Since the introduction of highly active antiretroviral therapy (HAART), the life expectancy of patients infected with human immunodeficiency virus 1 (HIV-1) has remarkably increased. Despite the clinical benefits, the long-term HAART is associated with a complex spectrum of untoward metabolic effects [1,2], including dyslipidemia and insulin resistance that lead to higher risk of developing cardiovascular diseases and diabetes mellitus [3–10], and lipodystrophy syndrome, characterized by morphologic changes that may stigmatize the patients and compromise their compliance to therapy [11–14]. The lipodystrophy syndrome and metabolic alterations have been related to various factors, including the advancing age and the class of drugs used .
However, these side effects do not occur in all treated patients, and there is a very large interindividual variability in the emergence and severity of the symptoms. This variability suggests that host genetic factors may play a role and inherited predispositions may have a significant influence on the appearance of lipodystrophy and metabolic alterations as well as on the viroimmunologic response to the drugs .
Single nucleotide polymorphisms (SNPs) in genes involved in lipid metabolism and, in apoptosis, may contribute to explain individual variations in developing morphologic and metabolic alterations during HAART.
Among the possible candidates, Apolipoprotein C3 (ApoC3), that is mainly produced by the liver and is located on very low density lipoprotein (VLDL), is one of the most studied; the ApoC3 content of triglyceride-rich lipoproteins (TRL) is a marker of TRL metabolism and clearance of VLDL and chylomicrons ; ApoC3 inhibits lipoprotein lipase in vitro and is normally repressed by insulin.
Not yet evaluated in HIV-related lipodystrophy are Fas and its ligand (FasL), which represent the main genes that control apoptosis in the immune system; the combination of some polymorphisms located in the promoters, and in the coding region of these genes have been associated to enhanced immune reconstitution during antiretroviral treatment .
The peroxisome proliferator-activated receptor γ (PPARγ) is a nuclear hormone receptor necessary for the differentiation of preadipocytes into mature adipose cells; it also plays an important role in lipid metabolism, insulin sensitivity, atherogenesis and immune regulation [20–23].
Adrenergic receptors (AR) are G-protein-coupled receptors for catecholamines; they are essential components of the autonomic nervous system, which controls various physiological functions including metabolism of glucose and lipids . The impairment of the autonomic nervous system function is associated with human obesity and related complications such as diabetes and cardiovascular diseases [25–27]. Several studies have suggested an association between obesity phenotypes and some polymorphisms located in the functional regions of the AR, particularly the β3 and the β2 AR [28,29].
The β2 adrenergic receptor protein has been shown to play a major role in lipolysis in subcutaneous fat . The two aminoacidic variants located in the extracellular portion of the β2 AR (Arg16Gly and Gln27Glu) are in linkage disequilibrium and have been previously associated with metabolic syndrome .
The aim of the present study was the evaluation of the role of known polymorphisms in the emergence of lipodystrophy in patients belonging to the Italian Cohort of Antiretroviral-Naïve Patients (ICoNa). In particular the SNPs we analyzed are the variant A→G in position −670 in the promoter of the Fas gene, the polymorphisms −455 T→C and −482 C→T in the promoter of ApoC3, the silent substitution C161T in the sixth exon of PPARγ, the polymorphism Trp64Arg in the β3-adrenergic receptor, and the two variants Arg16Gly and Gln27Glu located in the β2-adrenergic receptor.
Patients and methods
The ICoNA and LipoICoNA studies
The Italian Cohort of Antiretroviral-Naive Patients (ICoNA) is a multicentric observational study that has been previously described in detail [32,33].
The LipoICoNA is a nested study including patients attending 34 different medical centres; participants were enrolled between September 1999 and March 2000 . Physicians were requested to collect data prospectively every 6 months, reporting any observed adipose tissue alteration and lipid determinations collected during the routine laboratory analysis . Peripheral blood mononuclear cells were collected and stored from about 60% of the enrolled patients. A written informed consent was obtained from all the participants.
Exclusion criteria from the LipoICoNA were a previous diagnosis of AIDS, dementia or AIDS wasting syndrome (according to the Centres for Disease Control and Prevention Criteria), significant variations of body weight (≥10% of total weight or ≥8 kg), hypocaloric diets, anticancer drugs, and corticosteroid or anabolic treatments in the 12 months before enrolment. Moreover, patients who did not undergo a clinical examination every 6 months and those who did not regularly take antiretroviral therapy were excluded from LipoICoNA .
We randomly selected for this study 255 patients through progressive inclusion of one patient and exclusion of the next from the LipoICoNA cohort after excluding non-Italian and non-Caucasian subjects.
Lipoatrophy was defined as the presence of fat loss at any site (face, arms, legs or buttocks); fat accumulation was defined as the presence of at least one alteration such as buffalo hump, accumulation in breasts, abdomen, neck or lipomas. The alteration had to be prospectively recognized by both the patient and the physician.
For restriction fragment length polymorphism (RFLP) analysis, total genomic DNA was extracted according to standardized methods by using a commercially available kit (QIAamp DNA Blood Midikit; Qiagen, Hilden, Germany).
For the Mutector assay, total genomic DNA was purified from whole blood samples using a commercial kit for DNA isolation (Easy-DNA Kit; Invitrogen, Carlsbad, California, USA). DNA was quantified by reading the absorbance at 260 nm using a standard spectrophotometer (NanoDrop, Celbio, Milano, Italy), and each sample was diluted to the final concentration of 20 ng/μl.
