Biology subjects

Morris, J. C.

Publications and source records attributed to Morris, J. C..

14 recordsLinked to original sources

bioRxiv2025

A selective inhibitor of oncogenic JNK signalling perturbs metastatic outgrowth of triple-negative breast cancer through metabolic blockade

Although c-Jun N-terminal Kinase (JNK) represents an attractive anti-cancer target, its pleiotropic functionality limits the use of direct JNK inhibitors. Here, we identify a distinct subcellular pattern of JNK activity as a therapeutic vulnerability in breast cancer, where cytoplasmic JNK activity predicts poor survival outcomes, is elevated in triple-negative breast cancers (TNBC) and is essential for metastatic outgrowth. Mechanistic analyses reveal cytoplasmic JNK acts through multiple mechanisms, with downstream targets involved in cellular metabolism and cytoskeletal regulation. On this basis, we leveraged actin-based phenotypic drug-screening and identified K12, an indirect but selective inhibitor of cytoplasmic JNK that blocks TNBC metastatic outgrowth in vivo. We reveal that K12 inhibits glutaminase-1 and the pyruvate dehydrogenase complex, and that this poly-pharmacology overcomes pyruvate anaplerosis, a known resistance mechanism of existing glutaminase inhibitors. These findings demonstrate the potential of selectively targeting the oncogenic function of JNK, offering new treatment options for early-stage metastatic TNBC.

cancer biology↗

bioRxiv2024

The splicing factor kinase SRPK1 is a therapeutic target for Peripheral Vascular Disease

IntroductionIn peripheral arterial disease (PAD) anti-angiogenic VEGF-A165b isoform overexpression in monocytes contributes to impaired collateralisation. Serine-arginine protein-kinase-1 (SRPK1) regulates VEGF splicing. To determine whether SRPK1 controlled monocytic VEGF, impairing collateralisation, we investigated SRPK1 inhibition and monocyte-specific knockout in mouse models of and in human monocytes from PAD. MethodsVEGF-A165b activity was measured by co-culture of PAD patients monocytes with endothelial cells with SRPK1 inhibition. Mice with impaired revascularisation due to soluble-frizzled-related-protein-5 knockout (Sfrp5-/-), monocyte-specific Wnt5a gain-of-function (LysM-Wnt5aGOF), or obese mice on a high-fat high-sucrose (HF/HS) diet were subjected to femoral artery ligation and treated with SRPK1 inhibitor. We generated an SRPK1 conditional knockout and crossed it with monocyte-specific (LysM-Cre) driver line to specifically knockout SRPK1 in monocyte lineages. Blood flow was measured by Laser Speckle Imaging before, and for 28 days after surgery. ResultsMonocytes from PAD patients significantly inhibited endothelial cell migration, which was reversed by an anti-VEGF-A165b antibody. Surprisingly, migration was stimulated by SRPK1 inhibition, switching splicing from VEGF-A165b to VEGF-A165a. In Sfrp5-/-, LysM-Wnt5aGOF and HF/HS mouse models of PAD, blood flow was improved by SRPK1 inhibition. Impaired revascularisation in LysM-Wnt5aGOF mice was rescued in LysM-Wnt5aGOF:SRPK1MoKO mice, which had a phenotypic shift towards M2 macrophages. Impaired blood flow recovery was also rescued in obese-SRPK1MoKO mice. ConclusionVEGF splicing in monocytes is regulated differently from VEGF splicing in epithelial or cancer cells suggesting that control of splicing is dependent on cell type and/or environment. SRPK1 inhibition enhances collateralisation in mice, and in human in vitro models of monocyte-dependent impaired angiogenesis. New and NoteworthyA novel potential treatment for peripheral arterial disease (PAD) is described. Inhibition of SRPK1, or knockout in monocytes, induces angiogenesis by preventing splicing to anti-angiogenic VEGF (VEGF-A165b) in patients and animal models. In PAD, monocyte splicing control is different from other cell types and SRPK1 inhibition by drug like compounds can alter macrophage phenotype and reverse PAD in mice using a new cell specific SRPK1-LoxP mouse.

