The study population was divided according to ACE isoforms in urine as follows: ACE 65/90/190, presence of three ACE isoforms (n = 795), ACE 90+ (65/90) (n = 186), and ACE 90− (65/190) (n = 169) based on the presence (+) or absence (−) of the 90 kDa ACE isoform. The anthropometric parameters, lipid profile, serum levels of uric acid, glucose, and the systolic and diastolic BP were significantly greater in the ACE 90+ compared with the ACE 90− and ACE 65/90/190 individuals. We found that 98% of individuals from the ACE 90+ group and 38% from the ACE 65/90/190 group had hypertension, compared to only 1% hypertensive individuals in the ACE 90− group. There is a high presence of the 90 kDa N-domain ACE isoform (85%) in the studied population. The percentile of normotensive subjects with three isoforms was 62%. Our findings could contribute to the development of new efficient strategy to prevent and treat hypertension to avoid the development of cardiovascular disease.The aim of this paper was to investigate the presence of the urinary 90 kDa N-domain ACE in a cohort of the population from Vitoria, Brazil, to verify its association with essential hypertension since this isoform could be a possible genetic marker of hypertension. Anthropometric, clinical, and laboratory parameters of the individuals were evaluated ( Essential hypertension (EH) is a multifactorial and polygenic disorder affecting around 27% of adults worldwide . It has Many pathophysiological factors have been implicated in the genesis of EH . The ren Our group has recently described the 65 kDa N-domain isoform of ACE in the urine of both normotensive and hypertensive humans and rats, and the 90 kDa N-domain ACE isoform was solely found in the urine of hypertensive humans and rats –22. Acco Thus far, determinants of RAS activity are not completely known and it may play an important role in the pathogenesis of essential hypertension. Recently we described the association of 90 kDa N-domain ACE with plasma inflammatory markers, endothelial function, and family history of hypertension. Our data suggested that the 90 kDa ACE may be a marker for hypertension , 26. TheA cross-sectional study of cardiovascular risk factors was performed in the urban population of Vitoria, a city southeast region of Brazil, following the general guidelines of WHO-MONICA Project , 28. A rSubjects attended the University Hospital in 12 h fasting to blood sample collection and further evaluation of height, weight, smoking habits, blood pressure, electrocardiogram, aortic pulse wave velocity, and use of antihypertensive drugs. Fasting glucose, cholesterol, triglycerides, and uric acid were determined by standard techniques in a central laboratory. Diabetes mellitus was defined as fasting glucose >125 mg/dL. During the domicile visit all individuals were orientated to collect all urine produced from 7 pm to 7 am to estimate electrolyte  and creatinine nocturnal 12 h excretion. A sample of this urine was stored at −20°C and sent to a central laboratory to determine presence of ACE isoforms. Blood pressure (BP) was determined by trained nurses using standard mercury sphygmomanometer on the left arm after 5 min rest with the subject in the sitting position in three different times. The first and fifth phases of Korotkoff sounds were used for systolic and diastolic pressure, respectively. Clinic BP was determined as the mean value of two recordings obtained with a minimum 10 min interval. Presence of hypertension was defined as presence of clinic blood pressure ≥140/90 mmHg or use of antihypertensive drugs, including diuretics . This study was conducted in accordance with the Guidelines for Good Clinical Practice and the Declaration of Helsinki after approval by the Ethics Committees on Human Research from the Federal University of Espírito Santo (volume 4194/99-00) and from Federal University of Sao Paulo (0220/04). The informed consent was signed by all volunteers.μg denatured and reduced protein. Electrotransference was performed for 50 minutes at constant voltage (40 V) using a nitrocellulose membrane . The membrane was incubated in a 5.0% nonfat dry milk blocking solution for 4 hours before overnight incubation at room temperature (20°C) with monoclonal antibody 9B9  (diluted 1 : 1000). The subsequent steps were performed with the streptavidin/phosphatase alkaline system  and the bands were revealed using substrates NBT/BCIP as recommended by the manufacturer . In addition, the same researcher, blinded to clinical data, performed all western blotting of this survey.Urine samples were collected with the addition of proteases inhibitors  and subsequent frozen. After unfrozen, pH was corrected to 8.0 with 1 mol/L TRIS buffer. These samples were centrifuged 2568 ×g and the supernatant was concentrated in Microcon . The protein concentration was determined by the Bradford method  (Bio-RadTo exemplify the urine separation of ACE isoforms we used a DEAE-cellulose chromatography procedure. The supernatant (100 mL) of dialyzed urine collected in presence of protease inhibitors  was chromatographed on a DEAE-cellulose cellex D column (1.5 × 10 cm) equilibrated with 20 mM Tris/HCl buffer, pH 7.0. Elution was carried out with a linear gradient of 20 mM to 500 mM Tris/HCl buffer, pH 7.0 at a flow rate of 60 mL/h, the protein elution profile was monitored by UV absorbance at 280 nm, and the fractions were assayed for ACE activity against Z-Phenyl-L-Histidyl-L-Leucine (Z-Phe-His-Leu) as substrate (Bachem Bioscience Inc) as described previously , 33.