Differences in Inflammatory Pathways Between Dutch South Asians vs Dutch Europids With Type 2 Diabetes

Maaike E. Straat; Borja Martinez-Tellez; Huub J. van Eyk; Maurice B. Bizino; Suzanne van Veen; Eleonora Vianello; Rinke Stienstra; Tom H. M. Ottenhoff; Hildo J. Lamb; Johannes W. A. Smit; Ingrid M. Jazet; Patrick C. N. Rensen; Mariëtte R. Boon

Disclosures

J Clin Endocrinol Metab. 2023;108(4):931-940.

Abstract and Introduction

Abstract

Context: South Asian individuals are more prone to develop type 2 diabetes (T2D) coinciding with earlier complications than Europids. While inflammation plays a central role in the development and progression of T2D, this factor is still underexplored in South Asians.

Objective: This work aimed to study whether circulating messenger RNA (mRNA) transcripts of immune genes are different between South Asian compared with Europid patients with T2D.

Methods: A secondary analysis was conducted of 2 randomized controlled trials of Dutch South Asian (n = 45; age: 55 ± 10 years, body mass index [BMI]: 29 ± 4 kg/m²) and Dutch Europid (n = 44; age: 60 ± 7 years, BMI: 32 ± 4 kg/m²) patients with T2D. Main outcome measures included mRNA transcripts of 182 immune genes (microfluidic quantitative polymerase chain reaction; Fluidigm Inc) in fasted whole-blood, ingenuity pathway analyses (Qiagen).

Results: South Asians, compared to Europids, had higher mRNA levels of B-cell markers (CD19, CD79A, CD79B, CR2, CXCR5, IGHD, MS4A1, PAX5; all fold change > 1.3, false discovery rate [FDR] < 0.008) and interferon (IFN)-signaling genes (CD274, GBP1, GBP2, GBP5, FCGR1A/B/CP, IFI16, IFIT3, IFITM1, IFITM3, TAP1; all FC > 1.2, FDR < 0.05). In South Asians, the IFN signaling pathway was the top canonical pathway (z score 2.6; P < .001) and this was accompanied by higher plasma IFN-γ levels (FC = 1.5, FDR = 0.01). Notably, the ethnic difference in gene expression was larger for women (20/182 [11%]) than men (2/182 [1%]).

Conclusion: South Asian patients with T2D show a more activated IFN-signaling pathway compared to Europid patients with T2D, which is more pronounced in women than men. We speculate that a more activated IFN-signaling pathway may contribute to the more rapid progression of T2D in South Asian compared with Europid individuals.

Introduction

South Asian individuals, originating from the Indian subcontinent and encompassing 20% of the world population, are at particularly high risk of developing type 2 diabetes (T2D). In high-income countries such as the Netherlands, South Asian people have a 2- to 4-times higher risk of developing T2D compared to people of European origin, in the manuscript further called "Europid".^[1] Notably, at the moment of diagnosis, a high proportion of South Asian patients with T2D have a lower body mass index (BMI) and are at a younger age as compared to Europids. Additionally, in South Asians microvascular and macrovascular complications of T2D evolve within a shorter duration after start of the disease.^[2,3] Several factors have been proposed to underlie the increased susceptibility of South Asians to develop T2D compared to Europids, such as genetic predisposition, differences in lifestyle, central adiposity, low lean mass, low brown adipose tissue volume, and insulin resistance.^[4,5] However, the high rate of T2D in South Asian individuals cannot be fully explained by these factors alone.

Over the last decades, inflammation has been increasingly acknowledged to play an important role in the pathogenesis of T2D, at least partly by accelerating insulin resistance.^[6–8] Accordingly, clinical studies have shown that anti-inflammatory treatments, such as the interleukin-1-receptor antagonist Anakinra and the anti-inflammatory compound salsalate, improve glycemic control in patients with T2D.^[9–12] Although anti-inflammatory therapy is thus regarded as a promising strategy to improve T2D regulation, these studies have so far been conducted only in patients of Europid origin. Interestingly, previous studies support the presence of a more proinflammatory phenotype in South Asians compared with Europids. Concentrations of the nonspecific inflammatory marker C-reactive protein are higher in healthy middle-aged South Asian compared with Europid men and women.^[13,14] Furthermore, interleukin-6 levels are higher in healthy young South Asian men^[15] and healthy middle-aged South Asian women than in matched Europids.^[16] These data thus support a possible pathophysiological role for inflammation in explaining the increased risk of the South Asian population to develop T2D. However, which aspects of the immune system may be differentially regulated in South Asians with T2D is currently unknown.

To further pinpoint such a role and to elucidate the possible clinical benefit of anti-inflammatory therapy to reduce T2D burden in the South Asian population, a detailed overview of the inflammatory state of South Asian patients with T2D is urgently needed. Therefore, the aim of this study was to investigate whether circulating messenger RNA (mRNA) transcripts of a broad range of immune related genes (using an untargeted approach by measuring, eg, markers of T cells, B cells, natural killer cells, and interleukins) are different between patients with T2D from Dutch South Asian vs Dutch Europid descent.

