Epicardial adipose tissue volume and density is associated with cardiac dysfunction in asymptomatic people with type 2 diabetes

Background

Type 2 diabetes (T2D) is associated with several perturbations of cardiac structure and function, which are precursors to the development of heart failure. Excess accumulation of epicardial adipose tissue (EAT) may contribute to cardiac dysfunction in individuals with T2D. Lipid-laden adipocytes have a lower computed tomography (CT) attenuation and can be readily identified using cardiac CT. Using a multimodality cardiac imaging approach, we aimed to assess the association of total and low attenuation EAT volume with early markers of cardiac dysfunction in people with T2D.

Methods

Prospective case-control study, in which participants with and without T2D and no known cardiovascular disease, underwent comprehensive cardiovascular phenotyping including multiparametric cardiac magnetic resonance imaging (MRI), echocardiography and non-contrast cardiac CT. EAT volume was measured from CT scans using a deep learning method and volumes indexed to body surface area. Total EAT was defined according to CT adipose tissue attenuation range of −30 to −190 Hounsfield Units (HU) and low attenuation EAT as −90 to −190 HU. Left ventricular (LV) volumes, function and strain measurements were derived from cardiac MRI images and diastolic function also assessed using echocardiography. Markers of early cardiac dysfunction in those with T2D were assessed for associations with EAT in T2D participants using multivariable linear regression analyses.

Results

Two hundred and fifty-four participants were included: demographic, anthropometric and imaging variables are displayed in Table 1. Subjects with T2D had increased LV concentric remodelling (higher LV mass/volume ratio), diastolic dysfunction (lower circumferential peak early diastolic strain rate (PEDSR) and average E/e') and reduced systolic function (global longitudinal strain, GLS) compared with controls. Total and low attenuation indexed EAT volumes were 1.6-fold and 2-fold higher, respectively, in participants with T2D compared to controls (Figure 1). After adjustment for age, gender, ethnicity, insulin resistance, systolic blood pressure and waist/hip ratio, total and low attenuation indexed EAT volume were independently associated with LV mass/volume ratio (total indexed EAT volume: β=0.002, p=0.02, low attenuation indexed EAT volume: β=0.004, p=0.01) and LV GLS (total indexed EAT volume: β=−0.02, p<0.01, low attenuation indexed EAT volume: β=−0.04, p=0.02) in subjects with T2D, but not indices of diastolic dysfunction.

Conclusion

Total and low attenuation EAT volumes are higher in individuals with T2D, and excess EAT accumulation is independently associated with early markers of cardiac dysfunction. Further studies into the underlying mechanisms of this interaction may facilitate the development of interventions targeted at EAT, which could mitigate against the development of heart failure in people with T2D.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): United Kingdom National Institute for Health Research

Phytogenic silver nanoparticles from tissue-cultured Kaempferia angustifolia - an underutilized medicinal herb: a comparative antibacterial study on urinary pathogens

Background

Ethnomedicinally important Kaempferia angustifolia is a rhizomatous aromatic herb belonging to the family Zingiberaceae. The present manuscript deals with the green synthesis of silver nanoparticles through a rapid reduction process mediated by the rhizome extract of tissue culture-raised plants. The present study was conducted to evaluate the antimicrobial activity of the bio-nanoparticles, and the plant extracts themselves against seven multidrug-resistant urinary tract infecting (MDR-UTI) pathogens.

Result

The ethanolic extracts of the rhizomes of the plant executed a very rapid synthesis of silver bio-nanoparticles, and the generation of the nanoparticles was confirmed through UV-vis spectrophotometry, dynamic light scattering (DLS), and electron dispersion spectroscopic (EDS) analysis. Finally, the precise shapes and dimensions of these nanoparticles were confirmed under the transmission electron microscope (TEM). The shapes of the nanoparticles obtained were diverse in nature and varied from rod, triangular, spherical, to oval shaped, with the size, ranging from 10–60 nm. Silver nanoparticles exhibited a maximum zone of inhibition (ZI) of 16.93 ± 0.04 mm against isolate no. 42332. The ex vitro and in vivo extracts exhibited ZI 14.03 ± 0.04 mm and 11.56 ± 0.04 mm, respectively, against the same strain, which are comparatively lower than the nanoparticles but unignorable.

