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Brazilian Journal of Psychiatry

Print version ISSN 1516-4446On-line version ISSN 1809-452X

Rev. Bras. Psiquiatr. vol.37 no.2 São Paulo Apr./June 2015  Epub Feb 13, 2015

https://doi.org/10.1590/1516-4446-2014-1425 

Original Articles

Metabolic syndrome and related variables, insulin resistance, leptin levels, and PPAR-γ2 and leptin gene polymorphisms in a pedigree of subjects with bipolar disorder

Trino Baptista 1  

Ignacio Sandia 2  

Erika Fernandez 3  

Ligia Balzán 3  

Lissette Connell 3  

Euderruh Uzcátegui 2  

Ana Serrano 2  

Albis Pabón 2  

Félix Angeles 2  

Yarira Araque 2  

Heidy Delgado 2  

Alexy González 2  

Yonathan Alviarez 2  

Jose Piãero 2  

Enma A. de Baptista 4  

1Department of Physiology, Los Andes University Medical School, Mérida - Venezuela

2Department of Psychiatry, Los Andes University Medical School, Mérida - Venezuela

3Institute of Clinical Research Dr. Américo Negrette, Zulia University Medical School, Maracaibo - Venezuela

4Department of Microbiology, Los Andes University Pharmacy School, Mérida - Venezuela


ABSTRACT

Objective:

Evidence points to a high prevalence of metabolic dysfunction in bipolar disorder (BD), but few studies have evaluated the relatives of subjects with BD. We conducted a cross-sectional study in an extended family of patients with BD type I.

Methods:

The available relatives of the same family were interviewed (DSM-IV-R) and assessed in fasting conditions for body mass index, constituent variables of the metabolic syndrome (MS), leptin levels, insulin resistance index, and single nucleotide polymorphisms (SNPs) for the leptin receptor and promoter and PPAR-γ2 genes. The frequency of MS was compared with that recorded in the local general population.

Results:

Ninety-three relatives of three adults with BD were evaluated (30 aged < 18 years, 63 aged > 18 years). The frequency of MS was similar to that of the general population. Significantly higher frequencies of abnormal glucose, total and low density cholesterol (LDL-c) levels (all p < 0.05), waist circumference (p = 0.057), and leptin and insulin resistance values (in adults only) were observed in the family. Adults with the QQ genotype of the leptin receptor displayed higher LDL-c levels than carriers of the R allele.

Conclusions:

The associations among BD consanguinity, familial hypercholesterolemia, and leptin receptor SNPs reported herein should be replicated and extended in other pedigrees.

Key words: Bipolar disorder; familiar hypercholesterolemia; insulin sensitivity; leptin; metabolic syndrome

Introduction

Convergent evidence points to a high frequency of physical ailments in subjects with bipolar disorders (BD). These include metabolic syndrome (MS), migraine, type 2 diabetes mellitus, thyroid disorders, chronic kidney disease, cancer, chronic pain, and obstructive airway disease, among many others.1-8 Particular emphasis has been placed on characterizing the elevated frequency of MS among patients with BD4,9 and the postulated role of psychotropic medication in its development and maintenance.6,7,10,11

Even though a genetically-based predisposition to metabolic dysfunction in BD has been consistently suggested,12 few studies have evaluated metabolic status in relatives of patients with BD. Such studies might help clarify the role of environmental and genetic factors in the development of MS and related disorders in subjects with BD. In fact, a large study of a multigenerational kindred (508 relatives) including members with BD or schizophrenia in Quebec, Canada, showed obesity to be 2.5 times more frequent in antipsychotic-treated patients (30%) than in untreated family members (12%).13 This finding suggests that medication plays a role in the development of obesity. By contrast, in a large epidemiological study comprising data from the general population (GP), the authors reported that drug-free BD relatives showed the highest frequency of MS, obesity, and abnormal glucose and diastolic blood pressure (BP) levels among several comparison groups, including drug-treated patients and their relatives.7 In another study comprising subjects with schizophrenia or schizoaffective disorders and their first-degree relatives, the authors reported that, among the drug-treated groups, those receiving olanzapine displayed the highest blood levels of plasminogen activator inhibitor (PAI-1) and leptin, but levels were similar to those observed in their relatives after controlling for body mass index (BMI).14

These results indicate that variables other than medication play a role in the development of metabolic dysfunction in patients with BD and their relatives, such as shared environmental and/or genetic factors.

In the present article, we report a higher frequency of metabolic abnormalities in a single pedigree with several BD members compared to the local GP. In the same family, we also assessed potential associations between metabolic profile and the following single nucleotide polymorphisms (SNPs) that are involved in metabolism regulation: LEP2548/GA for the leptin promoter, LEPR Q223R for the leptin receptor, and Pro12/Ala for the peroxisome proliferator-activated receptor gamma (PPAR-γ2).

