ArticlePDF Available

Plasma and urine metabolic profiles are reflective of altered beta-oxidation in non-diabetic obese subjects and patients with type 2 diabetes mellitus

Authors:

Abstract

The two primary pathophysiological characteristics of patients with type 2 diabetes mellitus (T2DM) are insulin resistance (IR) and beta cell dysfunction. It has been proposed that the development of IR is secondary to the accumulation of triacylglycerols and fatty acids in the muscle and liver, which is in turn thought to be secondary to an enzymatic defect in mitochondrial beta-oxidation. The purpose of the present study was to analyze the molecules of intermediary metabolism to determine if an alteration in mitochondrial function exists in T2DM patients and, if so, to determine whether this alteration is caused by excess nutrients or an enzymatic defect. Design and Methods: Seventy-seven subjects were recruited and divided into four groups (21 T2DM patients, 17 non-diabetic overweight/obese subjects, 20 offspring of T2DM patients, and 19 healthy subjects). Anthropometric parameters were determined by air plethysmography, and biochemical and metabolic parameters were measured, including 31 acylcarnitines (ACs) and 13 amino acids quantified by MS/MS and 67 organic acids measured by GC/MS. Results: Patients with T2DM showed elevation of short-chain ACs (C2, C4), a glycogenic amino acid (valine), a glycogenic and ketogenic amino acid (tyrosine), and a ketogenic amino acid (leucine) as well as altered excretion of dicarboxylic acids. T2DM offspring with abnormal glucose tolerance test GTT showed increased levels of C16. Subjects in the obese group who were dysglycemic also showed altered urinary excretion of dicarboxylic acids and lower levels of a long-chain AC (C14:2). Conclusions: These results suggest that mitochondrial beta-oxidation is altered in T2DM patients and that the alteration is most likely caused by nutrient overload through a different pathway from that observed in obese subjects.
Plasma and urine metabolic profiles are reflective of
altered beta-oxidation in non-diabetic obese subjects
and patients with type 2 diabetes mellitus
Jesús Zacarías Villarreal-Pérez1
Email: zacvilla@yahoo.com.mx
Jesús Zacarías Villarreal-Martínez2
Email: chuyzacarias@hotmail.com
Fernando Javier Lavalle-González1
Email: drfernandolavalle@hotmail.com
María del Rosario Torres-Sepúlveda3
Email: qcbrtorres@live.com.mx
Consuelo Ruiz-Herrera3
Email: c_ruiz99@yahoo.com.mx
Ricardo Martín Cerda-Flores4
Email: ricardocerda_mx@yahoo.com.mx
Erick Rubén Castillo-García3
Email: qcberick_gen@hotmail.com
Irám Pablo Rodríguez-Sánchez3
Email: iramrodriguez@gmail.com
Laura Elia Martínez deVillarreal3*
* Corresponding author
Email: laelmar@yahoo.com.mx
1 Universidad Autónoma de Nuevo León, Hospital Universitario, Dr. José
Eleuterio González”, Servicio de Endocrinología, Monterrey, Nuevo León 64460,
México
2 Departamento de Medicina Interna, Universidad Autónoma de Nuevo León,
Hospital Universitario, Dr. José Eleuterio González”, Monterrey, Nuevo León
64460, México
3 Departamento de Genética, Universidad Autónoma de Nuevo León, Hospital
Universitario, Dr. José Eleuterio González”, Av. Gonzalitos s/n, Colonia Mitras
Centro, Monterrey, Nuevo León 64460, México
4 Universidad Autónoma de Nuevo León, Facultad de Enfermería, Avenida
Gonzalitos, 1500 Norte, Col. Mitras Centro, Monterrey, NL, México
Abstract
Objectives
The two primary pathophysiological characteristics of patients with type 2 diabetes mellitus
(T2DM) are insulin resistance (IR) and beta cell dysfunction. It has been proposed that the
development of IR is secondary to the accumulation of triacylglycerols and fatty acids in the
muscle and liver, which is in turn thought to be secondary to an enzymatic defect in
mitochondrial beta-oxidation. The purpose of the present study was to analyze the molecules
of intermediary metabolism to determine if an alteration in mitochondrial function exists in
T2DM patients and, if so, to determine whether this alteration is caused by excess nutrients or
an enzymatic defect
Design and methods
Seventy-seven subjects were recruited and divided into four groups (21 T2DM patients, 17
non-diabetic overweight/obese subjects, 20 offspring of T2DM patients, and 19 healthy
subjects). Anthropometric parameters were determined by air plethysmography, and
biochemical and metabolic parameters were measured, including 31 acylcarnitines (ACs) and
13 amino acids quantified by MS/MS and 67 organic acids measured by GC/MS
Results
Patients with T2DM showed elevation of short-chain ACs (C2, C4), a glycogenic amino acid
(valine), a glycogenic and ketogenic amino acid (tyrosine), and a ketogenic amino acid
(leucine) as well as altered excretion of dicarboxylic acids. T2DM offspring with abnormal
glucose tolerance test GTT showed increased levels of C16. Subjects in the obese group who
were dysglycemic also showed altered urinary excretion of dicarboxylic acids and lower
levels of a long-chain AC (C14:2)
Conclusions
These results suggest that mitochondrial beta-oxidation is altered in T2DM patients and that
the alteration is most likely caused by nutrient overload through a different pathway from that
observed in obese subjects.
Keywords
Acetylcarnitine, Butyrylcarnitine, T2DM, Beta-oxidation defect, Non-Diabetic Obese, Air
plethysmography
Introduction
Type 2 diabetes mellitus (T2DM) and obesity are two deleterious metabolic conditions [1]
whose incidence has increased worldwide in the last decade [2]. Both diet and sedentary
lifestyle are important risk factors for their development [3]. In Mexico, 74% of the adult
population is either overweight or obese, and 14.6% suffer from T2DM [4], which has a high
morbidity and mortality [2]. The primary pathophysiological characteristics in T2DM are
insulin resistance (IR) and beta-cell dysfunction [5,6]. IR is considered to be a state in which
peripheral tissues are rendered unresponsive to the glucose lowering, antilypolytic, and
anabolic properties of insulin, which is a hallmark of obesity and T2DM. IR is also accepted
as an early feature of T2DM because it typically appears one or two decades before the
manifestation of clinically overt diabetes [6].
Several studies suggest that IR occurs secondary to the accumulation of triacylglycerols and
fatty acids in the muscle and liver (lipotoxicity theory) [6]. Although the molecular
pathogenesis of lipotoxicity is not clear, it has been proposed that it occurs secondary to
altered mitochondrial function, resulting from a decline in beta-oxidation, an excess of non-
esterified fatty acids arriving at the mitochondria, or both [7]. Several reports indicate that
there is an increased rate of beta-oxidation in obese individuals as well as in T2DM patients
in a feeding state, whereas the rate of beta-oxidation is reduced during fasting [8]. Although
the mechanisms of this reduction are unknown, it has been proposed that inhibition of
carnitine palmitoyltransferase-1 (CPT1) as a result of increasing levels of malonyl coenzyme
A (malonyl CoA) could be responsible for the decreased beta-oxidation activity [9]. Recent
studies have suggested that lipid accumulation results from a lower oxidative capacity of the
mitochondria [7] or reduced activity of the tricarboxylic acid cycle [6]. Another possible
explanation for this reduction in beta-oxidation is an excessive increase in the delivery of
fatty acids to the mitochondria [10].
Defects in the beta-oxidation of fatty acids can be evaluated based on acylcarnitine (AC)
levels measured by tandem mass spectrometry, which is widely used in neonatal screening
for fatty acid oxidation disorders and organic acidemias [11,12].
This methodology has also been used to analyze mitochondrial function in diabetic patients.
Recent reports indicate that there is an increase in the levels of long-, medium-, and short-
chain ACs in the blood of patients with T2DM and an elevation of long-chain ACs in obese
subjects [13].
We designed this study to quantify intermediate metabolites in plasma and urine to determine
if they reflect a beta-oxidation defect in in patients with T2DM and obese individuals and to
determine whether an excess of nutrients or a blockage of beta-oxidation is the cause of the
alteration. Additionally, we postulated that if there is an alteration in mitochondrial function
in T2DM patients, it should be present before T2DM presents; for this reason, we explored
beta-oxidation in the offspring of T2DM patients.
Materials and methods
Population
We performed a descriptive, comparative, non-blinded study that included 77 subjects (21
T2DM patients, 17 non-diabetic overweight/obese subjects, 20 non-diabetic offspring of
T2DM patients [the latter two groups have a higher risk of developing T2DM], and 19
healthy subjects). Subjects with diabetes were recruited during 2010 from the outpatient
diabetes clinic of the Endocrinology Service of the Dr. José E González University Hospital,
Universidad Autónoma de Nuevo León (UANL), Monterrey, México. Volunteer participants
were recruited from the University Hospital and Medical School population, either as
subjects at risk for developing T2DM (overweight/obese and offspring of T2DM patients) or
as controls. Written informed consent was obtained from all subjects, and the Health
Research Ethics Board of the UANL Medical School approved the study (Approval #: EN-
10-030).
Men and women over 18 years of age were included. Participants were assigned to one of
four groups: 1) patients with T2DM diagnosed according to the criteria established by the
American Diabetes Association; 2) non-diabetic subjects considered to be overweight/obese
with a body mass index (BMI) ≥25 kg/m2 and without a history of T2DM in a first-degree
relative; 3) non-diabetic individuals who had at least one parent diagnosed with T2DM; and
4) healthy individuals with a normal BMI (>20 and <25 kg/m2), a normal oral glucose
tolerance test (OGTT), and no history of T2DM. The group of healthy subjects was
designated as the control group. T2DM patients were required to discontinue medication (oral
hypoglycemic drugs) and should not have received any insulin the night before the study.
