Biology subjects

Radhakrishnan, K.

Publications and source records attributed to Radhakrishnan, K..

5 recordsLinked to original sources

bioRxiv2025

7-ketocholesterol contributes to microglia-driven increases in astrocyte reactive oxygen species in Alzheimer's disease

Oxidative stress is a prominent feature of Alzheimers disease. Within this context, cholesterol undergoes oxidation, producing the pro-inflammatory product 7-ketocholesterol (7-KC). In this study, we observe elevated levels of 7-KC in the brains of the 3xTg mouse model of AD. To further understand the contribution of 7-KC on the oxidative environment, we developed a method to express a genetically encoded fluorescent hydrogen peroxide (H2O2) sensor in astrocytes, the primary source of cholesterol in the brain. With this sensor, we discovered that 7-KC increases H2O2 levels in astrocytes in vivo, but not when directly applied to astrocytes in vitro. Interestingly, when 7-KC was applied to a microglia cell line alone or mixed astrocyte and microglia cultures, it resulted in microglia activation and increased oxidative stress in astrocytes. Depletion of microglia from 3xTg mice resulted in reduced 7-KC in the brains of these mice. Taken together, these findings suggest that 7-KC, acting through microglia, contributes to increased astrocyte oxidative stress in AD. This study sheds light on the complex interplay between cholesterol oxidation, microglia activation, and astrocyte oxidative stress in the pathogenesis of AD.

neuroscience↗

bioRxiv2024

Effective Gene Therapy for Metachromatic Leukodystrophy Achieved with Minimal Lentiviral Genomic Integrations

Metachromatic leukodystrophy (MLD) is a fatal lysosomal storage disease (LSD) characterized by the deficient enzymatic activity of arylsulfatase A (ARSA). Combined autologous hematopoietic stem cell transplant (HSCT) with lentiviral (LV) based gene therapy has great potential to treat MLD. However, if enzyme production is inadequate, this could result in continued loss of motor function, implying a high vector copy number (VCN) requirement for optimal enzymatic output. This may place children at increased risk for genomic toxicity due to higher VCN. We increased the expression of ARSA cDNA at single integration by generating novel LVs, optimizing ARSA expression, and enhancing safety. In addition, our vectors achieved optimal transduction in mouse and human HSC with minimal multiplicity of infection (MOI). Our top-performing vector (EA1) showed at least 4X more ARSA activity than the currently EU-approved vector and a superior ability to secrete vesicle-associated ARSA, a critical modality to transfer functional enzymes from microglia to oligodendrocytes. Three-month-old Arsa-KO MLD mice transplanted with Arsa-KO BM cells transduced with 0.6 VCN of EA1 demonstrated behavior and CNS histology matching WT mice. Our novel vector boosts efficacy while improving safety as a robust approach for treating early symptomatic MLD patients.

molecular biology↗

bioRxiv2022

A deep learning workflow for quantification of Micronuclei in DNA damage studies in cultured cancer cell lines: a proof of principle investigation

The cytokinesis block micronucleus assay is widely used for measuring/scoring/counting micronuclei, a marker of genome instability in cultured and primary cells. Though a gold standard method, this is a laborious and time-consuming process with person-to-person variation observed in quantification of micronuclei. We report in this study the utilisation of a new deep learning workflow for detection of micronuclei in DAPI stained nuclear images. The proposed deep learning framework achieved an average precision of >90% in detection of micronuclei. This proof of principle investigation in a DNA damage studies laboratory supports the idea of deploying AI powered tools in a cost-effective manner for repetitive and laborious tasks with relevant computational expertise. These systems will also help improving the quality of data and wellbeing of researchers. Simple SummaryThis study aims to test a suitable deep learning method for micronucleus detection in images acquired for cytokinesis block micronucleus assay. This study has reached a mean average precision of >90%.

cancer biology↗

bioRxiv2019

Genomic Characterization of Posttraumatic Stress Disorder in a Large US Military Veteran Sample

