Alteration of Circulating levels of BDNF, SPARC, FGF-21, and GDF-15 after 1 Year of Anti-Obesity Treatments and Their Association with 1-Year Weight Loss

doi:10.21203/rs.3.rs-2715906/v1

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Research Article

Alteration of Circulating levels of BDNF, SPARC, FGF-21, and GDF-15 after 1 Year of Anti-Obesity Treatments and Their Association with 1-Year Weight Loss

https://doi.org/10.21203/rs.3.rs-2715906/v1

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published 11 Jul, 2023

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Conclusions: This study highlights the association of SPARC, FGF-21, and GDF-15 levels with BMI. Decreased circulating levels of GDF-15 and FGF-21 were associated with greater weight loss at 1 year regardless of types of anti-obesity modalities.

Purpose: Emerging evidence revealed that brain-derived neurotrophic factor(BDNF), secreted protein acidic and rich in cysteine(SPARC), fibroblast growth factor 21(FGF-21) and growth differentiation factor 15(GDF-15) are involved in energy metabolism and body weight regulation. Our study aimed at examining their association with BMI, their alterations after anti-obesity treatments, and their association with 1-year weight loss.

Methods: A prospective observational study of 171 participants with overweight and obesity and 46 lean controls was established. All participants received lifestyle educational intervention (LEI) with or without anti-obesity treatments (LEI+bariatric/metabolic surgery, n=41; LEI+topiramate, n=46; LEI+liraglutide, n=31; LEI+orlistat, n=12; and LEI alone, n=41). Anthropometric and metabolic parameters, insulin sensitivity, C-reactive protein (CRP), fasting plasma levels of BDNF, SPARC, GDF-15, and FGF-21 were measured at baseline and 1 year.

Results: Multiple linear regression showed that the fasting levels of SPARC, FGF-21, and GDF-15 were significantly associated with baseline BMI after adjusting for age and sex. At 1 year, average weight loss was 4.8% in the entire cohort with a significant improvement in glycemia, insulin sensitivity and CRP. Multiple linear regression adjusted for age, sex, baseline BMI, type of treatment, and the presence of T2DM revealed that the decrease in log₁₀FGF-21 and log₁₀GDF-15 at 1 year from baseline were significantly associated with greater 1-year percentage weight loss.

Body weight (BW) regulation is complex, requiring interaction from various organs. Emerging evidence revealed that several cytokines (1–3) and gut hormones (4) played an important role in metabolism, energy balance, and BW regulation, and many of them were being developed as novel therapies for obesity. Brain-derived neurotrophic factor (BDNF), secreted protein acidic and rich in cysteine (SPARC), fibroblast growth factor 21 (FGF-21), growth differentiation factor 15 (GDF-15) are examples of such cytokines which have therapeutic potential in obesity and metabolic diseases.

BDNF involves in neurotrophic activity, inflammation, metabolism, and cardiovascular diseases (5). Depletion of BDNF in the hypothalamus (6), BDNF haploinsufficiency (7), and mutation of its receptors (8) have been reported to be related to increased dietary intake, weight gain, hence obesity. SPARC, also known as osteonectin or BM-40, ubiquitously expresses in most tissues, especially in subcutaneous fat. Recently, SPARC has also gained substantial interest due to its roles in obesity, insulin resistance, and metabolic syndrome (9).

FGF-21, secreted primarily from the liver, has a crucial role in enhancing glucose uptake and lipolysis in adipose tissue, alleviating liver steatosis, and anti-inflammation (10). Furthermore, FGF-21 shifts food preference away from the sweet and high-calorie diet (11). It also increases energy expenditure via activating brown and beige adipose tissue (2). FGF-21 is therefore considered as a novel therapeutic potential for obesity, T2DM, and NAFLD (2).

GDF-15, a member of the transforming growth factor β superfamily, is a stress-responsive cytokine (12). GDF-15 expresses in various tissues, mainly in the liver (1), and it signals through a glial cell-derived neurotrophic factor receptor alpha-like (GFRAL) in the nucleus tractus solitarius and area prostrema (13), resulting in reduced food intake and BW, and glycemic improvement (14). GDF-15/GFRAL axis is therefore suggested as an essential part of energy homeostasis and BW regulation, and is currently a novel therapeutic target for obesity.

Studies examining these cytokines in people with overweight and obesity are limited. In addition, research describing the alterations in circulating levels of these cytokines in response to anti-obesity treatments including pharmacotherapy or bariatric/metabolic surgery is scarce. This information may throw light on these cytokines’ role in obesity pathogenesis and could lead to the development of novel obesity treatments.

The present study thus aimed at studying the association of circulating levels of BDNF, SPARC, FGF-21, and GDF-15 with BMI, the alterations of these four cytokines after 1 year of anti-obesity treatments (lifestyle modification plus either pharmacotherapy or bariatric/metabolic surgery), and their association with weight loss at 1 year after obesity therapy.

