Metabolic Syndrome,Homocysteine and uric acid in patients with obesity;experience from Obesity and Work Centre

Abstract

BACKGROUND:

Uric acid (UA) and homocysteine (HCys) are involved in cardiovascular diseases. Patients with obesity (PwO) are characterized by elevated cardiovascular risk.

OBJECTIVE:

To evaluate the relationship between HCys and UA concentrations in 1141 overweight patients and PwO with and without metabolic syndrome (MS).

METHODS:

MS was defined according to IDF criteria (2005). Anthropometric data were recorded and blood biochemical parameters were assessed with routine methods on fasting blood samples. Statistics: Spearman correlation and multiple regression analysis.

RESULTS:

Gender, obesity and MS influenced both UA and HCys levels, which were increased in males, MS patients, PwO with MS and positively correlated (p < 0.001). Patients without MS had normal or slightly high levels. Hypertension, hyperuricemia and hyperhomocysteinemia were found in PwO with MS. UA concentration correlated with systolic blood pressure, triglycerides and HDL (all p < 0.05). Multivariate analysis showed that HCys concentration was an independent determinant factor affecting UA levels (T value 3.5, p < 0.001).

CONCLUSIONS:

HCys and UA levels positively and significantly correlated in PwO, especially in those with MS. The significant correlation between UA and hypertension, triglycerides, HDL suggests the clinical usefulness of monitoring UA together with HCys concentrations as cardiovascular risk marker in these patients.

Keywords

Obesity homocysteine uric acid metabolic syndrome cardiovascular risk cardiovascular disease

List of abbreviations

BMI

Body mass index

CVR

Cardiovascular risk

HOMA-IR

Homeostasis model assessment index

Metabolic Syndrome

PwO

Patients with Obesity

SAH

S-adenosyl- L-homocysteine

Uric acid

HUA

Hyperuricemia

HCys

Homocysteine

HHCys

Hyperhomocysteinemia

1 Introduction

Homocysteine (HCys) is an alfa-amino acid, homologue of the amino acid cysteine, from which it differs for an additional methylene bridge (-CH₂-). It is not obtained from diet [1], but it is biosynthesized from methionine by the removal of its terminal methyl group. HCys can be converted into cysteine or recycled into methionine because it is metabolized through two different pathways: trans-sulfuration and remethylation. Thanks to HCys, mammals biosynthesize cysteine, a semi-essential amino acid in adult subjects, where it has numerous biological functions (e.g. precursor to the glutathione, precursor to iron-sulfur clusters and it plays an important role in many proteins) because of the high reactivity of its thiol group.

The HCys cycle, combined with the folate cycle and vitamin B12, has also an important epigenetic role, because the remethilation from HCys to methionine (B12 dependent) allows the formation of tetrahydrofolate, directly involved in the epigenetic DNA modifications.

Normal HCys levels are limited between 4.0 –12.0μmol/l and they are typically higher in male than in female subjects and increase with age [2, 3].

Plasma Hcys concentrations can be altered by errors into its metabolism (caused by genetic and/or acquired factors), by cigarette smoking [4] or by a diet poor in most vitamins [5].

High levels of plasma HCys, above 15μmol/l (hyperhomocysteinemia- HHCys), are reported to be a significant risk factor for the development of a wide range of diseases, such as thrombosis, neuropsychiatric illnesses [6] and fractures [7]. HHcys is also reported to be associated with microalbuminuria (a strong indicator of risk of future cardiovascular diseases and renal dysfunctions [8]), and, in presence of low serum folate and/or low vitamin B12 concentrations, associated with early pregnancy loss [9] and with neural tube defects [10].

Anyway, mild HHCys is considered especially an independent marker of cardiovascular diseases [6]. A dose response between level and risk, even within the reference interval, is reported [6].

HCys induced oxidative damage may contribute to increase the risk of vascular events [11].

Uric acid (UA) can also be associated with cardiovascular diseases and with oxidative stress. UA is an oxypurine that derives from the catabolism of purinic nucleotides and deoxynucleotides, catabolism that especially occurs in the liver. It is involved in many human illnesses, such as cardiovascular and cerebral diseases, and metabolic disorders: it promotes sodium retention and increases blood pressure [12], contributes to the development of insulin resistance, the accumulation of adipocytes and it has effects on oxidative stress [12, 13]. In addition, UA positively affects cognitive functions, improves innate immunity and enhances the defences to infection and tumors [14]. All this is possible because UA, in its physiological concentrations, is a potent plasma antioxidant, especially against peroxynitrite and hydroxyl radicals, produced during inflammation. However, it is also true that if UA levels are chronically elevated, they act as a pro-oxidant agent, capable of triggering a pro-inflammatory state in vascular endothelium, hypertension and insulin resistance. This reflects the oxidant-antioxidant paradox of UA [15].

It has been found a possible link between elevated serum UA (HUA) and HHCys [16]. It may be the molecule of adenosine, which derived by S-adenosyl- L-homocysteine (SAH) formed during HCys metabolism and then split into HCys and adenosine. In turn, adenosine can be metabolized to UA or can react with HCys to form SAH again.

Under conditions of hypoxia or tissue ischemia, adenosine is up-regulated: its concentrations increase and are rapidly degraded to UA (its levels increase), whereas HCys is accumulated.

PwO are characterized by hypoxia, especially in adipose tissue, and have increased cardiovascular risk (CVR). Hypoxia, cardiovascular risk and oxidative stress are accentuated definitely in patients with metabolic syndrome (MS).

In a recent study we showed that UA can be used as a cardiometabolic marker in case of obesity and that there is a gender-related relationship between UA and MS [17].

Based on previous results of our Obesity and Work Center, in the present study we evaluated the relationship between HCys and UA levels in a group of overweight and with obesity patients with and without MS.