Anthropometric, biochemical, and metabolic parameters
Body composition was obtained by air impedance plethysmography (BOD POD). For the
biochemical parameters, 30 mL of venous blood was collected after a 12- to 14-hour fast.
Glucose levels, free fatty acids (FFAs), insulin, transaminases (AST, ALT), uric acid, urea
nitrogen, cholesterol, and alkaline phosphatase as well as a lipid profile were examined in
serum or plasma, depending on the kit used. The Homeostasis Model Assessment (HOMA)
and Matsuda indices were calculated [14].
Blood samples were collected from all subjects to measure the levels of 31 ACs, 13 amino
acids, pyruvate, lactate, and ketone bodies. An OGTT (standardized fasting) was performed
in all groups except for the T2DM group. For AC quantification, blood samples were
collected on filter paper (SS903) and analyzed by tandem mass spectrometry (MS/MS, API
2000, Perkin Elmer Sciex; full-scan, multiple-scan monitoring (MRM)).
A urine sample was collected for the measurement of 67 organic acids with a gas
chromatograph/mass spectrometer (CLARUS 500, Perkin-Elmer Corporation, Norwalk, CT,
USA). The procedure for the extraction of organic acids consisted of calculating the sample
volume, then adjusting the volume according to creatinine excretion, which should be twice
the volume containing 0.06 mg/100 g creatinine. Urinary organic acids were determined by
oximation. Extraction was performed with ethyl acetate. Derivatization was performed by
adding BSTFA-1% TMCS (N, O-bis (trimethylsilyl) trifluoroacetamide with 1%
trimethylchlorosilane) and heating to 60°C in a water bath. Following this, the extract in
solution was injected into the gas chromatograph. Finally, spectral analysis and identification
were performed using the NIST MS Search Program Version 2.0.
Statistical analysis
Each study group was compared with the control group. For quantitative parameters,
Student´s t-test was used, whereas Fisher´s exact test was used for qualitative measurements.
A P <0.05 was defined as significant. IBM SPSS 20 statistical software (IBM Corporation,
Somers, NY) was used for data analysis.
Results
In total, 111 biochemical and metabolic parameters, including ACs, amino acids, and organic
acids, were measured in all groups. Comparison of the study groups with the control group
showed that in the three groups of cases, the average BMI, anthropometric parameters
obtained by BOD POD, and ages were higher.
Tables 1, 2, and 3 provide the biochemical parameters and metabolites that displayed
significant differences between the case groups and the control group. Regarding biochemical
parameters, subjects with T2DM had basal glucose, insulin levels, and ketone bodies levels in
blood and a HOMA index that were significantly higher than those of healthy controls.
Triacylglycerol, acetylcarnitine (C2), butyrylcarnitine (C4), alanine, tyrosine, and the
branched chain amino acids leucine and valine (Table 1) were also significantly elevated in
this group.
Table 1 Comparison of anthropometric and biochemical measurements in T2DM
patients and the control group
T2DM patients
Control (n =19) (X + SD)
P value
(n =21) (X + SD)
Age
52 ± 11.1
24.3 ± 3.7
<0.005
BMI
32.4 ± 6.0
22.8 ± 1.4
<0.005
Waist cm
103.3 ± 13.8
70.0 ± 7.7
<0.005
Hip cm
109.0 ± 13.3
95.0 ± 7.7
<0.005
% Fat
42.0 ± 8.9
25.6 ± 9.8
<0.005
% Lean mass
58.0 ± 9.0
74.3 ± 9.9
<0.005
Total weight
84.2 ± 17.1
63.1 ± 9.2
<0.005
Glucose 0´
148.2 ± 51.4
83.9 ± 12.5
<0.005
Glucose 30´
ND
ND
ND
Glucose 60´
ND
ND
ND
Glucose 90´
ND
ND
ND
Glucose 120´
ND
ND
ND
Insulin 0´
15.6 ± 7.9
7.3 ± 2.0
<0.005
HOMA IR
5.4 ± 2.7
1.5 ± 0.44
<0.005
Free fatty acids
0.6 ± 0.2
0.5 ± 0.3
>0.05
Beta-hydroxybutyrate
0.2 ± 0.1
0.2 ± 0.04
>0.05
ALP
63 ± 17
62.10 ± 16.9
>0.05
Uric Acid
5.8 ± 1.5
5.2 ± 1.0
>0.05
Serum creatinine
0.7 ± 0.17
0.8 ± 0.15
>0.05
Cholesterol
202.5 ± 50.7
200.6 ± 39.6
>0.05
Total bilirubin
0.2 ± 0.10
0.3 ± 0.2
>0.05
Direct bilirubin
.05 ± .02
0.06 ± 0.03
>0.05
Indirect Bilirubin
0.15 ± 0.1
0.2 ± 0.1
>0.05
Total protein
8.1 ± 0 .7
8.5 ± 0.9
>0.05
Albumin
4.7 ± 0.5
5.13 ± 0.5
<0.05
Globulin
3.4 ± 0.4
3.4 ± 0.5
>0.05
AST
17 ± 11.5
10.4 ± 2.0
<0.05
ALT
14.5 ± 10.1
8.0 ± 2.6
<0.005
C4
0.24 ± 0.10
0.18 + 0.08
<0.05
C2
10.1 ± 2.2
8.7 ± 1.6
<0.005
Leu
117.7 ± 22.3
96.1 ± 23.7
<0.05
Tyr
51.3 ± 10.4
41.5 ± 11.0
<0.005
Val
165.2 ± 19.0
135.0 ± 31.0
<0.005
Gly
242.0 ± 36.2
226.5 ± 47.0
>0.05
Arg
27.5 ± 9.8
27.4 ± 7.8
>0.05
Cit
18.4 ± 4.7
17.5 ± 4.2
>0.05
Met
21.7 ± 5.1
22.4 ± 5.2
>0.05
Orn
83.7 ± 13.8
76.6 ± 9.6
>0.05
Phe
41.2 ± 6.2
39.3 ± 10.8
>0.05
Ala
288.8 ± 63.0
238.0 ± 44.2
<0.005
Table 2 Comparison of anthropometric and biochemical measurements in the
overweight/obese patient group and the control group
Overweight/obesity
Control (n =19) (X + SD)
(n =17) (X + SD)
Age
39.2 ± 14.0
24.3 ± 3.7
BMI
30.2 ± 7.4
22.8 ± 1.4
Waist cm
99.1 ± 17.6
70.0 ± 7.7
Hip cm
111.3 ± 11.8
95.0 ± 7.7
% Fat
37.3 ± 11.4
25.6 ± 9.8
% Lean mass
62.7 ± 11.4
74.3 ± 9.9
30.6 ± 12.1
18.1 ± 11.7
Total weight
84.1 ± 17.3
63.1 ± 9.2
Glucose O´
90.5 ± 11.9
83.9 ± 12.5
Glucose 30´
144.2 ± 34.6
131 ± 30.9
Glucose 60´
126.5 ± 53.5
113.9 ± 25.3
Glucose 90´
120.5 ± 48.8
109.27 ± 33.33
Glucose 120´
107.6 ± 46.4
94.9 ± 21.7
Insulin 0´
10.7 ± 7.0
7.3 ± 2.0
Insulin 30´
81.4 ± 51.5
56.7 ± 24.6
Insulin 60´
89.9 ± 92.4
57.9 ± 36.2
Insulin 90´
72.9 ± 63.3
54.8 ± 35.8
Insulin 120´
76.3 ± 69.67
41.4 ± 37.0
Matsuda index
4.9 ± 2.5
6.2 ± 1.8
HOMA IR
2.3 ± 1.3
1.5 ± 0.44
Free Fatty Acids
0.5 ± 0.20
0.5 ± 0.3
Beta-hydroxybutyrate
0.2 ± 0.05
0.2 ± 0.3
ALP
57.9 ± 13.1
62.16 + 16.9
Uric acid
6.3 ± 1.4
5.2 ± 1.0
Serum creatinine
0.9 ± 0.3
0.8 ± 0.15
Cholesterol
214.0 ± 66.8
200.6 ± 39.6
Total bilirubin
0.4 ± 0.3
0.3 ± 0.2
Direct bilirubin
0.05 ± 0.03
0.06 ± 0.03
Indirect bilirubin
0.3 ± 0.26
0.2 ± 0.18
Total protein
8.2 ± 1.07
8.5 ± 0.9
Albumin
4.9 ± 0.4
5.1 ± 0.5
Globulin
3.3 ± 0.62
3.4 ± 0.5
AST
16.1 ± 9.3
10.4 ± 2.0
ALT
10.4 ± 3.3
8.2 ± 2.6
C4
0.19 ± 0.11
0.18 ± 0.08
C2
8.5 ± 2.3
8.7 ± 1.6
Leu
95.3 ± 28.0
103.8 ± 21.5
Tyr
43.4 ± 10.8
48.2 ± 10.5
Val
126.1 ± 41.7
138.8 ± 34.2
Gly
210.8 ± 54.1
220.6 ± 38.4
Arg
24.3 ± 10.5
24.1 ± 6.25
Cit
17.7 ± 4.1
17.9 ± 6.25
Met
21.26 ± 5.7
23.5 ± 6.25
Orn
85.5 ± 23.4
80.2 ± 15.0
Phe
38.2 ± 8.5
41.1 ± 8.3
Ala
209.9 ± 52.4
238. ± 45.2
Table 3 Comparison of anthropometric and biochemical measurements in the T2DM
patient offspring group and the control group
T2DM patient’s offspring
Control (n =19) (X + SD)
P value
(n =20) (X + SD)
Age
37.15 ± 13.4
24.3 ± 3.7
<0.005
BMI
29.3 ± 6.0
22.8 ± 1.4
<0.001
Waist cm
95.3 ± 17.1
70.0 ± 7.7
<0.0005
Hip cm