Study participants

A prospective cohort of 171 adults with overweight (BMI ≥23 kg/m²) and obesity (BMI ≥25 kg/m²) and 46 lean controls was established. All participants were ≥18 years old and were not pregnant or lactating. Controls reported no history of obesity, diabetes mellitus, high blood pressure, or dyslipidemia and were in good health. Written informed consent was given by all participants. The study was approved by the respective Institutional Ethics Committee for Clinical Research of Siriraj Hospital, Mahidol University, Thailand (Approval No. 129/2558), and was conducted at Siriraj Hospital, Faculty of Medicine Siriraj Hospital from 2017 to 2019. Study data were collected and managed using REDCap electronic data capture tools (15).

All participants with overweight and obesity received lifestyle educational intervention (LEI) with or without pharmacotherapy (for participants with BMI ≥27kg/m² with obesity-associated co-morbidities or BMI ≥30kg/m²) including topiramate, liraglutide, and orlistat, or bariatric/metabolic surgery (for participants with BMI ≥35kg/m² with obesity-associated co-morbidities or BMI ≥40kg/m²). The option of anti-obesity treatments was chosen based on specific contraindications for each individual. The decision was made by paticipants and an attending physician after a thorough discussion.

Anti-obesity treatments

Lifestyle education intervention (LEI)

Individual sessions of lifestyle education were provided by a registered dietitian or an obesity physician at baseline and every follow-up visit. The session focused on reduced energy intake, targeting at 2,093-4186 kJ (500-1,000 kcal) deficit per day; and regular exercise, aiming for at least 150-minute moderate-intensity exercise per week and/or 10,000 steps per day.

LEI + Topiramate

Dosage of topiramate was titrated in the first 4 weeks of intervention as follows: the first week, 25 mg before bedtime once a day; the second week, 25 mg twice daily after breakfast and before bedtime; the third week, 50 mg twice daily after breakfast and before bedtime; the fourth week, 50 mg after breakfast and 100 mg before bedtime. However, if the 150 mg dose could not be tolerated, the dose would be deescalated to a maximal tolerable dose.

LEI + Liraglutide

Liraglutide was administered by subcutaneous injection. The starting dose was 0.6 mg per day and then the dose was escalated by 0.6 mg each week until the dose of 3.0 mg was reached. However, if the 3.0 mg dose could not be tolerated, the dose would be deescalated to a maximal tolerable dose.

LEI + Orlistat

Orlistat was prescribed at a dose of 120 mg 2–3 times a day with meals.

LEI + Bariatric/metabolic surgery

Laparoscopic roux-en-Y gastric bypass (LRYGB) included the construction of a bilio-pancreatic limb with a 100- to 120-cm alimentary limb and a 30-mL gastric pouch. In laparoscopic sleeve gastrectomy (LSG), approximately 80% of the stomach is removed, producing a narrow, tubular stomach leading to rapid gastric emptying and nutrients passing rapidly into the duodenum and proximal part of the small intestine.

Outcomes measurement

Demographic data including age, sex, height, and co-morbidities were collected from the hospital electronic database. BW was recorded at every visit. Waist circumference (WC) and hip circumference (HC) were measured at baseline and 1 year. Total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-c), fasting plasma glucose (FPG), hemoglobin A1c (HbA_1c), fasting insulin, high-sensitivity C-reactive protein (CRP), and fasting plasma levels of BDNF, SPARC, FGF-21 and GDF-15 were measured at baseline and 1 year.

Anthropometric measurement

BW was measured, using a calibrated weighing scale (TANITA^® BC-587, Central trading Co., Ltd, Thailand). Participants were weighed while wearing indoor clothing without shoes and heavy accessories. BMI was calculated by BW (kg)/ (height [m])². WC and HC were measured using non-stretchable tape. WC was measured midway between iliac crests and the lowest ribs. HC was measured at the widest protrusion of the buttocks. W/H ratio was calculated by WC/HC. Percentage weight loss (PWL) was determined by ([baseline BW – BW at 1 year]/ baseline BW) x 100.

Biochemical analysis

A venous blood sample was collected after a 12-hour overnight fast. TC, HDL-c, LDL-c, TG, glucose, and insulin were determined by a biochemical auto-analyzer (Cobas® 8000 Modular Analyser Series, Roche Diagnostics, Indianapolis, United States). HbA_1c was analyzed with Cobas Integra® 800 analyzer, Roche Diagnostics, Indianapolis, United States. LDL-c levels were calculated by the Friedewald formula. Homeostatic model assessment insulin resistance (HOMA-IR) was calculated using the following formula: (FPG x fasting insulin)/ 22.5 in molar units.

