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Enkar Nur

Publications and source records attributed to Enkar Nur.

2 recordsLinked to original sources

Waist-to-height ratio as a practical indicator for screening pediatric metabolic dysfunction-associated steatotic liver disease in diverse populations and genetic backgrounds.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading chronic liver disease in children and adolescents; this parallels the global obesity epidemic. The contribution of genetic susceptibility to pediatric MASLD, and its interaction with anthropometric and biochemical indices used for non-invasive screening remains poorly understood. We aimed to evaluate waist-to-height ratio (WHtR) as a simple, equitable, and scalable tool for early identification of pediatric MASLD and relate this to genetic risk. METHODS: We combined school-based data from 1010 Chinese children with analyses of the Global Burden of Disease, the 1000 Genomes Project, and the US National Health and Nutrition Examination Survey (NHANES). Thirteen MASLD-related single-nucleotide polymorphisms (SNPs) were genotyped to construct a genetic risk score (GRS). We examined global epidemiological patterns, quantified inter-population allele divergence, and assessed how GRS modifies cutoffs and performance of nine anthropometric and biochemical indices. RESULTS: Genetic analysis revealed minimal frequency divergence across most ancestries (mean Fixation index&#x2009;<&#x2009;0.05), except for the African ancestry where there was moderate divergence. Higher GRS were associated with lower cutoffs across indices. When GRS Z-score increased from -3 to 3, visceral adiposity index showed the sharpest changes (Z-score decreased from 1.5 to -1.8), while BFP (1.2&#xa0;to&#xa0;0.1) and WHtR (1.5&#xa0;to&#xa0;0.1) showed gradual change. Furthermore, incorporating GRS into the base anthropometric models yielded only marginal improvements in overall screening performance [area under the receiver operating characteristic curve (AUC) and Youden Index]. Validation in NHANES showed WHtR&#x2009;&#x2265;&#x2009;0.48 retained high discrimination (AUC&#x2009;>&#x2009;0.87) across most genetic variants. CONCLUSIONS: This study suggests that WHtR is a consistent and practical tool for screening pediatric patients with MASLD across diverse populations. While genetic variation may influence optimal thresholds, WHtR&#x2009;&#x2265;&#x2009;0.48 appears broadly applicable, supporting its potential use as a frontline screening metric in diverse settings.

Humans

Plasma inflammatory proteome profiles identify MASLD among children with overweight or obesity.

BACKGROUND & AIMS: Pediatric metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly prevalent among children with overweight or obesity, yet its early diagnosis remains a major clinical challenge. This study aimed to identify circulating inflammatory proteins associated with MASLD and to develop a proteomic risk score (ProScore) to improve diagnostic accuracy. METHODS: In this cross-sectional study of 161 children (median age 8.5&#xa0;years) with overweight or obesity, MASLD was assessed by vibration-controlled transient elastography, with 42 cases identified. Plasma concentrations of 92 inflammation-related proteins were quantified using a high-throughput proximity extension assay. The ProScore was compared with eleven conventional anthropometric/metabolic indices (WHtR, METS-IR, SPISE, PNFI, VAI, LAP, TyG, TyG-ALT, TyG-WC, TyG-WHtR, and TyG-BMI) and a genetic risk score (GRS). Six machine learning algorithms were employed and diagnostic performance was assessed using area under the curve (AUC) with fivefold cross-validation. RESULTS: Fifteen proteins were significantly associated with MASLD. A six-protein panel (FGF-21, CDCP1, CD244, OPG, Flt3L, MCP-1) achieved the highest diagnostic accuracy (AUC&#x2009;=&#x2009;0.84), exceeding that of all conventional indices (AUC&#x2009;=&#x2009;0.65-0.78; all P&#x2009;<&#x2009;0.05). ProScore performance remained robust in school-based validation (AUC&#x2009;=&#x2009;0.83), with no substantial improvement when combined with conventional indices. Diagnostic accuracy was higher in children with lower GRS (AUC&#x2009;=&#x2009;0.92) than in those with higher GRS (AUC&#x2009;=&#x2009;0.80; P&#x2009;=&#x2009;0.003). CONCLUSIONS: A proteomic signature of systemic inflammation provides accurate, non-invasive identification of MASLD in at-risk children, outperforming conventional metabolic and genetic tools, and may have utility in clinical and public health settings.

Humans