physiology↗

bioRxiv2023

Mapping Sleep's Oscillatory Events as a Biomarker of Alzheimer's Disease

ObjectiveMemory-associated neural circuits produce oscillatory events within single-channel sleep electroencephalography (EEG), including theta bursts (TBs), sleep spindles (SPs) and multiple subtypes of slow waves (SWs). Changes in the temporal "coupling" of these events are proposed to serve as a biomarker for early stages of Alzheimers disease (AD) pathogenesis. MethodsWe analyzed data from 205 aging adults, including single-channel sleep EEG, cerebrospinal fluid (CSF) AD-associated biomarkers, and Clinical Dementia Rating(R) (CDR(R)) scale. Individual SW events were sorted into high and low transition frequencies (TF) subtypes. We utilized time-frequency spectrogram locations within sleep EEG to "map" the precision of SW-TB and SW-SP neural circuit coupling in relation to amyloid positivity (by CSF A{beta}42/A{beta}40 threshold), cognitive impairment (by CDR), and CSF levels of AD-associated biomarkers. ResultsCognitive impairment was associated with lower TB spectral power in both high and low TF SW-TB coupling (p<0.001, p=0.001). Cognitively unimpaired, amyloid positive aging adults demonstrated lower precision of the neural circuits propagating high TF SW-TB (p<0.05) and low TF SW-SP (p<0.005) event coupling, compared to cognitively unimpaired amyloid negative individuals. Biomarker correlations were significant for high TF SW-TB coupling with CSF A{beta}42/A{beta}40 (p=0.005), phosphorylated-tau181 (p<0.005), and total-tau (p<0.05). Low TF SW-SP coupling was also correlated with CSF A{beta}42/A{beta}40 (p<0.01). InterpretationLoss of integrity in neural circuits underlying sleep-dependent memory processing can be measured for both SW-TB and SW-SP coupling in spectral time-frequency space. Breakdown of sleeps memory circuit integrity is associated with amyloid positivity, higher levels of AD-associated pathology, and cognitive impairment.

neuroscience↗

bioRxiv2022

Systematic characterization of brain cellular crosstalk signaling networks in Alzheimer's disease reveals a novel role for SEMA6D in TREM2-dependent microglial activation

Cellular crosstalk, mediated by membrane receptors and their ligands, is crucial for brain homeostasis and can contribute to neurodegenerative diseases such as Alzheimers disease (AD). To discover crosstalk dysregulations in AD, we reconstructed crosstalk networks from single-nucleus transcriptional profiles from 67 clinically and neuropathologically well-characterized controls and AD brain donors. We predicted a significant role for TREM2 and additional AD risk genes mediating neuron-microglia crosstalk in AD. The gene sub-network mediating SEMA6D-TREM2 crosstalk is activated near A{beta} plaques and SEMA6D-expressing cells and is disrupted in late AD stages. Using CRISPR-modified human induced pluripotent stem cell-derived microglia, we demonstrated that SEMA6D induces microglial activation in a TREM2-dependent manner. In summary, we demonstrate that characterizing cellular crosstalk networks can yield novel insights into AD biology. One Sentence SummaryWe investigate cell-to-cell communication in Alzheimers disease to characterize disease biology and suggest new avenues for therapeutic intervention.

neuroscience↗

bioRxiv2022

Brain aerobic glycolysis and resilience in Alzheimer disease

The distribution of brain aerobic glycolysis (AG) in normal young adults correlates spatially with amyloid-beta (A{beta}) deposition in individuals with dementia of the Alzheimer type (DAT) and asymptomatic individuals with brain amyloid deposition. Brain AG decreases with age but the functional significance of this decrease with regard to the development of DAT symptomatology is poorly understood. Using PET measurements of regional blood flow, oxygen consumption and glucose utilization--from which we derive AG--we find that cognitive impairment is strongly associated with loss of the typical youthful pattern of AG. In contrast, amyloid positivity without cognitive impairment was associated with preservation of youthful brain AG, which was even higher than that seen in typical, cognitively unimpaired, amyloid negative adults. Similar findings were not seen for blood flow nor oxygen consumption. Finally, in cognitively unimpaired adults, white matter hyperintensity burden was found to be specifically associated with decreased youthful brain AG. Our results implicate preserved AG as a factor in brain resilience to amyloid pathology and suggest that white matter disease may be a cause and/or consequence of this impaired resilience.

neuroscience↗

bioRxiv2020

Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into the complex genetic architecture

