Citations

Abstract Study Objectives Rapid eye movement sleep behavior disorder (RBD) is strongly associated with phenoconversion to an overt synucleinopathy, e.g. Parkinson’s disease (PD), Lewy body dementia, and related disorders. Comorbid traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD)—henceforth “neurotrauma” (NT)—increase the odds of RBD by ~2.5-fold and are associated with an increased rate of service-connected PD in Veterans. Thus, RBD and NT are both independently associated with PD; however, it is unclear how NT influences neurological function in patients with RBD. Methods Participants ≥18 years with overnight polysomnogram-confirmed RBD were enrolled between 8/2018 to 4/2021 through the North American Prodromal Synucleinopathy Consortium. Standardized assessments for RBD, TBI, and PTSD history, as well as cognitive, motor, sensory, and autonomic function, were completed. This cross-sectional analysis compared cases (n = 24; RBD + NT) to controls (n = 96; RBD), matched for age (~60 years), sex (15% female), and years of education (~15 years). Results RBD + NT reported earlier RBD symptom onset (37.5 ± 11.9 vs. 52.2 ± 15.1 years of age) and a more severe RBD phenotype. Similarly, RBD + NT reported more severe anxiety and depression, greater frequency of hypertension, and significantly worse cognitive, motor, and autonomic function compared to RBD. No differences in olfaction or color vision were observed. Conclusions This cross-sectional, matched case:control study shows individuals with RBD + NT have significantly worse neurological measures related to common features of an overt synucleinopathy. Confirmatory longitudinal studies are ongoing; however, these results suggest RBD + NT may be associated with more advanced neurological symptoms related to an evolving neurodegenerative process.

The initial excitement generated more than two decades ago by the discovery of drugs targeting fatty acid synthase (FASN)‐catalyzed de novo lipogenesis for cancer therapy was short‐lived. However, the advent of the first clinical‐grade FASN inhibitor (TVB‐2640; denifanstat), which is currently being studied in various phase II trials, and the exciting advances in understanding the FASN signalome are fueling a renewed interest in FASN‐targeted strategies for the treatment and prevention of cancer. Here, we provide a detailed overview of how FASN can drive phenotypic plasticity and cell fate decisions, mitochondrial regulation of cell death, immune escape and organ‐specific metastatic potential. We then present a variety of FASN‐targeted therapeutic approaches that address the major challenges facing FASN therapy. These include limitations of current FASN inhibitors and the lack of precision tools to maximize the therapeutic potential of FASN inhibitors in the clinic. Rethinking the role of FASN as a signal transducer in cancer pathogenesis may provide molecularly driven strategies to optimize FASN as a long‐awaited target for cancer therapeutics.

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.

Abstract The CaPTC prostate cancer (CaP) Familial Cohort study (CaPFCS) was launched in 2017 to explore the CaP risk factors of African Black men (ABM). The study design is a prospective study that observes and follows healthy ABM and ABM diagnosed with CaP. Aim: The specific aim is to provide recommendations on statistical considerations for cohort studies focused on cancer disparities, based on lessons learned from the CaPTC CaPFCS. Methodology: Study participants were ABM in Cameroon, Nigeria, and the US. Using validated measures, data were collected mostly by self-administered or research assistant administered survey using paper survey (especially in Cameroon and Nigeria) with the responses transferred to REDCap by research coordinators. The statistical analysis for the CaPTC CaPFCS focused on the baseline epidemiological, behavioral, clinical and anthropometric measures of Black men. A total of 819 participants were included in the analyses. Statistical analyses included descriptive statistics (sample median, range, frequency and percentages) and unadjusted logistic regression models. Results: Data collection for the CaPTC CaPFCS were by multiple investigators/research coordinators at multiple sites in Cameroon, Nigeria, and the US. In preparation for the data analyses, we noted data entry errors and/or misinterpretation of data entry, which required extensive cleaning of the database prior to the analyses. The biostatisticians spent significant effort cleaning and ensuring data validity prior to the analyses. Confounding variables is another statistical consideration for cohort studies, such as the CaPTC CaPFCS. There was variability observed across age, education levels, employment status, household income and CaP diagnosis based on country of residence. CaP diagnosis was not reported by any of the ABM in the US, which may be due to the fact that they were all recruited within the community and no recruitment took place in the clinic. Finally, the CaPTC CaPFCS has several variables. Performing a lot of statistical tests may result in false-positive findings at P<0.05.Conclusion: The advantage of the CaPFCS is that it allows the CaPTC investigators to study epidemiological, behavioral, clinical and anthropometric variables associated with CaP over time. Being a longitudinal cohort study, investigators can track the changes in exposure and outcomes over time.However, statistical considerations need to be at the fore-front of multi-center, transatlantic cancer disparity studies such as the CaPTC CaPFCS, from data collection to data entry. The use of web-based survey with the ability to enter data directly into REDCaP will significantly reduce (if not totally eliminate) the need for database cleaning. There are multiple strategies that can be used to reduce confounder effect, including statistical adjustment and multivariate analysis to adjust for the confounders. The use of propensity score methods have especially been found to be effective in controlling baseline confounding factors. Citation Format: Daniel Lee, CaPTC Investigators, Jennifer Crook, Ruth Enuka, Fathi Parisa, Emeka Iweala Iweala, Oluwole Kukoyi, Ernest Kaninjing, Oluwaseyi Toye, Paul Jibrin, Folakemi Odedina. Importance of statistical considerations in multi-center, transatlantic cancer disparity studies: Lessons learned from the CaPTC prostate cancer familial cohort study [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C013.