Conclusion

Although the pathogens used in the present study are resistant to at least three or more types of pharmacologically important antibiotics, nanoparticles, as well as the plant extracts, exhibited significant inhibition to all the seven MDR-UTI pathogens, which confirms that they are highly antimicrobic. Hence, this underutilized medicinal plant extracts of K. angustifolia and the bio-nanoparticles synthesized from these can be explored in pharmaceutical industries to treat multidrug-resistant human pathogenic bacteria. Furthermore, their broad-spectrum activity leads to the opportunity for the synthesis of future generation drugs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43141-022-00414-4.

Muscle Transcriptome Sequencing Revealed Thermal Stress-Responsive Regulatory Genes in Farmed Rohu, Labeo rohita (Hamilton, 1822)

Rohu, Labeo rohita, is one of the most important aquaculture species in the Indian subcontinent. Understanding the molecular-level physiological responses to thermal stress or climate change is essential. In the present work, transcriptome sequencing was carried out in the muscle tissue of the rohu in response to heat stress (35 °C) in comparison with the control (28 °C). A total of 125 Gb of sequence data was generated, and the raw-reads were filtered and trimmed, which resulted in 484 million quality reads. Reference-based assembly of reads was performed using L. rohita genome, and a total of 90.17% of reads were successfully mapped. A total of 37,462 contigs were assembled with an N50 value of 1854. The differential expression analysis revealed a total of 107 differentially expressed genes (DEGs) (15 up-, 37 down-, and 55 neutrally regulated) as compared to the control group (Log2FC > 2, P < 0.05). Gene enrichment analysis of DEGs indicates that transcripts were associated with molecular, biological, and cellular activities. The randomly selected differentially expressed transcripts were validated by RT-qPCR and found consistent expression patterns in line with the RNA-seq data. Several transcripts such as SERPINE1(HSP47), HSP70, HSP90alpha, Rano class II histocompatibility A beta, PGC-1 and ERR-induced regulator, proto-oncogene c-Fos, myozenin2, alpha-crystallin B chain-like protein, angiopoietin-like protein 8, and acetyl-CoA carboxylases have been identified in muscle tissue of rohu that are associated with stress/immunity. This study identified the key biomarker SERPINE1 (HSP47), which showed significant upregulation (~ 2- to threefold) in muscle tissue of rohu exposed to high temperature. This study can pave a path for the identification of stress-responsive biomarkers linked with thermal adaptations in the farmed carps.

Independent predictors of major cardiovascular events as quantitatively assessed by coronary CT-angiography: a long-term follow-up analysis

Introduction

Quantitative CT coronary angiography using semi-automated software provides detailed information about plaque volume and high-risk plaque characteristics, beyond traditional measures like diameter stenosis. We assessed the potential value of plaque quantity and morphology to independently predict MACE in a cohort with long-term follow up.

Methods

In this secondary analysis of 301 symptomatic patients undergoing coronary CTA at baseline, total plaque volume (TPV), non-calcified- (NCPV), calcified- (CPV) and vulnerable coronary plaque volume (in mm3), diameter stenosis (in %) and remodeling index were quantified using semi-automated software (Autoplaque version 2.5, Cedars-Sinai Medical Center, Los Angeles, CA). Patients were followed for major cardiovascular events (MACE), defined as a composite of cardiovascular death, myocardial infarction and coronary revascularization. Optimal thresholds for each quantitative CTA measure were computed using CART-algorithm (Classification and Regression Trees).

Results

Complete follow-up was available for 234 (78%) patients. The mean age was 59±10 years. Over a median follow-up of 10.7 years, the composite outcome occurred in 34 (15%) patients (5 patients with cardiovascular death, 6 with myocardial infarction, 26 with revascularization). Patients experiencing MACE had more frequently hypertension (p=0.03) and a higher Framingham risk score (p=0.002). Survival anaylsis using cox proportional hazard ratios showed significant univariate associations between MACE and TPV (HR 5.16; 95% CI 1.58–16.89; p=0.007), NCPV (HR 4.83; 95% CI 1.45–15.81; p=0.009), CPV (HR 2.86; 95% CI 1.39–5.86; p=0.004), vulnerable plaque volume (HR 3.35; 95% CI 1.52–7.41; p=0.003), diameter stenosis (HR 5.19; 95% CI 2.64–10.22; p&lt;0.001) and remodeling index (HR 4.24; 95% CI 2.03–8.86; p&lt;0.001). In multivariable cox regression analysis diameter stenosis (HR 3.70; 95% CI 1.72–7.93; p=0.001) and remodeling index (HR 2.69; 95% CI 1.19–6.09; p=0.018) remained significant independent predictors of MACE, adjusted for Framingham risk score (HR 2.56; 95% CI 1.26–5.22; p=0.010), however plaque volume and plaque subcomponents did not.