Methods

Subjects

The study was conducted in an extended rural family in Mérida, Venezuela, three members of which are being treated for BD type I by the first author (TB). The roots of this family were traced to a single man who died 9 years ago at the age of 80. All available blood relatives who lived in a circumscribed area (Bailadores) were contacted, and all provided written informed consent for voluntary participation. In subjects aged < 18 years, the consent form was signed by one of their parents. All the evaluations were performed in a single visit.

The degree of consanguinity of each subject with the BP patients was defined as follows: first-degree relatives (parents, offspring, siblings), second-degree relatives (grandparent, grandchild, uncle, aunt, nephew, niece, half-sibling), or third-degree relatives (first cousin).15

The comparison groups were independent randomized samples of adults and child/adolescent subjects drawn from the local GP of Mérida. These data are published elsewhere.7,16

Procedure

The family consisted of 63 adults (aged ≥ 18 years), not including the subjects with BD, and 30 children/adolescents (aged < 18 years). The GP samples consisted of 270 adults and 370 children/adolescents. All subjects were evaluated in fasting conditions. From each subject, a blood sample was obtained from cubital veins and was immediately centrifuged and stored at -4°C until analysis.

Waist circumference (WC), body weight, and height were measured with subjects wearing light clothing. The BMI was calculated as follows: weight (kg)/height (m)2. Obesity was defined as a BMI ≥ 30 kg/m2in adults and as values above the 97th percentile of the BMI distribution in the GP for children/adolescents.16 BP was calculated as the average of three measures, obtained with the subject in standing, sitting, and supine positions.

MS was diagnosed in adults according to the criteria of the Latin American Diabetes Association,17 as follows: a) abdominal obesity (waist circumference ≥ 88 cm in women or ≥ 94 cm in men), plus at least two of the following criteria: b) triglycerides: > 150 mg/dL or under specific treatment; c) high density lipoprotein cholesterol (HDL-c): < 50 mg/dL in women or < 40 mg/dL in men or under specific treatment; d) elevated BP: systolic ≥ 130 mm/Hg, diastolic ≥ 85 mm/Hg, or under specific treatment; and e) glucose levels: ≥ 100 mg/dL or under specific treatment.

In children/adolescents, MS was diagnosed following a modified version of the Cook et al. criteria if three or more of the following were positive: WC and BP > 90th percentile; glucose > 100 mg/dL; triglycerides > 110 mg/dL; and HDL-c < 40 mg/dL.16

A detailed interview was conducted to obtain demographic data, mental and physical health history, and determine degree of consanguinity with the BD subjects. Psychiatric diagnosis was performed with the Structured Interview for the DSM-IV18 in adults and with the Kiddie-SADS-PL in children/adolescents.19

Chemical analysis

Glucose and lipid levels were measured using an enzymatic method (Humans, Germany). Insulin (detection limit: 1.76 µIU/mL) and leptin (detection limit: 1.0 ng/mL) were assessed by ELISA with commercial kits (DRG, Germany). The insulin resistance index (HOMA-IR) was calculated as follows: glucose (mmol/L) × insulin (µIU/mL)/22.5.

Genotyping

Genomic DNA was isolated from peripheral leukocytes.20,21 Genotyping was conducted by restriction fragment length polymorphism-polymerase chain reaction (RFLP-PCR).22 We used the 2548G/A and Q223R nomenclature for the leptin promoter and receptor genes, respectively. The GG and QQ are the “wild-type” homozygous genotypes, whereas the (GA/AA) and (QR/RR) variants are the heterozygous and homozygous genotypes. The nomenclature for the PPAR-γ2 gene polymorphism is Pro12/Ala; PRO/PRO is the “wild type” homozygous genotype, and the (PRO/ALA-ALA/ALA) variants are the heterozygous and homozygous genotypes respectively.

Statistical analysis

SPSS version 17.0 was used for all analyses. Data normality was estimated with the one-sample Kolmogorov-Smirnov test and Levene's test was used to assess the equality of variances. Categorical (MS, abnormal values of its constituting variables, and association with specific genotypes) and continuous data were analyzed with binary logistic regression and covariate analysis respectively, with age and BMI as covariates. Results were considered significant when p ≤ 0.05.

Results

Demographic and clinical features

The subjects with BD were three sisters aged 43, 46, and 63 years. Most family members were their second-degree relatives, and they had no first-degree relatives among the child/adolescent sample (Tables 1 and 2).