2 Methods

The cross-sectional study included 1141 overweight (BMI: 25–30 kg/m²) and with obesity patients (BMI > 30 kg/m²), recruited in our Department of Occupational Health Obesity and Work Clinic “L. Devoto”, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan (Italy). Overall, our sample consisted of 853 females and 288 males, with a mean age of 55±14 years and a body mass index (BMI) of 33.2±5.4 kg/m².

Upon entering the study, each participant signed an informed consent form and underwent medical examination. During the clinical examination, all patients were asked to fill in a questionnaire on general health, habitual dietary intake and lifestyle (i.e. smoking history, alcohol consumption, occupational activity). Anthropometric parameters (age, height, weight and BMI, waist circumference, systolic and diastolic blood pressure) were recorded during the first examination.

Exclusion criteria were: cancer, renal failure, pernicious anemia, leukaemia, nutritional deficiencies of vitamin (folate, vitamin B_12, vitamin B₆) and administration of medication known to interfere with HCys metabolism, special diet, nutritional supplements or lipid-lowering therapy.

2.1 Blood samples and biochemical parameters

Peripheral blood samples, drawn in the morning, after an overnight fast, were collected in test tubes, either without additives for assessing serum concentrations of routine biochemical parameters or with ethylenediaminetetraacetic acid (EDTA) to prevent coagulation for assessing plasma glycated haemoglobin and homocysteine (Hcys). A specimen of whole blood was centrifuged immediately for Hcy assay. Serum and plasma samples were frozen and stored at –80°C for batch analysis at the end of the study.

Routine biochemical parameters (glycaemia, insulin, triglycerides, total cholesterol, High-density lipoproteins (HDL), Low-density lipoproteins (LDL), UA, fibrinogen, C reactive protein (CRP), creatinine, aspartate transaminase (AST), alaninetransaminase (ALT), gamma-glutamiltransferase (GGT) were measured by Modular-Roche (Basel, Switzerland). Plasma glycated haemoglobin was measured by High-Performance Liquid Chromatography (HPLC). Plasma HCys concentrations were determined by immunoenzymatic assay using the relevant commercial kits on automated AxSYM analyser (Abbott, USA).

All the parameters were assessed at the central laboratory of Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan (Italy).

For insulin resistance, homeostasis model assessment index (HOMA-IR) was calculated using the formula: insulin (μU/ml) x glucose (mg/dl)/405.

Type 2 diabetes was defined when fasting glucose > 126 mg/dl (7 mmol/l) on two separate tests. The cut-off for hypertension diagnosis was defined if mean pressure was > 140/90 mmHg or use of antihypertensive treatment.

Obesity was considered if BMI > 30 kg/m² and MS was defined according to criteria of International Diabetes Federation in year 2005 [18].

Regarding lipid profile, an altered status was considered if total cholesterol concentration≥200 mg/dl (5.17 mmol/l) or triglyceride concentration≥150 mg/dl (1.69 mmol/l).

Because of the importance of reducing bias associated with obesity, we used people-first language (and we encourage scientific authors to do so), according to the standard recommendation of European Association for the Study of Obesity (EASO), The Obesity Society (TOS) and Obesity Canada (OC) (19–22).

The study was conducted according to the Good Clinical Practice guidelines and approved by Human Ethic Committee of Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico (Registration number: 852 –year 2012).

2.2 Statistical analysis

Variables were expressed as mean±standard deviation or median (ranges). Categorical variables were expressed as frequencies and percentages. For comparisons between groups, Mann-Whitney Rank Sum Test or Chi-Square were used. Spearman correlation was used to explore the relationship between tested parameters. Data were analyzed with SigmaPlot 11.0 software. It was accepted p < 0.05. Multiple regression analysis was also applied to verify the effect of independent variables (creatinine, HCys, BMI, age, gender, CRP, dyslipidemia, and hypertension) in determining UA values.

3 Results

Data from 1141 overweight and with obesity patients: 853 females (75%) and 288 males (25%) were collected. Table 1 summarizes the reference intervals or cut-offs, the means±SD or frequencies (%) of the analyzed anthropometric and biochemical data of all the patients divided by gender and MS presence. As shown, mean age of 55±14 years, obesity (32±5.4 kg/m²) present in 68.5%of all patients, average UA, CRP, fibrinogen, creatinine, triglycerides, HDL, insulin, and liver enzymes levels within normal reference values, whereas systolic/diastolic blood pressure, HCys, total cholesterol, LDL, glucose and glycated haemoglobin concentrations tending to the upper limit of acceptability or slightly above. Hypertension, HUA, HHCys, dyslipidemia, type 2 diabetes, and MS were present in 351 (30.8%), 241 (21%), 606 (53%), 643 (56.3%), 172 (15%) and 503 (44%) patients, respectively.

Table 1
Anthropometric and biochemical data of all the 1141 patients, divided by gender and Metabolic Syndrome (MS)

Variable Reference interval All patients (1141) Females (n = 853) Males (n = 288) p value MS, no (n = 638) MS, yes (n = 503) p value

Age (years) 16–84 55±14 56 [47;65.5] 57 [45;66] 0.702 52 [43;61] 61 [51;69] < 0.001

Sex, n (%) - - - 517 (81) F 121 (19) M 336 (67) F 167 (34) M < 0.001

Weight (kg) 87.0±16.7 81.0 [72.0;91.4] 96.5 [89.0;109.4] < 0.001 80.0 [71.0;90.4] 91.5 [81.0;102.0] < 0.001

WC (cm) < 89 F < 102 M 100±13.8 96 [88;105] 109 [101;118] < 0.001 93 [86;101] 107 [100;116] < 0.001

BMI (kg/m²) 18.5–25 32±5.4 32.0 [28.8;35.8] 32.9 [>30.3;36.5] < 0.001 30.5 [28.0;33.8] 34.5 [31.9;38.4] < 0.001