+ (65/90 kDa), and ACE 90− (65/190 kDa) based on the presence (+) or absence (−) of the 90 kDa N-domain ACE isoform. Based on our previous studies that the ACE 90+ group may be associated with higher BP levels [P < 0.05.To evaluate the association between blood pressure levels, metabolic and anthropometric parameters, the study population was divided according to ACE isoforms in urine as follows: ACE 65/90/190 kDa, presence of three ACE isoforms; ACE 903.1. ACE Isoforms and Activity Profile. The study population was stratified according to ACE isoforms and the mean age of the overall population was 44 years, range 23–65 years. Profile of ACE isoforms found by Western blotting analysis using the antibody (9B9) is shown in + group compared with the ACE 90− and ACE 65/90/190 groups , BMI , serum uric acid , urinary sodium excretion , and glucose  were independent predictors of systolic blood pressure in the entire sample. Similar analysis was performed to diastolic blood pressure and we found that age , BMI , waist-to-hip ratio , uric acid , and urinary sodium excretion  reached statistical significance.For the entire cohort, significant positive associations were observed between blood pressure levels and age, BMI, waist-to-hip ratio, total cholesterol, triglycerides, uric acid, glucose, and urinary sodium excretion . To esta+group, we performed an analysis of covariance controlling for potential confounding variables such as age, gender, race, smoking status, presence of diabetes, BMI, waist-to-hip ratio, antihypertensive drugs use lipid profile, glucose, uric acid and urinary sodium excretion. After these adjustments, the mean value for both diastolic and systolic blood pressure remained higher in the ACE 90+ group than that in the ACE 90− and in the ACE 65/90/190 groups, although there was a attenuation in the blood pressure levels between groups  .Urinary analysis of ACE isoforms showed that 85.3% of subjects present ACE 90 kDa isoform while in 14.7% of the subjects the 90 kDa ACE isoform was absent. Subjects presenting the three ACE isoforms 65/90/190 kDa represent the higher population subgroup (around 69.1%) and in this group 38% were hypertensive. These data strongly suggest that the presence of the 90 kDa N-domain ACE isoform in the urine could be associated with EH. These data confirm and extend previous studies of our laboratory where we detected a positive association of urinary 90 kDa ACE isoform with family history of hypertension and endothelial function in normotensive individuals . We alsoThe proteic profile of ACE isoforms found in the urine of volunteers repeated the previous results of our group , 25, 26,We showed normotensive subjects with two peaks with ACE activity corresponding to 190 and 65 kDa ACE, hypertensive subjects with two peaks with ACE activity corresponding to 90 and 65 kDa ACE, and normotensive subjects with three peaks with ACE activity corresponding to 190, 90 and 65 kDa ACE. The analysis of expression by Werstern blotting of urinary ACEs showed that the bands corresponding to these peaks confirm the profile found in the chromatography.− group and hypertension was almost absent.Statistical analysis showed a positive association between 90 kDa N-domain ACE isoform and presence of hypertension. Since this finding was observed in a transversal study, we cannot establish a casual relationship between these variables. However we can speculate some casual relation between presence of 90 kDa isoform and age-dependent blood pressure increase because blood pressure values were quite low in the ACE 90Several studies have shown that acid uric plasma level independently predicts hypertension development and can even be causal , 41. It  In Pearsons's analysis we observed a positive correlation between age, BMI, WHR, cholesterol, triglyceride, glucose, uric acid, sodium excretion, and either SBP and DBP. In addition to covariance analysis in subjects with presence or absence of the 90 kDa N-domain ACE isoform, both associations were sustained for both SBP and DBP in the group with 90 kDa N-domain ACE isoform present.Despite the correlation described previously, the physiological significance of the 90 kD ACE isoform remains to be determined. It will be important to determine whether it is a splicing variant, a posttranscription alteration product, or simply produced by the degradation of the 190 kDa isoform. Independent of the mechanism for production of the soluble form of N-domain ACE, this isoform may be physiologically and pathophysiologically important –46.−). As shown in  Analysis of blood pressure levels could show that subjects with 90 kDa ACE have systolic and diastolic values higher than the group without this isoform. When the group with 90 and 65 isoforms was analyzed, they have systolic and diastolic levels higher than the other two groups (ACE 65/90/165 and ACE 90There is a high presence of the 90 kDa N-domain ACE isoform (85%) in the studied population. In addition this enzyme is associated with many known risk factors for cardiovascular disease. Although the mechanism involved in the generation of this isoform remains unknown, some physiological alterations can be associated with this expression in human urine and this should be used to assess hypertension risk in normotensive individuals. However, casual relationships should be established in longitudinal studies.A second phase (5 years after) of this study is already being done prospectively analyzing ACE isoforms in the urine of these same volunteers, so causal associations may be evaluated. The percentile of normotensive subjects with three isoform was 62%; a prospective study of these subjects, specially, is very important to know how many will develop hypertension once they express the possible biomarker of hypertension (ACE 90 kDa) in their urine and will be possible confirm that this biomarker can really predict hypertension.Our findings could contribute to the development of new efficient strategy to prevent and treat hypertension to avoid the development of cardiovascular disease.The ACE 90 kDa absent is clearly associated with many important factors in maintenance of lower levels of blood pressure as  that increase with aging. These people can be a low proinflammatory status (opposite the group with the presence of the 90 kDa) and with low predisposition to increase of blood pressure levels. Finally the practical consequence of this study is that the 90 kDa ACE was associated with the presence of hypertension and the absence of this was associated with subjects with normal blood pressure levels, so this isoform would be a urinary marker of hypertension in normotensive subjects.