106.0 + 17.7
95.0 ± 7.7
<0.005
% Fat
32.5 ± 11.2
25.6 ± 9.8
<0.05
% Lean Mass
67.5 ± 11.2
74.3 ± 9.9
<0.05
Total Weight
82.54 ± 21.67
63.1 ± 9.2
<0.0005
Glucose O
90.25 ± 11.47
83.9 ± 12.5
>0.05
Glucose 30´
140.7 ± 32.76
131 ± 30.9
>0.05
Glucose 60´
141.2 ± 40.0
113.9 ± 25.3
<0.05
Glucose 90´
128.5 ± 46.46
109.27 ± 33.33
>0.05
Glucose 120
120.05 ± 33.21
94.9 ± 21.7
<0.005
Insulin 0´
11.1 ± 4.9
7.3 ± 2.0
<0.0005
Insulin 30´
80.7 ± 49.8
56.7 ± 24.6
<0.05
Insulin 60´
87.7 ± 58.3
57.9 ± 36.2
<0.05
Insulin 90´
79.4 ± 57.2
54.8 ± 35.8
<0.05
Insulin 120´
73.2 ± 49.6
41.4 ± 37.0
<0.0005
Free fatty acids
0.62 ± 0.24
0.5 ± 0.3
>0.05
Beta-hydroxybutyrate
0.18 ± 0.10
0.2 ± 0.3
>0.05
ALP
58.5 + 20.17
58.6 ± 20.2
>0.05
Uric acid
6.21 ± 1.33
5.2 ± 1.0
<0.05
Serum creatinine
0.91 ± 0.17
0.8 + 0.15
>0.05
Cholesterol
198.65 ± 28.4
200.6 ± 39.6
>0.05
Total bilirubin
0.34 ± 0.21
0.3 ± 0.2
>0.05
Direct bilirubin
0.05 ± 0.04
0.06 ± 0.03
>0.05
Indirect bilirubin
0.28 ± 0.21
0.2 ± 0.18
>0.05
Total protein
8.38 ± 0.80
8.4 ± 0.9
>0.05
Albumin
4.98 ± 0.39
5.11 ± 0.5
>0.05
Globulin
3.39 ± 0.55
3.4 ± 0.5
>0.05
AST
14.85 ± 8.64
10.4 ± 2.0
<0.05
ALT
13.7 ± 8.11
8.2 ± 2.6
<0.0005
Triacylglycerol
154.2 ± 114.9
110.6 ± 71.2
>0.05
C4
0.17 ± 0.08
0.18 ± 0.08
>0.05
C2
9.14 ± 1.44
8.7 ± 1.6
>0.05
Leu
103.8 ± 21.52
96.1 ± 23.7
>0.05
Tyr
48.2 ± 10.5
41.5 ± 11.0
>0.05
Val
138.8 ± 34.2
135.0 ± 31.0
>0.05
Gly
220.6 ± 38.4
226.5 ± 47
>0.05
Arg
24.1 ± 7.3
27.4 ± 7.84
>0.05
Cit
17.9 ± 3.09
17.5 ± 4.2
>0.05
Met
23.5 ± 6.25
22.4 ± 5.2
>0.05
Orn
80.2 ± 15.0
76.6 ± 9.5
>0.05
Phe
41.1 ± 8.3
39.3 ± 10.8
>0.05
Ala
231.0 ± 45.23
238.0 ± 44.2
>0.05
In addition to differences in anthropometric measurements, non-diabetic overweight/obese
subjects only had an increased HOMA index; we did not observe elevations of
triacylglycerols, amino acids, or ACs (Table 2). In this group, six (35.3%) patients with pre-
diabetes (basal glucose =101 - 125 mg/dl and/or OGTT 120 min =141 - 199 mg/dl) showed a
decrease in the level of C14:2 (tetradecenoyl carnitine) in addition to glucose elevations at
30, 60, 90, and 120 min during the OGTT and elevation of insulin levels at 120 min
compared with the control group (Table 4).
Table 4 Comparison of anthropometric and biochemical measurements in the
dysglycemic patient group and the control group
Dysglycemic/obese
(n = 6 ) (X ± SD)
Dysglycemic/ offspring
Control
(n = 5 )
(n =19)
(X ± SD)
(X ± SD)
Age
53.0 ± 7.66 *
46.6 ± 12.0*
24.3 ± 3.7
BMI
33.2 ± 8.28*
33.8 ± 6.7*
22.8 ± 1.4
Waist cm
99.9 ± 14.7*
109.0 ± 20.9*
70 ± 7.7
Hip cm
107.2 ± 8.7*
116.2 ± 24.5
95 ± 7.7
% Lean mass
66.8 ± 7.9
62.8 ± 15.1
74.3 ± 9.9
Total weight
87.2 ± 21.8*
95.8 ± 26.0*
63.1 ± 9.2
Glucose O´
97.2 ± 16.5
100.6 ± 8.8*
83.9 ± 12.5
Glucose 30´
169.7 ± 35.3*
177 ± 39.91
131 ± 30.9
Glucose 60´
182.8 ± 55.0*
196.2 ± 23.8*
113.9 ± 25.3
Glucose 90´
171.0 ± 42.8*
198.0 ± 38.5*
109.27 ± 33.33
Glucose 120´
150.0 ± 45.9*
165.0 ± 20.92*
94.9 ± 21.7
Insulin 0´
16.0 ± 9.6
12.6 ± 5.6
7.3 ± 2.0
Insulin 30´
87.4 ± 42.6
98.7 ± 54.3
56.7 ± 24.6
Insulin 60´
153.2 ± 135.6
126.2 ± 56.4*
57.9 ± 36.2
Insulin 90´
130.3 ± 77.3
131.7 ± 59.0*
54.8 ± 35.8
Insulin 120´
132.2 ± 84.1*
109.1 ± 46.0*
41.4 ± 37.0
Matsuda Index
2.9 ± 2.1*
2.4 ± 1.0*
6.2 ± 1.8
HOMA IR
3.5 ± 1.5*
3.2 ± 1.5
1.5 ± 0.4
Free Fatty Acids
0.5 ± 0.3
0.7 ± 0.2
0.5 ± 0.3
Uric Acid
6.4 ± 1.4
7.12 ± 0.6*
5.2 ± 1.0
Serum Creatinine
0.9 ± 0.3
0.9 ± 0.2
0.8 ± 0.15
Cholesterol
234.5 ± 22.7*
180.8 ± 21.5
200.6 ± 39.6
AST
16.5 ± 7.6
18.2 ± 10.8
10.4 ± 2.0
ALT
12.0 ± 3.2*
19.4 ± 9.9
8.2 ± 2.6
Triacylglycerol
204.8 ± 80.0*
283.6 ± 177.3
110.6 ± 71.2
C4
0.18 ± 0.08
0.25 ± 0.13
0.18 ± 0.08
C2
8.4 ± 1.6
9.8 ± 1.05
8.7 ± 1.6
C16
0.74 ± 0.17
0.85 ± 0.14*
0.67 ± 0.17
C 14: 2
0.03 ± 0.02*
0.05 ± 0.03
0.06 ± 0.3
* P value: <0.05.
The non-diabetic offspring of T2DM patients showed higher blood glucose levels during the
OGTT at 60 and 120 min as well as increased insulin levels at 0, 60, 90, and 120 min relative
to the control group (Table 3). Additionally, the Matsuda and HOMA indices were lower and
higher, respectively, as compared to control group (Table 3). In this group, 14 (66%) patients
were overweight/obese, and 5 (25%) were pre-diabetic. The pre-diabetic offspring exhibited a
significant elevation of palmitoylcarnitine (C16) and decreased glycine as well as significant
differences in anthropometric measurements, insulin at time 0, and the HOMA index relative
to the control group (Table 4).
All case groups demonstrated a significant elevation of transaminases (AST and ALT),
although uric acid was only increased in the overweight/obese and offspring groups.
Analysis of the organic acids in urine showed the presence of intermediate metabolites of
glycolysis and the Krebs cycle including lactic, 3OH-butyric, succinic, adipic, palmitic, citric,
and phenyl acetic acids in all subjects in all four groups. Some metabolites were detected in a
limited number of study participants. A significantly higher proportion of subjects with
T2DM excreted 2OH-butyric acid relative to the control group (90% vs. 20%, P <0.05), and
none exhibited sebacic acid excretion, compared with 40% in the control group (P <0.05). A
lower number of obese subjects excreted suberic acid relative to the control group (36% vs.
89%, P <0.05). There were no differences in the excretion of organic acids between the
offspring of T2DM patients and the control group.
Discussion
The present study was conducted to obtain more information regarding biochemical and
metabolic parameters in T2DM patients and to compare these parameters with healthy
subjects to determine whether altered mitochondrial beta-oxidation, secondary to either an
overload of nutrients or an enzymatic defect, exists in these patients. Additionally, the study
examined whether subjects at risk for developing T2DM present metabolic alterations prior to
developing the disease.
In the present study all the anthropometric parameters (i.e., BMI, waist, %fat) were
significantly higher in the individuals of the case groups when comparing against the control
group. However, only the offspring of T2DM patients showed altered plasma glucose and
insulin levels during the OGTT; obese subjects did not.
In the biochemical measurements, transaminases (AST, ALT) were significantly higher in all
case groups than in controls. It has been reported that individuals with T2DM have a higher
incidence of liver function test abnormalities than individuals who do not have diabetes.
Additionally, mild chronic elevations of transaminases often reflect underlying insulin
resistance [15].