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Abstract and Introduction
Materials and Methods
Results
Discussion
References

Table 1. Baseline characteristics
	Dutch Europid (n = 44)	Dutch South Asian (n = 45)
Demographics
Women, n, %	19, 43%	27, 60%
Age, y	59.6 ± 6.5	54.6 ± 10.3^a
Diabetes duration, y	10.7 ± 6.4	17.4 ± 9.9^b
Clinical parameters
Weight, kg	97.0 ± 14.0	79.6 ± 11.9^c
Length, cm	173.2 ± 8.9	165.6 ± 8.8^c
BMI	32.3 ± 4.0	29.4 ± 4.0^b
Waist-height ratio	0.64 ± 0.06	0.61 ± 0.06^a
Body fat, %	37.1 ± 9.4	37.1 ± 9.2
VAT/SAT ratio	0.6 ± 0.3	0.6 ± 0.3
HbA_1c, mmol/mol	66.1 ± 11.0	67.7 ± 11.5
HbA_1c, %	8.2 ± 1.0	8.3 ± 1.1
Total cholesterol, mmol/L	4.8 ± 1.0	4.2 ± 1.0^b
HDL-C, mmol/L	1.2 ± 0.3	1.2 ± 0.3
LDL-C, mmol/L	2.6 ± 0.9	2.1 ± 0.8^b
CRP, mmol/L	3.1 ± 3.3	3.6 ± 4.1
Diabetic complications/comorbidity
Diabetic retinopathy, n, %	4, 9%	23, 51%^c
Diabetic nephropathy, n, %	11, 25%	10, 22%
Diabetic neuropathy, n, %	15, 34%	12, 27%
Macrovascular disease, n, %	2, 5%	12, 27%^b
Concomitant medication use
Metformin, mg/d	2047 ± 569	1750 ± 659^a
Sulfonylurea, n, %	13, 30%	8, 18%
Insulin, n, %	28, 64%	34, 76%
Statin, n, %	36, 82%	34, 76%
Antihypertensive drug, n, %	34, 77%	32, 71%

Data are presented as mean ± SD unless specified otherwise. Specifically, in the section of diabetic complications/comorbidities, data are presented as the number of patients who reported to have these complications and the percentage of all. P values indicate differences between Dutch Europid vs Dutch South Asian patients.
Abbreviations: BMI, body mass index; CRP, C-reactive protein, HbA_1c, glycated hemoglobin A_1c; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; SAT, subcutaneous adipose tissue; VAT, visceral adipose tissue.
^a P less than .05.
^b P less than .01.
^c P less than .001.