The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer’s and Parkinson’s disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.Competing Interest StatementThomas G. Beach is a consultant for Prothena, Vivid Genomics and Avid Radiopharmaceuticals. He is a scientific advisory board member for Vivid Genomics. John A. Hardy, Huw R. Morris, Stuart Pickering-Brown, Andrew B. Singleton, and Bryan J. Traynor hold US, EU and Canadian patents on the clinical testing and therapeutic intervention for the hexanucleotide repeat expansion of C9orf72. Michael A. Nalls is supported by a consulting contract between Data Tecnica International and the National Institute on Aging, NIH, Bethesda, MD, USA; as a possible conflict of interest Dr. Nalls also consults for Neuron23 Inc., Lysosomal Therapeutics Inc., Illumina Inc., the Michael J. Fox Foundation and Vivid Genomics among others. Jose A. Palma is an editorial board member of Movement Disorders, Parkinsonism & Related Disorders, BMC Neurology, and Clinical Autonomic Research. Bradley F. Boeve, James Leverenz, and Sonja W. Scholz serve on the Scientific Advisory Council of the Lewy Body Dementia Association. Sonja W. Scholz is an editorial board member for the Journal of Parkinson's Disease. Bryan J. Traynor is an editorial board member for JAMA Neurology; Journal of Neurology, Neurosurgery, and Psychiatry; Brain; and Neurobiology of Aging. Zbigniew K. Wszolek serves as a principal investigator or co-principal investigator on Abbvie, Inc. (M15-562 and M15-563), Biogen, Inc. (228PD201) grant, and Biohaven Pharmaceuticals, Inc. (BHV4157-206 and BHV3241-301). Zbigniew K. Wszolek serves as the principal investigator of the Mayo Clinic American Parkinson Disease Association (APDA) Information and Referral Center, and as co-principal investigator of the Mayo Clinic APDA Center for Advanced Research. All other authors report no competing interests.View Full Text

genomics↗

bioRxiv2020

The transcriptome of Balamuthia mandrillaris trophozoites for structure-based drug design

Balamuthia mandrillaris, a pathogenic free-living amoeba (FLA), causes cutaneous skin lesions as well as the brain-eating disease: Balamuthia granulomatous amoebic encephalitis (GAE). These diseases, and diseases caused by other pathogenic FLA, Naegleria fowleri or Acanthamoeba species, are minimally studied from a drug discovery perspective; few targets have been validated or characterized at the molecular level, and little is known about the biochemical pathways necessary for parasite survival. Chemotherapies for CNS disease caused by B. mandrillaris require vast improvement. Current therapeutics are limited to a small number of drugs that were previously discovered in the last century through in vitro testing or identified after use in the small pool of surviving reports. Using our recently published methodology to identify potentially useful therapeutics, we screened a collection of 85 compounds that have previously been reported to have antiparasitic activity. We identified 59 compounds that impacted growth at concentrations below 220 M. Since there is no fully annotated genome or proteome, we used RNA-Seq to reconstruct the transcriptome of B. mandrillaris and locate the coding sequences of the specific genes potentially targeted by the compounds identified to inhibit trophozoite growth. We determined the sequence of 17 of these target genes and obtained expression clones for 15 that we validated by direct sequencing.

genomics↗

bioRxiv2020

Functional brain age prediction suggests accelerated aging in preclinical familial Alzheimer's disease, irrespective of fibrillar amyloid-beta pathology

We aimed at developing a model able to predict brain aging from resting state functional connectivity (rs-fMRI) and assessing whether genetic risk/determinants of Alzheimers disease (AD) and amyloid (A{beta}) pathology contributes to accelerated brain aging. Using data collected in 1340 cognitively unimpaired participants from 18 to 94 years old selected across multi-site cohorts, we showed that chronological age can be predicted across the whole lifespan from topological properties of graphs constructed from rs-fMRI. We subsequently used the difference between the model-predicted age and the chronological age in pre-symptomatic autosomal dominant AD (ADAD) mutation carriers and asymptomatic individuals at risk of sporadic AD and assessed the influence of genetics and A{beta} pathology on brain age. Applying our predictive model in the context of preclinical AD revealed that the pre-symptomatic phase of ADAD is characterized by accelerated functional brain aging. This phenomenon is independent from, and might precede, detectable fibrillar A{beta} deposition.

neuroscience↗

bioRxiv2019

Single- nuclei RNA sequencing from human brain to study for Mendelian and sporadic AD