Restriction fragment length polymorphism
For the determination of −670 A→G Fas polymorphism we performed the analysis of MvaI RFLP, using PCR amplification followed by MvaI restriction enzyme digestion as previously described . The primer sequences used for PCR were MvaIDir (5′-CTACCTAAGAGCTATCTACCGTTC-3′) and MvaIRev (5′-GGCTGTCCATGTTGTGGCTGC-3′). Each reaction was performed using 100 ng of DNA template in a final volume of 25 μl, and the reaction mixture contained a final concentration of 200 nmol/l of each primer, 200 mmol/l of deoxynucleotide triphosphates (dNTPs), 1.5 mmol/l MgCl2, 50 mmol/l KCl2, 10 mmol/l Tris HCl (pH 8.5), 1 U of Taq polymerase (Promega, Madison, Wisconsin, USA). The reaction was carried out in a PE 9700 Thermal Cycler (PerkinElmer, Boston, Massachusetts, USA) and the PCR conditions were as follows: 30 s at 94°C, 30 s at 62°C, 1 min at 72°C, for 30 cycles. After the PCR reaction, 10 μl of each amplified sample were digested with 5 U of MvaI restriction enzyme (Roche Biochemicals, Mannheim, Germany). The product was loaded onto a 3% agarose gel and run at 90 V for 40 min. Depending on the presence of A or G at −670 position of the Fas gene, two polymorphic alleles were produced: allele A (233 bp) or allele G (189 bp).
For the identification of the ApoC3 polymorphisms, the PPARγ variant, and the β2 and β3 adrenergic receptors polymorphisms, we used a technique called shifted termination assay (Mutector Detection Kit; TrimGen, Sparks, Maryland, USA), in which a sequence selective hybridization is followed by a sequence-dependent termination and a sequence-specific primer extension. The Mutector assay is designed to detect point mutations of known DNA sequence variations. The presence of a certain polymorphism can be simply detected by the presence or absence of colour, and by reading the absorbance of the samples at 405 nm. In particular, we used the Dual Well Test Kit. This testing system can easily genotype the mutation, the wild type, or the heterozygous sample for germ line mutations.
The DNA samples were amplified before starting the Mutector test; each PCR reaction was performed using 200 ng of DNA template in a volume of 50 μl. The reaction was carried out in a AB 9700 Thermal Cycler (Applied Biosystems, Foster City, California, USA); both the PCR conditions and the cycles of the amplification reaction were recommended by TrimGen. Amplified fragments were separated on 1.5% agarose gel and visualized by ethidium bromide staining. The Mutector assay was performed according to the manufacturer's instructions, using 10 μl of PCR products. This technology is highly sensitive and can detect as little as 1% of mutant DNA from a mixed sample.
A person-years analysis was conducted to study two main endpoints: the incidence of lipoatropy and of fat accumulation. We studied the time to the occurrence of the first event. Person-years at risk were calculated from date of recruitment in LipoICoNA until the last available follow-up, or development of the event, whichever occurred first. Standard Poisson regression multivariable model was used to study whether the polymorphisms listed below were predictors of lipoatrophy and/or fat accumulation: ApoC3-482 (CC [wild type], CT/TT), ApoC3-455 (CC [wild type], CT/TT), PPRγ exon 6 161 variant ((CC [wild type], CT/TT), Adrβ codon 64 (TT [wild type], TC/CC), Fas-670 (AA [wild type], AG/GG), Adrβ2 codon 16 (AA [wild type], AG/GG), Adrβ2 codon 27 (CC [wild type], CG/GG). Other covariates included in the analyses were HAART (>2 antiretroviral drugs) currently taken (NNRTI-based regimen/unboosted PI-based regimen), NRTI backbone currently taken (zidovudine (ZDV) + lamivudine (3TC), stavudine (d4T) + 3TC, d4T + didanosine (ddI), others), current years of exposure to ART (at least two antiretroviral drugs), CD4 nadir, hepatitis C virus (HCV)-Ab serum positivity, and demographics.
A total of 255 patients enrolled in LipoICoNA were included in the study. Clinical characteristics of the studied patients are displayed in Table 1. Median age was 37 years [interquartile (IQR) 32–42]; 75.7% of the patients were men, 38.8% were HCV-positive; 93 patients (36.5%) had been exposed to a mono–dual antiretroviral therapy for a median time of 12 months (IQR 6-22).
We compared the distribution of the different genotypes of all the genes studied in our cohort and in published studies on Caucasians as shown in Table 2, the genotypic frequencies of our patients were highly comparable with those of healthy subjects observed in literature, supporting the homogeneity and the reliability of our case file.
In a follow-up of 973 person-years, 70 patients developed lipoatrophy, 7.1 per 100 person-years of follow-up (PYFU) [95% confidence interval (CI) 5.6–9.1].