Table 2. Associations between baseline characteristics and messenger RNA levels of B-cell markers, interferon-signaling genes, and interferon-γ protein levels
					Males										Females
	Dutch Europid							Dutch South Asian							Dutch Europid								Dutch South Asian
	Age	DD	BMI	Body fat %	Waist- height ratio	HbA_1c	Metf. dose	Age	DD	BMI	Body fat %	Waist- height ratio	HbA_1c	Metf. dose	Age	DD	BMI	Body fat %	Waist- height ratio	HbA_1c	Metf. dose	Age	DD	BMI	Body fat %	Waist- height ratio	HbA_1c	Metf. dose
B-cell markers
CD19	−0.14	0.39	−0.03	−0.21	0.07	0.18	0.13	−0.12	0.17	0.12	−0.04	0.10	−0.14	0.17	−0.10	0.27	0.13	0.10	0.19	−0.41	0.11	−0.08	−0.01	0.16	0.11	0.20	−0.25	0.47 ^a
MS4A1 (CD20)	−0.12	0.23	0.20	−0.12	0.21	0.03	−0.09	−0.22	−0.03	0.25	0.18	0.14	0.00	0.06	0.13	−0.27	0.30	0.37	0.43	−0.31	0.05	−0.09	−0.05	0.04	−0.06	0.10	−0.26	0.34
CR2 (CD21)	−0.35	0.17	0.01	−0.17	−0.02	0.26	−0.05	−0.13	−0.25	0.19	0.19	0.19	0.05	−0.16	−0.58**	0.17	0.59**	0.22	0.38	0.13	−0.15	−0.26	−0.15	0.15	0.01	0.16	−0.19	0.33
CD79A	−0.24	0.24	0.07	−0.21	0.11	0.17	−0.02	−0.12	0.02	0.16	0.12	−0.22	−0.17	0.49	0.12	0.24	0.33	0.28	0.30	−0.52 ^a	0.15	−0.11	−0.06	0.11	0.04	0.16	−0.21	0.43
CD79B	−0.14	0.28	−0.01	−0.20	0.06	0.11	0.00	−0.07	0.26	−0.23	−0.21	−0.07	−0.09	0.25 ^a	−0.02	0.24	0.19	0.03	0.42	−0.44	0.01	−0.09	0.00	0.17	0.11	0.21	−0.11	0.41 ^a
CXCR5	−0.19	0.33	0.01	−0.15	0.06	0.08	0.04	−0.07	0.15	−0.01	−0.19	0.22	−0.23	−0.09	−0.15	0.17	0.33	0.25	0.24	−0.35	0.05	−0.24	−0.09	0.27	0.15	0.09	−0.21	0.37 ^a
IGHD	−0.39	0.24	0.15	−0.18	0.09	0.04	−0.05	0.11	0.18	0.12	−0.06	0.21	−0.01	0.09	−0.05	−0.02	0.34	0.25	0.50 ^a	−0.41	0.01	−0.19	−0.09	0.28	0.17	0.18	−0.21	0.37
PAX5	−0.23	0.24	0.12	−0.15	0.12	0.14	−0.03	0.04	0.25	0.29	0.24	0.36	0	0.19	−0.09	−0.12	0.4	0.37	0.33	−0.32	0.07	−0.1	0.01	0.07	−0.03	0.14	−0.24	0.34
IFN-signaling genes + IFN-γ
CD274	0.21	0.25	0.07	0.08	0.20	0.12	0.28	−0.06	0.25	0.30	0.09	0.27	0.23	−0.40	0.10	−0.08	−0.23	−0.18	−0.18	0.02	0.07	−0.10	0.08	0.49 ^b	0.39 ^a	0.32	−0.20	0.15
GBP1	0.13	0.10	0.09	−0.05	0.03	0.02	0.24	−0.13	−0.07	−0.02	0.02	0.01	0.03	−0.16	0.21	−0.08	−0.07	−0.14	0.15	0.11	0.37	0.01	0.26	0.24	0.03	0.33	−0.23	0.25
GBP2	−0.14	−0.16	0.34	0.15	0.30	−0.10	0.03	−0.21	−0.45	0.22	0.14	0.14	−0.05	−0.38	0.13	−0.06	0.03	−0.03	0.26	−0.10	0.01	0.04	0.11	0.25	0.13	0.33	−0.27	0.31
GBP5	0.20	0.20	0.11	−0.15	0.06	0.09	0.14	−0.14	−0.13	0.19	0.19	0.17	−0.16	−0.18	0.25	−0.08	−0.18	−0.16	−0.03	0.06	0.19	0.11	0.29	0.30	0.24	0.48 ^a	−0.27	0.19
FCGR1A/B/CP	0.03	−0.09	−0.11	−0.04	0.08	−0.13	0.17	−0.04	0.06	0.24	0.20	0.24	0.07	−0.13	−0.22	−0.02	0.18	0.12	0.30	0.00	0.33	−0.25	−0.20	0.49 ^b	0.48 ^a	0.35	−0.07	0.15
IFI16	−0.06	0.13	−0.01	−0.05	0.15	−0.24	0.28	−0.45	−0.29	0.31	0.06	0.13	−0.17	−0.28	0.08	0.05	0.05	−0.29	0.24	0.11	0.29	−0.31	−0.17	0.23	0.13	0.16	−0.19	0.16
IFIT3	0.14	0.04	0.03	0.00	0.05	−0.30	0.15	0.26	0.11	0.28	0.44	0.42	0.04	−0.18	0.29	−0.03	0.16	−0.12	0.31	−0.06	0.16	−0.35	−0.15	0.27	0.00	0.19	−0.21	0.09
IFITM1	0.01	−0.01	−0.25	−0.24	−0.09	−0.22	−0.05	−0.30	−0.12	−0.07	0.10	−0.12	0.18	0.01	−0.19	−0.03	−0.01	−0.22	0.08	−0.09	0.26	−0.20	−0.07	0.16	0.12	−0.02	−0.32	0.37
IFITM3	0.06	−0.01	−0.39	−0.25	−0.24	−0.34	0.11	0.11	0.05	0.53 ^a	0.53 ^a	0.58 ^a	0.26	−0.15	0.13	−0.23	0.35	0.23	0.54 ^a	−0.28	0.16	−0.21	−0.12	−0.09	−0.20	−0.31	−0.13	0.21
TAP1	−0.06	−0.01	0.23	0.17	0.25	−0.26	0.11	−0.18	−0.47 ^a	0.15	0.09	−0.04	−0.45	−0.19	−0.04	−0.53 ^a	0.21	0.27	0.18	−0.11	−0.11	0.01	0.04	0.10	−0.01	0.18	−0.25	0.16
IFN-γ (protein)	0.52**	0.02	−0.24	−0.20	−0.27	0.00	0.18	0.01	0.16	0.20	0.29	0.26	0.21	0.03	0.08	−0.13	−0.10	−0.08	−0.15	−0.07	0.20	−0.08	0.07	0.32	0.29	0.38	−0.38	0.15

Values indicate Pearson r. Correlations that were statistically significant before correction using the Benjamini-Hochberg false discovery rate procedure are highlighted in bold (P < .05). None of the correlations remained significant after correction.
Abbreviations: BMI, body mass index; DD, diabetes duration; HbA_1c, glycated hemoglobin A_1c; IFN, interferon; Metf., metformin.
^a P less than .05.
^b P less than .01.

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Differences in Inflammatory Pathways Between Dutch South Asians vs Dutch Europids With Type 2 Diabetes

Abstract and Introduction

Abstract

Introduction

Tables

Tables

References

Authors and Disclosures

Authors and Disclosures

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