The elevation of transaminases in diabetics, overweight/obese individuals, and offspring of
diabetic patients found in the present study may reflect fatty acid accumulation in the liver
[16], although FFAs were not significantly elevated. It has been previously reported that
elevated ALT in non-diabetic Swedish men is a risk factor for T2DM, independent of obesity,
body fat distribution, plasma glucose, lipid, AST, bilirubin concentration, and family history
of diabetes. In another study, non-diabetic Pima Indians were followed for an average of 6.9
years to determine whether hepatic enzyme elevations could be linked to the development of
T2DM. At baseline, ALT, AST, and the OGTT were related to percent body fat. After
adjusting for age, sex, body fat, whole body insulin sensitivity, and acute insulin response,
only elevated ALT at baseline was associated with an increase in hepatic glucose output.
Prospectively, increasing ALT concentrations were associated with a decline in hepatic
insulin sensitivity and risk of T2DM. The authors concluded that higher ALT is a risk factor
for T2DM and indicates a potential role of increased hepatic gluconeogenesis and/or
inflammation in its pathogenesis [15]. Our results are in agreement with the aforementioned
studies because only subjects with dysglycemia showed increased ALT in the subgroup
analysis of the overweight/obese and offspring groups. As expected T2DM patients, showed
high plasma triacylglycerol concentration, as well as disglycemic subjects from the obese and
offspring groups..
It has been reported that an overload of mitochondrial lipid oxidation results in the
accumulation of β-oxidation intermediates (ACs) and the depletion of Krebs cycle
intermediates, leading to mitochondrial stress and activating currently unknown signaling
pathways that interfere with insulin action [6]. Reports regarding the elevation of β-oxidation
intermediates in diabetics are controversial. Shure et al. reported elevation of long-chain ACs
and decreased levels of short-chain ACs [17], whereas Adams et al. and Mihalik et al.
reported elevation of short-, medium- and long-chain ACs in diabetic patients [13,18]. In a
study with streptozotocin-induced diabetic rats, short-chain ACs (C2 and C4) was
significantly elevated In a recent study, considerably higher levels of short-chain ACs and
lower levels of some long-chain ACs were detected in T2DM patients and patients with
metabolic syndrome [19].
In the present study, T2DM patients showed elevated levels of short-chain ACs (C2 and C4)
in the blood as compared to healthy controls. Disglycemic offspring showed elevation of a
long-chain AC (C:16). Notably, in contrast to these groups, dysglycemic obese patients had
lower levels of a specific long-chain AC (C14:2), which suggests the involvement of the
same metabolic systems in a different manner, as postulated by Bene et al. 2013 [19].
Acetylcarnitine (C2) is the final metabolite of the beta-oxidation pathway, which produces
acetyl CoA as a substrate for the Krebs cycle, whereas butyrylcarnitine (C4) is a marker of
ketogenesis and mitochondrial beta-oxidation. C4 levels reflect the concentration of tissue
butyryl CoA, which is a metabolite of glutamate and alpha-ketoglutarate, both of which are
intermediate metabolites of the Krebs cycle [20]. These findings exclusively in the T2DM
group would indicate an increase in mitochondrial beta-oxidation [21].
We believe that the differences in the levels of ACs found in the aforementioned studies, may
be the result of the conditions or characteristics of the patients at the time of the study. In a
previous study (unpublished results), we observed elevations of short-, medium-, and long-
chain ACs in individuals with diabetes; however, in that study, patients had overt diabetes
and were naive to treatment, which is in contrast to the patients in the present study, who
were under treatment, and the differences among the reported studies could be related to the
time of diagnosis, drug use, or BMI.
The AC profile is used in neonatal screening as an early marker of fatty acid disorders such
as beta-oxidation enzymatic defects. The results of the present study do not support the
hypothesis that there is an enzymatic defect in beta-oxidation that leads to fatty acid
accumulation and precludes IR because the earlier manifestations of beta-oxidation overload
were observed in the offspring of T2DM patients, who were already pre-diabetic. The pre-
diabetic offspring showed significant elevation of long-chain fatty acid (C16) concentrations,
whereas euglycemic offspring only showed a higher HOMA index relative to the control
group, which suggests that some insulin resistance was already present. However, the
elevation of C16 could be an early marker for the risk of developing diabetes, as previously
reported by Zhao et al. [22].
T2DM encompasses not only changes in glucose metabolism but also alterations in fatty acid
and protein levels with subsequent metabolic alterations in the pathways involved [23]. The
branched-chain amino acids (BCAAs) leucine and valine are glycogenic and modulators of
insulin secretion. According to Wang et al. [17], hyperaminoacidemia can promote diabetes
via hyperinsulinemia.
In a previous report, Vannini P et al. reported that the BCAAs leucine and valine were
increased in diabetic patients, indicating impaired short-term metabolic control [24].
BCAAs contribute to glucose recycling via the glucose-alanine cycle. Under normal
conditions, alanine arising from BCAA nitrogen likely accounts for 25% of gluconeogenesis
from amino acids [25,26].
Elevation of BCAAs in IR adults independent of BMI in conjunction with increases in
plasma ACs derived from amino acid oxidation suggests an increase in amino acid flux [27].
In a recent report, leucine, valine, tyrosine, and phenylalanine were found to be significantly
associated with the incidence of diabetes [28]. In the present study, we observed a significant
elevation of leucine, valine, tyrosine, and alanine in diabetic patients, although in contrast to
the study of Wang, we did not find any association of the amino acid concentration pattern
with the prediction of diabetes. Subjects in our study who were at risk for developing diabetes
(overweight/obese and the offspring of T2DM subjects) did not show any increase in amino
acid levels. In a study with diabetic db-/db- mice, clear evidence of increased
gluconeogenesis was found, as demonstrated by strongly decreased concentrations of the
gluconeogenic amino acids alanine, glycine, and serine [15]. Although in the present study
we observed increased alanine in T2DM patients, dysglycemic obese subjects had lower
levels of glycine, perhaps as a sign of altered glucose metabolism.
Obesity and a family history of T2DM are highly associated with development of the disease.
The underlying mechanisms that trigger and exacerbate obesity-associated insulin resistance
and the transition to T2DM remain unclear [29]. It has been suggested that a chronic positive
energy balance and increased storage of energy as fat are linked to impaired glucose
homeostasis and the development of diabetes [29]. Obesity is caused by the excessive
accumulation of triacylglycerols, and its effects on the use and storage of various fuels
(glucose, fatty acids, and amino acids) result in abnormalities in metabolism [30]. In the
present study, several analytes such as transaminases, glucose, and insulin were elevated in
both the obese group and the offspring group, which suggests that these metabolic alterations
are already present in both groups. When we analyzed the pre-diabetic subjects, these
metabolic abnormalities were present, and markers of altered mitochondrial beta-oxidation
were also detected. We found a lower level of unsaturated long-chain fatty acids (C14:2) in
the obese group, which could indicate a reduction in long-chain fatty acid metabolism.
Increases in short-, medium-, and long-chain AC levels in diabetic individuals suggest a
different and more complex defect compared with that of obese subjects.
Organic acids exist as intermediate compounds in many biochemical pathways, (glycolysis,
glyconeogenesis, lipolysis). The Krebs cycle is the central metabolic pathway for energy
molecules, and deficiencies in any of the Krebs cycle enzymes can cause inefficient cycling
of organic acid intermediates, which consequently increase their concentration in the urine of
the affected individual. In our study, differential urinary excretion of dicarboxylic acids was
observed, whereas the excretion of adipic acid and 3OH-butyrate, which are indicators of
ketogenesis, was similar in all groups. Ketosis is secondary to the fasting state and is a
metabolic marker of fatty acid metabolism that is accompanied by excessive urinary
excretion of adipic (C6) and suberic acids (C8) [31]. In the present study, a significantly
lower proportion of obese subjects excreted suberic acid (C8) relative to the control group
(36% vs. 89%), and none of the T2DM patients excreted sebacic acid (C10). This result could
be related to a decrease in medium-chain fatty acids in T2DM patients, which has been
reported previously [17] .
The lack of sebacic acid (C10) excretion in diabetic subjects would indicate active lipid
metabolism, as this has been reported in association with starvation, fat feeding, or
experimental diabetes [32], as well as an elevated rate of beta-oxidation to form C6-C8 [33],
contrary to what we found in dysglycemic obese patients.
The increased urinary excretion of hydroxyisobutyric acid in T2DM patients, which reflects
an increase in serum C4 levels (derived from fatty acid oxidation or amino acid catabolism),
indicates an increased metabolism of fats or proteins.
Specific patterns were observed for each analyzed group, and patients with T2DM had an
abnormal AC pattern that suggests an increase in the substrate for mitochondrial beta-
oxidation. This alteration could be present at earlier stages of the disease because pre-diabetic
T2DM offspring showed increased levels of C16. The group of obese subjects also showed
altered urinary excretion of dicarboxylic acids and lower levels of the long-chain AC C14:2
when pre-diabetic, suggesting altered mitochondrial beta-oxidation. Our results are in
agreement with those reported by Koves, et al. (6), who suggested that there is a
mitochondrial substrate overload in T2DM patients.
Conclusion
Patients with T2DM exhibit defective beta-oxidation that suggests an overload of nutrients,
as shown by higher levels of TGL and elevation of acetylcarnitine and butyrylcarnitine (both
of which are derived from the final products of beta-oxidation) as well as augmented urinary
excretion of intermediate metabolites. This beta-oxidation defect could be present at earlier
stages of the disease because the pre-diabetic offspring of T2DM patients showed increased
levels of C16. Moreover, obese subjects also showed altered mitochondrial beta-oxidation as
well as altered urinary excretion of dicarboxylic acids and reduced levels of C14:2 only when
disglycemic, indicating differential involvement of the metabolic pathways.
