Citations

Plasma neurofilament light is a reliable, uniform marker to estimate neuroaxonal injury and forecast all-cause mortality across major stroke types.

Abstract Introduction The cytoprotective PTEN‐induced kinase 1 (PINK1)‐parkin RBR E3 ubiquitin protein ligase (PRKN) pathway selectively labels damaged mitochondria with phosphorylated ubiquitin (pS65‐Ub) for their autophagic removal (mitophagy). Because dysfunctions of mitochondria and degradation pathways are early features of Alzheimer's disease (AD), mitophagy impairments may contribute to the pathogenesis. Methods Morphology, levels, and distribution of the mitophagy tag pS65‐Ub were evaluated by biochemical analyses combined with tissue and single cell imaging in AD autopsy brain and in transgenic mouse models. Results Analyses revealed significant increases of pS65‐Ub levels in AD brain, which strongly correlated with granulovacuolar degeneration (GVD) and early phospho‐tau deposits, but were independent of amyloid beta pathology. Single cell analyses revealed predominant co‐localization of pS65‐Ub with mitochondria, GVD bodies, and/or lysosomes depending on the brain region analyzed. Discussion Our study highlights mitophagy alterations in AD that are associated with early tau pathology, and suggests that distinct mitochondrial, autophagic, and/or lysosomal failure may contribute to the selective vulnerability in disease.

AbstractTau deposition is a key biological feature of Alzheimer’s disease that is closely related to cognitive impairment. However, it remains poorly understood why certain individuals may be more susceptible to tau deposition while others are more resistant. The recent availability of in vivo assessment of tau burden through positron emission tomography provides an opportunity to test the hypothesis that common genetic variants may influence tau deposition. We performed a genome-wide association study of tau-positron emission tomography on a sample of 754 individuals over age 50 (mean age 72.4 years, 54.6% men, 87.6% cognitively unimpaired) from the population-based Mayo Clinic Study of Aging. Linear regression was performed to test nucleotide polymorphism associations with AV-1451 (18F-flortaucipir) tau-positron emission tomography burden in an Alzheimer’s-signature composite region of interest, using an additive genetic model and covarying for age, sex and genetic principal components. Genome-wide significant associations with higher tau were identified for rs76752255 (P = 9.91 × 10−9, β = 0.20) in the tau phosphorylation regulatory gene PPP2R2B (protein phosphatase 2 regulatory subunit B) and for rs117402302 (P = 4.00 × 10−8, β = 0.19) near IGF2BP3 (insulin-like growth factor 2 mRNA-binding protein 3). The PPP2R2B association remained genome-wide significant after additionally covarying for global amyloid burden and cerebrovascular disease risk, while the IGF2BP3 association was partially attenuated after accounting for amyloid load. In addition to these discoveries, three single nucleotide polymorphisms within MAPT (microtubule-associated protein tau) displayed nominal associations with tau-positron emission tomography burden, and the association of the APOE (apolipoprotein E) ɛ4 allele with tau-positron emission tomography was marginally nonsignificant (P = 0.06, β = 0.07). No associations with tau-positron emission tomography burden were identified for other single nucleotide polymorphisms associated with Alzheimer’s disease clinical diagnosis in prior large case–control studies. Our findings nominate PPP2R2B and IGF2BP3 as novel potential influences on tau pathology which warrant further functional characterization. Our data are also supportive of previous literature on the associations of MAPT genetic variation with tau, and more broadly supports the inference that tau accumulation may have a genetic architecture distinct from known Alzheimer’s susceptibility genes, which may have implications for improved risk stratification and therapeutic targeting.