Table 1 Sociodemographic features of adult subjects 

Variable Family(n=63) General population(n=274)
Gender*
Female 49 (77.8) 175 (63.9)
Male 14 (22.2) 99 (36.1)
Ethnicity
Mixed 18 (28.6) 15 (5.5)
AA 0.0 (0.0) 67 (24.5)
White 45 (71.4) 134 (48.9)
Native 0.0 (0.0) 58 (21.2)
Age (years), mean ± SD
Female 38.7±13.7 41.3±15.3
Male 31.1±16.0 44.0±15.3
Degree of consanguinity with the BD subjects
First degree 13 (20.6) -
Second degree 39 (61.9) -
Third degree 11 (17.5) -

Data expressed as n (%), unless otherwise specified.

AA = African American; BD = bipolar disorder; SD = standard deviation.

*χ2(1) = 4.4, p = 0.03;

χ2(3) = 61.5, p = 0.000;

F(3) = 3.7, p = 0.01.

Table 2 Sociodemographic features of child/adolescent subjects 

Variable Family(n=30) General population(n=370)
Gender*
Female 15 (50.0) 177 (47.8)
Male 15 (50.0) 193 (52.2)
Ethnicity
Mixed 11 (36.7) -
AA - -
White 19 (63.3) -
Native - -
Age (years), mean ± SD
Female family members 11.9±3.7
Male family members 11.3±3.6
General population (males and females) 7.82±0.62
Degree of consanguinity with the BD subjects
First degree - -
Second degree 22 (73.3) -
Third degree 8 (26.7) -

Data expressed as n (%), unless otherwise specified.

AA = African American; BD = bipolar disorder; SD = standard deviation.

*χ2(1) = 0.001, p = 0.9.

The adult family members were younger than those in the GP sample. Females were more numerous in both groups (Table 1). The child/adolescent family members were numerically older than those of the GP, but the gender distribution was similar (Table 2). There were more African American subjects in the adult GP (Table 1). Ethnicity was not reported in the study of GP children/adolescents (Table 2).

The axis I diagnosis distribution (DSM-IV) in the family was as follows for adults: no diagnosis, n=40 (63.5%); mood disorders (excluding BD), n=9 (14.3%); anxiety disorders, n=10 (15.9%); others, n=4 (6.3%). In children/adolescents, the distribution of diagnoses was: no axis I diagnosis, n=27 (90%); attention deficit disorder, n=2 (6.7%); and alcohol abuse, n=1 (3.3%).

Metabolic syndrome and its constituting variables

The frequency of MS and obesity recorded in the adult members of the tested family was similar to that observed in the GP, but a significantly higher frequency of abnormal blood glucose, total and low-density lipoprotein cholesterol (LDL-c) levels, and WC (marginally significant) was recorded in the family adults (p < 0.05). By contrast, a significantly lower frequency of abnormal triglycerides, HDL-c, and BP levels was observed in the family adults (Table 3).

Table 3 Frequency (percentage) of metabolic syndrome and abnormal values of its constituting variables 

Adults Family (n=63) General population (n=274) p-value*
Metabolic syndrome 19.0 (9.3-28.7) 27.4 (24.7-30.1) 0.4
Obesity 27 (16-38) 24.2 (19.1-29.3) 0.4
Waist circumference 53.2 (40.9-65.5) 41.2 (38.2-44.2) 0.057
Abnormal blood glucose (mg/dL) 27 (16-38) 9.1 (7.4-10.8) 0.000
Triglycerides (mg/dL) 6.3 (0.3-12.3) 39.1 (33.5-44.9) 0.000
HDL-c (mg/dL) 41.3 (29.1-53.5) 84.7 (80.4-88.9) 0.000
Blood pressure (mmHg) 6.3 (0.3-12.3) 32.1 (26.6-37.6) 0.001
Total cholesterol (mg/dL) 54 (41.7-66.3) 9.1 (5.7-13.5) 0.000
LDL-c (mg/dL) 85.7 (77.1-94.3) 21.9 (17.0-26.8) 0.000
Children/adolescents Family (n=30) General population (n=370) p-value*
Metabolic syndrome 3.3 (-3.6-9.7) 4.6 (2.5-6.7) 0.7
Obesity 13.3 (1.2-25.4) 9.7 (6.7-12.7) 0.9
Waist circumference 13.3 (1.0-25.6) 10 (7.0-13.0) 0.7
Abnormal blood glucose (mg/dL) 13.3 (1.0-25.6) 6.5 (4.0-9.0) 0.3
Triglycerides (mg/dL) - 12.7 (9.3-16.1) 0.04
HDL-c (mg/dL) 10 (-0.3-20.7) 41.4 (36.4-46.4) 0.001
Blood pressure (mmHg) 10 (-0.3-20.7) 7.8 (5.1-10.5) 0.9
Total cholesterol (mg/dL) 30 (13.6-46.4) - -
LDL-c (mg/dL) 40 (22.5-57.5) 10.8 (7.6-14.0) 0.0001

Data expressed as percentage (95% confidence interval).