The absolute crude rates of incidence of lipoatrophy showed a role for gender with females at higher risk than males [incidence rate (IR) 8.32, 95% CI 53.08–130.46 per 100 PYFU vs 6.85, 95% CI 52.06–90.14] and for d4T/3TC backbone regimen compared with ZDV/3TC (IR 13.19, 95% CI 88.39–196.74 per 100 PYFU vs 4.72, 95% CI 31.34–70.97). Considering the different polymorphisms, ApoC3 −455 CC and β3-AR TT displayed a lower risk of developing lipoatrophy than ApoC3 −455 CT/TT and β3-AR TC/CC, respectively (IR 4.21, 95% CI 17.51–101.08 per 100 PYFU vs 7.70, 95% CI 59.43–99.88 and IR 7.00, 95% CI 53.48–91.62 per 100 PYFU vs 10.80, 95% CI 56.20–207.57). On the contrary, Fas 670 AA presented a higher risk than Fas 670 AG/GG (IR 9.83, 95% CI 67.89–142.82 per 100 PYFU vs 6.21, 95% CI 44.81–86.54) (Table 3). At this point, we performed a multivariate analysis to exclude confounding factors, among all the different polymorphisms ApoC3 −455 CC genotype was independently associated with lower risk of developing lipoatrophy (ARR 0.20, 95% CI 0.046–0.91 vs CT/TT, P = 0.037); β3-adrenergic receptor TT genotype carriers tended to be at lower risk of lipoatrophy as compared with those with a TC/CC genotype ARR 0.39, 95% CI 0.14–1.06 vs TC/CC, P = 0.066); on the contrary Fas AA genotype tended to be associated with a two-fold increased risk of lipoatrophy (ARR 1.99, 95% CI 0.99–3.99 vs AG/GG, P = 0.053). Other predictors of lipoatrophy were current use of d4T/3TC as NRTI backbone (ARR 2.74 vs ZDV/3TC, 95% CI 1.19–6.30, P = 0.017) and female sex (ARR 2.41 vs male, 95% CI 1.10–5.27, P = 0.028) (Table 3).
In a follow-up of 976 person-years, 63 patients developed at least one pathological characteristic typical of fat accumulation (IR 6.45, 95% CI 5,04–8.26 per 100 PY). The absolute crude rates of incidence of fat accumulation are reported in Table 4. Females showed a higher incidence of fat accumulation than males (IR 10.88, 95% CI 7.23–16.37 per 100 PYFU vs 5.23, 95% CI 3.84–7.13), as well as patients receiving d4T/3TC and protease inhibitors compared with ZDV/3TC and NNRTI, respectively (IR 9.98, 95% CI 6.37–15.65 per 100 PYFU vs 5.06, 95% CI 3.39–7.55 and IR 7.53, 95% CI 5.35–10.59 per 100 PYFU vs 4.23, 95% CI 2.11–8.45). The absolute crude rates did not show a clear difference of incidence among all the different polymorphisms.
In multivariate analysis, we found a strong correlation between the two β2-adrenergic receptor genotypes and the development of fat accumulation: indeed, the β2-adrenergic receptor codon 16 AA genotype was significantly associated with higher risk (ARR 3.72, 95%CI 1.58–8.76 vs AG/GG, P = 0.0026), whereas the β2-adrenergic receptor codon 27 CC genotype was significantly associated with lower risk (ARR 0.21, 95% CI 0.08–0.51 vs CG/GG, P = 0.0006). Older age was associated with higher risk of developing fat accumulation (ARR 1.72 per 10 years older, 95% CI 1.23–2.41, P = 0.0017), and female sex was associated with a dramatically higher risk of fat accumulation than male (ARR 7.22, 95% CI 3.13–16.67, P < 0.0001) (Table 4).
The main task of our study was to evaluate whether polymorphisms involved in apoptosis and lipid metabolism are associated to the risk of developing anomalies of adipose tissue.
Lipoatrophy causes a strongly negative impact on self-performance, quality of life, self-esteem and adherence to therapy. Moreover, the almost complete irreversibility of facial lipoatrophy is the cause of many requests of surgical correction, and further concerns are raised by the evidences supporting the association of lipoatrophy with metabolic alterations increasing the cardiovascular risk. The most involved drugs, the thymidine analogues (mostly stavudine) are still largely used and often represent a first-line choice in developing countries. Moreover, recent data suggest an independent role of efavirenz in causing lipoatrophy , but very few data are available on the role of host genetic factors in causing such a syndrome. Thus, all these reasons support the need of preventing the development of lipoatrophy and identifying potential predictors.
In our study, we confirmed in a multivariable analysis including various genetic polymorphisms the independent role of factors such as sex and d4T/3TC in inducing lipoatrophy as we and others previously reported [34,42].
Single nucleotide polymorphisms SNP may influence biological processes in many conceivable ways: reduce transcription factor binding affinity to the promoter region, alter microRNA binding sites, change mRNA stability, modify the RNA splicing pattern, destroy an internal ribosomal binding site and cause a key amino acid residue change in a critical protein functional domain resulting in altered protein function.
We identified two polymorphisms related to the emergence of lipoatrophy.
Indeed, ApoC3 −455 CC genotype was significantly associated with lower risk of developing lipoatrophy, whereas Fas AA genotype seemed to be associated with a higher risk. The −482 C→T polymorphism is located within an insulin responsive element (IRE) and has been previously associated with a reduction of the insulin response in vitro, resulting in the adequate expression of ApoC3 . In a small cohort of HIV-1 patients treated with protease inhibitors for at least one year and with d4T for at least 2 years, the −455 T→C variant has been associated with more severe dyslipidemia and also with anomalies of body mass composition, objectively measured with DEXA . More recently, Tarr et al found a correlation between the ApoC3 variants and an unfavourable lipid profile in patients with HIV. Moreover, in a cross-sectional analysis performed on a large group of HIV-infected patients of different ethnicity, it has been shown that the −455 and the −482 ApoC3 polymorphisms influence the triglyceride plasma levels in protease inhibitors-treated subjects .