Abstract Our group has demonstrated that combinations of epigenetic modifiers produce potent synergy in pre-clinical models of PTCL, and has confirmed this data in early phase clinical studies. We showed that the combination of romidepsin and hypomethylating agents, decitabine or azacytidine, uniquely induces the expression of genes, including cancer testis antigens, gamma interferon and endogenous retrovirus. We are conducting a phase 1 study of pembrolizumab combined with pralatrexate alone (Arm A), with pralatrexate + decitabine (Arm B), or decitabine alone (Arm C) in patients with peripheral T-cell lymphoma (PTCL) and cutaneous T-cell lymphoma. In addition, we are conducting a Phase 1/2A study of durvalumab combined with oral 5-azacitidine + romidepsin (Arm A), pralatrexate + romidepsin (Arm B), romidepsin (Arm C), or oral 5-azacitidine (Arm D) in patients with PTCL. Patient characteristics are listed in Table 1. We have treated a total of 12 patients across the 2 trials and 4 different Arms including pralatrexate plus pembrolizumab (3 patients), pralatrexate, decitabine and pembrolizumab (3 patients), decitabine and pembrolizumab (3 patients) and azacytidine, romidepsin and durvalumab (3 patients). Twelve patients out of 12 received at least one dose of drug and were evaluable for toxicity. There was a dose limiting toxicity (DLT) for each arm including prolonged grade 3 thrombocytopenia, febrile neutropenia, grade 3 hyponatremia and rash, and cytokine release syndrome, respectively. There were no treatment-related deaths. Eight patients out of 12 are evaluable for response at the time of this analysis. Three out of 8 patients achieved a complete remission, 3 out of 8 patients had a partial remission, and 2 out of 8 patients experienced progression of disease. Interestingly, all of the responses were seen in the triple combination of pralatrexate, decitabine, pembrolizumab and azacytidine, romidepsin and durvalumab. These preliminary clinical data suggest that the addition of immune-checkpoint inhibitors on an epigenetic backbone is safe and demonstrates encouraging responses in patient with PTCL and CTCL. These trials are registered at www.clinicaltrials.gov (NCT03240211, NCT03161223). Patient characteristics (n=12)Median age (range)68 (26-77)Sex, n (%) Male Female6 (50) 6 (50)Race, n (%)White/Non-Hispanic White/Hispanic Black Asian Unknown5 (42) 1 (8) 3 (25) 1 (8) 2 (17)Histology, n (%) PTCL, NOS AITL Mycosis Fungoides PTCL, NOS TFH ATLL Sezary Syndrome ALCL, ALK+2 (17) 2 (17) 2 (17) 1 (8) 1 (8) 1 (8) 1 (8)Stage at diagnosis IB II III IV Unknown1 (8) 2 (17) 3 (25) 4 (33) 2 (17)Median number of prior therapies (range) **2 unknown3 (0-5) Citation Format: Enrica Marchi, Helen Ma, Francesca Montanari, Ahmed Sawas, Jennifer K. Lue, Changchun Deng, Kareema T. Whitfield, Sandra Klein, Matthew V. Matthew, Freedy J. Loffredo, Luigi Scotto, Hyejung Lee, Hye A. Kim, Alice T. Jacobs, Aishling M. Rada, Karen A. Khan, Salvia Salvia, John Lister, Nora N. Benanni, Mark A. Francescone, Pier Luigi Zinzani, Wonseog Kim, Owen A. O'Connor. The integration of PD1 blockade with epigenetic therapy is highly active and safe in heavily treated patients with T-cell lymphoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT160.

Abstract Background: Persons of African ancestry (AA) experience a 1.5-2-fold risk of multiple myeloma (MM) compared to persons of European ancestry (EA). We assembled a set of MM patients with self-reported AA in order to evaluate the contribution of genetics to etiology in this high-risk group. Methods: Here we present the results of a meta-analysis of two GWAS in 1,813 cases and 8,871 controls of AA. We also conducted an admixture mapping scan to identify risk alleles associated with local ancestry, fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA, and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. Finally, we conducted an eQTL analysis measuring gene expression in those genes harboring a risk variant in malignant plasma cells from 292 of the patients from a single site. Results: In GWAS analysis, we identified two suggestive novel loci located at 9p24.3 and 9p13.1 at P<1 × 10-6, but no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. 20 of the 23 known EA risk variants showed directional consistency and 9 replicated at P<0.05 in AA individuals. In eight regions, we identified markers that better capture MM risk in persons of AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95%CI: 1.56, 2.11) increased MM risk compared to those with average risk (25-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P= 5.1 × 10–12). Conclusion: Our study shows that common genetic variation contributes to MM risk individuals of AA. This abstract is also being presented as Poster C040. Citation Format: Zhaohui Du, Niels Weinhold, Gregory Chi Song, Kristen A. Rand, David J. Van Den Berg, Amie E. Hwang, Xin Sheng, Victor Hom, Sikander Ailawadhi, Ajay K. Nooka, Seema Singhal, Karen Pawlish, Edward Peters, Cathryn Bock, Ann Mohrbacher, Alexander Stram, Sonja I. Berndt, William J. Blot, Graham Casey, Victoria L. Stevens, Rick Kittles, Phyllis J. Goodman, W. Ryan Diver, Anselm Hennis, Barbara Nemesure, Eric A. Klein, Benjamin A. Rybicki, Janet L. Stanford, John S. Witte, Lisa Signorello, Esther M. John, Leslie Bernstein, Antoinette Stroup, Owen W. Stephens, Maurizio Zangari, Frits Van Rhee, Andrew Olshan, Wei Zheng, Jennifer J. Hu, Regina Ziegler, Sarah J. Nyante, Sue Ann Ingles, Michael Press, John David Carpten, Stephen Chanock, Jayesh Mehta, Graham A Colditz, Jeffrey Wolf, Thomas G. Martin, Michael Tomasson, Mark A. Fiala, Howard Terebelo, Nalini Janakiraman, Laurence Kolonel, Kenneth C. Anderson, Loic Le Marchand, Daniel Auclair, Brian C.-H. Chiu, Elad Ziv, Daniel Stram, Ravi Vij, Leon Bernal-Mizrachi, Gareth J. Morgan, Jeffrey A. Zonder, Carol Ann Huff, Sagar Lonial, Robert Z. Orlowski, David V. Conti, Christopher A. Haiman, Wendy Cozen. A meta-analysis of genome-wide association study and eQTL analysis of multiple myeloma among African Americans [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr PR05.