HDL-c = high-density lipoprotein cholesterol. LDL-c = low-density lipoprotein cholesterol.

* Probability on binary regression analysis, with age and body mass index as covariates.

The frequency of abnormal LDL-c levels recorded in the family's children/adolescents was significantly higher than that observed in their GP counterparts. By contrast, the frequency of abnormal triglyceride and HDL-c levels was significantly lower than that recorded in the GP (Table 3).

Insulin resistance and leptin levels

Adults

The HOMA-IR was calculated in all subjects in both groups. The family members displayed significantly higher values than the GP did (Table 4).

Table 4 Insulin resistance index and leptin levels 

Family General population p-value
Adults*
Insulin resistance index (HOMA-IR) 2.4±0.2 1.6±0.1 0.004
Leptin (females) (ng/mL) 22.1±1.4 17.9±1.7 0.036
Leptin (males) (ng/mL) 7.5±1.8 7.8±1.8 0.9
Children/adolescents
Insulin resistance index (HOMA-IR) 2.2±1.8 - -
Leptin (females) (ng/mL) 13.1±12.7 - -
Leptin (males) (ng/mL) 5.9±8.4 - -

Data expressed as mean ± standard error.

HOMA-IR = insulin resistance index.

* p-value associated probability, general linear model with age and body mass index as covariates.

HOMA-IR, n=29; leptin: females, n=15; males, n=13.

Leptin was measured in all family members, but in only 12 males and 32 females of the GP subjects, since the latter was a probabilistic sample. Leptin levels were significantly higher among females in the adult family group (Table 4).

Children/adolescents

There are no normative data for the HOMA-IR and leptin levels in the Venezuelan child/adolescent GP. Thus, family data are presented in a purely descriptive manner (Table 4).

Regarding HOMA-IR values, besides the mean ± SEM presented in Table 4, we compared each individual value with the average reported in a local GP study and discriminated by BMI.23 By considering 1 SD above or below the mean as abnormal, five subjects (16.7%) in the young family group were above this cutoff point. Interestingly, three of these individuals had normal or low BMI (data not shown).

Genetic analysis

This analysis was conducted in 90 family members only. There were no adults with the RR genotype of the leptin receptor and no children/adolescents with the ALA/ALA genotype of the PPAR-γ2 gene. The genotype distribution for the whole sample was as follows. For the PPAR-γ2 gene: PRO/PRO = 58.9%; PRO/ALA = 38.9%; ALA/ALA = 2.2%; for the leptin receptor: QQ = 68.9%; QR = 28.9%; RR = 2.2%; for the leptin promoter: GG = 51.1%; GA = 43.3%; AA = 5.6%. None of these rates deviated from Hardy-Weinberg equilibrium (p > 0.05).

Adults

Subjects with the QR genotype of the leptin receptor gene displayed higher HOMA-IR values and a lower frequency of abnormal LDL-c than those carrying the QQ genotype (p < 0.05, Table 5).

Table 5 Selective description of the association between SNPs and metabolic dysfunction 

Polymorphism Variable Genotype Statistics
Adults
Leptin receptor Q223R HOMA-IR QQ QR F(1) = 8.3, p = 0.006
1.7 ± 0.5 5.1 ± 1.0
Leptin receptor Q223R LDL-c* QQ QR Wald(1) = 4.2, p = 0.03
93.5 (87.4-99.6) 71.4 (60.2-82.6)
Children/adolescents
    PPRAγ2 Systolic BP PRO/PRO PRO/ALA F(1) = 4.5, p = 0.04
98.4 ± 2.6 89.1 ± 3.5
    PPRAγ2 Diastolic BP PRO/PRO PRO/ALA F(1) = 5.9, p = 0.02
64.9 ± 2.4 55.2 ± 3.1
Leptin receptor Q223R WC* QQ (QR + RR) F(1) = 5.4, p = 0.02
70.1 ± 1.7 64.4 ± 1.8

Values expressed as mean ± SEM, unless otherwise specified. Statistics: univariate general linear model with age and body mass index as covariates.

BP = blood pressure; HOMA-IR = insulin resistance index; LDL-c = low density cholesterol; WC = waist circumference.

*Values expressed as percentage of subjects (95% confidence interval) with abnormal values. Statistics: binary logistic regression analysis with age and body mass index as covariates.