The data regarding the association of ApoC3 and lipoatrophy was already reported by others  even if the association with lipoatrophy was evident with the contemporary presence of three genetic variants in the gene and not only with one as we have observed. The biologic mechanism underlying such association has not been elucidated, but Bard et al have seen that increased levels of ApoC3 are related to clinical signs of lipodystrophy; therefore it is conceivable that the variant allele might cause a different expression of the gene reducing the production of ApoC3 and consequently reducing the risk of lipoatrophy.
CD95/Fas is involved in the induction of apoptosis and expressed on a large variety of cells, including adipocytes. In vitro, the inhibition of protein synthesis in preadipocytes and adipocytes leads to Fas-mediated apoptosis . The Fas −670 polymorphism is located in the promoter region of the gene; the oligonucleotide with −670A in the Fas promoter has a higher binding ability to signal tranducers and activators of transcription (STAT) molecules . The presence of the A–G mutation might determine lower transcription of the gene reducing its surface expression and possibly limiting apoptosis of adipocytes and consequently protecting against the emergence of lipoatrophy.
Previous studies support an association of polymorphisms in other apoptosis-related genes with an increased risk of developing lipoatrophy.
In a preliminary analysis, TNF-238 G/A, TNF-308 G/A and Fas-1377 were also evaluated in a subset of our patients and no correlation with lipodystrophy was found for all of them (data not shown). Possible variations in the distribution of these polymorphisms in different populations may explain these different results. For these reasons we preferred to postpone the assessment of the role of these polymorphisms to a more powerful study in a larger case file.
The lack of correlation with TNF polymorphisms has already been reported by Tarr et al[45,50] in contrast to previous studies, performed on a relatively low number of subjects, where significance was however low.
Factors associated with fat accumulation on combined antiretroviral therapy have been widely studied . Age, sex and protease inhibitor use are the more frequently reported correlates of risk in association with fat accumulation [52,53]. The first line treatment in our case file is representative of the time when the cohort was established: the large majority of patients were treated with unboosted protease inhibitor and thymidine analogues, NNRTI were administered to only to some of the most recently recruited; a few patients had already received initially suboptimal treatment always including thymidine analogues before starting cART. In this particular setting only age and gender among the cofactors previously reported to be related to an increased risk of fat accumulation showed a strong independent association with fat accumulation in the multivariate model including all the considered genetic polymorphisms.
However, it is interesting to note that none of the genes involved in lipoatrophy were related to the emergence of fat accumulation. On the contrary, we found a strong correlation between the two β2-adrenergic receptor genotypes and the development of fat accumulation: indeed, the β2-adrenergic receptor codon 16 AA genotype was significantly associated with a higher risk while the β2-adrenergic receptor codon 27 CC genotype was significantly associated with lower risk.
The Trp64Arg polymorphism in the β3-AR has been associated with accelerated weight gain, insulin resistance and early onset of diabetes mellitus [28,54,55] and with lowered receptor responsiveness to the β3-adrenergic receptor agonist [56,57]. A meta-analysis in a cohort of Japanese subjects revealed that this polymorphism is associated with the BMI . In a more recent study, an association between triglyceride levels and the presence of this genetic variant in Chilean women with polycystic ovary syndrome has been shown . Moreover, Vonkeman et al found a correlation between the Trp64Arg β3-AR polymorphism and the antiretroviral therapy-related lipodystrophy, suggesting that HIV patients who have this genetic variant are more prone to develop this syndrome, particularly the peripheral atrophy, when using antiretroviral therapy than those who do not.
In regard to the β2 adrenergic receptor, the Arg16Gly polymorphism has been found to be associated with altered function of the receptor, with Gly16 carriers showing a five-fold increase in agonist sensitivity . On the contrary, the Glu27 allele of the Gln27Glu variant has been shown to be associated with an increased risk for obesity and [61–65], higher BMI , larger fat cell size , dyslipidemia [67,68], increased risk for type 2 diabetes [64,68] and an independent risk factor for coronary atherosclerotic disease . Additionally, a correlation has been found between this polymorphism and the distribution of visceral adipose tissue in a population of African Americans and Hispanic Americans .
Therefore, our data support the involvement of AdrB2 polymorphisms CG/GG at position 27 in fat accumulation and underline the potential risk of long-term cardiovascular disease associated with the presence of such polymorphism particularly in HIV-1-infected patients receiving antiretroviral therapy.
As mentioned above, a possible limitation of our study is that our case file is representative of the period of time in which patients started treatment (e.g., 1997–1998) and, as a consequence, of the therapeutic choices that are different from those currently taken.
The significance of some genetic correlates of lipodystrophy as well as the lack of association of others might change in a different therapeutic setting.
A second limitation of the study is represented by its limited power due to the relatively small number of cases included.
For this reason, the role of some polymorphisms such as PPARγ and ApoC3-482, need to be answered in a larger case file before drawing definitive conclusions on their influence on the emergence of lipodystrophy. On the contrary, the significance of the genetic polymorphisms related to an increased risk of developing lipodystrophy is supported by the genetic characteristics of the studied population, in which the polymorphism frequencies is fully representative of the general population.