For cytokines analysis, EDTA plasma was separated by centrifugation at 3500 rpm for 10 min. Plasma was then collected and stored at -80°C, awaiting analysis for BDNF, SPARC, FGF-21, and GDF-15. Plasma levels of BDNF, SPARC, FGF-21 and GDF-15 were quantified using a bead-based multiplex assay kit (MILLIPLEX MAP Human Myokine Magnetic Bead Panel, Merck, Germany) according to the manufacturer’s instructions (respectively, intra-assay variability: <10%, < 10%, < 5%, < 10%, and inter-assay variability: <15%, < 20%, < 15%, < 10%).

Statistical analysis

Statistical analyses were performed using SPSS version 18.0 software. The normal distribution of variables was explored using the Kolmogorov-Smirnov and Shapiro-Wilk tests. Skewed distributions were logarithmically transformed for comparison. The independent and paired sample t-tests were used for quantitative in two unrelated samples and related sample groups, respectively. Analysis of variance (ANOVA) was used to study the difference between groups. The results of quantitative variables were expressed as mean ± standard deviation for normally distributed variables, and as median and interquartile ranges for non-normally distributed variables. The association of cytokines with BMI was tested by a multiple linear regression analysis adjusted for age and sex. The relationship between plasma cytokines and PWL was analyzed by a multiple linear regression model adjusted for age, sex, baseline BMI, type of anti-obesity treatments and the presence of T2DM. A p-value < 0.05 was considered statistically significant in all analyses.

Baseline characteristics

Table 1 presents clinical characteristics and fasting plasma levels of cytokines according to BMI groups at baseline. Overall, the average age was 39 years old. The majority of participants were female (62.7%), and 26.3% of participants had T2DM. There was an increasing number of participants with T2DM, HT, dyslipidemia (DLP), and obstructive sleep apnea (OSA) according to the increasing BMI. The CRP levels were also significantly increasing along with the increase in BMI groups (P < 0.001).

Table 1

Clinical characteristics and fasting plasma levels of cytokines according to BMI groups at baseline.
Parameters	Lean control (n = 46)	Group 1 (n = 14) BMI 27–29.9 kg/m²	Group 2 (n = 67) BMI 30–39.9 kg/m²	Group 3 (n = 90) BMI ≥ 40 kg/m²	P-value
Age, years	35.1 ± 8.7	42.3 ± 16.4	42.7 ± 13.4	36.6 ± 12.8	0.005
Female, n (%)	23 (50.0)	14 (100)	42 (62.7)	57 (63.3)	0.02
Type 2 diabetes mellitus, n (%)	0	1 (7.1)	17 (25.4)	27 (30.0)	0.19
Hypertension, n (%)	0	3 (21.4)	32 (47.8)	48 (53.3)	0.08
Dislipidemia, n (%)	0	2 (14.3)	19 (28.4)	26 (28.9)	0.51
Obstructive sleep apnea, n (%)	0	0	14 (25.4)	44 (48.9)	< 0.001
Inflammatory marker
CRP, mg/l	0.59 (0.30,1.14)	1.07 (0.86, 2.29)	3.63 (1.75, 5.72)	8.03 (4.75,13.19)	< 0.001
Cytokine concentrations
BDNF, pg/ml	475 (234, 1095)	759 (412, 1344)	670 (369, 1414)	646 (380, 1553)	0.12
SPARC, ng/ml	24.8 (17.2, 30.4)	42.1 (35.7, 51.1)	55.1 (41.2, 82.5)	58.6 (43.4, 75.3)	< 0.001
FGF-21, pg/ml	4.8 (2.21 10.7)	10.3 (4.7, 20.6)	18.7 (9.2, 33.8)	24.6 (12.2, 49.8)	< 0.001
GDF-15, pg/ml	420 (274, 532)	441 (323, 724)	777 (578, 1309)	968 (616, 1650)	< 0.001
^{Data are expressed as mean ±SD or median (interquartile range) according to data distribution}

The fasting levels of plasma BDNF were not significantly different across the groups (P = 0.12, Table 1, Fig. 1a). The fasting levels of plasma SPARC in BMI group 1, group 2, and group 3 were significantly greater than lean control (P < 0.01, P < 0.001, and P < 0.001, respectively, Table 1, Fig. 1b). The fasting levels of plasma FGF-21 in BMI group 2 and group 3 were significantly higher than lean control (p < 0.001 for both), and the levels in BMI group 3 were significantly higher than BMI group 1 (p < 0.01) (Table 1, Fig. 1c). The circulating GDF-15 levels in BMI group 2 and BMI group 3 were significantly greater than lean control (P < 0.001 for both), and the levels in BMI group 2 and BMI group 3 were significantly higher than BMI group 1 (P < 0.01 and P < 0.001) (Table 1, Fig. 1d).