Acknowledgements
The authors acknowledge the help of Michelle de J. Zamudio-Osuna, M.S., Brenda
Navarrete, M.D., and César Antonio Garza-Osorio, M.D. The authors also gratefully
acknowledge Sergio Lozano-Rodriguez, M.D., for his critical reading of the manuscript.
Funding
The work was performed using resources provided by each of the participating departments.
References
1. Galgani J, Diaz E: Obesity and fatty acids in the etiology of insulin resistance. Rev Med
Chil 2000, 128:13541360.
2. Aguilar-Salinas CA, Mehta R, Rojas R, Gomez-Perez FJ, Olaiz G, Rull JA: Management
of the metabolic syndrome as a strategy for preventing the macrovascular complications
of type 2 diabetes: controversial issues. Curr Diabetes Rev 2005, 1:145158.
3. Hu FB: Sedentary lifestyle and risk of obesity and type 2 diabetes. Lipids 2003,
38:103108.
4. Encuesta Nacional de Salud y Nutrición: Encuesta Nacional de Salud y Nutrición. In
2006. http://www.insp.mx/ensanut/ensanut2006.pdf.
5. Maassen JA, Romijn JA, Heine RJ: Fatty acid-induced mitochondrial uncoupling in
adipocytes as a key protective factor against insulin resistance and beta cell dysfunction:
a new concept in the pathogenesis of obesity-associated type 2 diabetes mellitus.
Diabetologia 2007, 50:20362041.
6. Koves TR, Ussher JR, Noland RC, Slentz D, Mosedale M, Ilkayeva O, Bain J, Stevens R,
Dyck JR, Newgard CB, et al: Mitochondrial overload and incomplete fatty acid oxidation
contribute to skeletal muscle insulin resistance. Cell Metab 2008, 7:4556.
7. Lieber CS, Savolainen M: Ethanol and lipids. Alcohol Clin Exp Res 1984, 8:409423.
8. Brands M, Verhoeven AJ, Serlie MJ: Role of mitochondrial function in insulin
resistance. Adv Exp Med Biol 2012, 942:215234.
9. Hesselink MK C, Mensink M, Schrauwen P: Lipotoxicity and mitochondrial
dysfunction in type 2 diabetes. Immunol Endoc Metab Agents Med Chem 2007, 7:317.
10. Goodpaster BH, Wolf D: Skeletal muscle lipid accumulation in obesity, insulin
resistance, and type 2 diabetes. Pediatr Diabetes 2004, 5:219226.
11. Zytkovicz TH, Fitzgerald EF, Marsden D, Larson CA, Shih VE, Johnson DM, Strauss
AW, Comeau AM, Eaton RB, Grady GF: Tandem mass spectrometric analysis for amino,
organic, and fatty acid disorders in newborn dried blood spots: a two-year summary
from the New England Newborn Screening Program. Clin Chem 2001, 47:19451955.
12. Spiekerkoetter U: Mitochondrial fatty acid oxidation disorders: clinical presentation
of long-chain fatty acid oxidation defects before and after newborn screening. J Inherit
Metab Dis 2010, 33:527532.
13. Adams SH, Hoppel CL, Lok KH, Zhao L, Wong SW, Minkler PE, Hwang DH, Newman
JW, Garvey WT: Plasma acylcarnitine profiles suggest incomplete long-chain fatty acid
beta-oxidation and altered tricarboxylic acid cycle activity in type 2 diabetic African-
American women. J Nutr 2009, 139:10731081.
14. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC:
Homeostasis model assessment: insulin resistance and beta-cell function from fasting
plasma glucose and insulin concentrations in man. Diabetologia 1985, 28:412419.
15. Harris EH: Elevated liver function tests in type 2 diabetes. Clin Diabetes 2005,
23:115119.
16. Begriche K, Massart J, Robin MA, Bonnet F, Fromenty B: Mitochondrial adaptations
and dysfunctions in nonalcoholic fatty liver disease. Hepatology 2013, 58:14971507.
17. Suhre K, Meisinger C, Doring A, Altmaier E, Belcredi P, Gieger C, Chang D, Milburn
MV, Gall WE, Weinberger KM, et al: Metabolic footprint of diabetes: a multiplatform
metabolomics study in an epidemiological setting. PLoS One 2010, 5:e13953.
18. Mihalik SJ, Goodpaster BH, Kelley DE, Chace DH, Vockley J, Toledo FG, DeLany JP:
Increased levels of plasma acylcarnitines in obesity and type 2 diabetes and
identification of a marker of glucolipotoxicity. Obesity (Silver Spring) 2010, 18:1695
1700.
19. Bene J, Marton M, Mohas M, Bagosi Z, Bujtor Z, Oroszlan T, Gasztonyi B, Wittmann I,
Melegh B: Similarities in serum acylcarnitine patterns in type 1 and type 2 diabetes
mellitus and in metabolic syndrome. Ann Nutr Metab 2013, 62:8085.
20. Fiehn O, Garvey WT, Newman JW, Lok KH, Hoppel CL, Adams SH: Plasma
metabolomic profiles reflective of glucose homeostasis in non-diabetic and type 2
diabetic obese African-American women. PLoS One 2010, 5:e15234.
21. Schooneman MG, Vaz FM, Houten SM, Soeters MR: Acylcarnitines: reflecting or
inflicting insulin resistance? Diabetes 2013, 62:18.
22. Zhao X, Fritsche J, Wang J, Chen J, Rittig K, Schmitt-Kopplin P, Fritsche A, Haring HU,
Schleicher ED, Xu G, Lehmann R: Metabonomic fingerprints of fasting plasma and spot
urine reveal human pre-diabetic metabolic traits. Metab 2010, 6:362374.
23. Wurtz P, Makinen VP, Soininen P, Kangas AJ, Tukiainen T, Kettunen J, Savolainen MJ,
Tammelin T, Viikari JS, Ronnemaa T, et al: Metabolic signatures of insulin resistance in
7,098 young adults. Diabetes 2012, 61:13721380.
24. Vannini P, Marchesini G, Forlani G, Angiolini A, Ciavarella A, Zoli M, Pisi E:
Branched-chain amino acids and alanine as indices of the metabolic control in type 1
(insulin-dependent) and type 2 (non-insulin-dependent) diabetic patients. Diabetologia
1982, 22:217219.
25. Ruderman NB: Muscle amino acid metabolism and gluconeogenesis. Annu Rev Med
1975, 26:245258.
26. Layman DK, Walker DA: Potential importance of leucine in treatment of obesity and
the metabolic syndrome. J Nutr 2006, 136:319S323S.
27. Huffman KM, Shah SH, Stevens RD, Bain JR, Muehlbauer M, Slentz CA, Tanner CJ,
Kuchibhatla M, Houmard JA, Newgard CB, Kraus WE: Relationships between circulating
metabolic intermediates and insulin action in overweight to obese, inactive men and
women. Diabetes Care 2009, 32:16781683.
28. Wang TJ, Larson MG, Vasan RS, Cheng S, Rhee EP, McCabe E, Lewis GD, Fox CS,
Jacques PF, Fernandez C, et al: Metabolite profiles and the risk of developing diabetes.
Nat Med 2011, 17:448453.
29. Adams SH: Emerging perspectives on essential amino acid metabolism in obesity and
the insulin-resistant state. Adv Nutr 2011, 2:445456.
30. Quiroga AD, Lehner R: Liver triacylglycerol lipases. Biochim Biophys Acta 1821,
2012:762769.
31. Gregersen N, Kolvraa S, Mortensen PB, Rasmussen K: C6-C10-dicarboxylic aciduria:
biochemical considerations in relation to diagnosis of beta-oxidation defects. Scand J
Clin Lab Invest Suppl 1982, 161:1527.
32. Mortensen PB: C6C10-dicarboxylic aciduria in starved, fat-fed and diabetic rats
receiving decanoic acid or medium-chain triacylglycerol. An in vivo measure of the rate
of beta-oxidation of fatty acids. Biochim Biophys Acta 1981, 664:349355.
33. Mortensen PB, Gregersen N: The biological origin of ketotic dicarboxylic aciduria. II.
In vivo and in vitro investigations of the beta-oxidation of C8-C16-dicarboxylic acids in
unstarved, starved and diabetic rats. Biochim Biophys Acta 1982, 710:477484.
... Typically, it is viewed that fasting fat oxidation is reduced in people with obesity and/or T2D (32). However, several studies indicate the rate of beta-oxidation is elevated in the fasted state in individuals with obesity and/or T2D (33). This elevated rate of fat breakdown to acetyl-CoA ultimately exceeds the capacity of the TCA cycle and/or electron transport chain and is associated with, in part, lipid accumulation in the form of acyl-carnitines (33). ...
... However, several studies indicate the rate of beta-oxidation is elevated in the fasted state in individuals with obesity and/or T2D (33). This elevated rate of fat breakdown to acetyl-CoA ultimately exceeds the capacity of the TCA cycle and/or electron transport chain and is associated with, in part, lipid accumulation in the form of acyl-carnitines (33). This incomplete fat oxidation is clinically relevant as acyl-carnitines may reduce insulin signaling for glucose uptake in people with obesity. ...