Individuals vary in their liability to develop Posttraumatic Stress Disorder (PTSD), the symptoms of which are highly heterogeneous, following exposure to life-threatening trauma. Understanding genetic factors that contribute to the biology of PTSD is critical for refining diagnosis and developing new treatments. Using genetic data from more than 250,000 participants in the Million Veteran Program, genomewide association analyses were conducted using a validated electronic health record-based algorithmically-defined PTSD diagnosis phenotype (48,221 cases and 217,223 controls), and PTSD quantitative symptom phenotypes (212,007 individuals). We identified several genome-wide significant loci in the case-control analyses, and numerous such loci in the quantitative trait analyses, including some (e.g., MAD1L1; TCF4; CRHR1) that were associated with multiple symptom sub-domains and total symptom score, and others that were more specific to certain symptom sub-domains (e.g., CAMKV to re-experiencing; SOX6 to hyperarousal). Genetic correlations between all pairs of symptom sub-domains and their total were very high (rg 0.93 - 0.98) supporting validity of the PTSD diagnostic construct. We also demonstrate strong shared heritability with a range of traits, show that heritability persists when conditioned on other major psychiatric disorders, present independent replication results, provide support for one of the implicated genes in postmortem brain of individuals with PTSD, and use this information to identify potential drug repositioning candidates. These results point to the utility of genetics to inform and validate the biological coherence of the PTSD syndrome despite considerable heterogeneity at the symptom level, and to provide new directions for treatment development.

genetics↗

bioRxiv2019

Reproducible Risk Loci and Psychiatric Comorbidities in Anxiety: Results from ~200,000 Million Veteran Program Participants

We used GWAS in the Million Veteran Program sample (nearly 200,000 informative individuals) using a continuous trait for anxiety (GAD-2) to identify 5 genome-wide significant (GWS) signals for European Americans (EA) and 1 for African Americans. The strongest findings were on chromosome 3 (rs4603973, p=7.40x10-11) near the SATB1 locus, a global regulator of gene expression and on chromosome 6 (rs6557168, p=1.04x10-9) near ESR1 which encodes estrogen receptor . A locus identified on chromosome 7 near MADIL1 (p=1.62x10-8) has been previously identified in GWAS of bipolar disorder and of schizophrenia and may represent a risk factor for psychiatric disorders broadly. SNP-based heritability was estimated to be ~6% for GAD-2. We also GWASed for self-reported anxiety disorder diagnoses (N=224,330) and identified two GWS loci, one (rs35546597, MAF=0.42, p=1.88x10-8) near the AURKB locus, and the other (rsl0534613, MAF=0.41, p=4.92x10-8) near the IQCHE and MADIL1 locus identified in the GAD-2 analysis. We demonstrate reproducibility by replicating our top findings in the summary statistics from the Anxiety NeuroGenetics Study (ANGST) and a UK Biobank neuroticism GWAS. We also replicated top findings from a large UK Biobank preprint, demonstrating stability of GWAS findings in complex traits once sufficient power is attained. Finally, we found evidence of significant genetic overlap between anxiety and major depression using polygenic risk scores, but also found that the main anxiety signals are independent of those for MDD. This work presents novel insights into the neurobiological risk underpinning anxiety and related psychiatric disorders. SignificanceAnxiety disorders are common and often disabling. They are also frequently co-morbid with other mental disorders such as major depressive disorder (MDD); these disorders may share commonalities in their underlying genetic architecture. Using one of the largest homogenously phenotyped cohorts available, the Million Veteran Program sample, we investigated common variants associated with anxiety in genome-wide association studies (GWASes), using survey results from the GAD-2 anxiety scale (as a continuous trait, n=199,611), and self-reported anxiety disorder diagnosis (as a binary trait, n=224,330). This largest GWAS to date for anxiety and related traits identified numerous novel significant associations, several of which are replicated in other datasets, and allows inference of underlying biology.

genetics↗