BMI > 30, n (%) 782 (68.5) 560 (66) 222 (77) < 0.001 346 (54) 436 (87) < 0.001

SBP (mmHg) 115–120 126±14 125 [115;135] 127.5 [120;140] < 0.001 120 [110;130] 130 [120;140] < 0.001

DBP (mmHg) 75–80 78±8 80 [70;80] 80 [75;85] < 0.001 75 [70;80] 80 [75;85] < 0.001

Hypertension, n (%) 351 (30.8) 237 (28) 114 (39.5) < 0.001 11 (1.8) 340 (67.5) < 0.001

Uric acid (mg/dl) 2.4–5.7 F 3.4–7.0 M 5.1±1.3 4.7 [4.0;5.5] 6.0 [5.2;6.9] < 0.001 4.7 [4.0;5.6] 5.5 [4.5;6.4] < 0.001

HUA, n (%) 241 (21) 169 (20) 72 (25) 0.075 89 (14) 152 (30) < 0.001

CRP (mg/dl) 0.5–1.0 0.44±0.6 0.27 [0.13;0.58] 0.23 [0.12;0.43] 0.003 0.23 [0.11;0.47] 0.30 [0.16;0.63] < 0.001

Fibrinogen (mg/dl) 150–400 330±68 332 [290;374] 305.5 [267;350] < 0.001 322 [280;358] 330 [289;377] 0.002

Creatinine (mg/dl) 0.8–1.2 0.79±0.2 0.72 [0.64;0.81] 0.93 [0.81;1.04] < 0.001 0.75 [0.66;0.85] 0.79 [0.67;0.92] < 0.001

HCys (μmol/l) 4.0–12.0 12.0±4.1 10.4 [8.7;12.5] 12.6 [>10.7;15.5] < 0.001 10.4 [8.8;12.6] 11.6 [9.5;14.1] < 0.001

HHCys, n (%) 606 (53) 416 (49) 190 (66) < 0.001 299 (47) 307 (61) < 0.001

Triglycerides (mg/dl) < 170 114±57 100 [74;128] 112.5 [79;153] < 0.001 87 [67;113] 121 [94;165] < 0.001

Total cholesterol (mg/dl) < 200 203±39 206 [183;229] 189 [168;215] < 0.001 205 [179;229] 198 [175;228] 0.069

HDL (mg/dl) > 65 F > 55 M 59±15 60 [52;72] 48 [40;57] < 0.001 63 [54;73] 51 [43;60] < 0.001

LDL (mg/dl) < 130 129±34 129 [107;152.5] 122.5 [103;143] 0.011 126 [107;148] 128 [103;152] 0.616

Dyslipidemia, n (%) 643 (56.3) 501 (58.8) 141 (49) 0.005 335 (52.5) 307 (61) 0.005

Glucose (mg/dl) 65–100 99±19.5 93 [87;102] 98.5 [25;108] < 0.001 90 [85;96] 103 [95;115] < 0.001

Insulin (μlU/ml) 2.6–25.0 14±9.7 10.9 [7.4;16.4] 13.7 [10.0;19.5] < 0.001 9.8 [6.8;13.1] 15.7 [10.2;22.4] < 0.001

Glycated Hb (mmol/mol) 20.0–42.0 40±7.6 38 [35;42] 38 [35;42] 0.710 37 [34;39] 42 [38;46] < 0.001