In conclusion, different factors are related to different manifestations of lipodystrophy syndrome and besides other previously identified factors such as sex, age and type of drug, also genetic predisposition, as hypothesized, plays an important role.
Given the high prevalence of the polymorphisms analysed and the increasing literature reports showing an association between some of these with lipodystrophy and also the relative low cost and feasibility of gene testing it might be useful to determine the genetic predisposition of each single HIV-1-positive patient starting antiretroviral therapy; therefore it could be possible to design individual regimens for each patient in order to avoid the rapid emergence of side effects and take adequate measures to delay their appearance.
This study was partially funded by the Istituto Superiore di Sanità with grant numbers: 30F.22, 30G.64 and 30G.62. The authors would like to thank Ms Bianca Ghisi for editorial work and all the patients and physicians from ICoNA who participated in the study, in particular Dr. Dolores Repetto for selection of the patients.
ICONA PARTICIPATING PHYSICIANS AND CENTERS
Italy M. Montroni, G. Scalise, A. Costantini, A. Riva (Ancona); U. Tirelli, F. Martellotta (Aviano-PN); G. Pastore, N. Ladisa, (Bari); F. Suter, F. Maggiolo (Bergamo); F. Chiodo, V. Colangeli, C. Fiorini, (Bologna); G. Carosi, G. Cristini, C. Torti, C. Minardi, D. Bertelli (Brescia); T. Quirino, (Busto Arsizio); P.E. Manconi, P. Piano (Cagliari); E. Pizzigallo, M. D'Alessandro (Chieti); G. Carnevale, A. Zoncada (Cremona); F. Ghinelli, L. Sighinolfi (Ferrara); F. Leoncini, F. Mazzotta, M. Pozzi, S. Lo Caputo (Firenze); B. Grisorio, S. Ferrara (Foggia); G. Pagano, G. Cassola, A. Alessandrini, R. Piscopo (Genova); F. Soscia, L. Tacconi (Latina); A. Orani, P. Perini (Lecco); D. Tommasi, P. Congedo (Lecce); F. Chiodera, P. Castelli (Macerata); M. Moroni, A. Lazzarin, G. Rizzardini, L. Caggese, A. d'Arminio Monforte, A. Galli, S. Merli, C. Pastecchia, M.C. Moioli (Milano); R. Esposito, C. Mussini (Modena); A. Gori, S. Cagni (Monza), N. Abrescia, A. Chirianni, CM Izzo, M. De Marco, R. Viglietti, E. Manzillo (Napoli); C. Ferrari, P. Pizzaferri (Parma); G. Filice, R. Bruno, (Pavia); G. Magnani, M.A. Ursitti (Reggio Emilia); M. Arlotti, P. Ortolani (Rimini); R. Cauda, M. Andreoni, A. Antinori, G. Antonucci, P. Narciso, V. Tozzi, V. Vullo, A. De Luca, M. Zaccarelli, R. Acinapura, P. De Longis, M.P. Trotta, M. Lichtner, F. Carletti, (Roma); M.S. Mura, M. Mannazzu (Sassari); P. Caramello, G. Di Perri, G.C. Orofino, M. Sciandra (Torino); E. Raise, F. Ebo (Venezia); G. Pellizzer, D. Buonfrate (Vicenza).
B.Z.P. contributed to analysis of the PPARγ variant, the β2 and β3 adrenergic receptors polymorphisms and writing of the paper; A.R. to the ideation of the study, supervision of laboratory work in Milan and writing of the paper; M.N. to the analysis of Fas and FasL polymorphisms; P.C. to the statistical analysis; V.B. to the analysis of ApoC3 polymorphisms; A.C.L. to the statistical analysis; D.M. to the DNA extraction and quality control; F.M. to the collection of epidemiological and clinical data and of biological material (I.CoNA.); A.D'A.M. to the collection of epidemiological and clinical data and of biological material (Coordinator of I.CoNA.); C.M. to the collection of epidemiological and clinical data and of biological material (I.CoNA.); A.C. to the ideation of the study, supervision of laboratory work in Modena and M.G. to the writing of the paper, responsible of the laboratory in Milan.
1. Behrens GM, Stoll M, Schmidt RE. Lipodystrophy syndrome in HIV infection: what is it, what causes it and how can it be managed? Drug Saf 2000; 23:57–76.
2. Eid AJ, Orenstein R. Metabolic and morphologic complications of HIV infection. J Med Liban 2006; 54:97–105.
3. Jain RG, Furfine ES, Pedneault L, White AJ, Lenhard JM. Metabolic complications associated with antiretroviral therapy. Antiviral Research 2001; 51:151–177.
4. Barbaro G. Reviewing the cardiovascular complications of HIV infection after the introduction of HAART. Curr Drug Targets Cardiovasc Haematol Disord 2005; 5:337–343.
5. Balasubramanyam A, Sekhar RV. HIV-associated lipodystrophy syndrome: an accelerated form of the metabolic syndrome of insulin resistance due to altered fat distribution. Res Initiat Treat Action 2006; 12:5–11.
6. Sudano I, Spieker LE, Noll G, Corti R, Weber R, Lüscher TF. Cardiovascular disease in HIV infection. Am Heart J 2006; 151:1147–1155.