Alzheimer Disease (AD) is the most common form of dementia. This neurodegenerative disorder is associated with neuronal death and gliosis heavily impacting the cerebral cortex. AD has a substantial but heterogeneous genetic component, presenting both Mendelian and complex genetic architectures. Using bulk RNA-seq from parietal lobes and deconvolution methods, we previously reported that brains exhibiting different AD genetic architecture exhibit different cellular proportions. Here, we sought to directly investigate AD brain changes in cell proportion and gene expression using single cell resolution. To do so, we generated unsorted single-nuclei RNA-sequencing data from brain tissue. We leveraged tissue donated from a carrier of a Mendelian genetic mutation and two family members who suffer from AD, but do not have the same mutation. We evaluated alternative alignment approaches to maximize the titer of reads, genes and cells with high quality. In addition, we employed distinct clustering strategies to determine the best approach to identify cell clusters that reveal neuronal and glial cell types and avoid artifacts such as sample and batch effects. We propose an approach to cluster cells that reduces biases and enable further analyses. We identified distinct types of neurons, both excitatory and inhibitory, and glial cells, including astrocytes, oligodendrocytes, and microglia among others. In particular, we identified a reduced proportion of excitatory neurons in the Mendelian mutation carrier, but a similar distribution of inhibitory neurons. Furthermore, we investigated whether single-nuclei RNA-seq from human brains recapitulate the expression profile of Disease Associated Microglia (DAM) discovered in mouse models. We also determined that when analyzing human single-nuclei data it is critical to control for biases introduced by donor specific expression profiles. In conclusion, we propose a collection of best practices to generate a highly-detailed molecular cell atlas of highly informative frozen tissue stored in brain banks. Importantly, we have developed a new web application to make this unique single-nuclei molecular atlas publicly available.

genomics↗

bioRxiv2018

Enzymatic and structural characterization of the Naegleria fowleri glucokinase

Infection with the free-living amoeba Naegleria fowleri leads to life-threatening primary amoebic meningoencephalitis. Efficacious treatment options for these infections are limited and the mortality rate is very high (~98%). Parasite metabolism may provide suitable targets for therapeutic design. Like most other organisms, glucose metabolism is critical for parasite viability, being required for growth in culture. The genome of the parasite encodes a single glucose phosphorylating enzyme, a glucokinase (Glck). The products of this enzyme are required for both glycolysis and the pentose phosphate pathway. The N. fowleri Glck (NfGlck) shares limited (25%) amino acid identity with the mammalian host enzyme (HsGlck), suggesting that parasite-specific inhibitors with anti-amoeba activity could be generated. Following heterologous expression, NfGlck was found to have a limited hexose substrate range, with greatest activity observed with glucose. The enzyme had apparent Km values of 42.5 {+/-} 7.3 M and 141.6 {+/-} 9.9 M for glucose and ATP, respectively. The NfGlck structure was determined and refined to 2.2 [A] resolution, revealing that the enzyme shares greatest structural similarity with the Trypanosoma cruzi Glck. These similarities include binding modes and binding environments for substrates. To identify inhibitors of NfGlck, we screened a small collection of inhibitors of glucose phosphorylating enzymes and identified several small molecules with IC50 values < 1 M that may prove useful as hit chemotypes for further lead and therapeutic development against N. fowleri.

biochemistry↗

bioRxiv2018

Genetic variants associated with Alzheimer's disease confer different cerebral cortex cell-type population structure

Alzheimers disease (AD) is characterized by neuronal loss and astrocytosis in the cerebral cortex. However, the effects of brain cellular composition are often ignored in high-throughput molecular studies. We developed and optimized a cell-type specific expression reference panel and employed digital deconvolution methods to determine brain cellular distribution in three independent transcriptomic studies. We found that neuronal and astrocyte proportions differ between healthy and diseased brains and also among AD cases that carry specific genetic risk variants. Brain carriers of pathogenic mutations in APP, PSEN1 or PSEN2 presented lower neurons and higher astrocytes proportions compared to sporadic AD. Similarly, the APOE {varepsilon}4 allele also showed decreased neurons and increased astrocytes compared to AD non-carriers. On the contrary, carriers of variants in TREM2 risk showed a lower degree of neuronal loss than matched AD cases in multiple independent studies. These findings suggest that genetic risk factors associated with AD etiology have a specific imprinting in the cellular composition of AD brains. Our digital deconvolution reference panel provides an enhanced understanding of the fundamental molecular mechanisms underlying neurodegeneration, enabling the analysis of large bulk RNA-seq studies for cell composition, and suggests that correcting for the cellular structure when performing transcriptomic analysis will lead to novel insights of AD.