Conclusion

On long term follow-up, remodeling index and coronary diameter stenosis obtained by quantitative coronary CT angiography independently predicted MACE on multivariable assessment. More comprehensive plaque assessment algorithms including plaque volume as well as plaque subcomponents were significantly associated with MACE in univariate, but not multivariate analysis after adjustment for diameter stenosis and remodeling index.

Funding Acknowledgement

Type of funding sources: None.

P6151Fully automated epicardial adipose tissue volume and density measured from non-contrast CT predict major adverse cardiovascular events in asymptomatic subjects

Background

Epicardial adipose tissue (EAT) volume and density has shown to correlate with standard markers of coronary artery disease (CAD) and may predict major adverse cardiovascular events (MACE).

Purpose

We aimed to evaluate the prognostic value of EAT volume and density measured by fully automated deep-learning software from non-contrast cardiac computed tomography (CT).

Methods

We assessed 2071 consecutive asymptomatic subjects (age 56±9 years, 59% male) from the EISNER (Early Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) trial with long-term follow-up after coronary artery calcium (CAC) measurement. EAT volume and mean density were quantified using automated deep-learning software from non-contrast cardiac CT. MACE was defined as myocardial infarction (MI), cardiac death, late (>90 days) revascularization and acute coronary syndrome (ACS). EAT volume and density were systematically compared to CAC score and atherosclerotic cardiovascular disease (ASCVD) risk score using Cox proportional hazards regression for MACE prediction.

Results

At 14±3 years, 217 subjects suffered MACE. In age-and-gender-adjusted multivariate analysis, ASCVD risk score, CAC (two-fold increase) and EAT volume (two-fold increase) were associated with increased risk of suffering MACE [Hazard Ratio (HR) (95% CI): 1.03 (1.01–1.04); 1.25 (1.19–1.30); and 1.36 (1.08–1.70) respectively, p<0.01 for all] (Figure); the corresponding Harrell's C-statistic was 0.76. The area-under-the curve from receiver-operator characteristic analysis for MACE prediction increased significantly from 0.69 to 0.77 (p<0.0001) when EAT volume and CAC were added to the current clinical standard (ASCVD, family history and obesity measures BMI and BSA). Both in men and women, increase in EAT volume was associated with increased risk of MACE, with HR 1.14 (1.06–1.22), p<0.001 in men vs. 1.15 (1.01–1.31), p=0.03 in women, for each 20 cubic centimeter increase in volume. EAT density (HU) was independently inversely associated with MACE [HR: 0.96 (0.93–0.99), p=0.01].

MACE Prediction

Conclusions

EAT volume and density measurements improve prediction of MACE in asymptomatic populations over the current clinical standard. Fully automated EAT volume and density quantification by deep-learning from non-contrast cardiac CT can provide additional prognostic value for the asymptomatic patient.

Acknowledgement/Funding

1R01HL133616, Forschungsstiftung Medizin Universitätsklinikum Erlangen, grant from Dr Miriam and Sheldon G. Adelson Medical Research Foundation

Cardiometabolic predictors of quantitative high-risk plaque features in a diverse patient population

Background/Introduction

Little is known about the prevalence of high-risk plaque features or cardiometabolic predictors in diverse patient populations with underrepresented minorities, in the setting of stable chest pain.

Purpose

The goals of our study are to 1) describe plaque characteristics in a diverse patient population with underrepresented minorities and 2) characterize cardiometabolic risk factors associated with high prevalence of high-risk quantitative low attenuation noncalcified plaque (LDNCP) burden.

Methods

Our study included patients with chest pain undergoing CCTA between June 2016 and October 2021 for stable chest pain, who had a complete cardiometabolic panel including lipoprotein(a) and lipid panel, and at least one blood pressure recording before CCTA. Patients with prior PCI or CABG where excluded. CACS was performed before CCTA as per Agatston method and quantified in Agatston Units (AU). Stenosis was graded as per SCCT guidelines by cardiologists and radiologists with level 3 cardiac CT expertise. Plaque measurements were performed using previously validated semiautomated software (AutoPlaque version 2.5) in all patients with CAD-RADS &gt;0 by expert readers blinded from patients' characteristics. Coronary atherosclerotic plaque volumes were measured. Independent predictors for plaque on CCTA among patients were examined using Wilcox multivariate logistic regression.