Article
Purpose People characterized as late chronotype have elevated type 2 diabetes and cardiovascular disease risk compared to early chronotype. It is unclear how chronotype is associated with insulin sensitivity, metabolic flexibility, or plasma TCA cycle intermediates concentration, amino acids (AA), and/or beta-oxidation. Methods The Morning-Eveningness Questionnaire (MEQ) was used to classify adults with metabolic syndrome (ATP III Criteria) as either early (n=15 (13F), MEQ = 64.7±1.4) or late (n=19 (16F), MEQ = 45.5±1.3) chronotype. Fasting bloods determined hepatic (HOMA-IR) and adipose insulin resistance (Adipose-IR) while a 120 min euglycemic clamp (40 mU/m 2/min, 5 mmoL/L) was performed to test peripheral insulin sensitivity (glucose infusion rate (GIR)). Carbohydrate (CHOOX) and fat oxidation (FOX) as well as non-oxidative glucose disposal (NOGD) were also estimated (indirect calorimetry). Plasma TCA intermediates, AA, and acyl-carnitines were measured along with VO2max and body composition (DXA). Results There were no statistical differences in age, BMI, fat-free mass, VO2max or ATP III criteria between groups. Early chronotype, however, had higher peripheral insulin sensitivity (P=0.009) and lower HOMA-IR (P=0.02) and Adipose-IR (P=0.05) compared to late chronotype. Further, early chronotype had higher NOGD (P=0.008) and greater insulin-stimulated CHOOX (P=0.02). While fasting lactate (P=0.01), TCA intermediates (isocitrate, ꭤ-ketoglutarate, succinate, fumarate, malate (all P≤0.04)) and some AA (proline, isoleucine (P=0.003-0.05)) were lower in early chronotype, other AA (threonine, histidine, arginine (all P≤0.05)) and most acyl-carnitines were higher (P≤0.05) compared to late chronotype. Conclusions Greater insulin sensitivity and metabolic flexibility relates to plasma TCA concentration in early chronotype.
... Metabolites were measured in maternal urine samples collected at three time points during pregnancy (median GA in weeks (25th, 75th percentile): T1, 10 (8, 13); T2, 21 (19,22); T3, 29 (27,31)), Fig. 2. We used the AbsoluteIDQ® p180 Urine Extension kit (Biocrates Life Sciences AG, Innsbruck, Austria) to perform the targeted mass spectrometry (MS)-based quantitative metabolomic assay that directly measured metabolite concentrations in urine samples. This kit includes two separate parts that are analyzed by multiple reaction monitoring (MRM) tandem MS (MS\MS) analysis. ...
... Concentrations of long-chain acylcarnitines, C14, C14:1, C14:1-OH, C14:2-OH, C16:2, C16:2-OH, and C18:2 were lower in obese participants compared with normal/underweight participants. Changes to long-chain acylcarnitine concentrations have been observed in prior studies among non-pregnant people with reported lower urinary concentrations of C14:2 in individuals with obesity and abnormal blood sugar levels compared with nondiabetic individuals with normal BMIs and higher plasma C14:1 levels among adults with obesity and those with Type 2 diabetes compared to lean adults [31,32]. Involved in fatty acid metabolism, long-chain acylcarnitines have been linked with obesity as well as prediabetes, type 2 diabetes, and metabolic syndrome in non-pregnant individuals [32][33][34]. ...
Article
Full-text available
Background/Objectives Excessive gestational weight gain (GWG) and pre-pregnancy obesity affect a significant portion of the US pregnant population and are linked with negative maternal and child health outcomes. The objective of this study was to explore associations of pre-pregnancy body mass index (pBMI) and GWG with longitudinally measured maternal urinary metabolites throughout pregnancy. Subjects/Methods Among 652 participants in the New York University Children’s Health and Environment Study, a longitudinal pregnancy cohort, targeted metabolomics were measured in serially collected urine samples throughout pregnancy. Metabolites were measured at median 10 (T1), 21 (T2), and 29 (T3) weeks gestation using the Biocrates AbsoluteIDQ® p180 Urine Extension kit. Acylcarnitine, amino acid, biogenic amine, phosphatidylcholine, lysophosphatidylcholine, sphingolipid, and sugar levels were quantified. Pregnant people 18 years or older, without type 1 or 2 diabetes and with singleton live births and valid pBMI and metabolomics data were included. GWG and pBMI were calculated using weight and height data obtained from electronic health records. Linear mixed effects models with interactions with time were fit to determine the gestational age-specific associations of categorical pBMI and continuous interval-specific GWG with urinary metabolites. All analyses were corrected for false discovery rate. Results Participants with obesity had lower long-chain acylcarnitine levels throughout pregnancy and lower phosphatidylcholine and glucogenic amino acids and higher phenylethylamine concentrations in T2 and T3 compared with participants with normal/underweight pBMI. GWG was associated with taurine in T2 and T3 and C5 acylcarnitine species, C5:1, C5-DC, and C5-M-DC, in T2. Conclusions pBMI and GWG were associated with the metabolic environment of pregnant individuals, particularly in relation to mid-pregnancy. These results highlight the importance of both preconception and prenatal maternal health.
... Metabolites detected in urine reflect endogenous processes such as lipid metabolism and insulin resistance, as well as exogenous influences such as dietary intake and gut microbial activity [21][22][23][24]. For instance, studies have shown that obesity is associated with differences in acylcarnitines in urine, which likely reflect upstream impairments in fatty acid beta-oxidation, a key process in energy homeostasis [25]. Yet, a 2021 review of metabolomic studies of childhood obesity identified 33 studies measuring metabolomics in blood, while only 4 utilized urine [18]. ...
Article
Full-text available
Background/objective: Approximately one-third of pregnant individuals in the U.S. are affected by obesity, which can adversely impact the in utero environment and offspring. This study aimed to investigate the differences in urine metabolomics between children exposed and unexposed to maternal obesity. Methods: In a study nested within a larger pregnancy cohort of women–offspring pairs, we measured untargeted metabolomics using liquid chromatography–mass spectrometry in urine samples from 68 children at 4–8 years of age. We compared metabolite levels between offspring exposed to maternal obesity (body mass index [BMI] ≥ 30.0 kg/m2) vs. unexposed (maternal BMI 18.5–24.9 kg/m2) and matched them on covariates, using two-sample t-tests, with additional sensitivity analyses based on children’s BMI. This study reports statistically significant results (p ≤ 0.05) and potentially noteworthy findings (fold change > 1 or 0.05 < p < 0.15), considering compounds’ involvement in common pathways or similar biochemical families. Results: The mean (SD) maternal age at study enrollment was 28.0 (6.3) years, the mean child age was 6.6 (0.8) years, 56% of children were male, and 38% of children had a BMI in the overweight/obese range (BMI ≥ 85th percentile). Children exposed to maternal obesity had lower levels of 5-hydroxyindole sulfate and 7-hydroxyindole sulfate and higher levels of secondary bile acids. Phenylacetic acid derivatives were lower in offspring exposed to obesity and in offspring who had a current BMI in the overweight/obese range. Exposure to maternal obesity was associated with lower levels of androgenic steroid dehydroepiandrosterone sulfate (DHEA-S). Conclusions: In this preliminary study, children exposed to maternal obesity in utero had differences in microbiome-related metabolites in urine suggestive of altered microbial catabolism of tryptophan and acetylated peptides. Some of these differences were partially attributable to the offspring’s current BMI status. This study highlights the potential of urine metabolomics to identify biomarkers and pathways impacted by in utero exposure to maternal obesity.
... In mitochondria, multi-step reactions are implemented to generate acetyl-CoA, which provides energy by participating in the tricarboxylic acid cycle (TCA cycle) [27]. AcylC metabolism has been broadly examined regarding T2DM and insulin resistance in different populations [28][29][30][31][32]. However, we know little about the role of AcylCs in various stages of diabetes. ...
Article
Full-text available
Objective This study investigates the metabolic differences between normal, prediabetic and diabetic patients with good and poor glycaemic control (GGC and PGC). Design In this study, 1102 individuals were included, and 50 metabolites were analysed using tandem mass spectrometry. The diabetes diagnosis and treatment standards of the American Diabetes Association (ADA) were used to classify patients. Methods The nearest neighbour method was used to match controls and cases in each group on the basis of age, sex and BMI. Factor analysis was used to reduce the number of variables and find influential underlying factors. Finally, Pearson's correlation coefficient was used to check the correlation between both glucose and HbAc1 as independent factors with binary classes. Results Amino acids such as glycine, serine and proline, and acylcarnitines (AcylCs) such as C16 and C18 showed significant differences between the prediabetes and normal groups. Additionally, several metabolites, including C0, C5, C8 and C16, showed significant differences between the diabetes and normal groups. Moreover, the study found that several metabolites significantly differed between the GGC and PGC diabetes groups, such as C2, C6, C10, C16 and C18. The correlation analysis revealed that glucose and HbA1c levels significantly correlated with several metabolites, including glycine, serine and C16, in both the prediabetes and diabetes groups. Additionally, the correlation analysis showed that HbA1c significantly correlated with several metabolites, such as C2, C5 and C18, in the controlled and uncontrolled diabetes groups. Conclusions These findings could help identify new biomarkers or underlying markers for the early detection and management of diabetes.
... Out of the total studies, 33 specifically focused on blood (plasma, serum), 3 studies examined umbilical cord blood, and 1 study used saliva samples, while 6 studies utilized urine samples [10,[24][25][26][27][28][29]. Urine contains diverse metabolites reflecting the overall metabolic status of an individual, offering a comprehensive view of obesity-related changes including the excretion of metabolites derived from various biological processes [30]. Unlike plasma and serum, urine is less affected by factors such as diet, medication, or circadian rhythms [31]. ...