Abstract Background: Genetic studies have shifted to sequencing-based rare variants discovery after decades of success in identifying common disease variants by Genome-Wide Association Studies using Single Nucleotide Polymorphism chips. Sequencing-based studies require large sample sizes for statistical power but often inadvertently introduce batch effects because samples are typically collected, processed, and sequenced at multiple centers. Conventionally, batch effects are first detected and visualized using Principal Components Analysis and then controlled by including batch covariates in the disease association models. For sequencing-based genetic studies, because all variants included in the association analyses have passed quality control measures, this conventional approach treats every variant as equal and ignores the substantial differences still remaining in variant qualities and characteristics such as genotype quality scores, alternative allele fractions (fraction of reads supporting alternative allele at a variant position) and sequencing depths. Results: In the Alzheimer’s Disease Sequencing Project (ADSP) exome dataset of 9,904 cases and controls, we discovered hidden variant-level differences between sample batches of three sequencing centers and two exome capture kits. Although sequencing centers were included as a covariate in our association models, we observed differences at the variant level in genotype quality and alternative allele fraction between samples processed by different exome capture kits that significantly impacted both the confidence of variant detection and the identification of disease-associated variants. Furthermore, we found that the association signals of a subset of top disease risk variants came exclusively from samples processed by one exome capture kit that was more effective at capturing the alternative alleles compared to the other kit. Conclusions: Our findings highlight the importance of additional variant-level quality control for large sequencing-based genetic studies. More importantly, we demonstrate that automatically filtering out variants with batch differences may lead to false negatives if the batch discordance came largely from quality differences and if the variants from one batch had better quality scores.

Abstract Objective To determine whether distinct microtubule‐associated protein tau MAPT H1 subhaplotypes are associated with clinical and demographic features in Parkinson’s disease. Methods A retrospective cohort study included 855 unrelated Caucasian patients with Parkinson’s disease who were seen by Movement Disorder specialists at the Mayo Clinic Florida between 1998 and 2016. The primary outcome measures were specific demographic and clinical features of Parkinson’s disease, including age at onset, disease progression, survival, motor signs, dementia, dystonia, dyskinesia, autonomic dysfunction, impulse control disorder, psychiatric features, REM sleep behavior disorder, restless legs syndrome, and Parkinson’s disease subtype. Specific clinical features were measured at the initial visit and most recent visit. These outcomes were assessed for association with MAPT H1 subhaplotypes, which were defined by six haplotype tagging variants. Results Median onset age was 64 years (range: 22‐94 years); 548 (64%) of patients were male. Significant associations ( P < 0.0029) were observed between MAPT H1b and orthostatic hypotension (OR = 1.72, P = 0.001); between H1j and rest tremor (OR = 0.15; P < 0.001) as well as REM sleep behavior disorder (OR = 3.87, P < 0.001); between H1r and bradykinesia (OR = 0.11; P < 0.001); and between H1v and restless legs syndrome (OR = 4.02, P = 0.002). Interpretation Four MAPT H1 subhaplotypes, but not the H2 haplotype, were significantly associated with specific clinical features in Parkinson’s disease. MAPT haplotypic structure may explain some of the phenotypic variability in disease. Replication of our findings will be critical to fully resolve the Parkinson’s disease risk association signal at Chr17q21.