Multiple linear regression also showed that log10SPARC, log10FGF-21, and log10GDF-15 were significantly associated with BMI after adjusting for age and sex (β = 12.4, P < 0.001 for log10SPARC; β = 10.2, P < 0.001 for log10FGF-21; β = 22.5, P < 0.001 for log10GDF-15) (Fig. 2). There was no relationship between log10BDNF levels and BMI at baseline.

Changes in parameters at 1 year

Anthropometric parameters

In the entire cohort, there was a significant decrease in BW, BMI, and WC at 1 year from baseline (P < 0.001 for all, Table 2). BW and BMI significantly reduced in LEI + topiramate (P < 0.001 for both), BW and WC significantly decreased in LEI + liraglutide (P < 0.001 and P < 005, respectively), and BW, BMI, WC, and W/H ratio significantly reduced in LEI + bariatric/metabolic surgery (P < 0.001 for all) (Table 2). The average PWL at 1 year was 4.8% with the highest PWL in LEI + bariatric/metabolic surgery (21.6%), 5.7% in LEI + topiramate, 3% in LEI + liraglutide, and 0.8% in LEI alone. In contrast, LEI + orlistat experienced a weight gain of 2% (Table 2).

Table 2

Changes in anthropometric parameters, metabolic indices, inflammatory marker and cytokines concentrations in subjects with overweight and obesity at 1 year from baseline, divided by type of anti-obesity treatments
Parameters	Total (n = 171)		P	LEI (n = 41)		P	LEI + topiramate (n = 46)		P	LEI + liraglutide (n = 31)		P	LEI + orlistat (n = 12)		P	LEI + bariatric/metabolic surgery (n = 41)		P
Parameters	baseline	1 year	P	baseline	1 year	P	baseline	1 year	P	baseline	1 year	P	baseline	1 year	P	baseline	1 year	P
Anthropometric parameters
BW, kg	112 ± 31	101 ± 27	< 0.001	106 ± 27	105 ± 27	0.10	109 ± 32	101 ± 32	< 0.001	94.6 ± 18.5	90.8 ± 18.1	< 0.001	114 ± 32	116 ± 34	0.61	134 ± 31	102 ± 26	< 0.001
BMI, kg/m²	41.7 ± 9.8	37.7 ± 8.4	< 0.001	39.1 ± 8.3	38.6 ± 8.5	0.10	40.3 ± 9.5	37.2 ± 9.5	< 0.001	36.5 ± 5.2	35.7 ± 6.7	0.28	40.6 ± 9.6	41.2 ± 10.8	0.58	50.2 ± 9.3	38.0 ± 7.4	< 0.001
WC, cm	119 ± 21	114 ± 18	< 0.001	114 ± 16	113 ± 16	0.47	119 ± 25	116 ± 23	0.38	114 ± 15	110 ± 13	0.03	122 ± 25	122 ± 24	1.00	132 ± 21	113 ± 16	< 0.001
W/H ratio	0.93 ± 0.09	0.92 ± 0.07	0.29	0.91 ± 0.08	0.91 ± 0.08	0.85	128 ± 22	125 ± 22	0.96	0.94 ± 0.06	0.92 ± 0.05	0.11	0.92 ± 0.08	0.94 ± 0.07	0.45	0.93 ± 0.08	0.91 ± 0.07	< 0.001
PWL, %	-	4.76 (0.8, 16.2)	-	-	0.78 (-1.4, 3.1)	-	-	5.65 (1.7, 10.8)	-	-	3.01 (0.5, 8.0)	-	-	-1.97 (-5.5, 5.3)	-	-	21.6 (18.6, 29.3)	-
Glycemic and insulin sensitivity indices
FPG, mmol/L	6.01 ± 1.69	5.52 ± 1.51	< 0.001	5.50 ± 1.07	5.35 ± 1.30	0.38	5.76 ± 1.15	5.60 ± 1.72	0.53	6.25 ± 1.58	6.14 ± 1.44	0.66	5.87 ± 0.96	5.00 ± 1.68	0.21	6.66 ± 2.54	5.25 ± 1.32	< 0.001
HbA1c, %	6.09 ± 1.05	5.75 ± 0.76	< 0.001	5.67 ± 0.57	5.74 ± 0.81	0.37	6.0 ± 0.8	5.8 ± 0.8	0.30	6.19 ± 0.91	6.03 ± 0.63	0.16	5.89 ± 0.48	5.78 ± 0.59	0.37	6.63 ± 1.58	5.44 ± 0.69	< 0.001