HOMA-IR 0.23–2.50 3.55±3.1 2.53 [1.64;4.08] 3.31 [2.41;5.02] < 0.001 2.15 [1.50;3.06] 4.07 [2.62;6.15] < 0.001

IR, n (%) 564 (49) 378 (44) 186 (64.5) < 0.001 216 (34%) 348 (70) < 0.001

T2DM, n (%) 172 (15) 115 (14) 57 (20) 0.013 14 (2%) 158 (31) < 0.001

MS, n (%) 503 (44) 336 (39) 167 (58) < 0.001 - - -

AST (U/l) 8–43 F 8–48 M 21±8.1 19 [16;22] 22 [18;26] < 0.001 19 [16;22] 20 [17;25] < 0.001

ALT (UI/l) 7–45 F 7–55 M 24±14.6 18 [15;25] 26 [20;34] < 0.001 18 [14;25] 23 [17;32] < 0.001

GGT (U/l) 4–18 F 6–28 M 24±26.1 16 [12;23] 23 [18;35] < 0.001 15 [11;22] 21 [16;33] < 0.001

Variable	Reference interval	All patients (1141)	Females (n = 853)	Males (n = 288)	p value	MS, no (n = 638)	MS, yes (n = 503)	p value
Age (years)	16–84	55±14	56 [47;65.5]	57 [45;66]	0.702	52 [43;61]	61 [51;69]	< 0.001
Sex, n (%)			-	-	-	517 (81) F 121 (19) M	336 (67) F 167 (34) M	< 0.001
Weight (kg)		87.0±16.7	81.0 [72.0;91.4]	96.5 [89.0;109.4]	< 0.001	80.0 [71.0;90.4]	91.5 [81.0;102.0]	< 0.001
WC (cm)	< 89 F < 102 M	100±13.8	96 [88;105]	109 [101;118]	< 0.001	93 [86;101]	107 [100;116]	< 0.001
BMI (kg/m²)	18.5–25	32±5.4	32.0 [28.8;35.8]	32.9 [>30.3;36.5]	< 0.001	30.5 [28.0;33.8]	34.5 [31.9;38.4]	< 0.001
BMI > 30, n (%)		782 (68.5)	560 (66)	222 (77)	< 0.001	346 (54)	436 (87)	< 0.001
SBP (mmHg)	115–120	126±14	125 [115;135]	127.5 [120;140]	< 0.001	120 [110;130]	130 [120;140]	< 0.001
DBP (mmHg)	75–80	78±8	80 [70;80]	80 [75;85]	< 0.001	75 [70;80]	80 [75;85]	< 0.001
Hypertension, n (%)		351 (30.8)	237 (28)	114 (39.5)	< 0.001	11 (1.8)	340 (67.5)	< 0.001
Uric acid (mg/dl)	2.4–5.7 F 3.4–7.0 M	5.1±1.3	4.7 [4.0;5.5]	6.0 [5.2;6.9]	< 0.001	4.7 [4.0;5.6]	5.5 [4.5;6.4]	< 0.001
HUA, n (%)		241 (21)	169 (20)	72 (25)	0.075	89 (14)	152 (30)	< 0.001
CRP (mg/dl)	0.5–1.0	0.44±0.6	0.27 [0.13;0.58]	0.23 [0.12;0.43]	0.003	0.23 [0.11;0.47]	0.30 [0.16;0.63]	< 0.001
Fibrinogen (mg/dl)	150–400	330±68	332 [290;374]	305.5 [267;350]	< 0.001	322 [280;358]	330 [289;377]	0.002
Creatinine (mg/dl)	0.8–1.2	0.79±0.2	0.72 [0.64;0.81]	0.93 [0.81;1.04]	< 0.001	0.75 [0.66;0.85]	0.79 [0.67;0.92]	< 0.001
HCys (μmol/l)	4.0–12.0	12.0±4.1	10.4 [8.7;12.5]	12.6 [>10.7;15.5]	< 0.001	10.4 [8.8;12.6]	11.6 [9.5;14.1]	< 0.001
HHCys, n (%)		606 (53)	416 (49)	190 (66)	< 0.001	299 (47)	307 (61)	< 0.001
Triglycerides (mg/dl)	< 170	114±57	100 [74;128]	112.5 [79;153]	< 0.001	87 [67;113]	121 [94;165]	< 0.001
Total cholesterol (mg/dl)	< 200	203±39	206 [183;229]	189 [168;215]	< 0.001	205 [179;229]	198 [175;228]	0.069
HDL (mg/dl)	> 65 F > 55 M	59±15	60 [52;72]	48 [40;57]	< 0.001	63 [54;73]	51 [43;60]	< 0.001
LDL (mg/dl)	< 130	129±34	129 [107;152.5]	122.5 [103;143]	0.011	126 [107;148]	128 [103;152]	0.616
Dyslipidemia, n (%)		643 (56.3)	501 (58.8)	141 (49)	0.005	335 (52.5)	307 (61)	0.005
Glucose (mg/dl)	65–100	99±19.5	93 [87;102]	98.5 [25;108]	< 0.001	90 [85;96]	103 [95;115]	< 0.001
Insulin (μlU/ml)	2.6–25.0	14±9.7	10.9 [7.4;16.4]	13.7 [10.0;19.5]	< 0.001	9.8 [6.8;13.1]	15.7 [10.2;22.4]	< 0.001
Glycated Hb (mmol/mol)	20.0–42.0	40±7.6	38 [35;42]	38 [35;42]	0.710	37 [34;39]	42 [38;46]	< 0.001
HOMA-IR	0.23–2.50	3.55±3.1	2.53 [1.64;4.08]	3.31 [2.41;5.02]	< 0.001	2.15 [1.50;3.06]	4.07 [2.62;6.15]	< 0.001
IR, n (%)		564 (49)	378 (44)	186 (64.5)	< 0.001	216 (34%)	348 (70)	< 0.001
T2DM, n (%)		172 (15)	115 (14)	57 (20)	0.013	14 (2%)	158 (31)	< 0.001
MS, n (%)		503 (44)	336 (39)	167 (58)	< 0.001	-	-	-
AST (U/l)	8–43 F 8–48 M	21±8.1	19 [16;22]	22 [18;26]	< 0.001	19 [16;22]	20 [17;25]	< 0.001
ALT (UI/l)	7–45 F 7–55 M	24±14.6	18 [15;25]	26 [20;34]	< 0.001	18 [14;25]	23 [17;32]	< 0.001
GGT (U/l)	4–18 F 6–28 M	24±26.1	16 [12;23]	23 [18;35]	< 0.001	15 [11;22]	21 [16;33]	< 0.001

In order, variable interval reference or cut off, mean and standard deviation/frequencies (%) of all patients, median (ranges)/frequencies (%) of females and males values, p-value, median (ranges)/frequencies (%) of patients with and without Metabolic Syndrome and p-value. ALT, alanine transaminase; AST, aspartate transaminase; BMI, body mass index; CRP, C reactive protein; DBP, diastolic blood pressure; GGT, γ-Glutamyltransferase; Glycated Hb, glycated heamoglobin; HDL, high density lipoproteins; HHCys, hyperhomocysteinemia; HOMA-IR, homeostasis model assessment index; HUA, hyperuricemia; IR, insulin resistance; LDL, low density lipoproteins; MS, metabolic syndrome; SBP, systolic blood pressure; T2DM, type 2 diabetes mellitus; WC, waist circumference.

As regards gender, Table 1 shows that statistical differences were observed for each parameter analyzed, except for age (p = 0.702), HUA (p = 0.075), and glycated haemoglobin values (p = 0.710). Moreover, women had median higher values of CRP (p = 0.003), fibrinogen, total cholesterol, HDL, and LDL (all p < 0.001) than men. On the other hand, dyslipidemia and HHCys were less frequent in men (p < 0.005 and p < 0.001, respectively) than in women, while creatinine levels were higher in males (p < 0.001) than in females.

As regards the MS presence (Table 1), 503 patients (44%), both overweight and with obesity, had MS presenting a typical profile due to values above the reference thresholds for each variable analyzed except total cholesterol and LDL.

