Biology subjects

Khurshid, S.

Publications and source records attributed to Khurshid, S..

8 recordsLinked to original sources

bioRxiv2026

Prefrontal cortex transcriptomes distinguish Alzheimers disease from asymptomatic amyloid pathology, neuropeptide loss, immune-complement activation and glial remodelling

Alzheimer's disease (AD) is now defined biologically by cortical amyloid-{beta} (A) and tau (T) pathology, yet the transcriptional programmes that separate symptomatic AD (A+T+) from amyloid-positive, tau-negative pathology ageing (A+T-) and from pathology-free controls (A-T-) remain incompletely resolved in the association cortex. We re-analysed bulk RNA-sequencing data from the dorsolateral prefrontal cortex (DLPFC) of 15 donors (BioProject PRJNA1017546; 87 sequencing runs aggregated to donor level): Normal (n = 2), pathology ageing (n = 5) and AD (n = 8). Differential expression was tested with DESeq2 (adjusted P < 0.05, |log2 fold change| > 1), and up- and down-regulated gene sets were analysed separately by Gene Ontology (GO) and KEGG over-representation. APOE and TREM2 p.Arg47His contrasts were treated as exploratory. AD versus Normal yielded 341 differentially expressed genes (DEGs; 223 up, 118 down) and AD versus pathology ageing yielded 496 (358 up, 138 down), whereas pathology ageing versus Normal yielded only six. Genes reduced in AD were dominated by neuropeptide and hormone signalling (VGF, VIP, CRH, GRP, TAC1, PENK; neuroactive ligand-receptor interaction, adjusted P = 8.8 x 10-5; neuropeptide hormone activity, adjusted P = 6.3 x 10-8), most of which also differed from pathology ageing. Genes increased in AD were enriched for interferon-{gamma} response, myeloid activation, adaptive immunity and classical complement (C1QA, C1QB, C1QC). Relative to pathology ageing, AD additionally showed induction of gliogenesis, oligodendrocyte differentiation and myelination programmes (gliogenesis, 21 genes, adjusted P = 2.6 x 10-6; SOX10, MYRF) and of the microglial purinergic receptor gene P2RX7 (log2FC = 1.46, adjusted P = 1.5 x 10-5). All six pathology-ageing DEGs, including the myeloid genes VSIG4 and CD163, were also DEGs in AD, and 50 DEGs shared by the two AD contrasts moved in the same direction. Genotype-stratified analyses were underpowered or confounded with diagnosis. In the DLPFC, AD is therefore characterised by a graded loss of neuropeptidergic signalling, myeloid-complement activation that begins at the pathology-ageing stage, and an AD-specific glial/oligodendrocyte response. These signatures nominate candidate biomarkers and mechanisms for early intervention, but the small cohort demands replication in larger, covariate-annotated datasets.

bioinformatics↗

bioRxiv2026

Conserved sequence elements in the final exon of MDM2-eight-exon skipping event reveal a cassette regulon model of alternative splicing controlled by a distal regulatory element.

Modern sequencing technologies have revealed that cancers exhibit widespread dysregulation of alternative splicing, which plays a significant role in driving tumor hallmarks. Alternative splicing enables a single gene to generate multiple mRNA variants, a fundamental mechanism that shapes the distinctive characteristics of normal cells as well as cancer cells. These splicing events are governed by complex interactions between cis- and trans-acting factors and understanding these mechanisms is crucial for effectively targeting cancer cells. This study highlights a unique splicing event in which genotoxic stress induces the skipping of eight-exons in the proto-oncogene MDM2, resulting in the formation of MDM2-ALT1, an isoform that is overexpressed in various cancers. To effectively target this splicing event, it is important to unfold the regulatory mechanism behind it. We hypothesize that the event occurs either by the autonomous regulation of individual exons (Exon autonomous model), where each exon is regulated independently or by the coordinated exclusion of an eight-exon-regulon unit (Exon Regulon model). Utilizing in-silico tools, a comprehensive modular minigene system, CRISPR-mutated cell line, and murine models, we demonstrate that this complex MDM2 splicing event is regulated by sequences within a distal terminal exon, which emerge as critical regulators, orchestrating the alternative splicing of MDM2. Constitutive expression of the Mdm2-MS2 isoform (the mouse ortholog of the human MDM2-ALT1 splice variant), achieved by mutating the Srsf2 binding-site on exon 11, modulates proliferation and apoptosis dynamics in NIH3T3 cells. Moreover, in a p53-wildtype in-vivo setting, this isoform confers a protective effect against age-induced neoplasia. Our findings support the Exon Regulon model of MDM2 splicing, regulated by distal elements analogous to distal enhancer elements that control transcription. These finding sheds light on intricacies in the splicing code that could have significant implications for developing splice variant targeting cancer therapies.