Results

A total of 227 consecutive patients were included in our study (see table; age 55.00 [47.50–62.00] years, 63% female, 16% diabetes, 44% hypertension, 40% hyperlipidemia and 32% with current or previous smoking history). Majority of patients were Hispanic (64%) and the rest were Black (27%), White (6%) and Asian (3%).

Patients with LDNCP burden &gt;4% were older (60.00 [52.00–66.50] vs 53.00 [43.75–61.00]; p&lt;0.001), more likely to be diabetic (27.7 vs 11.5%; p=0.005), hypertensive (67.7 vs 33.8%; p&lt;0.001), hyperlipidemic (64.6 vs 29.9%; p&lt;0.001) and present smokers (31.3 vs 13.9%; p=0.003). Almost all patients (63/67) with LDNCP burden &gt;4% had non-obstructive disease (CAD-RADS&lt;4).

Patient with LDNCP burden &gt;4% were more likely to be on statin therapy (46.0 vs 30.4%; p=0.041). There was no differences in ethnicity, hemoglobin A1C, TC, LDL-C, HLD-C, TGs, lipoprotein(a), SBP or DBP.

By logistic regression analysis, age (OR [CI]: 1.06 [1.01–1.08]), hypertension (2.20, [1.06–4.63]) and hyperlipidemia (2.73 [1.37–5.47]) increased the likelihood of LDNCP burden &gt;4%, but not Lipoprotein (a)&gt;175 nmol/L (OR [CI]: 1.07 [0.48–2.31].

Conclusions

In our cohort of patients with high number of unrepresented minorities presenting with stable chest pain, almost all patients (94%) with LDNCP burden &gt;4% had non-obstructive CAD (CAD-RADS&lt;4). There were no differences in prevalence of LDNCP or CAD-RADS among different ethnic groups. Age, hypertension and hyperlipidemia, were the cardiometabolic factors related to LDNCP burden &gt;4%.

Funding Acknowledgement

Type of funding sources: None.

Exercise induced coronary inflammation in masters athletes

Background

Chronic endurance exercise has been linked to increased prevalence of coronary artery disease (CAD) in male master athletes. Data are limited regarding the presence of exercise-induced coronary inflammation and its association with atherosclerosis in master endurance athletes. Human coronary inflammation can be detected non-invasively by imaging pericoronary adipose tissue (PCAT). We tested the hypothesis that chronic endurance exercise leads to increased prevalence of atherosclerosis via coronary inflammation.

Methods

Computed tomography coronary angiogram CTCA scans from 2 cohorts of master athletes and age-matched controls, without known risk factors for CAD, were analysed post-hoc and the PCAT attenuation index was calculated around the proximal right coronary artery (FAIRCA). The athletes and the healthy controls also underwent an electrocardiogram, an echocardiogram, a cardiopulmonary exercise test (CPET), a 24-hour Holter tape and a Cardiac Magnetic Resonance (CMR) scan.

Results

Scans from 243 masters endurance athletes (62% females) and 58 age and Framingham CAD risk score matched healthy controls were analysed. FAIRCA was significantly higher (less negative) in male masters athletes vs female masters athletes [−61.3 Hounsfield Units (HU) vs −62.8 HU, p=0.01], in male athletes vs male controls (−61.3 HU vs −68.6 HU, p&lt;0.001) and in female athletes vs female controls (−62,8 HU vs −67.5 HU, p=0.005). In female masters athletes, peak oxygen consumption during CPET (peak VO2) statistically significantly predicted the FAIRCA, F(1,146) = 22.62, p&lt;0.0001. There was no correlation between the FAIRCA and presence of atherosclerosis in male masters athletes.

Conclusions

Masters athletes show increased markers of coronary inflammation. This effect appears to be greater in male masters athletes and is associated with a higher peak VO2 in female masters athletes. However, we did not identify a link between coronary inflammation and coronary atherosclerosis in this cohort.