Table 2 shows the population stratified in relation to BMI: 359 (31.5%) patients with a BMI 25–30 kg/m² and 782 PwO (68.5%) with a BMI > 30 kg/m². Although the two compared cohorts were not different in age (p = 0.138), the PwO group had a worse glycaemic and blood pressure profile together higher CRP levels than the other group. Overall, hypertension (38%), type 2 diabetes (19.4%) and MS (55.8%) were found predominantly in patients with BMI > 30 kg/m² (all p < 0.001). No difference was found in creatinine (p = 0.703), total cholesterol (p = 0.676), LDL (p = 0.262) and AST (p = 0.422) levels. HUA was observed in 188 (24%) patients with BMI > 30 kg/m², despite an overall median value of 5.2 [4.2; 6.1] mg/dl but significantly different from the levels measured in the other group (p < 0.001). HHCys was found in 53%of patients, with a significantly higher percentage in the BMI > 30 kg/m² group (55.8%, p = 0.010, with median HCys values of 11.2 [9.2; 13.6] μmol/l, p < 0.001) compared to BMI 25–30 group.

Table 2

Anthropometric and biochemical data of all patients divided by BMI. Only PwO (BMI > 30) according to the presence or absence of Metabolic Syndrome (MS)

					BMI > 30
Variable	Reference interval	BMI 25–30 (n = 359)	BMI > 30 (n = 782)	p value	MS, no (n = 346)	MS, yes (n = 436)	p value
Age (years)	16–84	57 [48; 67]	60 [46;65]	0.138	50 [39;59]	60 [51;68]	< 0.001
Sex, n (%)	-	293 (34) F 560 (66) M	66 (23) F 222 (77) M	< 0.001	272 (79) F 74 (21) M	288 (66) F 148 (34) M	< 0.001
Weight (kg)	-	71.5 [66.8;78.0]	91.0 [82.5;101.1]	< 0.001	87.5 [81.0;98.1]	93.0 [84.5;105.0]	< 0.001
WC (cm)	< 89 F < 102 M	88 [82;94]	105 [98;113]	< 0.001	99 [93;108]	109 [102;118]	< 0.001
BMI (kg/m²)	18.5–25	28 [27;29]	34.3 [32;39]	< 0.001	33.5 [31.5;36.2]	35.5 [32.7;39.09]	< 0.001
SBP (mmHg)	115–120	120 [115;130]	125 [120;140]	< 0.001	120 [110;130]	130 [120;140]	< 0.001
DBP (mmHg)	75–80	75 [70;80]	80 [70;85]	< 0.001	80 [70;80]	80 [75;85]	< 0.001
Hypertension, n (%)		53 (14.8)	298 (38)	< 0.001	7 (2)	291 (67)	< 0.001
Uric acid (mg/dl)	2.4–5.7 F 3.4–7.0 M	4.8 [4.0;5.6]	5.2 [4.2;6.1]	< 0.001	4.8 [4.1;5.7]	5.5 [4.4;6.4]	< 0.001
HUA, n (%)		53 (14.8)	188 (24)	< 0.001	55 (16)	133 (30.5)	< 0.001
CRP (mg/dl)	0.5–1.0	0.16 [0.08;0.31]	0.32 [0.17;0.65]	< 0.001	0.32 [0.17;0.62]	0.32 [0.18;0.66]	0.692
Fibrinogen (mg/dl)	150 –400	313 [273;354]	330 [291;372]	< 0.001	328 [291;365]	333 [291;379]	0.183
Creatinine (mg/dl)	0.8–1.2	0.76 [0.67;0.86]	0.76 [0.67;0.89]	0.703	0.74 [0.66;0.85]	0.78 [0.67;0.92]	< 0.001
HCys (μmol/l)	4.0–12.0	10.4 [8.6;12.5]	11.2 [9.2;13.6]	< 0.001	10.7 [9.1;12.9]	11.6 [9.5;14.2]	< 0.001
HHCys, n (%)		170 (47.3)	436 (55.8)	0.010	170 (49)	266 (61)	< 0.001
Triglycerides (mg/dl)	< 170	85 [65;116]	109.5 [82.8;143.5]	< 0.001	93 [71;118]	122 [97;165]	< 0.001
Total cholesterol (mg/dl)	< 200	203 [177;228]	201 [>178;229]	0.676	204 [179;230]	198 [175;228]	0.211
HDL (mg/dl)	> 65 F > 55 M	62 [54;74]	55 [46;66]	< 0.001	61.5 [52;71.2]	51 [43;60]	< 0.001
LDL (mg/dl)	< 130	126 [105;147]	128.5 [106;150]	0.262	126.5 [106;149]	129 [104;153]	0.561
Dyslipidemia, n (%)		193 (53.8)	449 (57.4)	0.275	165 (47.7)	168 (38.5)	0.012
Glucose (mg/dl)	65–100	91 [85;97]	97 [90;106]	< 0.001	91 [85;97]	104 [96;117]	< 0.001
Insulin (μlU/ml)	2.6–25.0	8.3 [6.0;11.7]	13.7 [9.4;19.9]	< 0.001	11.5 [8.2;15.2]	16.2 [11.2;22.8]	< 0.001
Glycated Hb (mmol/mol)	20.0–42.0	37 [34;40]	39 [66;43]	< 0.001	37 [34;39]	42 [38;47]	< 0.001
HOMA-IR	0.23–2.50	1.87 [1.33;2.65]	3.32 [2.21;5.03]	< 0.001	2.60 [1.85;3.41]	4.22 [2.86;6.43]	< 0.001
IR, n (%)		91 (25)	473 (60)	< 0.001	160 (46)	313 (72)	< 0.001
T2DM (%)		20 (5.6)	152 (19.4)	< 0.001	6 (1.8)	146 (33)	< 0.001
MS, n (%)		67 (18.7)	436 (55.8)	< 0.001	-	-	-
AST (U/l)	8–43 U/l F 8–48 U/l M	19 [16;23]	19 [16;24]	0.422	19 [16;22]	20 [17;25]	< 0.001
ALT (UI/l)	7–45 U/l F 7–55 U/l M	18 [14;25]	21 [16;29]	< 0.001	19 [15;26]	23 [18;33]	< 0.001
GGT (U/l)	4–18 U/l F 6–28 U/l M	15 [11;21]	19 [14;28]	< 0.001	16 [12;24]	21 [16;33]	< 0.001