Article
Full-text available
Obesity in children and adolescents has increased globally. Increased body mass index (BMI) during adolescence carries significant long-term adverse health outcomes, including chronic diseases such as cardiovascular disease, stroke, diabetes, and cancer. Little is known about the metabolic consequences of changes in BMI in adolescents outside of typical clinical parameters. Here, we used untargeted metabolomics to assess changing BMI in male adolescents. Untargeted metabolomic profiling was performed on urine samples from 360 adolescents using UPLC–QTOF-MS. The study includes a baseline of 235 subjects in a discovery set and 125 subjects in a validation set. Of them, a follow-up of 81 subjects (1 year later) as a replication set was studied. Linear regression analysis models were used to estimate the associations of metabolic features with BMI z-score in the discovery and validation sets, after adjusting for age, race, and total energy intake (kcal) at false-discovery-rate correction (FDR) ≤ 0.1. We identified 221 and 16 significant metabolic features in the discovery and in the validation set, respectively. The metabolites associated with BMI z-score in validation sets are glycylproline, citrulline, 4-vinylsyringol, 3′-sialyllactose, estrone sulfate, carnosine, formiminoglutamic acid, 4-hydroxyproline, hydroxyprolyl-asparagine, 2-hexenoylcarnitine, L-glutamine, inosine, N-(2-Hydroxyphenyl) acetamide glucuronide, and galactosylhydroxylysine. Of those 16 features, 9 significant metabolic features were associated with a positive change in BMI in the replication set 1 year later. Histidine and arginine metabolism were the most affected metabolic pathways. Our findings suggest that obesity and its metabolic outcomes in the urine metabolome of children are linked to altered amino acids, lipid, and carbohydrate metabolism. These identified metabolites may serve as biomarkers and aid in the investigation of obesity’s underlying pathological mechanisms. Whether these features are associated with the development of obesity, or a consequence of changing BMI, requires further study.
... Tandem mass spectrometry (MS/MS) is widely used in new-born screening programmes to detect fatty acid mitochondrial ß-oxidation disorders through acylcarnitine (ACS) analysis. In a previous study by our group, we described a characteristic AC pattern in patients with type 2 diabetes mellitus (DT2), 18 finding that there is an overload of fatty acids in the mitochondria which are derived from the accumulation of short, medium, and long-chain ACs which play an important role in activating the inflammatory pathways. 19 A well-defined pattern of AC has been described for insulin-resistant, diabetic and obese patients. ...
Article
Background: Psoriasis is strongly associated with insulin resistance (IR). Lipid profile disturbances and upregulation of enzymes crucial for fatty acid oxidation have been reported in patients with psoriasis. Mitochondrial ß-oxidation is altered in patients with IR. Common mitochondrial dysfunction may be involved in the origin of both diseases. Objective: This study aimed to evaluate mitochondrial ß-oxidation, intermediary metabolism, and mitochondrial content in psoriatic patients with or without IR and compare them to healthy controls. Methods: The participants were divided into three groups: 1) psoriasis and IR (n = 26); 2) psoriasis without IR (n = 17); and 3) healthy controls (n = 17). Quantification of amino acids and acylcarnitines (AC) by tandem mass spectrometry, determination of urinary organic acids by gas chromatography/mass spectrometry (GC/MS), and mitochondrial DNA quantification were performed in all groups. Results: When comparisons were made between the two psoriatic groups, no differences were found between: C5DC+C6OH, C16:1, Met/Leu, Met/Phe, C16:1/C16, and C5DC+C6OH/C4DC+C5OH ratios. Nine analytes were different: phenylalanine, Cit/Phe, and Cit/Tyr ratios, C0, C3, C5, C6DC, C16, and C18:1OH. There were no correlations between psoriasis area and severity index (PASI), body mass index (BMI), and duration of disease with ACs. A higher proportion of patients with psoriasis showed increased urine levels of uric acid and hippuric acid (p= 0.01). The mtDNA content was significantly higher in cases than in controls, with no differences between IR and non-IR psoriatic patients. Conclusions: Psoriasis patients with and without IR have a different acylcarnitine profile reflecting impaired ß-oxidation. A distinctive profile of acylcarnitines suggests an involvement of mitochondrial function associated with an increase in stearoyl CoA desaturase (SCD) activity in psoriatic patients with and without IR.
... There is a lack of agreement across the decreased or increased amount of specific short-, medium-, and longchain acylcarnitines in association with diabetes incidence. Besides, reports concerning the fluctuations of FAO and TCA intermediates in diabetics are controversial [23,27,28]. As a notice, Lu Y et al. pointed out that the mitochondrial dysregulation caused by acylcarnitines may aggravate the development of DM more exactly than act as a trigger [29]. ...
Article
Full-text available
Background Diabetes mellitus (DM) and its cardiovascular disease (CVD) complication are among the most frequent causes of death worldwide. However, the metabolites linking up diabetes and CVD are less understood. In this study, we aimed to evaluate serum acylcarnitines and amino acids in postmenopausal women suffering from diabetes with different severity of CVD and compared them with healthy controls. Methods Through a cross-sectional study, samples were collected from postmenopausal women without diabetes and CVD as controls ( n = 20), patients with diabetes and without CVD ( n = 16), diabetes with low risk of CVD ( n = 11), and diabetes with a high risk of CVD ( n = 21) referred for CT angiography for any reason. Metabolites were detected by a targeted approach using LC–MS/MS and metabolic -alterations were assessed by applying multivariate statistical analysis. The diagnostic ability of discovered metabolites based on multivariate statistical analysis was evaluated by ROC curve analysis. Results The study included women aged from 50–80 years with 5–30 years of menopause. The relative concentration of C14:1, C14:2, C16:1, C18:1, and C18:2OH acylcarnitines decreased and C18 acylcarnitine and serine increased in diabetic patients compared to control. Besides, C16:1 and C18:2OH acylcarnitines increased in high-risk CVD diabetic patients compared to no CVD risk diabetic patients. Conclusion Dysregulation of serum acylcarnitines and amino acids profile correlated with different CAC score ranges in diabetic postmenopausal women. (Ethic approval No: IR.TUMS.EMRI.REC.1399.062).
Article
Full-text available
Succinic (SUA), glutaric (GLA), pimelic (PA), suberic (SUBA), adipic (ADA), azelaic (AZA), and sebacic acids (SA) make up the majority of medium-chain dicarboxylic acids (MCDAs) with chain lengths of C4–C10, and are widely utilised in the chemical, food, textile, pesticide, pharmaceutical, and liquid crystal sectors. The MCDAs' two carboxyl groups provide them with an incredibly broad variety of applications. The focus of significant scientific research now is on the increasingly varied pharmacological effects of MCDAs. However, only a few studies have compared the biological characteristics of MCDAs in the contemporary pharmaceutical and cosmetic sectors and thoroughly examined the most recent research and marketing initiatives for MCDAs. This review's objective is to offer a thorough analysis of academic works on MCDAs, to assess the usefulness of these substances' chemical–pharmacological properties for use in the contemporary pharmaceutical and cosmetic industries, and to investigate the direction of their possible applications in these two disciplines. In addition, this review investigates how these compounds are metabolised in the human body.
Article
Background and aims Over the past few years, branched-chain amino acids (BCAAs) are increasingly being linked to insulin resistance and type 2 diabetes mellitus (T2DM), but their relevance for metabolic dyslipidaemia in T2DM is unclear. This study aims to determine the plasma and urinary BCAAs and their association with insulin resistance, lipid profile and glycated haemoglobin in patients with T2DM among Indian adults. Methods In this analytical cross-sectional study, a total of eighty subjects were recruited, 40 T2DM cases and 40 healthy controls. Blood samples collected were subjected to fasting blood sugar (FBS), lipid profile, HbA1c, insulin and BCAAs analysis and urine samples were assessed for BCAAs. All associations were assessed using Spearman Rank Correlation. Results The plasma levels of BCAAs were significantly higher (p < 0.05) in subjects with T2DM than in control subjects. Spearman Rank Correlation analyses revealed a non-significant (p = 0.21) but positive association between BCAAs and homeostasis model assessment of insulin resistance (HOMA-IR) in patients with T2DM (Rho: 0.27). Among lipid profile parameters, only triglycerides had a significant positive correlation to plasma BCAAs in cases (Rho: 0.5971) but not in control subjects. Findings also revealed a significant positive (p < 0.05) association between plasma BCAAs and HbA1c in patients with T2DM (Rho: 0.5325). Urinary BCAAs levels had a non-significant increase in T2DM subjects and did not show any significant correlation with other parameters assessed. Conclusion Elevated levels of plasma BCAAs are positively associated with triglyceride and HbA1c. They could serve as an effective marker for the assessment of metabolic dyslipidaemia in subjects with T2DM. Further, large scale studies are needed for confirmation of the same.
Article
Full-text available
Background/aims: In type 1 diabetes (T1D), type 2 diabetes (T2D) and metabolic syndrome (MetS), the associated complex metabolomic changes in the involvement of carnitine metabolism in total carnitine ester level has already been documented; here we extended the investigations to the individual acylcarnitines. Methods: The fasting serum acylcarnitine concentrations were determined in 49 T1D, 38 T2D and 38 MetS patients and 40 controls by isotope dilution electrospray ionization tandem mass spectrometry. Results: The acylcarnitine profiles of the 3patient groups shared elements with the controls. Considerably higher levels of almost all short-chain acylcarnitines (p < 0.05) and lower levels of some long-chain acylcarnitines were detected in T2D and MetS patients. The amounts of C3 and C4 carnitine were higher and most of the medium-chain and long-chain acylcarnitine levels were lower (p < 0.05) in T1D and MetS patients than in the controls. In T1D and T2D, the levels of C3 and C4 acylcarnitines were markedly elevated and some long-chain acylcarnitines were lower than the controls (p < 0.05). Moreover, significantly lower concentrations of free- and total carnitine were observed in T1D patients (p < 0.05). Conclusions: Profound alterations were detected in acylcarnitine profiles in the 3 patient groups. Similarities in the patterns suggest different degrees of involvement of the same metabolic systems in a systems biology approach.
