 4 weeks following cessation of study medication. Outcomes were assessed following the 8-week FD phase and 4 weeks after taper completion. The primary outcome measure was the response rate determined by subjective improvement in OD on the Clinical Global Impression of Improvement (CGI-I) after the FD phase. Other subjective and objective measures of olfactory function were also assessed as secondary outcome measures. Sixty-eight participants were enrolled (34 randomized to each arm), a total of 44 participants completed the FD period and 20 (45.4%) reported response to treatment with at least slight improvement in olfaction from baseline. Of those randomized, 51 (75%) were women and 56 were White (82%) with a mean (SD) age of 43 (13.5) years. Baseline demographic features including age, sex, and race and ethnicity were not significantly different between the groups. Of the 18 participants in the gabapentin group, 8 (44%) were responders and of the 26 participants in the placebo group, 12 (46%) reported response to treatment (percent difference, 1.7%; 95% CI, -31.6% to 28.2%). Mixed-model analysis of all secondary outcome measures demonstrated no clinically meaningful or statistically significant difference between the gabapentin and placebo groups throughout the trial. There were no serious adverse events. In this randomized clinical trial, gabapentin was not associated with statistically significant or clinically meaningful benefit over placebo and likely is not an efficacious therapy for COVID-19-induced OD. ClinicalTrials.gov Identifier: NCT05184192.

Mutations associated with progression in follicular lymphoma predict inferior outcomes at diagnosis: Alliance A151303

AbstractFollicular lymphoma (FL) is clinically heterogeneous, with select patients tolerating extended watch-and-wait, whereas others require prompt treatment, suffer progression of disease within 24 months of treatment (POD24), and/or experience aggressive histologic transformation (t-FL). Because our understanding of the relationship between genetic alterations in FL and patient outcomes remains limited, we conducted a clinicogenomic analysis of 370 patients with FL or t-FL (from Cancer and Leukemia Group B/Alliance trials 50402/50701/50803, or real-world cohorts from Washington University School of Medicine, Cleveland Clinic, or University of Miami). FL subsets by grade, stage, watch-and-wait, or POD24 status did not differ by mutation burden, whereas mutation burden was significantly higher in relapsed/refractory (rel/ref) FL and t-FL than in newly diagnosed (dx) FL. Nonetheless, mutation burden in dx FL was not associated with frontline progression-free survival (PFS). CREBBP was the only gene more commonly mutated in FL than in t-FL yet mutated CREBBP was associated with shorter frontline PFS in FL. Mutations in 20 genes were more common in rel/ref FL or t-FL than in dx FL, including 6 significantly mutated genes (SMGs): STAT6, TP53, IGLL5, B2M, SOCS1, and MYD88. We defined a mutations associated with progression (MAP) signature as ≥2 mutations in these 7 genes (6 rel/ref FL or t-FL SMGs plus CREBBP). Patients with dx FL possessing a MAP signature had shorter frontline PFS, revealing a 7-gene set offering insight into FL progression risk potentially more generalizable than the m7–Follicular Lymphoma International Prognostic Index (m7-FLIPI), which had modest prognostic value in our cohort. Future studies are warranted to validate the poor prognosis associated with a MAP signature in dx FL, potentially facilitating novel trials specifically in this high-risk subset of patients.

Neuropsychiatric Symptoms and Alzheimer Disease Biomarkers Independently Predict Progression to Incident Cognitive Impairment

To investigate the effect of neuropsychiatric symptoms and depression symptoms, respectively, and Alzheimer disease (AD) biomarkers (cerebrospinal fluid [CSF] or Positron Emission Tomography [PET] imaging) on the progression to incident cognitive impairment among cognitively normal older adults. Prospective, observation, longitudinal study. Knight Alzheimer Disease Research Center (ADRC) at Washington University School of Medicine. Older adults aged 65 and above who participated in AD longitudinal studies (n=286). CSF and PET biomarkers, Clinical Dementia Rating (CDR), Geriatric Depression Scale (GDS), and Neuropsychiatric Inventory Questionnaire (NPI-Q). Participants had an average follow-up of eight years, and 31 progressed from CDR 0 to CDR >0. After adjusting for sex, age, and education in the Cox proportional hazards survival models, neuropsychiatric symptoms as a time-dependent covariate was statistically significant in the three CSF (Aβ42/Aβ40, t-Tau/Aβ42, p-Tau/Aβ42) PET imaging models (HR=1.33-1.50). The biomarkers were also significant as main effects (HR=2.00-4.04). Change in depression symptoms was not significant in any models. The interactions between biomarkers and neuropsychiatric symptoms and depression were not statistically significant. Changes in neuropsychiatric symptoms increase the risk of progression to cognitive impairment among healthy, cognitively normal adults, independent of AD biomarkers. Routine assessment of neuropsychiatric symptoms could provide valuable clinical information about cognitive functioning and preclinical disease state.