Children/adolescents

Subjects with the wild-type genotype of the PPAR-γ2gene (PRO/PRO) displayed higher systolic and diastolic BP values than carriers of the PRO/ALA genotype (p < 0.05, Table 5). Similarly, those subjects with the wild-type genotype of the leptin receptor (QQ) showed a higher frequency of abnormal WC than those of the (QR/RR) group (p < 0.05, Table 5).

Influence of the degree of consanguinity

The relevance of this analysis is hindered by the small sample size, particularly when considering first-degree relatives. The second-degree relatives were significantly younger than the other groups (first-degree group, 52.2±13.5 years; second-degree group, 23.5±13.2 years; third-degree group, 30.0±16.9 years, f(2) = 22.1, p = 0.000). Most differences among the three consanguinity groups were nonsignificant when age was entered as a covariate, either when considering absolute values or the proportion of abnormal levels.

The only significant findings were a lower proportion of abnormal WC and HDL-c values and lower absolute diastolic BP values in the second-degree group when compared with the other two groups (p < 0.05, data not shown).

Discussion

In this study, we evaluated a single multigenerational pedigree with several members diagnosed with BD type I, instead of the most frequently used approach, which consists of assessing relatives in samples of unrelated BD patients. Since such studies can assess large numbers of genetically-related subjects, they may be particularly suitable for detection of putative markers of the disease.

A MEDLINE search conducted in May 2014 by the first author identified 297 family genetic studies of BD carried out since 1967; however, most were designed to explore the genetic basis of the psychiatric disorder itself and/or its related clinical features, but not its metabolic regulation. Hence, in this pioneering study, we expected to detect metabolic patterns and genotype distributions in relevant genes that could generate hypotheses to support further comparative studies.

Metabolic profile

This study showed that a significant proportion of relatives of subjects with BD displayed metabolic abnormalities. The frequency of abnormal blood glucose, total and LDL-c levels, WC (only marginally significant), insulin resistance index, and leptin levels (in women) were higher in the adult relatives of the subjects with BP than in the GP. These high leptin levels suggest an elevated rate of insulin resistance in the family.24

In the children/adolescents group, the frequency of abnormal LDL-c was also significantly higher than that recorded in the GP. Furthermore, 13% of the children/adolescent group exhibited abnormal fasting blood glucose levels (vs. 6.5% of the GP, Table 3), and 16.7% of them presented abnormal HOMA-IR. Conversely, the frequency of abnormal triglycerides, HDL-c, and BP (in adults only) was lower in the BD relatives than in the GP.

The lipid profile strongly suggests a mild familiar hypercholesterolemia (FH),25 because 85.7% of adults and 40% of children/adolescents had abnormal LDL-c levels. This is an autosomal dominant disorder linked to abnormal LDL receptor functioning. More than 700 meaningful mutations of this receptor have been identified. This underlies the heterogeneity of the clinical picture, which is severe in homozygotes and mild in heterozygotes. The homozygote and heterozygote types have an estimated prevalence of 1 in 500 and 1 in 1 million respectively.25 Elevated triglyceride and glucose levels and BP dysregulation - which are the other components of the MS - are not primarily linked to FH.25

Hence, it appears that this family carries simultaneously mild FH and some components of the MS, mainly carbohydrate dysregulation, expressed as abnormal fasting blood glucose levels and HOMA-IR indices. The MS is frequently observed in subjects with BD,1-4 but the association between FH and BD has so far not been explored.

Numerous studies have analyzed the lipid profile of subjects with BD. A consistent finding is the high frequency of abnormal triglyceride and low HDL-c levels, as defined in the MS criteria.1-4,7,8 As a matter of fact, this profile, along with abnormal WC and insulin levels, accounts for most of the metabolic differences observed between psychiatric and internal medicine patients.26 Total and LDL-c levels are not formally included in the MS criteria and are often unreported, but they are among the strongest predictors of atherosclerosis and cardiovascular diseases.27

In a context different from BD, a negative correlation between blood cholesterol levels and impulsive, violent, and suicidal behaviors has been extensively explored, with conflicting results.28,29 Some studies have also included low triglyceride levels in that pathogenic model.30 Finally, low cholesterol levels have been reported during the manic state31-33 and have been suggested as a trait rather than a state marker of the manic phase of BD.33

In short, in patients with BD, high cholesterol levels are linked to cardiovascular risk, whereas low levels are related to psychopathological traits. However, this is the first report of FH in a BD pedigree. As stated above, this metabolic disorder differs from the MS because it does not primarily involve abnormal glucose, HDL-c, triglyceride, or BP values. The remaining discussion about our genetic findings will focus on their relationship with total and LDL-c levels.

