Fakhoury et al. 2022 Gene Expression Profiling of PBMCs in Type 2 Diabetes

Fakhoury et al. used qRT-PCR to profile PBMC mRNA expression of macrophage phenotypic markers, cholesterol efflux proteins, scavenger receptors, and adenosine receptors across four groups of Saudi adults, finding a metabolically activated macrophage (MMe)-like phenotype in T2D PBMCs that differs from classical M1/M2 patterns and is modulated by metformin.

Citation

• Full citation: Fakhoury HMA, Elahi MA, Al Sarheed S, Al Dubayee M, Alshahrani A, Zhra M, Almassri A, Aljada A. Gene Expression Profiling of Peripheral Blood Mononuclear Cells in Type 2 Diabetes: An Exploratory Study. Medicina. 2022;58(12):1829. ¹
• DOI: 10.3390/medicina58121829. ¹
• Publication date: 2022-12-12. ¹
• Study type: cross-sectional exploratory study. ¹
• URL: https://www.mdpi.com/1648-9144/58/12/1829

Research Question

The study examined the relative expression of macrophage phenotypic surface markers, cholesterol efflux proteins, scavenger receptors, and adenosine receptors in PBMCs from T2D patients, with the aim of phenotypically characterizing circulating PBMCs and identifying biomarkers for the metabolically activated macrophage (MMe) phenotype. ¹

Cohort And Ancestry

• The study enrolled 110 Saudi adults from King Abdulaziz Medical City in Riyadh, Saudi Arabia, in four groups: 30 normal-weight non-diabetic (BMI 23.0±0.3), 30 obese non-diabetic (BMI 39.1±1.7), 20 newly diagnosed T2DM (BMI 32.5±1.9), and 30 T2DM on metformin (BMI 40.5±1.5, 9 months–15 years duration). ¹
• The T2D and T2D-on-metformin groups were significantly older than the non-diabetic groups; age did not significantly correlate with any mRNA expression marker. Gender distribution differed significantly across groups but was not significantly associated with biomarker expression. ¹
• The paper does not report genetic ancestry inference — the cohort is single-ancestry (Saudi Arabian), which limits generalizability but is useful as a non-European T2D PBMC dataset. ²

PBMC Assay

• PBMCs were isolated from 10 mL EDTA blood by Ficoll–Hypaque density gradient centrifugation. ¹
• Total RNA was DNase-treated and quality-checked on an Agilent Bioanalyzer 2100. cDNA was synthesized from 1 µg RNA using a first-strand synthesis kit. ¹
• qRT-PCR was performed on a 7900HT Fast Real-Time PCR System using SYBR Green with gene-specific primers for IL-12 (IL12RB2), CXCL10, CCL17, CCR7, ABCA1, ABCG1, CYP27A (sterol 27-hydroxylase), SR-A1, LOX-1, CXCL16, A2AR, and A3R. ¹
• Normalization was to Cyclophilin A using the 2^−∆∆CT method; Ubiquitin C and RPL13 showed similar trends. ¹
• Statistical analysis used one-way ANOVA on ranks (Kolmogorov–Smirnov normality test failed) with Dunn’s test for pairwise comparisons; Spearman’s rank correlation for age-biomarker associations. ¹

Findings Relevant To The Paper

Macrophage Phenotypic Markers

• IL-12 expression was significantly higher in the T2DM group vs. lean and obese groups (p<0.05); metformin significantly lowered it. ¹
• CCR7 expression was significantly higher in T2DM vs. both non-diabetic groups (p<0.05); metformin had no significant effect. ¹
• CXCL10 and CCL17 mRNA expression were significantly lower in T2DM vs. both non-diabetic groups (p<0.05); metformin conferred no significant change. ¹
• The increased IL-12 + CCR7 with decreased CXCL10 + CCL17 pattern diverges from pure M1 or M2 classifications — the authors interpret this as an MMe-like circulating phenotype. ²