Parkinson disease (PD) is characterized by the degeneration of nigrostriatal dopaminergic neurons. However, postmortem evidence indicates that the pathology of lower brainstem regions, such as the pons and medulla, precedes nigral involvement. Consistently, pontomedullary damage was implicated by structural and PET imaging in early PD. Neurochemical correlates of this early pathological involvement in PD are unknown.To map biochemical alterations in the brains of individuals with mild-moderate PD we quantified neurochemical profiles of the pons, putamen and substantia nigra by 7 tesla (T) proton magnetic resonance spectroscopy. Thirteen individuals with idiopathic PD (Hoehn & Yahr stage 2) and 12 age- and gender-matched healthy volunteers participated in the study. γ-Aminobutyric acid (GABA) concentrations in the pons and putamen were significantly higher in patients  than controls . The GABA elevation was more pronounced in the pons (64%) than in the putamen (32%). No other neurochemical differences were observed between patients and controls.The GABA elevation in the putamen is consistent with prior postmortem findings in patients with PD, as well as with in vivo observations in a rodent model of PD, while the GABA finding in the pons is novel. The more significant GABA elevation in the pons relative to the putamen is consistent with earlier pathological involvement of the lower brainstem. This study provides in vivo evidence for an alteration in the GABAergic tone in the lower brainstem and striatum in early-moderate PD, which may underlie disease pathogenesis and may provide a biomarker for disease staging. The major pathologic marker of PD is the degeneration of nigrostriatal dopaminergic neurons which leads to a reduction in dopamine (DA) content within the striatum 1H MRS) that can non-invasively monitor alterations in neurochemical levels and has been used to study neurochemical alterations in PD with some success Motivated by these histological, positron emission tomography (PET) and MRI findings indicative of early functional and structural changes in PD, we sought to gain further insights into biochemical alterations in this disease that are thought to precede structural changes. We utilized in vivo proton magnetic resonance spectroscopy  and 12 age-matched healthy volunteers  participated in the study after giving written informed consent using procedures approved by the Institutional Review Board: Human Subjects Committee of the University of Minnesota. Participants were not demented  and mild-moderate disease severity of patients was established with the Unified Parkinson Disease Rating Scale (UPDRS) and Hoehn & Yahr Staging (H&Y) . Patient2; TR = 3 s; TE = 93 ms; flip angle = 150°; slice thickness = 3 mm; 48 slices; one average) were used to select the SN VOI. Destructive B1+ interferences in the VOI were reduced by localized B1+ shimming as described before 3, number of transients NT = 128), posterior putamen  and SN   equipped with a Siemens console. A 16-channel transmit/receive transmission line array head coil was used T = 384) . Pons anUnsuppressed water spectra acquired from the same VOI were used to remove residual eddy current effects and to reconstruct the phased array spectra 1 weighted brain image constructed from 152 normal subjects at the Montreal Neurological Institute, Montreal, QC, Canada) using FSL-FLIRT  Linear Image Registration Tool) To delineate exactly which nuclei were included in our VOI, the MPRAGE and turbo spin echo images were registered by full affine transformations to the MNI152 space (average Tmyo-inositol (myo-Ins), lactate (Lac), NAA, N-acetylaspartylglutamate (NAAG), phosphoethanolamine (PE), scyllo-inositol (scyllo-Ins) and taurine (Tau) were generated based on previously reported chemical shifts and coupling constants 1 and T2 effects because long TR and ultra-short TE values were used. Metabolites quantified with Cramér-Rao lower bounds  >50% were classified as not detected, as suggested by the LCModel manual Metabolites were quantified using LCModel Statistical analyses were conducted using SPSS . MRS data from the two groups were compared using a one-way analysis of variance for each metabolite concentration and CRLB in each brain region. Due to the pilot nature of the study p-values shown have not been adjusted for multiple testing. Relationships between clinical scores and metabolite concentrations were evaluated using Pearson correlation coefficients. Measures of spectral quality  and demographic and clinical characteristics  of the two groups were compared using the two-tailed, unpaired student's t-test.Patient and control groups were not different with regards to age and gender . All patArtifact free spectra with good SNR and spectral resolution and excellent water suppression were obtained in all brain regions for both patients and controls. The full width at half maximum and SNR values determined by LCModel were not different between patients and controls for any VOI p>0.05, , therefoThis spectral quality enabled the quantification of a neurochemical profile consisting of 11 metabolites in the pons and putamen and 7 metabolites in the SN . The neuThere were no significant relationships between the GABA concentrations and either the UPDRS scores  or H&Y scores for any of the VOIs.Here using ultra-high field MRS we demonstrate elevated GABA levels in the pons and putamen of patients with mild-moderate PD as compared to age- and gender-matched healthy controls. The striatal GABA elevation is consistent with postmortem findings in patients with PD 1 in the pontomesencephalic junction 1 decrease. Thus, a neurochemical abnormality was expected in the caudorostral extent of the pons. The most likely neurochemical alteration to indicate neuronal loss would be a lower NAA level 18F-dopa uptake in the LC region in patients with more advanced PD (H&Y 2–3) indicating a progressive loss of noradrenergic terminal function Since Braak suggested a caudorostral progression of α-synuclein pathology in PD starting in the medulla oblongata in vivo in patients with mild-moderate PD. This GABA elevation in the putamen likely stems from striatal GABAergic neurons, rather than GABAergic afferents, because the primary afferents to the striatum are glutamatergic and dopaminergic, while the predominant cell type in the striatum is the medium sized GABAergic spiny neurons. Animal models of PD have shown that experimental lesions of the dopaminergic nigrostriatal pathway result in elevated striatal GABA content 1H MRS studies to investigate the consequences of striatal GABA alterations in other regions could also provide further insight. Specifically, investigations of GABA concentrations in the medial pallidal segment and motor thalamic nuclei would be critical since these regions play an important role regarding the outputs of the basal ganglia to the cerebral cortex.Regarding our putamenal findings, postmortem studies of individuals with advanced disease demonstrated elevated striatal GABA levels, particularly in the putamen The main limitation of our study is the small sample size. This may have prevented the detection of neurochemical alterations in the SN. Alternatively, the very small size of the VOI (∼1 mL) necessitated by the anatomy of the SN (resulting in low SNR), and high iron content  and therefore the finding is robust. The difference in the putamen was less significant, which may reflect the earlier involvement of the pons in PD pathogenesis. Alternatively, the CRLB cut-off (CRLB ≤50%) we used to select reliable concentrations may have biased the GABA concentration estimates of controls in the putamen. In the putamen, seven of eleven control subjects' GABA concentrations met our reliable quantification criterion and four subjects' GABA concentrations had CLRB in the range of 50–55% and hence were excluded from the analyses. These excluded GABA concentrations were around ∼1 µmol/g and their inclusion would lower the average GABA concentration in the control group and increase the significance level of the GABA difference in putamen (p<0.001). On the other hand, a larger GABA difference in the pons (52%) vs. the putamen (20%) was supported by evaluation of averaged spectra  that ovemyo-inositol, respectively, and in neurotransmitter levels, such as glutamate and GABA. Based on the findings of the current study, future studies can utilize edited spectroscopy to focus on measurements of GABA in PD. However, edited MRS measurements of GABA require larger VOI than those utilized here because of longer echo times and consequently lower SNR. Also, edited GABA measurements need to take potential differences in T2 between patients and controls into account when interpreting concentration differences. Such potential T2 differences are negligible at the ultra-short echo times used in the current study. While T2 differences between patients with PD and controls are unlikely for the pons and putamen based on similar linewidths we observed  from the 3 regions-of-interest in patients with PD and healthy controls. Only metabolites quantified with CRLB ≤50% in at least half of the spectra from a brain region were included. CRLB of metabolites that were significantly different or showed a trend between the two groups are marked with *p<0.07, **p<0.001. Error-bars: inter-subject SD. Asc, ascorbate; GABA, γ-aminobutyric acid; Gln, glutamine; Glu, glutamate; GSH, glutathione; (TIF)Click here for additional data file.