In order, variable interval reference or cut off, median (ranges)/frequencies (%) of overweight (BMI 25–30 kg/m²) and with obesity patients (BMI > 30 kg/m²) values, p-value, median (ranges)/frequencies (%) of values of PwO (BMI > 30 kg/m²) with and without Metabolic Syndrome and p-value. ALT, alanine transaminase; AST, aspartate transaminase; BMI, body mass index; CRP, C reactive protein; DBP, diastolic blood pressure; GGT, γ-Glutamyltransferase; Glycated Hb, glycated heamoglobin; HDL, high density lipoproteins; HHCys, hyperhomocysteinemia; HOMA-IR, homeostasis model assessment index; HUA, hyperuricemia; IR, insulin resistance; LDL, low density lipoproteins; MS, metabolic syndrome; PwO, patients with obesity; SBP, Systolic blood pressure; T2DM, type 2 diabetes mellitus; WC, waist circumference.

The analysis of the variables within the PwO group identified two cohorts according to the presence or absence of MS (Table 2). The two groups were statistically different for most of the parameters analyzed, with, obviously, a more unfavourable situation for the patients with MS. No difference was found for CRP, fibrinogen, total cholesterol, and LDL concentrations. PwO with MS showed hypertension (67%), dyslipidemia (38.5%) and type 2 diabetes (38%), median UA levels of 5.5 [4.4; 6.4] mg/dl (vs 4.8 [4.1; 5.7] of PwO, p < 0.001) with 30.5%of them affected by HUA. At same time, PwO with MS had median blood HCys levels of 11.6 [9.5; 14.2] μmol/l (vs 10.7 [9.1; 12.9] μmol/l of PwO, p < 0.001) and 61%of them presented HHCys.

In addition, as shown in Table 3, 128 PwO had simultaneous presence of both HUA and HHCys: 97 with and 30 without MS. In particular, PwO with MS had a typical profile, characterized by major age, high body weight, with accumulation of abdominal fat, hypertension, altered liver enzymes and impaired glucose metabolism that in 36%of cases led to type 2 diabetes. No difference was found for the other parameters included, obviously, UA and HCys concentrations.

Table 3

Anthropometric and biochemical data of 128 PwO with simultaneous HHCys and HUA, divided according to the presence or absence of Metabolic Syndrome (MS)

	BMI > 30 + HUA + HHCys
Variable	MS, no (n = 30)	MS, yes (n = 97)	p value
Age (years)	50 [38;60]	62.5 [55;67]	< 0.001
Sex, n (%)	21 (70) F 9(30) M	53 (55) F 44 (45) M	0.201
Weight (kg)	86.2 [78.9;96.3]	96.5 [89.2;108.5]	< 0.001
WC (cm)	104 [95;110]	112 [104;121]	< 0.001
BMI (kg/m²)	34.2 [32.3;36.0]	36.2 [33.4;40.2]	0.011
SBP (mmHg)	120 [110;135]	135 [120;140]	0.005
DBP (mmHg)	80 [70;80]	80 [75;85]	0.015
Hypertension, n (%)	0 (0)	75 (77)	< 0.001
Uric acid (mg/dl)	6.6 [5.9;7.5]	7.1 [6.1;7.8]	0.192
Fibrinogen (mg/dl)	340 [295;397]	326 [288;378]	0.615
CRP (mg/dl)	0.43 [0.21;0.95]	0.38 [0.20;0.73]	0.516
Creatinine (mg/dl)	0.81 [0.75;0.90]	0.90 [0.76;1.03]	0.074
Homocysteine (μmol/l)	13.5 [11.8;14.7]	13.7 [11.8;16.9]	0.525
Triglycerides (mg/dl)	121 [93;149]	134 [103;187]	0.042
Total cholesterol (mg/dl)	207.4±41.2	207.1±41.0	0.967
HDL (mg/dl)	54.5 [47.5;67.2]	50.0 [42.0;62.0]	0.101
LDL (mg/dl)	133±37	135±37	0.804
Dyslipidemia, n (%)	17 (57)	62 (64)	0.617
Glucose (mg/dl)	91.5 [85.7;98.0]	104.0 [97.0;115.5]	< 0.001
Insulin (μlU/ml)	14.6 [11.6;19.0]	17.4 [13.2;28.0]	0.062
Glycated Hb (mmol/mol)	39.5 [35.8;41.0]	42.0 [38.5;45.0]	0.002
HOMA-IR	3.39 [2.61;4.38]	4.70 [3.31;7.84]	0.002
IR, n (%)	22 (73)	77 (79)	0.655
T2DM, n (%)	0 (0)	35 (36)	< 0.001
AST (U/l)	20.5 [17.8;24.0]	21.0 [18.0;28.0]	0.223
ALT (UI/l)	19.5 [15.5;28.1]	23 [18;33]	0.037
GGT (U/l)	19.0 [14.8;23.0]	24.0 [18.0;42.0]	0.010

ALT, alanine transaminase; AST, aspartate transaminase; BMI, body mass index; CRP, C reactive protein; DBP, diastolic blood pressure; GGT, γ-Glutamyltransferase; Glycated Hb, glycated heamoglobin; HDL, high density lipoproteins; HHCys, hyperhomocysteinemia; HOMA-IR, homeostasis model assessment index; HUA, hyperuricemia; IR, insulin resistance; LDL, low density lipoproteins; PwO, patients with obesity; SBP, systolic blood pressure; T2DM, type 2 diabetes mellitus; WC, waist circumference.