7. Barbaro G. Metabolic and cardiovascular complications of highly active antiretroviral therapy for HIV infection. Curr HIV Res 2006; 4:79–85.
8. Carr A. Cardiovascular risk factors in HIV-infected patients. JAIDS 2003; 34:S73–S78.
9. Kino T, Mirani M, Alesci S, Chrousos GP. AIDS-related lipodystrophy/insulin resistance syndrome. Horm Metab Res 2003; 35:129–136.
10. Hadigan C, Kamin D, Liebau J, Mazza S, Barrow S, Torriani M, et al
. Depot-specific regulation of glucose uptake and insulin sensitivity in HIV-lipodystrophy. Am J Physiol Endocrinol Metab 2006; 290:E289–E298.
11. Nolan D, Mallal S. Antiretroviral-therapy-associated lipoatrophy: current status and future directions. Sex Health 2005; 2:153–163.
12. Torriani M, Thomas BJ, Barlow RB, Librizzi J, Dolan S, Grinspoon S. Increased intramyocellular lipid accumulation in HIV-infected women with fat redistribution. J Appl Physiol 2006; 100:609–614.
13. Gallagher DM. Current Clinical Issues Impacting the Lives of Patients Living With HIV/AIDS. J Assoc Nurses AIDS Care 2007; 18(1 Suppl):S11–S16.
14. Bernasconi E, Boubaker K, Junghans C, Flepp M, Furrer HJ, Haensel A, et al
. Abnormalities of body fat distribution in HIV-infected persons treated with antiretroviral drugs: the Swiss HIV Cohort Study. J Acquir Immune Defic Syndr 2002; 31:50–55.
15. Fontas E, van Leth F, Sabin CA, Friis-Møller N, Rickenbach M, d'Arminio Monforte A, et al
. Lipid profiles in HIV-infected patients receiving combination antiretroviral therapy: are different antiretroviral drugs associated with different lipid profiles? J Infect Dis 2004; 189:1056–1074.
16. Fox J, Boffito M, Winston A. The clinical implications of antiretroviral pharmacogenomics. Pharmacogenomics 2006; 7:587–596.
17. Hodis HN, Mack WJ. Triglyceride-rich lipoproteins and the progression of coronary heart disease. Curr Opin Lipidol 1995; 6:209–214.
18. Wang C, McConathy WJ, Kloer HU, Alaupovic P. Modulation of lipoprotein lipase activity by apolipoproteins. J Clin Invest 1985; 75:384–390.
19. Nasi M, Pinti M, Bugarini R, Troiano L, Lugli E, Bellodi C, et al
. Genetic polymorphisms of Fas (CD95) and Fas ligand (CD178) influence the rise in CD4+ T cell count after antiretroviral therapy in drug-naïve HIV-positive patients. Immunogenetics 2005; 57:628–635.
20. Auwerx J, Martin G, Guerre-Millo M, Staels B. Transcription, adipocyte differentiation, and obesity. J Mol Med 1996; 74:347–352.
21. Deeb SS, Fajas L, Nemoto M, Pihlajamäki J, Mykkänen L, Kuusisto J, et al
. A Pro12Ala substitution in PPARgamma2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity. Nat Genet 1998; 20:284–287.
22. Wang XL, Oosterhof J, Duarte N. Peroxisome proliferator-activated receptor gamma C161T polymorphism and coronary artery disease. Cardiovasc Res 1999; 44:588–594.
23. Wada K, Nakajima A, Blumberg RS. PPARgamma and inflammatory bowel disease: a new therapeutic target for ulcerative colitis and Crohn's disease. Trends Mol Med 2001; 7:329–331.
24. Yasuda K, Matsunaga T, Adachi T, Aoki N, Tsujimoto G, Tsuda K. Adrenergic receptor polymorphisms and autonomic nervous system function in human obesity. Trends in Endocrinol and Metab 2006; 17:269–275.
25. Lafontan M. Fat cells: afferent and efferent messages define new approaches to treat obesity. Annu Rev Pharmacol Toxicol 2005; 45:119–146.
26. Snitker S, Macdonald I, Ravussin E, Astrup A. The sympathetic nervous system and obesity: role in aetiology and treatment. Obes Rev 2000; 1:5–15.
27. van Baak MA. The peripheral sympathetic nervous system in human obesity. Obes Rev 2001; 2:3–14.
28. Clement K, Vaisse C, Manning BS, Basdevant A, Guy-Grand B, Ruiz J, et al
. Genetic variation in the beta 3-adrenergic receptor and an increased capacity to gain weight in patients with morbid obesity. N Engl J Med 1995; 333:352–354.
29. Large V, Hellstrom L, Reynisdottir S, Lönnqvist F, Eriksson P, Lannfelt L, et al
. Human beta-2 adrenoceptor gene polymorphisms are highly frequent in obesity and associate with altered adipocyte beta-2 adrenoceptor function. J Clin Invest 1997; 100:3005–3013.
30. Kissebah AH, Krakower GR. Regional adiposity and morbidity. Physiol Rev 1994; 74:761–811.
31. Dallongeville J, Helbecque N, Cottel D, Amouyel P, Meirhaeghe A. The Gly16Arg and the Gln27Glu polymorphisms of Beta-2-adrenergic receptor are associated with metabolic syndrome in men. J Clin Endocrinol Metab 2003; 88:4862–4866.