Genetic analysis

Since our research group has studied the metabolic risk associated with SNPs in the leptin promoter/receptor and PPAR-γ2 genes in Venezuelan GP and psychiatric patients before,34-36 we explored this potential association in the family under study.

PPAR-γ2 gene

The ALA substitution of the PPAR-γ2 gene (genotypes PRO/ALA and ALA/ALA) has been associated with a favorable metabolic profile in non-psychiatric populations, such as lower triglyceride levels and BP and higher HDL-c levels than the wild-type genotype (PRO/PRO).34,37 There was only one significant result in our sample, and it is consistent with the above-mentioned findings: the child/adolescent population with the PRO/ALA genotype had lower BP values than those recorded in the PRO/PRO group.

No published studies have explored the association between PPAR-γ2 polymorphisms and BP in children/adolescents. Jermendy et al.38 reported lower post-challenge glucose and insulin values in obese children carrying the ALA allele, but no difference in BP was observed. Interestingly, when we discriminated between normal and abnormal BMI (according to the 97th percentile of the Venezuelan child/adolescent GP), a protective effect of the ALA allele was observed only in those subjects with normal BMI, for both systolic (p = 0.01) and diastolic (p = 0.007) BP. In any case, no particular PPAR-γ2 SNP was associated with the high total and LDL-c levels reported in this pedigree.

Leptin promoter (2548G/A)

Early studies reported a positive association between excessive weight gain and SNPs for this gene,39 but numerous contradictory reports that point to ethnicity and drug treatment as significant confounding variables were later published.35 Similar conflicting results have been reported regarding the MS and its constituting variables.40,41

We did not find any significant association between the various 2548G/A SNPs and any of the metabolic variables under study.

Leptin receptor (Q223R)

Early reports showed that R allele carriers were less obese than non-carriers (reviewed elsewhere35). This association was confirmed here in children/adolescents when considering WC values.

The adult R allele carriers in the BD family displayed significantly lower LDL-c levels than the non-carriers. Hence, hypercholesterolemia in this pedigree appears to be associated with the wild-type genotype (QQ). This finding has not been previously reported.

In conclusion, the extended family of three subjects with BD exhibited higher total and LDL cholesterol levels, insulin resistance, leptin levels (in women only), abdominal obesity, and abnormal blood glucose levels than the GP. Most genetic-metabolic associations agreed with those described in drug-free subjects. These results confirm that relatives of patients with BD are also at high risk of metabolic dysfunction.

Also, we did not find any published study about the association between BD and familial hypercholesterolemia. This finding, along with its association with the QQ genotype of the leptin receptor, could thus be specific of this particular family. For this and other reasons, the present study should be replicated in different geographical locations and ethnic groups.

Finally, the small sample size made it difficult to analyze separate genotypes and the influence of the degree of consanguinity. Furthermore, approximately 25% of the extended family could not be contacted. Therefore, these results should be considered preliminary.

Acknowledgements

We are grateful to the family members for their cooperation and to Françoise Salager-Meyer for her editorial assistance. This study was funded by VALMOR, C.A., and the Venezuelan College of Neuropsychopharmacology.

References

. Gomes FA, Almeida KM, Magalhães PV, Caetano SC, Kauer-Sant'Anna M, Lafer B, et al. Cardiovascular risk factors in outpatients with bipolar disorder: a report from the Brazilian Research Network in Bipolar Disorder. Rev Bras Psiquiatr. 2013;35:126-30. [ Links ]

. Smith DJ, Martin D, McLean G, Langan J, Guthrie B, Mercer SW. Multimorbidity in bipolar disorder and undertreatment of cardiovascular disease: a cross sectional study. BMC Med. 2013;11:263. [ Links ]

. Crump C, Sundquist K, Winkleby MA, Sundquist J. Comorbidities and mortality in bipolar disorder: a Swedish national cohort study. JAMA Psychiatry. 2013;70:931-9. [ Links ]

. Czepielewski L, Daruy Filho L, Brietzke E, Grassi-Oliveira R. Bipolar disorder and metabolic syndrome: a systematic review. Rev Bras Psiquiatr. 2013;35:88-93. [ Links ]

. Baptista T, Uzcátegui E, Arapé Y, Serrano A, Mazarella X, Quiroz S, et al. Migraine lifetime prevalence in mental disorders: concurrent comparisons with first-degree relatives and the general population. Invest Clin. 2012;53:38-51. [ Links ]

. McIntyre RS, Alsuwaidan M, Goldstein BI, Taylor VH, Schaffer A, Beaulieu S, et al. The Canadian Network for Mood and Anxiety Treatments (CANMAT) task force recommendations for the management of patients with mood disorders and comorbid metabolic disorders. Ann Clin Psychiatry. 2012;24:69-81. [ Links ]