As shown in Table 4, the Spearman analysis evaluated only the most important significant correlations in different groups and subgroups. Positive correlation between UA and HCys levels in the group of all patients and in all the other groups analysed was identified. Moreover, other correlations between HCys/CRP, HCys/Fibrinogen, UA/CRP, UA/Fibrinogen, UA/systolic blood pressure (SPB), UA/diastolic blood pressure (DBP), UA/HDL, UA/LDL, UA/total cholesterol and UA/triglycerides were tested in all groups. No significant correlation between HCys/CRP, and HCys/Fibrinogen were found, while UA/Fibrinogen correlated only in women (data not shown). In addition, UA/SPB correlated in PwO, in patients without MS, and in PwO without MS. Finally, a strong correlation was found between UA/HDL and UA/triglycerides in all groups analyzed and between UA/LDL in PwO. After multivariate adjustment for creatinine, BMI, age, gender, CRP, SBP, DBP, HDL, LDL, and triglycerides, HCys concentrations still represented an independent determinant factor affecting UA levels in the study population (T value 3.5, p < 0.001).

Table 4

Spearman correlation analysis in different patients groups and patients subgroups

Group/subgroups (n)	HCys/UA		UA/CRP		UA/SBP		UA/DBP		UA/HDL		UA/LDL		UA/total cholesterol		UA/TG
	rho	p value	rho	p value	rho	p value	rho	p value	rho	p value	rho	p value	rho	p value	rho	p value
All patients (1141)	0.314	< 0.001	0.119	< 0.001	0.117	< 0.001	0.122	< 0.001	–0.249	< 0.001	0.064	0.030	0.009	0.777	0.314	< 0.001
Gender
Males (288)	0.262	< 0.001	0.142	0.016	–0.013	0.827	0.056	0.346	–0.172	0.004	0.085	0.153	0.059	0.320	0.266	< 0.001
Females (853)	0.204	< 0.001	0.186	< 0.001	0.117	< 0.001	0.090	0.009	–0.080	0.020	0.110	0.002	0.108	0.002	0.300	< 0.001
BMI
< 30 (359)	0.294	< 0.001	0.046	0.389	0.090	0.092	0.122	0.021	–0.187	< 0.001	0.033	0.535	0.004	0.938	0.289	< 0.001
> 30 (782)	0.305	< 0.001	0.089	0.013	0.102	0.004	0.096	0.007	–0.239	< 0.001	0.073	0.043	0.010	0.776	0.287	< 0.001
MS
No (638)	0.253	< 0.001	0.113	0.004	0.090	0.024	0.073	0.067	–0.173	< 0.001	0.050	0.211	0.016	0.683	0.261	< 0.001
Yes (503)	0.309	< 0.001	0.064	0.149	–0.026	0.539	0.062	0.168	–0.143	0.001	0.072	0.105	0.028	0.533	0.197	< 0.001
BMI > 30 + MS
No (346)	0.245	< 0.001	0.102	0.059	0.093	0.08	0.032	0.554	–0.239	< 0.001	0.045	0.373	–0.008	0.885	0.269	< 0.001
Yes (436)	0.309	< 0.001	0.084	0.084	–0.011	0.810	0.061	0.202	–0.122	0.011	0.085	0.074	0.045	0.353	0.186	< 0.001

BMI, body mass index; CRP, C reactive protein; DBP, diastolic blood pressure; HDL, high density lipoproteins; LDL, low density lipoproteins; MS, metabolic syndrome; SBP, systolic blood pressure; TG, triglycerides.

4 Discussion

The present study showed a significant positive correlation between HCys and UA levels in a group of patients with obesity tested at an Italian Obesity and Work Center and in the subgroup of PwO with MS. This correlation could suggest the clinical usefulness of monitoring UA and HCys concentrations in the prevention of CVR in PwO and, especially, in PwO with MS.

Central obesity increases CVR by means of classical (dyslipidemia, hypertension, glucose dysmetabolism) and less conventional mechanisms (i.e. HHCys and oxidative stress [23]. In fact, HHCys has been suggested as a potential marker for atherosclerosis progression in patients with MS as it correlates positively with hypertension and hyperlipoproteinemia [24].

Genetic background, vitamin deficiencies, especially B vitamins, as well as preserved function of kidney, are factors that directly affect HCys level [11]. The genetic status of HCys or the HCys-related vitamin levels of the patients were not evaluated in this study as, indeed, these panels are rarely considered in some studies, unless explicitly requested, because they are not part of the routine examinations. On the other hand, as well documented, abdominal obesity can cause an increase in HCys levels. In fact, it is a source of prothombogenic and inflammatory factors, leading to disorders of glucose and insulin metabolism, hypertension, HUA, microalbuminuria, liver disease and HHCys. Therefore, it has been reported that PwO have an increased CVR when compared to normal weight patients [25]. Recently, plasma HCys concentration is commonly required as a useful marker to assess presence and/or development of CVR and various hypotheses have been made regarding the mechanism by which HHCys could induce vascular injury 11 [11]. Among them, endothelial prothrombotic activity and damage to endothelial cells by free radicals derived from oxidative stress, platelet accumulation, and inhibition of the activity of the enzyme nitric oxide synthesis have been included [6, 26].

Plasma HUA concentrations are also related to the development of the atherosclerosis through many mechanisms, including, as in the case of HHCys, endothelial dysfunction and reduction of nitric oxide availability [27].

In the present study the relationship between HCys and UA in patients with BMI > 25 kg/m² and, in particular, in PwO with and without MS were evaluated. It has been reported that PwO have a high risk of death for cardiovascular diseases [25] and MS can increase the risk of mortality.