Insulin, pmol/L	147 (98, 219)	101 (66, 185)	< 0.001	147 (98, 219)	101 (66, 185)	0.23	139 (96, 218)	133 (75, 245)	0.24	158 (94, 205)	149 (81, 220)	0.72	152 ± 74	156 ± 103	0.90	228 ± 153	81.1 ± 48.1	< 0.001
HOMA-IR	2.70 (1.85, 4.15)	2.00 (1.20, 3.40)	< 0.001	2.70 (1.85, 4.15)	2.00 (1.20, 3.40)	0.25	2.50 (1.80, 4.05)	2.55 (1.45, 4.37)	0.33	2.90 (1.80, 3.70)	2.95 (1.55, 4.12)	0.65	2.70 (1.93, 3.80)	1.80 (1.20, 3.70)	0.79	2.70 (1.85, 4.15)	2.00 (1.20, 3.40)	< 0.001
Lipid profile
TC, mg/dl	180 ± 36	179 ± 38	0.73	183 ± 32	180 ± 32	0.36	175 ± 34	184 ± 47	0.10	178 ± 39	179 ± 38	0.86	182 ± 31.3	189 ± 29.4	0.40	183 ± 43	170 ± 35	0.048
TG, mg/dl	122 (95, 171)	112(810, 156)	0.03	121 ± 45	123 ± 62	0.83	140 (104, 204)	132 (90, 167)	0.50	138 ± 51	138 ± 52	0.91	128 ± 60	122 ± 39	0.63	135 ± 66	70.0 ± 371	0.001
HDL-c, mg/dl	46.6 ± 12.8	50.2 ± 34.5	< 0.001	47.9 ± 11.7	49.4 ± 13	0.11	43.0 ± 12.2	48.5 ± 15.1	0.00	48 ± 13	51 ± 16	0.00	52.2 ± 16.3	49.9 ± 13.2	0.19	47.3 ± 12.9	51.9 ± 11.2	0.002
LDL-c, mg/dl	106 ± 35	102 ± 33	0.07	112 ± 31	106 ± 30	0.10	101 ± 29	101 ± 29	0.98	104 ± 36	100 ± 39	0.34	104 ± 29	114 ± 33	0.23	107.9 ± 42.8	96.6 ± 36.2	0.073
Inflammatory marker
CRP, mg/l	5.03 (2.51, 9.58)	3.32 (1.62, 5.52)	< 0.001	5.03 (2.51, 9.58)	3.32 (1.62, 6.62)	0.65	4.15 (2.16, 7.40)	3.47 (1.63, 6.71)	0.10	4.68 (1.38, 11.11)	2.66 (1.19, 7.55)	0.72	3.36 (1.79, 7.09)	6.06 (2.63, 9.37)	0.25	8.58 (4.93, 12.44)	3.05 (1.13, 5.12)	< 0.001
Cytokine concentrations
BDNF, pg/ml	663 (381, 1376)	680 (428, 1555)	0.75	611 (280, 1190)	535 (331, 1136)	0.74	935 (539, 1851)	918 (544, 2202)	0.39	548 (319, 984)	551 (384, 1636)	0.65	754 (442, 1330)	613 (482, 1403)	0.48	706 (351, 1425)	734 (499, 1164)	0.96
SPARC, ng/ml	55.0 (41.4, 76.5)	39.9 (28.9, 56.2)	< 0.001	37.6 (27.0, 50.8)	33.9 (22.5, 46.0)	0.07	55.1 (43.3, 83.2)	46.2 (31.3, 64.8)	0.002	80.8 (66.2, 104.2)	41.0 (31.1, 64.1)	< 0.001	45.8 (39.8, 53.5)	47.5 (39.0, 140.0)	0.70	58.6 (48.7, 71.0)	38.6 (27.1, 53.4)	< 0.001
FGF-21, pg/ml	20.7 (9.3, 42.8)	18.8 (9.9, 33.8)	0.70	15.4 (7.1, 26.5)	18.7 (9.8, 31.8)	0.08	24.4 (11.1, 51.3)	21.3 (10.0, 55.3)	0.78	12.8 (6.7, 29.2)	19.4 (7.1, 36.5)	0.12	18.6 (12.9, 45.0)	21.5 (12.3, 40.6)	0.81	31.4 (14.0, 54.0)	14.7 (9.9, 26.4)	0.005
GDF-15, pg/ml	853 (572, 1515)	770 (506, 1201)	0.052	676 (453, 1061)	817 (545, 1184)	0.012	1041 (650, 2075)	974 (506, 1472)	0.021	701 (451, 868)	706 (540, 1148)	0.38	673 (496, 1448)	706 (498, 1040)	0.70	1165 (674, 1864)	606 (444, 1381)	0.003

Metabolic and insulin sensitivity indices

In all participants, there was a significant decrease in TG levels (P < 0.05) and a significant increase in HDL-c levels (P < 0.001) (Table 2). In LEI + bariatric/metabolic surgery group, participants had significantly reduced TG and total cholesterol levels (P = 0.001 and P < 0.05), and increased HDL-c levels (P < 0.01) (Table 2). There was a significant increase in HDL-c levels in LEI + topiramate and LEI + liraglutide (P < 0.01 for both) (Table 2).