The TP53BP1 gene may be involved in the development of cancer through disrupting DNA repair. However, studies investigating the relationship between TP53BP1 Glu353Asp (rs560191) polymorphism and cancer yielded contradictory and inconclusive outcomes. In order to realize these ambiguous findings, a meta-analysis was performed to assess the association between the TP53BP1 Glu353Asp (rs560191) polymorphism and susceptibility to cancer.We conducted a search of all English reports on studies for the association between the TP53BP1 Asp353Glu (rs560191) polymorphism and susceptibility to cancer using Medline, the Cochrane Library, EMbase, Web of Science, Google (scholar), and all Chinese reports were identified manually and on-line using CBMDisc, Chongqing VIP database, and CNKI database. The strict selection criteria and exclusion criteria were determined, and odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of associations. The fixed or random effect model was selected based on the heterogeneity test among studies. Publication bias was estimated using funnel plots and Egger’s regression test.A total of seven studies were included in the meta-analysis including 3,213 cases and 3,849 controls. The results indicated that the Glu353Asp (rs560191) polymorphism in TP53BP1 gene had no association with cancer risk for all genetic models. In the subgroup analysis, the results suggested that Glu353Asp polymorphism was not associated with the risk of cancer according to ethnicity, cancer type, genotyping method, adjusted with control or not, HWE and quality score.This meta-analysis suggested that the Glu353Asp (rs560191) polymorphism in TP53BP1 gene was not associated with risk of cancer. It was reported that there were about 12.7 million new cancer cases and 7.6 million cancer deaths through out the world in 2008 TP53BP1 gene has played an important role in both DNA repair and cell cycle control and also mediates the DNA damage checkpoint through cooperation with damage sensors and signal transducers Considering a single study may lack the power to provide a reliable conclusion, we performed a meta-analysis on these eligible studies to investigate the precise relationship between TP53BP1 Asp353Glu (rs560191) polymorphism and susceptibility to cancer, which would have a much greater possibility of reaching reasonably strong conclusions.We searched Medline , Embase, the Cochrane Library, Chinese Biological Medicine, China National Knowledge Infrastructure, Wang Fang Data and Chongqing VIP database  using the terms “p53-binding protein 1 or TP53BP1 or 53BP1”, “Asp353Glu or rs560191 or D353E”, “cancer or tunor or carcinoma” and “polymorphism, variant or mutation”. The selection was done without restriction on language, but we only included published articles written in English or Chinese. We used the PubMed option “Related Articles” for each study to retrieve additional potentially relevant articles. Reference lists were checked and researchers were contacted for additional literatures.Studies were selected if they met the following criteria: (1) association study with a case-control or cohort design; (2) the study investigated the association between TP53BP1 (rs560191) polymorphism and the risk of cancer; (3) in the case of multiple publications from the same study group, the most complete and recent results were used.The exclusion criteria were defined as: 1) abstracts, reviews and animal studies; 2) useless data reported, genotype number or frequency not included; and 3) study without sufficient data for meta-analysis. If more than one study was published by the same authors using the same case series, only the most recent study or the study with the largest size of samples was included in our meta-analysis.Two reviewers (Lei Liu and Jinghua Jiao) independently scrutinized studies on the associations between TP53BP1 Asp353Glu (rs560191) polymorphism and risk of cancer. When discrepancies were appeared, all investigators were recruited to assess the data. The following information was collected: First author, publication year, location, ethnicity, sample sizes of patients and controls, study design and genotype numbers.The reviewers developed a quality assessment scale , which wThe review and analysis were guided to conduct by the PRISMA statement for preferred reporting of systematic review and meta-analysis 2I statistic interpreted as the proportion of total variation contributed by between-study variation. We also measured the effect of heterogeneity using a quantitative measure, 2I = 100%×(Q−d f)/Q. If there was a statistical difference in terms of heterogeneity , the random effects model would be used to estimate the pooled ORs P value of smaller than 0.05 for any test was considered to be statistically significant.Odds ratios (ORs) with 95% confidence intervals (CIs) for genotypes and alleles were used to assess the strength of association between TP53BP1 Asp353Glu (rs560191) polymorphism and risk of cancer. The ORs were performed for the allele contrasts, additive genetic model, as well as recessive genetic model and dominant genetic model, respectively. Heterogeneity was examined with As showed in As showed in According to sensitivity analysis, the results showed us that there was no substantial modification of our estimates after exclusion of individual studies, indicating that the results were stable (data not shown).It is well known that SNPs may contribute to an individual’s susceptibility to cancer and TP53BP1 is a key component in the cellular response to DNA damage To the best of our knowledge, some researches that aim at the role of Asp353Glu (rs560191) polymorphism in cancer risk have been performed, but the results are controversial. In order to evaluate on the association between the Asp353Glu (rs560191) polymorphism and cancer risk, we performed this meta-analysis.We have not found a sinificant association between TP53BP1 Asp353Glu (rs560191) polymorphism and cancer risk in overall population, but different ethnicity, study design, genotyping methods and cancer type would be responsible for the negtive conclusions. We perfomed subgroup analysis based on these factors. However, the resluts showed us that Asp353Glu (rs560191) polymorphism were not associated with the risk of cancer according to ethnicity, cancer type, study with matching or not, genotyping methods, HWE and study score. That may be because only one study Some studies indicate that TP53BP1 variants may have protective effects on squamous cell carcinoma of the head and neck (SCCHN) risk but such effects were confined to TP53 Arg72Pro variant allele/haplotype carriers The meta-analysis by Timofeeva et al. There are several limitations in this meta-analysis that should be considered. First, cancer is a multi-factorial disease including complex interactions from environmental exposure to gene factors. In this meta-analysis, we had insufficient data to perform an evaluation of such interactions for the independent role of TP53BP1 Asp353Glu (rs560191) polymorphism in cancer development. Second, only seven studies were included in this meta-analysis. Thus, more studies are needed to identify this association more comprehensively. Third, study by Naidu et al. In conclusion, this meta-analysis suggested that the polymorphism in TP53BP1 Asp353Glu (rs560191) gene could not be regarded as a genetic risk factor for cancer. At the same time, this result should be interpreted cautiously. To verify this result, large scale case-control studies with detailed individual information are needed.Checklist S1PRISMA 2009 Checklist.(DOC)Click here for additional data file.


