Galectin-1 in Obesity and Type 2 Diabetes

Galectin-1 is a carbohydrate-binding protein expressed in many tissues. In recent years, increasing evidence has emerged for the role of galectin-1 in obesity, insulin resistance and type 2 diabetes. Galectin-1 has been highly conserved through evolution and is involved in key cellular functions such as tissue maturation and homeostasis. It has been shown that galectin-1 increases in obesity, both in the circulation and in the adipose tissue of human and animal models. Several proteomic studies have independently identified an increased galectin-1 expression in the adipose tissue in obesity and in insulin resistance. Large population-based cohorts have demonstrated associations for circulating galectin-1 and markers of insulin resistance and incident type 2 diabetes. Furthermore, galectin-1 is associated with key metabolic pathways including glucose and lipid metabolism, as well as insulin signalling and inflammation. Intervention studies in animal models alter animal weight and metabolic profile. Several studies have also linked galectin-1 to the progression of complications in diabetes, including kidney disease and retinopathy. Here, we review the current knowledge on the clinical potential of galectin-1 in obesity and type 2 diabetes

Gene expression levels of PAI-1 in A. platelets compared with reference genes and B. in subcutaneous adipose tissue compared with reference genes.

There were no significant differences in gene expression levels of PAI-1 in platelets between participants with T2D, obese and lean control subjects (T2D n = 6, obese n = 7 and lean control subjects n = 7)(A.). There was a significant difference in gene expression levels of PAI-1 in subcutaneous adipose tissue between lean control subjects and T2D or obese non-diabetic control subjects (T2D n = 7, obese n = 6 and lean control subjects n = 6) * P = 0.003, ** P = 0.038 (B.). Abb. PAI-1: Plasminogen Activator Inhibitor -1; T2D: type 2 diabetes.</p

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Cardiorespiratory fitness and the association with galectin-1 in middle-aged individuals.

Galectin-1 plays a functional role in human metabolism and the levels are altered in obesity and type 2 diabetes (T2D). This study investigates the association of cardiorespiratory fitness (CRF) with galectin-1 and the interconnection with body fatness. Cross-sectional data from the Swedish CArdioPulmonary bioImage Study (SCAPIS) pilot was analyzed, including a sample of 774 middle-aged individuals. A submaximal cycle ergometer test was used to estimate CRF as an indirect measure of the physical activity (PA) level. Serum-galectin-1 concentration was determined from venous blood collected after an overnight fast. Body mass index (BMI) was used as an indirect measure of body fatness. CRF was significantly associated with galectin-1, when controlled for age and sex (regression coefficient (regr coeff) = -0.29, p&lt;0.001). The strength of the association was attenuated when BMI was added to the regression model (regr coeff = -0.09, p = 0.07), while the association between BMI and galectin-1 remained strong (regr coeff = 0.40, p&lt;0.001). CRF was associated with BMI (regr coeff = -0.50, p&lt;0.001). The indirect association between CRF and galectin-1 through BMI (-0.50 x 0.40) contributed to 69% of total association (mediation analysis). In group comparisons, individuals with low CRF-high BMI had the highest mean galectin-1 level (25 ng/ml), while individuals with high CRF-low BMI had the lowest level (21 ng/ml). Intermediate levels of galectin-1 were found in the low CRF-low BMI and high CRF-high BMI groups (both 22 ng/ml). The galectin-1 level in the low CRF-high BMI group was significantly different from the other three groups (P&lt;0.001). In conclusion, galectin-1 is associated with CRF as an indirect measure of the PA level through interconnection with body fatness. The size of the association is of clinical relevance

Gene expression of PAI-1 in subcutaneous adipose tissue of lean, obese and T2D normalized against LRP10.

ANOVA with Bonferroni’s multiple comparisons test. N = 6 for all groups. Abb. PAI-1: Plasminogen Activator Inhibitor -1; T2D: type 2 diabetes.</p

Pool of PAI-1 in A. plasma, B. serum and C. platelets in T2D patients, lean and control participants.

There was a significant increase of plasma PAI-1 in participants with T2D and obese non-diabetic control subjects compared with lean control subjects (T2D n = 6, obese n = 7 and lean control subjects n = 8). * P˂0.001, ** P˂0.001. B. No significant difference in serum PAI-1 between the three groups (T2D n = 6, obese n = 7 and lean control subjects n = 8). C. There was no significant difference in platelet PAI-1 between the three groups (T2D n = 4, obese n = 5 and lean control subjects n = 8). Abb. PAI-1 = plasminogen activator inhibitor -1; T2D = type 2 diabetes.</p

Primers and probes for qPCR.

Primers and probes for qPCR.</p

Platelets in T2D patients compared with obese and lean control subjects.