The levels of FPG, HbA_1c, fasting insulin, and HOMA-IR significantly decreased at 1 year, compared to baseline only in LEI + bariatric/metabolic surgery group (P < 0.001 for all) (Table 2).

Inflammatory marker

The circulating CRP levels significantly reduced at 1 year in LEI + bariatric/metabolic surgery group (P < 0.001) (Table 2).

Cytokines

At 1 year, the levels of BDNF were not significantly different from baseline in all groups (Table 2, Fig. 3a). Circulating SPARC levels were significantly lower than baseline in the entire cohort (P < 0.001), LEI + topiramate (P < 0.01), LEI + liraglutide (P < 0.001), and LEI + bariatric/metabolic surgery (P < 0.001) (Table 2, Fig. 3b). The levels of FGF-21 significantly reduced in LEI + bariatric/metabolic surgery at 1 year (P < 0.01) (Table 2, Fig. 3c). The circulating levels of GDF-15 significantly decreased in LEI + topiramate (P < 0.05) and LEI + bariatric/metabolic surgery (P < 0.01) (Table 2, Fig. 3d).

Association study of cytokines levels with 1-year PWL

Multiple linear regression adjusted for age, sex, baseline BMI, type of anti-obesity treatments, and the presence of T2DM was performed to examine an association between cytokines levels and 1-year PWL. It revealed that the decrease in log₁₀FGF-21 and log₁₀GDF-15 at 1 year from baseline (∆log₁₀FGF-21 and ∆log₁₀GDF-15) were significantly associated with greater 1-year PWL (β=-4.4, P < 0.001 and β=-4.5, P < 0.05, respectively, Table 3).

Table 3

Association study of plasma cytokines levels with 1-year percentage weight loss, adjusted for age, sex, baseline BMI, type of anti-obesity treatments and the presence of T2DM
Parameters	β			R²	P-value
Parameters	β	Lower bound	Upper bound	R²	P-value
At baseline
Log10 BDNF, pg/ml	-0.63	-3.43	2.17	0.63	0.66
Log10 SPARC, ng/ml	-0.62	-4.60	3.36	0.63	0.76
Log10 FGF-21, pg/ml	1.04	-1.33	3.40	0.63	0.39
Log10 GDF-15, pg/ml	-1.71	-6.16	2.75	0.63	0.45
Changes at 1 year from baseline
ΔLog10 BDNF, pg/ml	0.07	-2.19	2.33	0.63	0.95
ΔLog10 SPARC, ng/ml	0.46	-2.31	3.24	0.63	0.74
ΔLog10 FGF-21, pg/ml	-4.39	-6.62	-2.16	0.66	< 0.001
ΔLog10 GDF-15, pg/ml	-4.49	-8.46	-0.52	0.64	0.027

The present study demonstrated that circulating levels of SPARC, FGF-21, and GDF-15 but BDNF positively correlated with BMI. At 1 year after anti-obesity treatments, there was a significant reduction in BW (average PWL = 5%), BMI and WC, and a significant improvement in glycemia, insulin-sensitivity indices and inflammatory marker. The levels of SPARC also significantly decreased at 1 year after weight loss. The reduction of FGF-21 and GDF-15 levels was also observed; however, this fell short of statistical significance. There was no significant change in circulating levels of BDNF at 1 year from baseline. Furthermore, we discovered that the decreasing levels of circulating FGF-21 and GDF-15 were associated with greater 1-year weight loss regardless of the type of anti-obesity therapies.

Despite advantages of BDNF on BW, a systematic review and meta-analysis revealed that there was no difference in circulating levels of BDNF between people with obesity and lean controls (5). This is in agreement with our findings that there was no significant association between plasma BDNF levels and BMI. Furthermore, BDNF levels at 1 year after anti-obesity treatments were comparable to the levels at baseline. The reasons explaining these results could be: first, circulating levels of BDNF may not genuinely represent BDNF levels in the hypothalamus which is the key organ regulating BW; second, the main source of circulating BDNF is still poorly understood (different sources might have different functions) (16); and third, it has been reported that there was a lack of standard protocol in collecting and processing plasma and/or serum BDNF (5).

Adipose expandability concept (17) describes that adipose expansion is vital for coping with surplus energy intake. When the expandability is restricted, excess TG enters the circulation, contributing to hyperlipidemia, and ectopic fat accumulation. This accordingly results in insulin resistance and metabolic syndrome. SPARC is claimed to be responsible for adipose tissue fibrosis, thus restricting adipose expandability and adipogenesis (18). However, recent evidence showed that SPARC had advantages on energy metabolism. SPARC increased thermogenesis through brown adipose tissue (19) and increased energy expenditure in skeletal muscle (20).