Article
Full-text available
The incidence of obesity and insulin resistance is growing, and the increase in type 2 diabetes mellitus (DM2) constitutes one of the biggest challenges for our healthcare systems. Many theories are proposed for the induction of insulin resistance in glucose and lipid metabolism and its metabolic sequelae. One of these mechanisms is lipotoxicity (1–4): excess lipid supply and subsequent lipid accumulation in insulin-sensitive tissues such as skeletal muscle interfere with insulin-responsive metabolic pathways. Various lipid intermediates, like ceramides, gangliosides, diacylglycerol, and other metabolites, have been held responsible for insulin resistance (2,3,5–10). These intermediates can exert such effects because they are signaling molecules and building blocks of cellular membranes, which harbor the insulin receptor. In addition, lipids play an important role in energy homeostasis. Fatty acids (FA) can be metabolized via mitochondrial FA oxidation (FAO), which yields energy (11). As such, FAO competes with glucose oxidation in a process known as the glucose-FA, or Randle, cycle (12). Muoio and colleagues (1,13,14) proposed an alternative mechanism in which FAO rate outpaces the tricarboxylic acid cycle (TCA), thereby leading to the accumulation of intermediary metabolites such as acylcarnitines that may interfere with insulin sensitivity. This accumulation of acylcarnitines corroborates with some human studies showing that acylcarnitines are associated with insulin resistance (15–17). In addition, acylcarnitines have a long history in the diagnosis and neonatal screening of FAO defects and other inborn errors of metabolism (18). This knowledge may aid to understand the interaction between FAO and insulin resistance and fuel future research. In this review, we discuss the role of acylcarnitines in FAO and insulin resistance as emerging from animal and human studies.
Article
Full-text available
The prevalence of pre-diabetes and type 2 diabetes increases alarmingly the last few decades and esti-mates indicate this rise will continue the forthcoming decades. Transition of the pre-diabetic to the diabetic state is a slow but inevitable process. It is therefore of importance to intervene in this transition period in order to prevent overt type 2 diabetes to occur. While the focus of research towards type 2 diabetes has long been glucocentric, over the last decade the focus has shifted to a more lipocentric view. Thus, subnormal fat oxidative capacity, increased mitochondrial damage (lipo-toxicity) and decrease mitochondrial function and biogenesis have been identified as factors associated with type 2 diabetes. Within a mitocentric framework, we aim to evaluate the available literature on lipotoxicity and mitochondrial dys-function and its contribution to the development of insulin resistance and finally type 2 diabetes. In addition, pu-tative targets of intervention will be identified and the modes of action of currently available anti-diabetic agents will be reviewed. In the majority of this review the organ of interest will be the skeletal muscle, as this is the major site of insulin resistance.
Article
Full-text available
Metabolite associations with insulin resistance were studied in 7,098 young Finns (age 31 ± 3 years; 52% women) to elucidate underlying metabolic pathways. Insulin resistance was assessed by the homeostasis model (HOMA-IR) and circulating metabolites quantified by high-throughput nuclear magnetic resonance spectroscopy in two population-based cohorts. Associations were analyzed using regression models adjusted for age, waist, and standard lipids. Branched-chain and aromatic amino acids, gluconeogenesis intermediates, ketone bodies, and fatty acid composition and saturation were associated with HOMA-IR (P < 0.0005 for 20 metabolite measures). Leu, Ile, Val, and Tyr displayed sex- and obesity-dependent interactions, with associations being significant for women only if they were abdominally obese. Origins of fasting metabolite levels were studied with dietary and physical activity data. Here, protein energy intake was associated with Val, Phe, Tyr, and Gln but not insulin resistance index. We further tested if 12 genetic variants regulating the metabolites also contributed to insulin resistance. The genetic determinants of metabolite levels were not associated with HOMA-IR, with the exception of a variant in GCKR associated with 12 metabolites, including amino acids (P < 0.0005). Nonetheless, metabolic signatures extending beyond obesity and lipid abnormalities reflected the degree of insulin resistance evidenced in young, normoglycemic adults with sex-specific fingerprints.
Article
Background: Tandem mass spectrometry (MS/MS) is rapidly being adopted by newborn screening programs to screen dried blood spots for >20 markers of disease in a single assay. Limited information is available for setting the marker cutoffs and for the resulting positive predictive values. Methods: We screened >160 000 newborns by MS/MS. The markers were extracted from blood spots into a methanol solution with deuterium-labeled internal standards and then were derivatized before analysis by MS/MS. Multiple reaction monitoring of each sample for the markers of interest was accomplished in ∼1.9 min. Cutoffs for each marker were set at 6–13 SD above the population mean. Results: We identified 22 babies with amino acid disorders (7 phenylketonuria, 11 hyperphenylalaninemia, 1 maple syrup urine disease, 1 hypermethioninemia, 1 arginosuccinate lyase deficiency, and 1 argininemia) and 20 infants with fatty and organic acid disorders (10 medium-chain acyl-CoA dehydrogenase deficiencies, 5 presumptive short-chain acyl-CoA dehydrogenase deficiencies, 2 propionic acidemias, 1 carnitine palmitoyltransferase II deficiency, 1 methylcrotonyl-CoA carboxylase deficiency, and 1 presumptive very-long chain acyl-CoA dehydrogenase deficiency). Approximately 0.3% of all newborns screened were flagged for either amino acid or acylcarnitine markers; approximately one-half of all the flagged infants were from the 5% of newborns who required neonatal intensive care or had birth weights <1500 g. Conclusions: In screening for 23 metabolic disorders by MS/MS, an mean positive predictive value of 8% can be achieved when using cutoffs for individual markers determined empirically on newborns.
Article
The β-oxidation of C8–C16-dicarboxylic acids to short-chain dicarboxylic acids was investigated in vivo and in rat liver homogenate. The β-oxidation in vivo was evaluated from the excretions of C6–10-dicarboxylic acids in urine from rats given C8–C16-dicarboxylic acids. Correspondingly, the β-oxidation in vitro was determined from the rise in concentration of C6–C10(12)-dicarboxylic acids in the postnuclear (600 × g) fraction of rat liver homogenates incubated with C8–C16-dicarboxylic acids. The results showed that C10–C14-dicarboxylic acids were far better substrates for β-oxidation than were C8- and C16-dicarboxylic acids. In particular, hexadecanedioic acid could only be β-oxidized to a minor degree, and, in contrast to the other dicarboxylic acids, it was toxic for starved rats. The activity of the lipid metabolism (unstarved, starved and diabetic ketotic rats) was of decisive significance for the quantity and pattern of the C6]–C10-dicarboxylic acids present both in vivo and in vitro, since adipic acid was increased and sebacic acid decreased with increasing lipid catabolism i.e. the adipic: sebacic acid ratio increased with increasing rates of β-oxidation. On comparison with earlier investigations on the chain-length dependency of the ω-oxidation of monocarboxylic acids it was concluded that the biological origin of the ketotic C6–C8-dicarboxylic aciduria is C10–C14-monocarboxylic acids, and that an elevated β-oxidation rate is important for the formation of C6–C8-dicarboxylic aciduria.
Article
Fatty acids, obesity and insulin resistance relationship are discussed. In the last decades fatty acids (FA) have been implicated in the etiology of insulin resistance. Initially, this process was related to FA inhibitory effects on glucose uptake mediated by the FA oxidation metabolites. This mechanism known as the Randle cycle has been presently discarded based on recent evidence for FA effects on glucose metabolism. Now is known that cytosolic lipid content and FA molecular structure determines higher or lower storage and oxidation capacity. Another factor is given by Tumor Necrosis Factor-a, which is overexpressed in animal and human obesity, producing insulin signaling and glucose uptake inhibition. This paper discuss the role played by FA and obesity on insulin resistance, mainly in relation to FA effects on glucose metabolism in the liver, muscle and adipose tissues. In the obesity condition adipose tissue releases higher levels of free FA which in turn stimulates hepatic glucose production. Adipose tissue also, increase TNF-a secretion impairing glucose utilization and insulin signaling. In muscle, cytosolic lipid content activate a Protein Kinase that inhibits the insulin signaling and reduce GLUT-4 translocation. The study of cellular and metabolic changes associated to weight gain and its relationship with insulin resistance etiology are encouraged (Rev Méd Chile 2000; 128: 1354-60).
Article
IN BRIEF Individuals with type 2 diabetes have a higher incidence of liver function test abnormalities than individuals who do not have diabetes. Mild chronic elevations of transaminases often reflect underlying insulin resistance. Elevation of transaminases within three times the upper limits of normal is not a contraindication for starting oral antidiabetic or lipid-modifying therapy. In contrast, antidiabetic agents have generally been shown to decrease alanine aminotransferase levels as tighter blood glucose levels are achieved.
Article
The worldwide epidemic of obesity and insulin resistance favours nonalcoholic fatty liver disease (NAFLD). Insulin resistance (IR) in the adipose tissue increases lipolysis and the entry of non-esterified fatty acids (NEFAs) in the liver, whereas IR-associated hyperinsulinemia promotes hepatic de novo lipogenesis. However, several hormonal and metabolic adaptations are set up in order to restrain hepatic fat accumulation, such as increased mitochondrial fatty acid oxidation (mtFAO). Unfortunately, these adaptations are usually not sufficient to reduce fat accumulation in liver. Furthermore, enhanced mtFAO without concomitant up-regulation of the mitochondrial respiratory chain (MRC) activity induces reactive oxygen species (ROS) overproduction within different MRC components upstream of cytochrome c oxidase. This event seems to play a significant role in the initiation of oxidative stress and subsequent development of nonalcoholic steatohepatitis (NASH) in some individuals. Experimental investigations also pointed to a progressive reduction of MRC activity during NAFLD, which could impair energy output and aggravate ROS overproduction by the damaged MRC. Hence, developing drugs that further increase mtFAO and restore MRC activity in a coordinated manner could ameliorate steatosis, but also necroinflammation and fibrosis by reducing oxidative stress. In contrast, physicians should be aware that numerous drugs of the current pharmacopoeia are able to induce mitochondrial dysfunction, which could aggravate NAFLD in some patients. (HEPATOLOGY 2013.).