P values may allow for less spurious findings. Permutation has not been empirically tested in meta-regression. The objective of this study was to perform an empirical investigation to explore the differences in results for meta-analyses on a small number of trials using standard large sample approaches verses permutation-based methods for meta-regression.In meta-regression, as the number of trials in the analyses decreases, the risk of false positives or false negatives increases. This is partly due to the assumption of normality that may not hold in small samples. Creation of a distribution from the observed trials using permutation methods to calculate P values between methods.We isolated a sample of randomized controlled clinical trials (RCTs) for interventions that have a small number of trials . Trials were then grouped by herbal species and condition and assessed for methodological quality using the Jadad scale, and data were extracted for each outcome. Finally, we performed meta-analyses on the primary outcome of each group of trials and meta-regression for methodological quality subgroups within each meta-analysis. We used large sample methods and permutation methods in our meta-regression modeling. We then compared final models and final P values for the covariates in the final model were larger in 78% (7/9) of the cases for permutation and identical for 22% (2/9) of the cases.We collected 110 trials across 5 intervention/outcome pairings and 5 to 10 trials per covariate. When applying large sample methods and permutation-based methods in our backwards stepwise regression the covariates in the final models were identical in all cases. The P values in meta-regression of multiple covariates for relatively small amount of trials.We present empirical evidence that permutation-based resampling may not change final models when using backwards stepwise regression, but may increase  Systematic reviews are prone to various forms of heterogeneity between included studies. Variability in the participants, interventions and outcomes across studies may be termed clinical heterogeneity; variability in the trial design and quality is typically termed methodological heterogeneity; variability in treatment effects between trials can be termed statistical heterogeneity ,2. MethoIn systematic reviews that assess heterogeneity, this is typically examined through subgroup analyses or meta-regression. Subgroup analyses involve dividing the complete dataset into smaller subgroups to make comparisons between them. It is suggested that subgroup analyses be preplanned as part of a systematic review protocol, and even then they should be interpreted with caution . SubgrouMeta-regression is an extension of subgroup analyses that allows continuous as well categorical variables to be examined and for the investigation of multiple variables of interest, with the exception of comparisons with less than 10 trials . Meta-reFirst, meta-regression involves making observational associations that are subject to bias  and confounding . Also, many systematic reviews using this technique include only a small number of studies while any one of a large number of characteristics of these studies could be a cause of heterogeneity ,2. That P value is based upon the assumption that the two statistics were sampled from a normal distribution. For permutation tests, a covariance matrix, or distribution, is created for all possible pairs of observations for groups A and B . Next, a ratio is created relative to the frequency that the observed difference in treatment effect found in the primary analysis exceed the overall summary differences obtained from the permutation analysis resulting in a P value . A simulation study has demonstrated that permutation analyses result in more conservative P values and less false positive rates than standard meta-regression (when referring to the t statistic) especially in the presence of heterogeneity, when there are a small number of studies, or when there are a large number of covariates [The permutation test is useful for analyses of a small number of studies or a large number of covariates and has the goal of maintaining the type 1 error rate . Permutavariates .Due to the large number of treatment level covariates in trials of herbal interventions  and the Hypericum perforatum L. (St. John's wort) for treating patients with depression, Ginkgo biloba (ginkgo) for dementia, Serenoa repens  for benign prostatic hypertrophy, and Allium sativum (garlic) for blood lipids . Next, we examined the details of the included RCTs for each pairing and determined which trials included similar outcome measures. All other trials were excluded from the analyses.From a sample of 406 randomized controlled trials (RCTs) of herbal medicine identified through a literature search reported elsewhere , 2 indivA generally accepted 'rule of thumb' is that ten events per predictor variable (EPV) will maintain bias and variability at acceptable levels. This guidance derives from two simulation studies carried out for logistic and Cox modeling strategies -11. ThisNext, we identified a variety of intervention level covariates for which to explore heterogeneity. We consulted a group of four individuals with expertise in RCTs of herbal medicine interventions who were asked to identify characteristics of the herbal medicine interventions that might influence estimates of treatment effect . The list intervention level covariates was compiled and included: dose, duration of use, percentage of active constituent, part of plant used, form of product , method of extraction, and the extraction solvent used.Methodological quality was assessed separately and