molecular biology↗

bioRxiv2024

Blockade of Interleukin-6 (IL-6) Signaling in Dedifferentiated Liposarcoma (DDLPS) Decreases Mouse Double Minute 2 (MDM2) Oncogenicity via Alternative Splicing

Effective therapies for retroperitoneal (RP) dedifferentiated liposarcoma (DDLPS) remain unavailable. Loco-regional recurrence occurs in >80% of cases; 5-year disease-specific survival is only 20%. DDLPS is especially prevalent in the retroperitoneum and abdomen; evaluation of the DDLPS microenvironment in these high-fat compartments appears pertinent. Adipose is a main supplier of interleukin-6 (IL6); excessive activation of IL6 signal transducer glycoprotein 130 (GP130) underlies the development of some diseases. The role of GP130 pathway activation remains unstudied in DDLPS, so we examined the role of microenvironment fat cell activation of the IL6/GP130 signaling cascade in DDLPS. All DDLPS tumors and cell lines studied expressed elevated levels of the GP130-encoding gene IL6ST and GP130 protein compared to normal tissue and cell line controls. IL6 increased DDLPS cell growth and migration, possibly through increased signal transducer and activator of transcription 1 (STAT1) and 3 (STAT3) activation, and upregulated mouse double minute 2 (MDM2). GP130 loss conveyed opposite effects; pharmacological blockade of GP130 by SC144 produced the MDM2 splice variant MDM2-ALT1, known to inhibit full length MDM2 (MDM2-FL). Although genomic MDM2 amplification is pathognomonic for DDLPS, mechanisms driving MDM2 expression, regulation, and function beyond the MDM2:p53 negative feedback loop are poorly understood. Our findings suggest a novel preadipocyte DDLPS-promoting role due to IL6 release, via upregulation of DDLPS MDM2 expression. Pharmacological GP130 blockade reduced the IL6-induced increase in DDLPS MDM2 mRNA and protein levels, possibly through enhanced expression of MDM2-ALT1, a possibly targetable pathway with potential as future DDLPS patient therapy.

molecular biology↗

bioRxiv2022

Cross-Modal Autoencoder Framework Learns Holistic Representations of Cardiovascular State

A fundamental challenge in diagnostics is integrating multiple modalities to develop a joint characterization of physiological state. Using the heart as a model system, we develop a cross-modal autoencoder framework for integrating distinct data modalities and constructing a holistic representation of cardio-vascular state. In particular, we use our framework to construct such cross-modal representations from cardiac magnetic resonance images (MRIs), containing structural information, and electrocardiograms (ECGs), containing myoelectric information. We leverage the learned cross-modal representation to (1) improve phenotype prediction from a single, accessible phenotype such as ECGs; (2) enable imputation of hard-to-acquire cardiac MRIs from easy-to-acquire ECGs; and (3) develop a framework for performing genome-wide association studies in an unsupervised manner. Our results provide a framework for integrating distinct diagnostic modalities into a common representation that better characterizes physiologic state.

bioinformatics↗

bioRxiv2021

Genetic Analysis of Right Heart Structure and Function in 40,000 People

The heart evolved hundreds of millions of years ago. During mammalian evolution, the cardiovascular system developed with complete separation between pulmonary and systemic circulations incorporated into a single pump with chambers dedicated to each circulation. A lower pressure right heart chamber supplies deoxygenated blood to the lungs, while a high pressure left heart chamber supplies oxygenated blood to the rest of the body. Due to the complexity of morphogenic cardiac looping and septation required to form these two chambers, congenital heart diseases often involve maldevelopment of the evolutionarily recent right heart chamber. Additionally, some diseases predominantly affect structures of the right heart, including arrhythmogenic right ventricular cardiomyopathy (ARVC) and pulmonary hypertension. To gain insight into right heart structure and function, we fine-tuned deep learning models to recognize the right atrium, the right ventricle, and the pulmonary artery, and then used those models to measure right heart structures in over 40,000 individuals from the UK Biobank with magnetic resonance imaging. We found associations between these measurements and clinical disease including pulmonary hypertension and dilated cardiomyopathy. We then conducted genome-wide association studies, identifying 104 distinct loci associated with at least one right heart measurement. Several of these loci were found near genes previously linked with congenital heart disease, such as NKX2-5, TBX3, WNT9B, and GATA4. We also observed interesting commonalities and differences in association patterns at genetic loci linked with both right and left ventricular measurements. Finally, we found that a polygenic predictor of right ventricular end systolic volume was associated with incident dilated cardiomyopathy (HR 1.28 per standard deviation; P = 2.4E-10), and remained a significant predictor of disease even after accounting for a left ventricular polygenic score. Harnessing deep learning to perform large-scale cardiac phenotyping, our results yield insights into the genetic and clinical determinants of right heart structure and function.

genetics↗

bioRxiv2020

Splice-switching of the insulin receptor in rhabdomyosarcoma: Rescuing the IR-B isoform for better treatment options.