genetics↗

bioRxiv2018

Data-driven models of dominantly-inherited Alzheimer’s disease progression

Dominantly-inherited Alzheimers disease is widely hoped to hold the key to developing interventions for sporadic late onset Alzheimers disease. We use emerging techniques in generative data-driven disease-progression modelling to characterise dominantly-inherited Alzheimers disease progression with unprecedented resolution, and without relying upon familial estimates of years until symptom onset (EYO). We retrospectively analysed biomarker data from the sixth data freeze of the Dominantly Inherited Alzheimer Network observational study, including measures of amyloid proteins and neurofibrillary tangles in the brain, regional brain volumes and cortical thicknesses, brain glucose hypometabolism, and cognitive performance from the Mini-Mental State Examination (all adjusted for age, years of education, sex, and head size, as appropriate). Data included 338 participants with known mutation status (211 mutation carriers: 163 PSEN1; 17 PSEN2; and 31 APP) and a baseline visit (age 19-66; up to four visits each, 1{middle dot}1 {+/-} 1{middle dot}9 years in duration; spanning 30 years before, to 21 years after, parental age of symptom onset). We used an event-based model to estimate sequences of biomarker changes from baseline data across disease subtypes (mutation groups), and a differential-equation model to estimate biomarker trajectories from longitudinal data (up to 66 mutation carriers, all subtypes combined). The two models concur that biomarker abnormality proceeds as follows: amyloid deposition in cortical then sub-cortical regions (approximately 24{+/-}11 years before onset); CSF p-tau (17{+/-}8 years), tau and A{beta}42 changes; neurodegeneration first in the putamen and nucleus accumbens (up to 6 {+/-} 2 years); then cognitive decline (7 {+/-} 6 years), cerebral hypometabolism (4 {+/-} 4 years), and further regional neurodegeneration. Our models predicted symptom onset more accurately than EYO: root-mean-squared error of 1{middle dot}35 years versus 5{middle dot}54 years. The models reveal hidden detail on dominantly-inherited Alzheimers disease progression, as well as providing data-driven systems for fine-grained patient staging and prediction of symptom onset with great potential utility in clinical trials.

neuroscience↗

bioRxiv2018

Evaluation of gene-based family-based methods to detect novel genes associated with familial late onset Alzheimer disease

Gene-based tests to study the combined effect of rare variants towards a particular phenotype have been widely developed for case-control studies, but their evolution and adaptation for family-based studies, especially for complex incomplete families, has been slower. In this study, we have performed a practical examination of all the latest gene-based methods available for family-based study designs using both simulated and real datasets. We have examined the performance of several collapsing, variance-component and transmission disequilibrium tests across eight different software and twenty-two models utilizing a cohort of 285 families (N=1,235) with late-onset Alzheimer disease (LOAD). After a thorough examination of each of these tests, we propose a methodological approach to identify, with high confidence, genes associated with the studied phenotype with high confidence and we provide recommendations to select the best software and model for family-based gene-based analyses. Additionally, in our dataset, we identified PTK2B, a GWAS candidate gene for sporadic AD, along with six novel genes (CHRD, CLCN2, HDLBP, CPAMD8, NLRP9, MAS1L) as candidates genes for familial LOAD.

genetics↗

bioRxiv2017

Polygenic Risk Score of Sporadic Late Onset Alzheimer Disease Reveals a Shared Architecture with the Familial and Early Onset Forms

ObjectiveTo determine whether the genetic architecture of sporadic late-onset Alzheimers Disease (sLOAD) has an effect on familial late-onset AD (fLOAD), sporadic early-onset (sEOAD) and autosomal dominant early-onset (eADAD).\n\nMethodsPolygenic risk scores (PRS) were constructed using previously identified 21 genome-wide significant loci for LOAD risk.\n\nResultsWe found that there is an overlap in the genetic architecture among sEOAD, fLOAD, and sLOAD. sEOAD showed the highest odds for the PRS (OR=2.27; p=1.29x10-7), followed by fLOAD (OR=1.75; p=1.12x10-7) and sLOAD (OR=1.40; p=1.21x10-3). PRS is associated with cerebrospinal fluid ptau181-A{beta}42 on eADAD.\n\nConclusionOur analysis confirms that the genetic factors identified for sLOAD also modulate risk in fLOAD and sEOAD cohorts. Furthermore, our results suggest that the burden of these risk variants is associated with familial clustering and earlier-onset of AD. Although these variants are not associated with risk in the eADAD, they may be modulating age at onset.

genetics↗