In the present study, we found that SPARC levels were significantly associated with BMI. This could be explained by: first, the higher levels of inflammation, insulin resistance, leptin, fat mass in the higher BMI associated with increased SPARC levels as reported by several previous studies (9, 19, 21, 22); second, a body’s attempt to limit adipose tissue expansion in higher BMI; and third, a compensation to increase energy expenditure via brown and beige adipocytes, and skeletal muscles.

After 1 year of anti-obesity treatments, SPARC levels significantly decreased in the entire cohort, LEI + topiramate, LEI + liraglutide, and LEI + bariatric/metabolic surgery, where they were groups showing a significant weight loss. This corresponds with previous studies revealing that a gene encoding SPARC could be downregulated by energy restriction in mice (23), and a very-low-calorie diet reduced SPARC expression by 33% in humans (9). Furthermore, two studies examining SPARC concentrations after bariatric/metabolic surgery showed that there was a significant decrease in SPARC levels (9, 24). The significant reduction of SPARC levels after anti-obesity treatments in our study could be due to the improved obesity-associated metabolic abnormalities and inflammation. Therefore, the elevated levels of SPARC to counteract the obesity state and its complications may be no longer needed. The direct effects of topiramate and liraglutide on SPARC concentrations remain poorly understood.

Interestingly, Lee et al. reported that changes in serum SPARC levels after bariatric/metabolic surgery significantly correlated with changes in HOMA-IR, not BMI (24). This is in line with our findings that the changes in circulating SPARC showed no association with 1-year PWL in a multiple linear regression adjusting for age, sex, baseline BMI and the presence of T2DM.

At baseline, we found that the circulating levels of FGF-21 were significantly associated with BMI. This confirms that the secretion of FGF-21 is influenced by physiological or environmental stress in people with obesity as reported in previous studies (25). Interestingly, an FGF-21 resistant state in obesity could be another reason. A previous study in diet-induced obesity mice demonstrated that there was decreased expression of the FGF-21 receptor in white adipose tissue, and after administration of FGF-21, the reduction in plasma glucose was attenuated, compared to lean ones (26). A study in people living with obesity and T2DM demonstrated that the expression of genes comprising the FGF21 signalling pathway was also lower in visceral fat than in subcutaneous fat. They concluded that Human FGF21 resistance in T2DM and obesity could result from increases in FGF21-resistant ectopic fat accumulation (27).

Our results revealed that the decreasing levels of FGF-21 at 1 year from baseline were significantly associated with greater PWL. This was driven mainly by the group ‘LEI + bariatric/metabolic surgery’ since the reduction in the 1-year levels of FGF-21 was the most striking in this group. The changes in FGF-21 levels in response to bariatric/metabolic surgery are reportedly varied and inconclusive. A meta-analysis by Hosseinzadeh et al. indicated that the alteration of fasting FGF-21 levels was dominantly affected by follow-up duration (10). The fasting levels of FGF-21 significantly increased after RYGB, particularly in the early post-op; however, the levels considerably declined at ≥ 1 year follow-up duration. This supports our findings that the fasting levels of FGF-21 significantly decreased at 1 year after bariatric/metabolic surgery.

The proposed mechanisms explaining the reduction in 1-year levels of circulating FGF-21 include: first, resolved FGF-21 resistant state after a significant weight reduction; second, improved metabolic stress since FGF-21 is a stress-induced cytokine; and third, significantly reduced food intake as FGF-21 is strictly controlled nutritionally (10, 28). Evidence in rats revealed that there was an improvement in FGF-21 sensitivity as well as restoration of FGF-21 signalling pathway following SG and duodenal-jejunal bypass at 1 year (29). In addition, an upregulation of FGF-21 receptors in adipose tissue in humans after RYGB has been reported (30).

GDF-15 concentrations have been reported to positively correlate with age, BMI, W/H ratio, adiposity, glucose, degrees of insulin resistance, and CRP (13, 31). This is in agreement with our results showing that the levels of GDF-15 were significantly associated with BMI at baseline.

Studies in mice revealed that GDF-15 causes weight loss and taste aversion away from high-calorie food (12, 32–35). In addition, Li and colleagues discovered that GDF-15 could prevent endothelial cell injury and cell apoptosis from high plasma glucose (36). Considering that systemic inflammatory state is a manifestation of obesity and T2DM. Hence, in addition to simply being a cell/tissue stress-induced cytokine, it is plausible that the role of higher levels of GDF-15 in obesity and diabetes is to prevent progressive weight gain and to play a role in anti-inflammation (12, 13).