Rhabdomyosarcoma (RMS) is an aggressive pediatric tumor with poor prognosis for metastasis and recurrent disease. Large scale sequencing endeavors demonstrate that RMS tumors have limited mutations and a dearth of driver mutations that are precisely targetable. However, IGF2 signaling is known to be grossly altered in RMS. The IGF2 signalling molecule binds both its innate IGF1 receptor as well as the insulin-receptor-variant-A (IR-A) with high affinity. Mitogenic and proliferative signalling via the canonical IGF2 pathway is therefore augmented by IR-A. The insulin receptor (IR) which is a transmembrane tyrosine-kinase receptor exists in two alternatively spliced isoforms, IR-A and IR-B. In this study, we show that RMS patients express increased IR-A compared to control tissues that express predominantly the IR-B isoform. We also found that Hif1a is significantly increased in RMS tumors, portraying their hypoxic phenotype. Furthermore, the alternative-splicing of IR adapts to produce more IR-A in response to hypoxic stress. Upon examining the pre-mRNA structure of the gene, we identified a hypoxia-responsive-element, which is also the binding site for the RNA-binding protein CUG-BP1. We designed Splice-Switching-Oligonucleotides (SSO) against this binding site to decrease the levels of IR-A in RMS cell-lines and consequently rescue the IR-B expression levels. SSO treatment resulted in significant reductions in proliferation, migration and angiogenesis. Our data show promising insight into how impeding the IGF-2 pathway by reducing IR-A expression mitigates tumor growth. Our data reveal that RMS tumors use IR alternative-splicing as yet another survival strategy which can be exploited as therapeutic intervention in conjunction with already established anti-IGF-1 receptor therapies.

cancer biology↗

bioRxiv2020

Deep learning enables genetic analysis of the human thoracic aorta

The aorta is the largest blood vessel in the body, and enlargement or aneurysm of the aorta can predispose to dissection, an important cause of sudden death. While rare syndromes have been identified that predispose to aortic aneurysm, the common genetic basis for the size of the aorta remains largely unknown. By leveraging a deep learning architecture that was originally developed to recognize natural images, we trained a model to evaluate the dimensions of the ascending and descending thoracic aorta in cardiac magnetic resonance imaging. After manual annotation of just 116 samples, we applied this model to 3,840,140 images from the UK Biobank. We then conducted a genome-wide association study in 33,420 individuals, revealing 68 loci associated with ascending and 35 with descending thoracic aortic diameter, of which 10 loci overlapped. Integration of common variation with transcriptome-wide analyses, rare-variant burden tests, and single nucleus RNA sequencing prioritized SVIL, a gene highly expressed in vascular smooth muscle, that was significantly associated with the diameter of the ascending and descending aorta. A polygenic score for ascending aortic diameter was associated with a diagnosis of thoracic aortic aneurysm in the remaining 391,251 UK Biobank participants who did not undergo imaging (HR = 1.44 per standard deviation; P = 3.7{middle dot}10-12). Defining the genetic basis of the diameter of the aorta may enable the identification of asymptomatic individuals at risk for aneurysm or dissection and facilitate the prioritization of potential therapeutic targets for the prevention or treatment of aortic aneurysm. Finally, our results illustrate the potential for rapidly defining novel quantitative traits derived from a deep learning model, an approach that can be more broadly applied to biomedical imaging data.

genomics↗

bioRxiv2019

SRSF2 regulation of MDM2 reveals splicing as a therapeutic vulnerability of the p53 pathway

MDM2 is an oncogene and critical negative regulator of tumor suppressor p53. Genotoxic stress causes alternative splicing of MDM2 transcripts, which leads to alterations in p53 activity and contributes to tumorigenesis. MDM2-ALT1 is one of transcripts predominantly produced in response to genotoxic stress and is comprised of terminal coding exons 3 and 12. Previously, we found that SRSF1 induces MDM2-ALT1 by promoting MDM2 exon 11 skipping. Here we report that splicing regulator SRSF2 antagonizes the regulation of SRSF1 by facilitating the inclusion of exon 11 through binding at two conserved exonic splicing enhancers. Overexpression of SRSF2 reduced the generation of MDM2-ALT1 in genotoxic stress condition, whereas knockdown induces the expression of MDM2-ALT1 in absence of genotoxic stress. Consistently, blocking the exon 11 SRSF2 binding sites using oligonucleotides promotes MDM2-ALT1. The regulation of MDM2 splicing by SRSF2 is also conserved in mouse as mutation of one SRSF2 binding site in Mdm2 exon 11, using CRISPR-Cas9, increases the expression MDM2-ALT1 homolog Mdm2-MS2 and proliferation of NIH 3T3 cells. Taken together, these findings underscore the relevance of MDM2 alternative splicing in cancer and suggest that p53 levels can be modulated by artificially regulating MDM2 splicing.

cancer biology↗