At first, different subgroups were analyzed, based on gender, MS and BMI. Males and females had median UA levels within their respective reference ranges whereas significantly higher HCys levels were found in men than in women. Much evidence has shown that metabolism and HCys levels were different in the two sexes. Several preclinical [28] and clinical [3, 16] studies have reported that males have an increased risk of developing HHCys. In a murine model, Schwahn et al’s study reported that in males there is a greater activity of the enzymes involved in the pathway of remethylation (specifically betaine-homocysteine-methyltransferase), while in females the HCys flow through the trans-sulfuration pathways is greater [28]. Other clinical evidence suggests that among men, those with the MTHFR 677TT genotype have an elevated risk of developing HHCys and are more vulnerable to several factors (i.e. smoking and low folate levels) leading to HCys increasing effects. Among females (regardless of MTHFR genotype), smokers are the most at risk [3].

According to the literature [17], MS patients had higher concentrations of UA and HCys than patients without MS, with a high frequency of HUA and HHCys. In particular, PwO with MS, HUA and HHCys are characterized by hypertension and impaired glucose metabolism, and, consequently, leading to a higher risk of developing type-2 diabetes and related complications than PwO. Interestingly, a possible link between the two parameters (UA and HCys) is the adenosine molecule [16]. Briefly, HCys can metabolize through two different pathways, trans-sulfuration or remethylation. In the first case, HCys is converted to cysteine while, in the second pathway, HCys is converted into methionine which then receives an adenosine group from an adenosine triphosphate (ATP) molecule to give S-adenosyl methionine (SAM). SAM is converted to S-adenosyl- L-homocysteine (SAH), which is broken down into HCys and adenosine. The HCys cycle can then start over again whereas the adenosine, thus formed, can be metabolised to UA.

It has been reported that HCys and UA can be confounding factors of MS, as well as fibrinogen and CRP [29]. The present study highlighted the correlation between UA and HCys in all groups and subgroups analysed and not only in MS patients, while the correlation between UA and CRP was present only in patients without MS. The study population could help explain this evidence: patients were characterised by a BMI > 25 kg/m² and 68.5%affected by obesity. The relationship between HCys and UA in these patients may be due to an increase in remethylation pathways. In conditions of hypoxia or tissue ischemia, the synthesis and release of vascular adenosine are upregulated, causing an increase in its blood concentrations. As a result, adenosine is rapidly broken down into UA and, consequently, HCys accumulates [16].

In addition, HUA can also be caused by a genic component or by intensive activity of xanthine oxidoreductase (the most important enzyme of UA metabolism) or by a diet with excessive consumption of foods rich in purines (especially meat).

As reported by Tsushima et al’s study, PwO (due to hypoxia in adipose tissue and a chronic inflammatory state) have generally an increased activity of xanthine oxidoreductase that causes an increase of UA production and release [30]. As already mentioned, hypoxia increases synthesis and release of vascular adenosine, with conversion to UA and accumulation of HCys. For these mechanisms, PwO, especially those affected by MS, can have conditions of HUA and HHCys. These parameters are used also as markers of an initially inflammatory state, and could be a useful tool to accurately distinguish healthy from pathological patients [31].

In some studies with multi-variant testing the apparent correlation between HCys and UA is caused by renal function [32, 33]. However, in our population multiple regression analysis showed that the HCys represent an independent determinant for UA. The results of the present study, even if discordant with the literature, could probably depend on the younger patients than those analyzed by other research groups.

As previously reported in several studies, HCys levels has been identified as a potential marker of CVR in different pathological conditions [24, 34]. However, this is not the same for UA concentrations. The difficult relationship between UA and cardiovascular diseases is well reported by Ndrepepa’s study [35]. Several experimental and clinical studies have highlighted the potential mechanisms by which UA high concentrations exerts adverse effects on cardiovascular health. Among these mechanisms, increased oxidative stress, reduced availability of nitric oxide and endothelial dysfunction, inflammation, impaired metabolism are reported [27]. In the present study, analyses of the data showed that, already in overweight patients, there is a strong relationship between UA and blood pressure, a relationship that intensifies in PwO. Moreover, high levels of triglycerides and cholesterol are both CVR factors: UA levels correlate positively with triglycerides and negatively with HDL concentrations in all the subgroups analyzed.

5 Conclusion

The present study, carried on 1141 patients enrolled at an Italian Obesity and Work Center, showed the significant positive relationship between HCys and UA levels in PwO especially in those with MS. Normally, the assessment of plasma HCys levels is required in specific pathological conditions as an important CVR index. In the treatment of PwO, it is routinely required, because the obesity is a risk factor: the possibility to have a cardiovascular event increases considerably in presence of obesity, especially visceral obesity. On the other hand, plasma UA concentration is not routinely assessed for diagnosis of PwO even if the association between UA and hypertension [34, 36], triglycerides and HDL seems to suggest that the monitoring of the UA concentrations is also important in the diagnosis of CVR and is therefore to be included as a marker in the prevention panel.

In conclusion, even if the possible link between UA and HCys levels could be adenosine, the significant relationship between the two parameters, as reported in this study, can help the clinical evaluation of cardiovascular risk in obesity with and without metabolic syndrome.

Footnotes

Acknowledgments

The authors are very grateful to Prof Ms Catherine Ricci for linguistic consultation.

Foundings

No found have been received.

Conflicts of interest

The authors have no conflict of interest to report.

Funding

none.

Authors’ contributions

GF, VL and TAS designed and supervised the study. GF and VC statistically analyzed the data. PA and LV contributed to patients enrollment. TAS was responsible for blood clinical analyses. DG, CV and BF critically revised the paper. GF, VL and TAS wrote this article. VC and VL are last co-authors.

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