Funding Acknowledgement

Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Cardiac Risk in the Young, UK

Machine learning from quantitative coronary computed tomography angiography predicts ischemia and impaired myocardial blood flow

Background

Atherosclerotic plaque characteristics influence the hemodynamic consequences of coronary lesions. This study sought to assess the performance of a machine learning (ML) score integrating coronary computed tomography angiography (CCTA)-based quantitative plaque features for the prediction of ischemia by invasive fractional flow reserve (FFR) and impaired myocardial blood flow (MBF) by [15O]H2O positron emission tomography (PET).

Methods

This post-hoc analysis of the PACIFIC (Prospective Comparison of Cardiac PET/CT, SPECT/CT Perfusion Imaging and CT Coronary Angiography With Invasive Coronary Angiography) trial included 208 patients with suspected coronary artery disease who underwent CCTA, [15O]H2O PET, and 3-vessel invasive FFR. Plaque quantification from CCTA was performed using semiautomated software. A boosted ensemble ML algorithm (XGBoost) trained on data from the NXT (Analysis of Coronary Blood Flow using CT Angiography: Next Steps) trial was used to develop a ML score for the prediction of per-vessel ischemia (invasive FFR ≤0.80). The performance of the ML score was evaluated in 551 vessels from the PACIFIC trial for external validation. Thereafter, we assessed the discriminative ability of the ML score for per-vessel impaired hyperemic MBF (≤2.30 mL/min/g).

Results

In total, 138 (25.0%) vessels had ischemia and 195 (35.4%) vessels had impaired hyperemic MBF. CCTA-derived quantitative percent diameter stenosis and low-density noncalcified plaque (LDNCP) volume were higher in ischemic vessels compared with non-ischemic vessels (60.8% vs. 19.9%; and 42.3 mm3 vs. 9.1 mm3; both p&lt;0.001). The ML score demonstrated a significantly higher area under the receiver-operating characteristic curve (AUC) for predicting ischemia (0.92, 95% confidence interval [CI] 0.89–0.94) compared with visual stenosis grade (0.84, 95% CI 0.80–0.87; p&lt;0.001). Overall, quantitative percent diameter stenosis and LDNCP volume had greatest feature importance for ML, followed by percent area stenosis, minimum luminal diameter, and contrast density drop (Figure 1). An individualized explanation of ML ischemia prediction is shown in Figure 2. When applied for impaired MBF discrimination, the ML score exhibited an AUC of 0.82 (95% CI 0.78–0.85) and was superior to visual stenosis grade (AUC 0.76, 95% CI 0.72–0.80; p=0.03).

Conclusions

An externally validated ML score integrating CCTA-based quantitative plaque features accurately predicts FFR-defined ischemia and abnormal MBF by PET, outperforming standard visual CCTA interpretation.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Heart, Lung, and Blood Institute, United States Performance of the ML scoreIndividual explanation of ML prediction

18F-sodium fluoride positron emission tomography and coronary plaque radiomics derived from computed tomography angiography for prediction of myocardial infarction

Background

Assessments of coronary disease activity with 18F-sodium fluoride positron emission tomography (18F-NaF PET) and radiomics-based precision coronary plaque phenotyping derived from contrast-enhanced computed tomography (CT) have both been shown to enhance risk stratification in patients with coronary artery disease (CAD). To date, no study has investigated whether these two promising methods (which can be obtained during a single imaging session on a hybrid PET/CT scanner) are interchangeable or can provide superior predictive performance when used in combination.

Purpose

We sought to investigate whether the prognostic information provided by latent morphological radiomic coronary plaque features and assessments of disease activity by 18F-NaF PET are complementary in prediction of myocardial infarction.

Methods

Patients with known CAD underwent coronary 18F-NaF PET and CT angiography on a hybrid PET/CT scanner. Coronary 18F-NaF uptake was determined by the coronary microcalcification activity (CMA). We performed quantitative plaque analysis of coronary CT angiography datasets. Additionally, coronary plaque segmentations on CT angiography were used to extract 1103 radiomic features. Using weighted correlation network analysis we derived latent morphological features of coronary plaques which were aggregated to patient-level radiomic normograms to predict myocardial infarction using univariate and multivariate Cox proportional hazard models.

Results

The study cohort comprised of 260 patients with established CAD (age: 65±9 years; 84% men); 179 (69%) participants showed increased coronary 18F-NaF activity (CMA &gt;0). Over 53 [40–59] months of follow-up 18 patients had a myocardial infarction. Using weighted correlation network analysis, from the 1103 radiomic features we derived 15 distinct eigen radiomic features representing latent morphological coronary plaque patterns. On univariate cox modelling 7 of these emerged as predictors of myocardial infarction (Figure). Following adjustments for calcified, noncalcified and low-density noncalcified plaque volumes and 18F-NaF CMA 4 radiomic features (related to texture and geometry) remained independent predictors of myocardial infarction (Figure).