independently by two individuals. We assessed the sequence generation, allocation sequence concealment, blinding, and description of withdrawals and dropouts, which was the Cochrane practice at the time of this research ,14. EachAll assessments were entered into preformatted extraction forms. The assessors met on a weekly basis to discuss disagreements that were then resolved by consensus. A third party was not required to resolve any disagreements.One individual extracted the following data and a second individual checked all extractions: type of intervention, details of the intervention identified above, summary effect estimates , relative risk (RR), risk difference (RD), no. needed to treat (NNT), no. needed to harm (NNH)) for the outcomes of interest, baseline values for the outcomes of interest in each group, participant levels characteristics , sample sizes per group (intention to treat where available), measures of central tendency for all groups  and measures of variability  before and after treatment on all outcomes of interest, trial length (in weeks), and year of publication.All statistical procedures were performed by one individual (JJG) using STATA 10.0 .P values, ranges or interquartile ranges according to methods described in the Cochrane handbook [For each trial, where effect sizes were not reported for continuous outcome measures we calculated them from reported means for all outcomes of interest. For continuous variables the effect sizes calculated were mean differences (MD) from baseline. All effect estimates for the outcomes of interest were calculated on intention to treat (ITT) data where reported. When variance data were not reported as SDs, they were calculated from the trial data using the standard error of the mean (SE), 95% confidence intervals, reported handbook . When trP value for the main effect and I2 results for statistical heterogeneity with the associated P value. Where measures of variance were imputed from the average across the other trials, we performed a sensitivity analysis by removing those trials and comparing the results with the findings for the analysis including all trials.The main meta-analysis used a random effects model on the weighted mean differences (WMD) of the primary outcome of interest across all trials. We then collected the WMD, together with 95% CI, 2 statistic measures the magnitude of statistical heterogeneity that can be expected by partitioning out the chance heterogeneity. Therefore, the presence of statistical heterogeneity was tested using Cochran's Q test [2 [2 of 0% to 40% will indicate no observed statistical heterogeneity, 30% to 60% moderate heterogeneity, 50% to 90% substantial heterogeneity, and 75% to 100% considerable heterogeneity [Statistical heterogeneity was detected with Cochran's Q test ,16, whics Q test ,16 and tWe performed multivariable meta-regression on the summary treatment effect for the covariates identified above, separated into two models for all intervention outcome pairings. Covariates representing similar topics were grouped into models through a small group process with the investigators. The first model (model 1) included methodological covariates  and adequate allocation concealment). The second model (model 2) included participant level and intervention level covariates . All categorical covariates were coded in a binary manner.P value for contribution to the model was dropped and the regression was repeated. For each model we used standard large sample methods (referring to the t distribution) and permutation-based resampling to arrive at P values. Variables were dropped until only significant predictors of the treatment effect remained. To maintain model validity, if a binary coded categorical variable was statistically significant, both categories of the variable were kept in the model. Collinear variables were also dropped from the model and explored individually for significance. Statistically significant P values were those less than 0.05. We then compared the final models and models obtained with each method.We used backwards stepwise elimination in which the variable with the largest non-significant o:ux = uy. The assumption being if × data are sampled from the distribution Px and the Y data from Py then under the null hypothesis all permutations of observations are equally probable. The test statistic was the WMD from the meta-analysis results above on all levels of the covariates across trials. We then estimated the null distribution for the treatment effect by permuting (randomly shuffling) the observations in the combined × and Y samples to create all possible distributions. We then compared the effect estimate (or difference in effect) obtained with meta-regression for each covariate against the permuted distribution of effects to arrive at a P value. All permutations were set at 10,000 shuffles for each analysis and were performed simultaneously across all variables.In the permutation test we tested the equality of two means: H2 values ranging from 65.7% to 99.1%.A total of 110 trials were included in our analyses -A. sativum (garlic) and for total cholesterol (TC)-A. sativum resulted in no covariates remaining significant. The P values and I2 of the backwards stepwise elimination procedure for large sample methods (referring to the t table) and the corresponding P values using permutation-based resampling including are listed in Tables P values for the covariates in the final model were larger in 78% (7/9) of the cases for permutation and identical for 22% (2/9) of the cases.Many of the intervention level covariates were not reported in the included trials. Also, in no instance did a trial report enough information to code a trial as performing inadequate allocation concealment. Therefore, this variable was coded in a binary manner . For the backward stepwise meta-regression procedures, the covariates remaining in the final models were identical for large sample techniques and for permutation-based resampling methods of arriving at Hypericum perforatum (St. John's wort)-Hamilton Depression scale (HAM-D) pairing, the backward stepwise elimination meta-regression and permutation P values are listed in Table P values obtained with the permutation tests exceeded those obtained with standard meta-regression. The stepwise elimination meta-regression and permutation P values for the influence of covariates on the effect of Allium sativum on high-density lipoprotein (HDL) are listed in Table P values obtained with permutation were identical to those obtained with standard large sample meta-regression. This analysis yielded the smallest I2 value (45.8%) of all stepwise