In the present study, at 1 year, the reduction of GDF-15 levels was statistically significant in LEI + topiramate and LEI + bariatric/metabolic surgery where they were the top two weight-reduction strategies in this cohort (PWL = 21.6% and 5.7%, respectively). The magnitude of GDF-15 reduction was highest in LEI + bariatric/metabolic surgery where weight loss was also greatest. This could indicate that at least 5% of weight loss is required for the reduction in GDF-15 concentrations.

Furthermore, a multiple linear regression analysis suggests that the reduction of GDF-15 at 1 year from baseline was associated with greater PWL after anti-obesity treatments at 1 year. This could be explained by weight loss leading to reduced inflammatory burden and a substantial decrease in the need for GDF-15 in preventing progressive weight gain, thus a decrease in circulating GDF-15 levels.

Our findings question whether or not GDF-15 is a key mediating weight loss after anti-obesity treatments, particularly bariatric/metabolic surgery. Frikke-Schmidt et al. reported that deletion of Gdf15 did not affect weight loss and feeding behaviour after SG in mice (35). Adolph and colleagues also showed that weight loss by laparoscopic adjustable gastric banding related with decreased Gdf15 expression in the liver (37).

In contrast, several studies revealed that the levels of GDF-15 increased after SG (38, 39) and RYGB (31, 40) and positively correlated with weight loss, suggesting that GDF-15 could be a key mechanism for weight-loss benefit after bariatric/metabolic surgery. However, the levels of GDF-15 at baseline in these studies were lower (215–487 pg/ml) than our study (1,165 pg/ml). Previous studies have shown that there was variability in GDF-15 response to anti-obesity treatments. After a week of daily 60-minute aerobic exercise training, GDF-15 levels increased in 67% (6/9) of participants and reduced in 33% (3/9) of participants (41). Furthermore, a 3-week of lifestyle intervention brought about an increase in GDF-15 in 77% and a decrease in 23% of total participants (42). This emphasizes the differences between individuals in physiology and secretion profiles of GDF-15 in response to obesity intervention. The effect of topiramate on GDF-15 concentrations is currently unknown.

The strengths of the present study entail: first, it is a large sample size cohort of people with overweight and obesity reporting circulating levels of BDNF, SPARC, FGF-21, and GDF-15 before and after obesity therapy; second, we demonstrated the changes in circulating levels of the four cytokines in response to several anti-obesity treatments including LEI with or without pharmacotherapy or bariatric/metabolic surgery; and third, the study participants were Asian ethnicity where this kind of study is still lacking.

Some limitations are worth noting: first, a small sample size in the LEI + orlistat group leading to inconclusive results in this group; second, the circulating levels of cytokines were not measured at each follow-up visit between baseline and 1 year, making the study of the temporal relationship of the changes in cytokine levels is impossible; and third, pharmacotherapy used in the present study reflect local practice context in Thailand, thus other pharmacotherapy options were not evaluated.

In conclusion, the circulating levels of SPARC, FGF-21, and GDF-15 positively correlated with BMI, and after weight-reduction therapy, these levels reduced according to weight loss. Furthermore, decreasing levels of FGF-21 and GDF-15 were associated with greater weight loss at 1 year. This could indicate that the physiological effects of these cytokines may depend on the clinical context. In the obesity state, they are released in response to stress and inflammation, and could function to prevent further weight gain and metabolic derangements. In the weight-reduced state, the improvement of inflammation, stress, and metabolic abnormalities probably results in reduced levels of the cytokines. Further research should focus on how these cytokines function in a weight-reduced state and how they respond to anti-obesity treatments.

Acknowledgements

This research project was supported by Siriraj Center of Research Excellence for Diabetes and Obesity (SiCORE-DO) and Siriraj research fund, Faculty of Medicine Siriraj Hospital, Mahidol University. REDCap service at Faculty of Medicine Siriraj Hospital is currently supported partly by the Health Science Research Institute (HSRI) Grant Number HSRI 64-143.

Competing Interests

The authors declare no competing financial interests

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Alteration of Circulating levels of BDNF, SPARC, FGF-21, and GDF-15 after 1 Year of Anti-Obesity Treatments and Their Association with 1-Year Weight Loss

Status:

Journal Publication

Version 1

Abstract

Figures

Introduction

Materials And Methods

Study participants

Anti-obesity treatments

Lifestyle education intervention (LEI)

LEI + Topiramate

LEI + Liraglutide

LEI + Orlistat

LEI + Bariatric/metabolic surgery

Outcomes measurement

Anthropometric measurement

Biochemical analysis

Statistical analysis

Results

Baseline characteristics

Changes in parameters at 1 year

Anthropometric parameters

Metabolic and insulin sensitivity indices

Inflammatory marker

Cytokines

Association study of cytokines levels with 1-year PWL

Discussion

Declarations

References

Status:

Journal Publication

Version 1