Objective: To investigate whether the quantitative insulin sensitivity check index (QUICKI) and the reciprocal index of homeostasis model assessment (1/HOMA-IR) derived from fasting plasma glucose and insulin level are excellent surrogate indices of insulin resistance in both normal range-weight and moderately obese type 2 diabetic and healthy subjects.
Research Design And Methods: The association between QUICKI or 1/HOMA-IR and insulin resistance index assessed by euglycemic-hyperinsulinemic clamp (clamp-IR) was investigated in 121 type 2 diabetic and 29 healthy subjects recruited from among 120 (age 55 +/- 11, 48 +/- 15, and 52 +/- 15 years [means +/- SD], respectively). Type 2 diabetic subjects were divided into groups of 76 normal range-weight and 45 moderately obese subjects (BMI 21.4 +/- 2.3 vs. 27.2 +/- 2.2 kg/m(2), P < 0.0001).
Results: QUICKI and 1/HOMA-IR were significantly lower in the moderately obese group than in the normal range-weight type 2 diabetic and healthy groups (n = 120) (QUICKI, 0.338 +/- 0.030, 0.371 +/- 0.037, and 0.389 +/- 0.041, respectively, P < 0.0001; 1/HOMA-IR, 0.50 +/- 0.33, 0.92 +/- 0.55, and 1.24 +/- 0.82, P < 0.0001). QUICKI was strongly correlated with clamp-IR in normal range-weight, moderately obese type 2 diabetic, and healthy subjects (r = 0.641, 0.570, and 0.502, respectively; all subjects, r = 0.608, P < 0.01) and 1/HOMA-IR exhibited correlations comparable to those of QUICKI with clamp-IR (r = 0.637, 0.530, and 0.461, respectively; all subjects, r = 0.589, P < 0.001). In multiple regression models including QUICKI or 1/HOMA-IR as an independent variable, the estimation formula accounted for 55% of the variability of clamp-IR for the group of all type 2 diabetic subjects (R(2) = 0.547 and 0.551, respectively, P
Conclusions: QUICKI and 1/HOMA-IR were highly correlated with clamp-IR, with comparable coefficients in both normal range-weight and moderately obese type 2 diabetic patients and nondiabetic subjects. The latter can probably be applied clinically in view of its convenience.
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http://dx.doi.org/10.2337/diacare.26.8.2426 | DOI Listing |
Nat Methods
January 2025
Broad Institute of MIT and Harvard, Cambridge, MA, USA.
A key challenge of the modern genomics era is developing empirical data-driven representations of gene function. Here we present the first unbiased morphology-based genome-wide perturbation atlas in human cells, containing three genome-wide genotype-phenotype maps comprising CRISPR-Cas9-based knockouts of >20,000 genes in >30 million cells. Our optical pooled cell profiling platform (PERISCOPE) combines a destainable high-dimensional phenotyping panel (based on Cell Painting) with optical sequencing of molecular barcodes and a scalable open-source analysis pipeline to facilitate massively parallel screening of pooled perturbation libraries.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Endocrinology and Metabolism, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China.
With the rapid advancement of proteomics, numerous scholars have investigated the intricate relationships between plasma proteins and various diseases. Therefore, this study aims to elucidate the relationship between BDH1 and type 2 diabetes using Mendelian randomization (MR) and to identify novel targets for the prevention and treatment of type 2 diabetes through proteomics. This study primarily employed the Mendelian Randomization (MR) method, leveraging genetic data from numerous large-scale, publicly accessible genome-wide association studies (GWAS).
View Article and Find Full Text PDFIntroduction: The most frequent form of diabetes in pediatric patients is polygenic autoimmune diabetes (T1D), but single-gene variants responsible for autoimmune diabetes have also been described. Both disorders share clinical features, which can lead to monogenic forms being misdiagnosed as T1D. However, correct diagnosis is crucial for therapeutic choice, prognosis and genetic counseling.
View Article and Find Full Text PDFBr J Nutr
January 2025
Laboratório de Nutrição e Metabolismo, Faculdade de Nutrição, Universidade Federal de Alagoas, Maceió, Brazil.
To determine the prevalence of FA in individuals with type 2 diabetes and to assess the association between FA and type 2 diabetes. MEDLINE, EMBASE, Web of Sciences, Latin American and Caribbean Literature in Health Sciences, ScienceDirect, Scopus, and PsycINFO were searched until November 2024. This study was registered with PROSPERO (CRD42023465903).
View Article and Find Full Text PDFSLAS Discov
January 2025
Bonds Biosystems, 27 Strathmore Rd, Natick, MA, USA. Electronic address:
Obesity and type 2 diabetes (T2D) are strongly linked to abnormal adipocyte metabolism and adipose tissue (AT) dysfunction. However, existing adipose tissue models have limitations, particularly in the stable culture of fat cells that maintain physiologically relevant phenotypes, hindering a deeper understanding of adipocyte biology and the molecular mechanisms behind differentiation. Current model systems fail to fully replicate in vivo metabolism, posing challenges in adipose research.
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