. Baptista T, Serrano A, Uzcátegui E, ElFakih Y, Rangel N, Carrizo E, et al. The metabolic syndrome and its constituting variables in atypical antipsychotic-treated subjects: comparison with other drug treatments, drug-free psychiatric patients, first-degree relatives and the general population in Venezuela. Schizophr Res. 2011;126:93-102. [ Links ]

. Sicras A, Rejas J, Navarro R, Serrat J, Blanca M. Metabolic syndrome in bipolar disorder: a cross-sectional assessment of a Health Management Organization database. Bipolar Disord. 2008;10:607-16. [ Links ]

. Baskaran A, Cha DS, Powell AM, Jalil D, McIntyre RS. Sex differences in rates of obesity in bipolar disorder: postulated mechanisms. Bipolar Disord. 2014;16:83-92. [ Links ]

. Baptista T, De Mendoza S, Beaulieu S, Bermúdez A, Martinez M. The metabolic syndrome during antipsychotic drug treatment: mechanisms and management. Metab Syndr Relat Disord. 2004;2:290-307. [ Links ]

. Vancampfort D, Vansteelandt K, Correll CU, Mitchell AJ, De Herdt A, Sienaert P, et al. Metabolic syndrome and metabolic abnormalities in bipolar disorder: a meta-analysis of prevalence rates and moderators. Am J Psychiatry. 2013;170:265-74. [ Links ]

. Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447:661-78. [ Links ]

. Chagnon YC, Merette C, Bouchard RH, Emond C, Roy MA, Maziade M. A genome wide linkage study of obesity as secondary effect of antipsychotics in multigenerational families of eastern Quebec affected by psychoses. Mol Psychiatry. 2004;9:1067-74. [ Links ]

. Carrizo E, Fernandez V, Quintero J, Connell L, Rodriguez Z, Mosquera M, et al. Coagulation and inflammation markers during atypical or typical antipsychotic treatment in schizophrenia patients and drug-free first-degree relatives. Schizophr Res. 2008;103:83-93. [ Links ]

. U.S. National Library of Medicine. Genetics Home Reference. Glossary [Internet]. 2014 [cited May 21, 2014]. http://ghr.nlm.nih.gov/glossary=firstdegreerelativeLinks ]

. Paoli M, Uzcátegui L, Zerpa J, Gomez-Perez R, Camacho N, Molina Z, et al. [Obesity in schoolchildren from Merida, Venezuela: association with cardiovascular risk factors]. Endocrinol Nutr. 2009;56:218-26. [ Links ]

. Consenso Latinoamericano de la Asociación Latinoamericana de Diabetes (ALAD). Epidemiologia, diagnóstico, control, prevención y tratamiento del síndrome metabólico en adultos. Rev Asoc Latinoam Diab. 2010;18:25-44. [ Links ]

. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DMS-IV Axis I Disorders - Clinician Version (SCID-CV) (Spanish Version). Washington: American Psychiatric Press; 1997. [ Links ]

. Ulloa RE, Ortiz S, Higuera F, Nogales I, Fresan A, Apiquian R, et al. [Interrater reliability of the Spanish version of Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime version (K-SADS-PL)]. Actas Esp Psiquiatr. 2006;34:36-40. [ Links ]

. Miller SA, Dykes DD, Polesky HF. A simple salting out procedure for extraction DNA from human nucleated cells. Nucleic Acids Res. 1988;16:1215. [ Links ]

. Ausubel F, Brent R, Kingston R, Moore D, Seidman J, Smith J, et al. Preparation of genomic DNA. Phenol extraction and concentrationof DNA from aqueous solutions. In: Short protocols in molecular biology. Current protocols in molecular biology. New York: Reene Publishing associates and Wiley-Interscience; 1989. p. 114.1-5.4. [ Links ]

. Snoussi K, Strosberg AD, Bouaouina N, Ben Ahmed S, Helal AN, Chouchane L. Leptin and leptin receptor polymorphisms are associated with increased risk and poor prognosis of breast carcinoma. BMC Cancer. 2006;6:38. [ Links ]

. Quijada Z, Paoli M, Zerpa Y, Camacho N, Cichetti R, Villarroel V, et al. The triglyceride/HDL-cholesterol ratio as a marker of cardiovascular risk in obese children; association with traditional and emergent risk factors. Pediatr Diabetes. 2008;9:464-71. [ Links ]

. Marquina D, Peãa R, Fernández E, Baptista T. Abnormal correlation between serum leptin levels and body mass index may predict metabolic dysfunction irrespective of the psychopharmacological treatment. Int Clin Psychopharmacol. 2011;26:169-72. [ Links ]