Cholesterol Efflux Proteins

• ABCA1 expression was significantly higher in T2DM vs. non-diabetic groups (p<0.05); not altered by metformin. ¹
• ABCG1 expression was significantly lower in T2DM vs. disease-free groups (p<0.05). ¹
• Sterol 27-hydroxylase (CYP27A) expression was significantly lower in T2DM vs. non-diabetic groups (p<0.05); metformin significantly increased it. ¹
• The ABCA1-high/ABCG1-low/CYP27A-low pattern in T2DM PBMCs is consistent with disrupted cholesterol efflux in the circulation. ²

Scavenger Receptors

• SR-A1 expression was significantly higher in T2DM vs. disease-free groups (p<0.05); metformin showed a non-significant reduction. ¹
• LOX-1 was not significantly lower in T2DM vs. disease-free groups, but metformin significantly increased it (p<0.05), contradicting the M1-associated LOX-1 increase reported in THP-1 cells. ¹
• CXCL16 was not significantly higher in T2DM, but metformin significantly increased it (p<0.05). ¹
• Metformin’s increase of CXCL16 and LOX-1 is interpreted as an athero-protective effect. ²

Adenosine Receptors

• A2AR and A3R expression were significantly lower in T2DM vs. disease-free groups (p<0.05). ¹
• Metformin significantly increased A2AR expression (p<0.05) but not A3R. ¹
• The authors propose that NF-κB pathway activation in T2DM could be mediated by A2AR and A3R inhibition, as adenosine receptors normally suppress NF-κB signaling. ¹
• Metformin’s upregulation of both A2AR and CYP27A is interpreted as enhancing cholesterol efflux through the adenosine receptor pathway. ²

Ancestry-Relevant Interpretation

• Fakhoury et al. provides qRT-PCR-based PBMC gene expression data from a Saudi Arabian cohort, adding a non-European, non-East-Asian data point to the T2D PBMC literature. ²
• The source does not test ancestry-associated PBMC differences — it is a single-cohort design without ancestry stratification. Its value for the paper is as a Middle Eastern T2D PBMC reference for MMe marker expression patterns. ²
• The metformin-modulation findings may be useful for discussing medication effects in ancestry-aware PBMC analyses. ²

Limitations

• The study uses bulk PBMCs rather than isolated monocytes, introducing cell-heterogeneity confounds — purified monocytes could be a better model, but purification itself can activate monocytes. ¹
• The study measures mRNA only — protein-level validation using tandem mass spectrometry is needed. ¹
• The T2D and metformin groups were significantly older than the non-diabetic groups, though age-biomarker correlations were non-significant. ¹
• A relatively small sample size (n=20–30 per group) limits statistical power for subgroup analyses. ²

Links

• T2D PBMC MMe-like Phenotype
• T2D PBMC Cholesterol Efflux and Scavenger Receptors
• T2D PBMC Adenosine Receptors and Metformin
• PBMC Immune Changes in Type 2 Diabetes
• Paper Evidence Map: T2D PBMC Ancestry

Sources

• _raw/Fakhoury2022_gene.pdf

Footnotes

1. extracted; from Fakhoury et al. 2022 ↩ ↩² ↩³ ↩⁴ ↩⁵ ↩⁶ ↩⁷ ↩⁸ ↩⁹ ↩¹⁰ ↩¹¹ ↩¹² ↩¹³ ↩¹⁴ ↩¹⁵ ↩¹⁶ ↩¹⁷ ↩¹⁸ ↩¹⁹ ↩²⁰ ↩²¹ ↩²² ↩²³ ↩²⁴ ↩²⁵ ↩²⁶ ↩²⁷

2. inferred; the paper does not perform genetic ancestry inference or multi-ancestry comparison ↩ ↩² ↩³ ↩⁴ ↩⁵ ↩⁶ ↩⁷ ↩⁸ ↩⁹