Platelets in T2D patients compared with obese and lean control subjects.</p

The role of circulating galectin-1 in type 2 diabetes and chronic kidney disease : evidence from cross-sectional, longitudinal and Mendelian randomisation analyses

Aims/hypothesis: Galectin-1 modulates inflammation and angiogenesis, and cross-sectional studies indicate that galectin-1 may be a uniting factor between obesity, type 2 diabetes and kidney function. We examined whether circulating galectin-1 can predict incidence of chronic kidney disease (CKD) and type 2 diabetes in a middle-aged population, and if Mendelian randomisation (MR) can provide evidence for causal direction of effects. Methods: Participants (n = 4022; 58.6% women) in the Malmö Diet and Cancer Study–Cardiovascular Cohort enrolled between 1991 and 1994 (mean age 57.6 years) were examined. eGFR was calculated at baseline and after a mean follow-up of 16.6 ± 1.5 years. Diabetes status was ascertained through registry linkage (mean follow-up of 18.4 ± 6.1 years). The associations of baseline galectin-1 with incident CKD and type 2 diabetes were assessed with Cox regression, adjusting for established risk factors. In addition, a genome-wide association study on galectin-1 was performed to identify genetic instruments for two-sample MR analyses utilising the genetic associations obtained from the Chronic Kidney Disease Genetics (CKDGen) Consortium (41,395 cases and 439,303 controls) and the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium (74,124 cases and 824,006 controls). One genome-wide significant locus in the galectin-1 gene region was identified (sentinel SNP rs7285699; p = 2.4 × 10−11). The association between galectin-1 and eGFR was also examined in individuals with newly diagnosed diabetes from the All New Diabetics In Scania (ANDIS) cohort. Results: Galectin-1 was strongly associated with lower eGFR at baseline (p = 2.3 × 10−89) but not with incident CKD. However, galectin-1 was associated with increased risk of type 2 diabetes (per SD increase, HR 1.12; 95% CI 1.02, 1.24). Two-sample MR analyses could not ascertain a causal effect of galectin-1 on CKD (OR 0.92; 95% CI 0.82, 1.02) or type 2 diabetes (OR 1.05; 95% CI 0.98, 1.14) in a general population. However, in individuals with type 2 diabetes from ANDIS who belonged to the severe insulin-resistant diabetes subgroup and were at high risk of diabetic nephropathy, genetically elevated galectin-1 was significantly associated with higher eGFR (p = 5.7 × 10−3). Conclusions/interpretation: Galectin-1 is strongly associated with lower kidney function in cross-sectional analyses, and two-sample MR analyses suggest a causal protective effect on kidney function among individuals with type 2 diabetes at high risk of diabetic nephropathy. Future studies are needed to explore the mechanisms by which galectin-1 affects kidney function and whether it could be a useful target among individuals with type 2 diabetes for renal improvement. Graphical abstract: [Figure not available: see fulltext.

Hyperinsulinemia and insulin resistance in the obese may develop as part of a homeostatic response to elevated free fatty acids : A mechanistic case-control and a population-based cohort study

Background: It is commonly accepted that in obesity free fatty acids (FFA) cause insulin resistance and hyperglycemia, which drives hyperinsulinemia. However, hyperinsulinemia is observed in subjects with normoglycaemia and thus the paradigm above should be reevaluated. Methods: We describe two studies: MD-Lipolysis, a case control study investigating the mechanisms of obesity-driven insulin resistance by a systemic metabolic analysis, measurements of adipose tissue lipolysis by microdialysis, and adipose tissue genomics; and POEM, a cohort study used for validating differences in circulating metabolites in relation to adiposity and insulin resistance observed in the MD-Lipolysis study. Findings: In insulin-resistant obese with normal glycaemia from the MD-Lipolysis study, hyperinsulinemia was associated with elevated FFA. Lipolysis, assessed by glycerol release per adipose tissue mass or adipocyte surface, was similar between obese and lean individuals. Adipose tissue from obese subjects showed reduced expression of genes mediating catecholamine-driven lipolysis, lipid storage, and increased expression of genes driving hyperplastic growth. In the POEM study, FFA levels were specifically elevated in obese-overweight subjects with normal fasting glucose and high fasting levels of insulin and C-peptide. Interpretation: In obese subjects with normal glycaemia elevated circulating levels of FFA at fasting are the major metabolic derangement candidate driving fasting hyperinsulinemia. Elevated FFA in obese with normal glycaemia were better explained by increased fat mass rather than by adipose tissue insulin resistance. These results support the idea that hyperinsulinemia and insulin resistance may develop as part of a homeostatic adaptive response to increased adiposity and FFA.De två första författarna delar förstaförfattarskapet.</p