elimination values in all models. The stepwise elimination meta-regression and permutation P values for the effect of covariates on changes in triglyceride (TG) for Allium sativum are listed in Table P values for permutation were larger than those obtained with large sample methods.For the 2 value 4.8% of al2), and the P values for both the large sample methods and permutation-based resampling. In the model exhibiting moderate levels of statistical heterogeneity , and with an adequate number of trials per variable  both methods of arriving at P values produce identical values.In Table Approximately 50% of systematic reviews use statistical techniques to combine study results and most of these assess consistency across the studies . SeveralOur study found that using backwards stepwise meta-regression with large sample methods or with permutation-based resampling resulted in identical final models. To the best of our knowledge this is the first empirical test of permutation in meta-regression modeling using an elimination procedure. The results are surprising given that we only had 5 to 6.25 trials per covariate in all of the initial models, which is well below the recommended 10 trials per variable -12. GiveP values obtained using permutation tests are more conservative, or larger, than P values obtained using standard meta-regression methods. Specifically, the P values for significant covariates obtained with stepwise meta-regression were larger with permutation 78% of the time and identical 22% of the time compared with using standard large sample methods of obtaining P values. This finding is particularly important when P values are near a set level of statistical significance , since any increase in the P value will render the result non-significant. This finding provides empirical evidence that permutation tests increase P values and that permutation can be used in meta-analyses especially when examining the effects of multiple covariates, when faced with a relatively small number of included primary studies, or when a large amount of statistical heterogeneity is present. However, these results do not indicate that permutation-based resampling protects against associations arising due to ecological bias. One must always be aware that some associations found at the group level, in this case the study level, may not apply at the individual level.We also found that the P values, but not in all instances. For example, they found that for the covariate 'intention to treat analysis' the P value obtained by meta-regression was larger than that found with permutation. We found that out of nine significant covariates the P values for seven of these were larger in the permutation tests. In the other two instances the P values were identical. It is possible that the relatively low heterogeneity found in the latter final model (45.8%), or the relative normality of the distribution of effects in the final model resulted in this finding. It is possible that the level of statistical heterogeneity plays a larger role than the number of trials in meta-regression. This hypothesis remains to be tested.Our findings are similar to those of Higgins and Thompson  who founP values when exploring heterogeneity in these circumstances and will lead to more conservative probability estimates. In some cases the P value may cross over to non-significance. This finding is important in meta-analytic research especially since meta-analyses often include a small number of primary studies [Meta-regression may result in spurious findings with either multiple covariates, with a small number of primary studies ,25-28 or studies ,15, incl studies , and the studies . The abi studies  it is adP values are likely robust. Another strength of this study is that it extends the statistical techniques that can be used in meta-analyses, giving reviewers an empirically validated method when analyzing the influence of covariates.This study has several strengths. First, we included a large number of primary studies and crosschecked the data extractions. By including a large number of studies we have performed an empirical test of permutation, which goes beyond previous simulations . Next, wP values obtained from standard meta-regression and permutation tests on a sample of trials for several covariates. This project was in effect an empirical exercise comparing two separate statistical techniques for arriving at P values. Another potential drawback of this study was that at no point did the permutation test change a significant P value to a non-significant one. Even though we did not see this, this would be expected since in most instances the permutation P value exceeded the meta-regression values. It is conceivable that such P value increases would result in a marginally significant P value obtained with meta-regression to become non-significant with permutation [P values are often used to determine the existence of covariate-based effect modification, one should be certain to complement P values with actual differences in the effects estimates to determine if changes in the effect are clinically significant. Further research could build upon the intersection of statistical and clinical significance in effect modification. Finally, the last drawback of this research was that data from eight trials for the SJW depression pairing were extracted from Cochrane reviews [A drawback of this study is that it may not include all RCTs examining the herbal medicine outcome pairings chosen. That is, the treatment effect estimates presented in Table mutation . Also, t reviews ,32. TherIn summary, given that systematic reviews frequently contain a small number of studies and often wish to explore the influence of covariates to explain heterogeneity, the permutation test may help to protect against spurious findings when using meta-regression. However, the changes in significance level we found for the permutation test in the sample of trials we included were small. Furthermore, the relationship between the magnitude of statistical heterogeneity, events per variable and meta-regression with permutation-based resampling should be explored in future research.The authors declare that they have no competing interests.JJG conceived of the study design, performed all data extractions and data analysis and wrote the manuscript. JB conceived of the study design and helped write and edit the manuscript. DM aided in the study design and helped edit the manuscript. HB aided in the study design and helped edit the manuscript. CB aided in the study design and helped edit the manuscript. All authors read and approved the final manuscript.