. Nordestgaard BG, Chapman MJ, Humphries SE, Ginsberg HN, Masana L, Descamps OS, et al. Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus statement of the European Atherosclerosis Society. Eur Heart J 2013;34:3478-90a. [ Links ]

. Margari F, Lozupone M, Pisani R, Pastore A, Todarello O, Zagaria G, et al. Metabolic syndrome: differences between psychiatric and internal medicine patients. Int J Psychiatry Med. 2013;45:203-26. [ Links ]

. Glasziou PP, Irwig L, Kirby AC, Tonkin AM, Simes RJ. Which lipid measurement should we monitor? An analysis of the LIPID study. BMJ Open. 2014;4:e003512. [ Links ]

. De Berardis D, Conti CM, Serroni N, Moschetta FS, Carano A, Salerno RM, et al. The role of cholesterol levels in mood disorders and suicide. J Biol Regul Homeost Agents. 2009;23:133-40. [ Links ]

. D'Ambrosio V, Salvi V, Bogetto F, Maina G. Serum lipids, metabolic syndrome and lifetime suicide attempts in patients with bipolar disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2012;37:136-40. [ Links ]

. Liao PJ, Chen CH, Chan HY, Tan HK, Hsu KH. Serum lipid profile could predict the inception and impacts of violent behaviors among acute psychiatric inpatients. Chang Gung Med J. 2012;35:382-91. [ Links ]

. Fiedorowicz JG, Palagummi NM, Behrendtsen O, Coryell WH. Cholesterol and affective morbidity. Psychiatry Res. 2010;175:78-81. [ Links ]

. Atmaca M, Kuloglu M, Tezcan E, Ustundag B, Bayik Y. Serum leptin and cholesterol levels in patients with bipolar disorder. Neuropsychobiology. 2002;46:176-9. [ Links ]

. Ghaemi SN, Shields GS, Hegarty JD, Goodwin FK. Cholesterol levels in mood disorders: high or low? Bipolar Disord. 2000;2:60-4. [ Links ]

. Fernández E, Morales LM, Vargas R, Sandrea L, Molero-Conejo E, Fernández V, et al. Polimorfismo Pro12Ala del gen PPAR-γ2 y síndrome metabólico: Estudio preliminar. Acta Bioquim Clin Latinoam. 2009;43:3-9. [ Links ]

. Fernández E1, Carrizo E, Fernández V, Connell L, Sandia I, Prieto D, et al. Polymorphisms of the LEP- and LEPR genes, metabolic profile after prolonged clozapine administration and response to the antidiabetic metformin. Schizophr Res. 2010;121:213-7. [ Links ]

. Fernandez E, Carrizo E, Connell L, Baptista T. Pro12Ala polymorphism in PPARg2 gene, the metabolic syndrome and response to metformin in clozapine-treated patients. Schizophr Res. 2012;137:262-3. [ Links ]

. Costa V, Gallo MA, Letizia F, Aprile M, Casamassimi A, Ciccodicola A. PPARG: gene expression regulation and next-generation sequencing for unsolved issues. PPAR Res. 2010;pii:409168. [ Links ]

. Jermendy A, Korner A, Kovacs M, Madacsy L, Cseh K. PPAR-gamma2 pro12Ala polymorphism is associated with post-challenge abnormalities of glucose homeostasis in children and adolescents with obesity. J Pediatr Endocrinol Metab. 2011;24:55-9. [ Links ]

. Templeman LA, Reynolds GP, Arranz B, San L. Polymorphisms of the 5-HT2Creceptor and leptin genes are associated with antipsychotic drug-induced weight gain in Caucasian subjects with a first-episode psychosis. Pharmacogenet Genomics. 2005;15:195-200. [ Links ]

. Suriyaprom K, Tungtrongchitr R, Thawnasom K. Measurement of the levels of leptin, BDNF associated with polymorphisms LEP G2548A, LEPR Gln223Arg and BDNF Val66Met in Thai with metabolic syndrome. Diabetol Metab Syndr. 2014;6:6. [ Links ]

. Boumaiza I, Omezzine A, Rejeb J, Rebhi L, Ouedrani A, Ben Rejeb N, et al. Relationship between leptin G2548A and leptin receptor Q223R gene polymorphisms and obesity and metabolic syndrome risk in Tunisian volunteers. Genet Test Mol Biomarkers. 2012;16:726-33. [ Links ]

Received: April 7, 2014; Accepted: July 14, 2014

Correspondence: Trino Baptista, Department of Physiology, Los Andes University Medical School, Tulio Febres Cordero Ave., n° 4-27, 5101-A, Mérida, Venezuela. E-mail: trinbap@yahoo.com

Disclosure The authors report no conflicts of interest.

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