Conclusion(s)

In patients with established CAD latent morphological features of coronary plaques are predictors of myocardial infarction above and beyond plaque volumes and 18F-NaF uptake. Comprehensive plaque analysis with radiomics may enhance risk stratification of CAD patients.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): NIH, Wellcome Trust

DNA Methylation Profiling of Ovarian Tissue of Climbing Perch (Anabas testudienus) in Response to Monocrotophos Exposure

Epigenetic modifications like DNA methylation can alter an organism's phenotype without changing its DNA sequence. Exposure to environmental toxicants has the potential to change the resilience of aquatic species. However, little information is available on the dynamics of DNA methylation in fish gonadal tissues in response to organophosphates. In the present work, reduced-representation bisulfite sequencing was performed to identify DNA methylation patterns in the ovarian tissues of Anabas testudienus exposed to organophosphates, specifically monocrotophos (MCP). Through sequencing, an average of 41,087 methylated cytosine sites were identified and distributed in different parts of genes, i.e., in transcription start sites (TSS), promoters, exons, etc. A total of 1058 and 1329 differentially methylated regions (DMRs) were detected as hyper-methylated and hypo-methylated in ovarian tissues, respectively. Utilizing whole-genome data of the climbing perch, the DMRs, and their associated overlapping genes revealed a total of 22 genes within exons, 45 genes at transcription start sites (TSS), and 218 genes in intergenic regions. Through gene ontology analysis, a total of 16 GO terms particularly involved in ovarian follicular development, response to oxidative stress, oocyte maturation, and multicellular organismal response to stress associated with reproductive biology were identified. After functional enrichment analysis, relevant DMGs such as steroid hormone biosynthesis (Cyp19a, 11-beta-HSD, 17-beta-HSD), hormone receptors (ar, esrrga), steroid metabolism (StAR), progesterone-mediated oocyte maturation (igf1ar, pgr), associated with ovarian development in climbing perch showed significant differential methylation patterns. The differentially methylated genes (DMGs) were subjected to analysis using real-time PCR, which demonstrated altered gene expression levels. This study revealed a molecular-level alteration in genes associated with ovarian development in response to chemical exposure. This work provides evidence for understanding the relationship between DNA methylation and gene regulation in response to chemicals that affect the reproductive fitness of aquatic animals.

Secondary metabolite fingerprinting, anti-pathogenic activity, elite chemotype selection and conservation of Curcuma caesia- an ethnomedicinally underutilized species

Curcuma caesia Roxb. is an ethnomedicinally important, essential oil (EO) yielding aromatic plant. A total of twelve accessions of this plant rhizome were collected from six different agro-climatic zones of West Bengal, India and evaluated for their antimicrobial activities against eight disease-causing, multi-drug-resistant pathogenic strains of urinary-tract infection and respiratory-tract infection. The EO and extracts demonstrated antibacterial activity, with the highest inhibition zone of 18.00 ± 0.08 and 17.50 ± 0.14 mm against Klebsiella pneumoniae by accession 06, even where all the broad-spectrum antibiotics failed to respond. In this study, we employed high-performance thin-layer chromatography (HPTLC) to quantify curcumin, the primary secondary metabolite of C. caesia, and the highest 0.228 mg/gm of curcumin resulted from accession 06. Hence, on the basis of all aspects, accession 06 was identified as the elite chemotype among all twelve accessions. The chemical profiling of EO from accession 06 was done using gas chromatography-mass spectroscopy (GC-MS). Conceivably, about 13 medicinally significant compounds were detected. As this plant species is seasonal and has difficulties in conventional breeding due to dormancy, it must be conserved through in vitro tissue culture for a steady supply throughout the year in massive amounts for agricultural demand. A maximum number of 19.28 ± 0.37 shoots has been obtained in MS medium fortified with 6-Benzylaminopurine, Kinetin, and Naphthalene acetic acid. The genetic uniformity of the plants has been studied through Start Codon Targeted Polymorphism. Therefore, this study must help meet the need for essential phytoactive compounds through a simple, validated, and reproducible plant tissue culture protocol throughout the year.