32. d'Arminio Monforte A, Lepri AC, Rezza G, Pezzotti P, Antinori A, Phillips AN, et al
. Insights into the reasons for discontinuation of the first highly active antiretroviral therapy (HAART) regimen in a cohort of antiretroviral naive patients: Italian Cohort of Antiretroviral-Naive Patients. AIDS 2000; 14:499–507.
33. Rezza G, Lepri AC, d'Arminio Monforte A, Pezzotti P, Castelli F, Dianzani F, et al
. Plasma viral load concentrations in women and men from different exposure categories and with known duration of HIV infection. J Acquir Immune Defic Syndr 2000; 25:56–62.
34. Galli M, Cozzi-Lepri A, Ridolfo AL, Gervasoni C, Ravasio L, Corsico L, et al
. Incidence of adipose tissue alterations in first-line antiretroviral therapy. Arch Intern Med 2002; 162:2621–2628.
35. Huang QR, Danis V, Lassere M, Edmonds J, Manolios N. Evaluation of a new Apo-1/Fas promoter polymorphism in rheumatoid arthritis and systemic lupus erythematosus patients. Rheumatology (Oxford) 1999; 38:645–651.
36. Garenc C, Aubert S, Laroche J, Girouard J, Vohl MC, Bergeron J, et al
. Population prevalence of APOE, APOC3 and PPAR-alpha mutations associated to hypertriglyceridemia in French Canadians. J Hum Genet 2004; 49:691–700.
37. Olivieri O, Bassi A, Stranieri C, Trabetti E, Martinelli N, Pizzolo F, et al
. Apolipoprotein C-III, metabolic syndrome, and risk of coronary artery disease. J Lipid Res 2003; 44:2374–2381.
38. Ellsworth DL, Coady SA, Chen W, Srinivasan SR, Boerwinkle E, Berenson GS. Interactive effects between polymorphisms in the beta-adrenergic receptors and longitudinal changes in obesity. Obes Res 2005; 13:519–526.
39. Zee RY, Cook NR, Reynolds R, Cheng S, Ridker PM. Haplotype analysis of the beta2 adrenergic receptor gene and risk of myocardial infarction in humans. Genetics 2005; 169:1583–1587.
40. Orio F, Matarese G, Di Biase S, Palomba S, Labella D, Sanna V, et al
. Exon 6 and 2 peroxisome proliferator-activated receptor-gamma polymorphisms in polycystic ovary syndrome. J Clin Endocrinol Metab 2003; 88:5887–5892.
41. Haubrich R, Riddler S, DiRienzo G, Komarow L, Powderly W, Garren K, et al
. Metabolic outcomes of ACTG 5142: a prospective, randomised, phase III trial of NRTI-, PI-, and NNRTI-sparing regimens for initial treatment of HIV-1 infection [abstract].Program and abstracts of the 14th Conference on Retroviruses and Opportunistic Infections
; 25–28 February 2007; Los Angeles, California.
42. McComsey GA, Paulsen DM, Lonergan JT, Hessenthaler SM, Hoppel CL, Williams VC, et al
. Improvements in lipoatrophy, mitochondrial DNA levels and fat apoptosis after replacing stavudine with abacavir or zidovudine. AIDS 2005; 19:15–23.
43. Li WW, Dammerman MM, Smith JD, Metzger S, Breslow JL, Leff T. Common genetic variation in the promoter of the human apoCIII gene abolishes regulation by insulin and may contribute to hypertriglyceridemia. J Clin Invest 1995; 96:2601–2605.
44. Bonnet E, Genoux A, Bernard J, Fauvel J, Massip P, Perret B. Impact of genetic polymorphisms on the risk of lipid disorders in patients on anti-HIV therapy. Clin Chem Lab Med 2007; 45:815–821.
45. Tarr PE, Taffé P, Bleiber G, Furrer H, Rotger M, Martinez R, et al
. Modeling the influence of ApoC3, ApoE, and TNF polymorphisms on the risk of antiretroviral therapy-associated lipid disorders. J Inf Dis 2005; 191:1419–1426.
46. Foulkes AS, Wohl DA, Frank I, Puleo E, Restine S, Wolfe ML, et al
. Associations among race/ethnicity, ApoC3 genotypes, and lipids in HIV-1-infected individuals on antiretroviral therapy. Plos Medicine 2006; 3:337–347.
47. Bard JM, Lassalle R, Capeau J, Bach-Ngohou K, Nazih-Sanderson F, Remy G, et al
. Association of apolipoproteins C3 and E with metabolic changes in HIV-infected adults treated with a protease-inhibitor-containing antiretroviral therapy. Antivir Ther 2006; 11:361–370.
48. Fischer-Posovszky P, Tornqvist H, Debatin KM, Wabitsch M. Inhibition of death-receptor mediated apoptosis in human adipocytes by the insulin-like growth factor I (IGF-I)/IGF-I receptor autocrine circuit. Endocrinology 2004; 145:1849–1859.
49. Kanemitsu S, Ihara K, Saifddin A, Otsuka T, Takeuchi T, Nagayama J, et al
. A functional polymorphism in fas (CD95/APO-1) gene promoter associated with systemic lupus erythematosus. J Rheumatol 2002; 29:1183–1188.
50. Maher B, Alfirevic A, Vilar FJ, Wilkins EG, Park BK, Pirmohamed M. TNF-alpha promoter region gene polymorphisms in HIV-positive patients with lipodystrophy. AIDS 2002; 16:2013–2018.
51. Carr A. HIV lipodystrophy: risk factors, pathogenesis, diagnosis and management. AIDS 2003; 17(Suppl 1):S141–S148.
52. Galli M, Veglia F, Angarano G, Santambrogio S, Meneghini E, Gritti F, et al
. A. Gender differences in antiretroviral drug-related adipose tissue alterations. Women are at higher risk than men and develop particular lipodystrophy patterns. J Acquir Immune Defic Syndr 2003; 34:58–61.
53. Galli M, Ridolfo AL, Adorni F, Cappelletti A, Morelli P, Massetto B, et al
. Correlates of risk of adipose tissue alterations and their modifications over time in HIV-1-infected women treated with antiretroviral therapy. Antivir Ther 2003; 8:347–354.
54. Walston J, Silver K, Bogardus C, Knowler WC, Celi FS, Austin S, et al
. Time of onset of non-insulin-dependent diabetes mellitus and genetic variation in the beta 3-adrenergic receptor gene. N Engl J Med 1995; 333:343–347.
55. Widén E, Lehto M, Kanninen T, Walston J, Shuldiner AR, Groop LC. Association of a polymorphism in the beta 3-adrenergic-receptor gene with features of the insulin resistance syndrome in Finns. N Engl J Med 1995; 333:348–351.
56. Hoffstedt J, Poirier O, Thörne A, Lönnqvist F, Herrmann SM, Cambien F, et al
. Polymorphism of the human beta3-adrenoceptor gene forms a well-conserved haplotype that is associated with moderate obesity and altered receptor function. Diabetes 1999; 48:203–205.
57. Leineweber K, Büscher R, Bruck H, Brodde OE. Beta-adrenoceptor polymorphisms. Naunyn Schmiedebergs Arch Pharmacol 2004; 369:1–22.
58. Kurokawa N, Nakai K, Kameo S, Liu ZM, Satoh H. Association of BMI with the beta3-Adrenergic receptor gene polymorphism in japanese: meta-Analysis. Obes Res 2001; 9:741–745.
59. Pèrez-Bravo F, Echiburù B, Maliqueo M, Santos JL, Sir-Petermann T. Tryptophan 64 Arginine polymorphism of beta-3-adrenergic receptor in Chilean women with polycystic ovary syndrome. Clin Endocrinol 2005; 62:126–131.
60. Vonkeman HE, ten Napel CH, van Oeveren-Dybicz AM, Vermes I. Beta-3-Adrenergic receptor polymorphism and the antiretroviral therapy-related lipodystrophy syndrome. AIDS 2000; 14:1463–1464.
61. Corbalán MS, Marti A, Forga L, Martínez-González MA, Martínez JA. B2-adrenergic receptor mutation and abdominal obesity risk: effect modification by gender and HDL-cholesterol. Eur J Nutr 2002; 41:114–118.
62. Hellström L, Large V, Reynisdottir S, Wahrenberg H, Arner P. The different effects of a Gln27Glu b2-adrenoceptor gene polymorphism on obesity in males and in females. J Intern Med 1999; 245:253–259.
63. Mori Y, Kim-Motoyama H, Ito, Katakura T, Yasuda K, Ishiyama-Shigemoto S, et al
. The Gln27Glu b2-adrenergic receptor variant is associated with obesity due to subcutaneous fat accumulation in Japanese men.Biochem Biophys Res Commun
64. Yamada K, Ishiyama-Shigemoto S, Ichikawa F, Yuan X, Koyanagi A, Koyama W, et al
. Polymorphism in the 5′-leader cistron of the b2-adrenergic receptor gene associated with obesity and type 2 diabetes. J Clin Endocrinol Metab 1999; 84:1754–1757.
65. Martinez JA, Corbalan MS, Sanchez-Villegas A, Forga L, Marti A, Martínez-González MA. Obesity risk is associated with carbohydrate intake in women carrying the Gln27Glu beta2-adrenoceptor polymorphism. J Nutr 2003; 133:2549–2554.
66. Bengtsson K, Orho-Melander M, Melander O, Lindblad U, Ranstam J, Råstam L, et al
. Beta(2)-adrenergic receptor gene variation and hypertension in subjects with type 2 diabetes. Hypertension 2001; 37:1303–1308.
67. Iaccarino G, Trimarco V, Lanni F, Cipolletta E, Izzo R, Arcucci O, et al
. beta-Blockade and increased dyslipidemia in patients bearing Glu27 variant of beta2 adrenergic receptor gene. Pharmacogenomics J 2005; 5:292–297.
68. Ishiyama-Shigemoto S, Yamada K, Yuan X, Ichikawa F, Nonaka K. Association of polymorphisms in the beta2-adrenergic receptor gene with obesity, hypertriglyceridaemia, and diabetes mellitus. Diabetologia 1999; 42:98–101.
69. Lange LA, Norris JM, Langefeld CD, Nicklas BJ, Wagenknecht LE, Saad MF, et al
. Association of adipose tissue deposition and beta-2 adrenergic receptor variants: the IRAS family study. Int J Obes 2005; 29:449–457.