Genetic variability may influence methadone metabolism, dose requirements, and risk of relapse.CYP2B6*6 or ABCB1 (rs1045642) polymorphisms are associated with variation in methadone response .To determine whether the CYP2B6*6 or ABCB1 polymorphisms.Two independent reviewers searched Medline, EMBASE, CINAHL, PsycINFO, and Web of Science databases. We included studies that reported methadone plasma concentration, methadone response, or methadone dose in relation to the CYP2B6*6 homozygous carriers when compared to non-carriers  with minimal heterogeneity (I2 = 0%). Similarly, trough (S) methadone plasma concentration was higher in homozygous carriers of the *6 haplotype when compared to non-carriers,  however significant heterogeneity was observed (I2 = 69%). Carriers of the CYP2B6*6 haplotype were not found to be significantly different from non-carriers with respect to dose or response to treatment. We found no significant association between the ABCB1 polymorphism and the trough (R), (S) plasma concentrations, methadone dose, or methadone response.We screened 182 articles and extracted 7 articles for inclusion in the meta-analysis. Considerable agreement was observed between the two independent raters on the title , abstract , and full text screening . Trough (R) methadone plasma concentration was significantly higher in CYP2B6*6 genotype have higher trough (R) and (S) methadone plasma concentrations, suggesting that methadone metabolism is significantly slower in *6 homozygous carriers.Although the number of studies included and sample size were modest, this is the first meta analysis to show participants homozygous for the  Methadone maintenance therapy (MMT) is a substitute opioid therapy (SOT) used to treat opioid withdrawal symptoms. SOT is a harm reduction approach aimed to treat the symptoms of opioid withdrawal in a controlled environment. Currently methadone is the most common and efficaciously used SOT in the treatment of opioid addiction Continued opioid abuse is one of the most common risk factors for mortality among patients in MMT, often because of the high risk for overdose when taking methadone in concurrence with other opioids ABCB1) SNP (rs1045642) and the Cytochrome p450 2B6 *6 haplotype SNPs. The ABCB1 SNP and CYP2B6 haplotype were the most widely reviewed genetic determinants within the methadone literature. See Table S1 for a list of the SNPs reviewed during the process of SNP selection, which was constructed to outline all the SNPs reviewed in the preliminary search, and all available studies were cited within this chart. Before explicitly addressing the objectives of this systematic review, we will first provide background information on the MMT treatment regime and the genes of interest for this review.While meta-analyses have been completed to examine the genetic determinants of opioid addiction ABCB1) gene, which is the primary focus of this study. The ABCB1 gene is located on chromosome 7, and is responsible for encoding the efflux drug transporter P glycoprotein The most consistent gene that is implicated in MMT drug response is the ATP-binding cassette, sub family B, member 1  studied methadone metabolism by observing trough  methadone plasma levels among various populations and found that individuals possessing the rs1045642TT genotype had lower methadone plasma levels, indicating faster methadone metabolism CYP2B6) has also been commonly studied in opioid dependence and drug response, and as such will be another focus of this study. CYP2B6 is located on chromosome 19 and is responsible for coding metabolic enzymes of the Cytochrome P450 family CYP2B6, which can in part be explained by genetic polymorphisms CYP2B6*6 haplotype, a combination of the *9 , and *4  SNPs, influences opioid addiction and methadone related outcomes CYP2B6 haplotype in methadone dose requirements have also found inconsistent results, making it difficult to draw a direct conclusion for this particular outcome. However, it is suggested that carriers of the *6 variant may require lower doses than non-carriers CYP2B6 haplotype variant and methadone clearance, plasma levels, and dose CYP2B6 and its role in drug response are inconsistent; therefore the aim of this review is to systematically combine these results to reach a general conclusion.Cytochrome p450 2B6 (CYP2B6 and ABCB1 genetic polymorphisms and methadone maintenance therapy (MMT) patient response. For the purpose of this systematic review, individual patient response to MMT as an outcome will be analyzed separately for: methadone dose, methadone blood level, and methadone response as defined by the absence of illicit opioids use. Please refer to Table S2 for an explicit outline of the individual research questions. We constructed This current study aims to perform a systematic review to investigate the association between Determine whether or not there is a genetic predisposition among MMT patients for any one of the aforementioned outcomes related to MMT response;When appropriate, combine the results of the studies found in this systematic review in a meta analysis in an effort to estimate a mean difference, relative risk, or odds ratio that reflect the results of multiple studies in a summary estimate;Evaluate where the gaps in the current literature are in an effort to determine the important questions that need be answered in future research;Using the results of this systematic review and meta-analysis to provide unbiased estimates that will in effect improve the current understanding of MMT treatment practices.http://www.crd.york.ac.uk/prospero/.A specific protocol was designed for this systematic review and is available upon request. The protocol was registered with PROSPERO in December 2012 at Table S3 for the full search strategy. It is important to note that the OVID Medline database encompasses PubMed within the search. Separate key terms were evaluated for use in the search strategy in an effort to adequately locate the necessary articles pertaining to the aforementioned research questions outlined in section 3.1. A McMaster University Faculty of Health Science librarian was consulted during the selection of databases and during the creation of the search strategy. Two independent reviewers  completed the title, abstract, and full text screening in duplicate, in addition to an individual search of the bibliographies to locate additional literature from all studies that passed the abstract screening stage. No language restrictions were put on this systematic review. The search has been restricted to human studies. In addition, only published literature were allowed into the systematic review for full data abstraction. Authors were contacted during the data extraction process to inform them about the review and request additional results related to their published works when needed during data abstraction.The electronic databases Medline, EMBASE, CINAHL, PsycINFO, and Web of Science were reviewed using a comprehensive search strategy. Please refer to –The literature search encompassed an initial title search, title screening, abstract screening, and full text extraction. Both independent reviewers were responsible for completing: 1) the title search using the aforementioned search strategy, 2) the title and abstract screening with the use of pre determined inclusion criteria, 3) determining the eligibility of articles, and 4) the full data abstraction on eligible articles. Any disagreements that arose during the literature search and screening process were resolved by discussion, however a third party  was brought in to resolve disagreements when discussion could not. Both reviewers used the inclusion criteria determined a priori as the guide for determining the eligibility of an article. The kappa statistic was used to calculate level of agreement between independent raters Only observational studies investigating patients on MMT for the purpose of treating opioid addiction were included in the systematic review. The observational studies needed to have: a) investigated one of the SNPs of interest AND b) looked at this SNP in relation to one of the outcomes of interest . No age or sex restriction was placed on the study populations.Eligible studies included in this systematic review must have been performed in human study populations. There were no restriction dates on publications, however for the purpose of time and resources, unpublished literature was not included in this review. Observational studies examining opioid addiction patients using buprenorphine or a substitute opioid therapy (SOT) other than methadone were not eligible for inclusion. However, for studies examining the genetic predisposition for treatment response outcomes in patients on methadone in comparison to patients on a different SOT, only the data on the MMT patients were extracted. In addition, pilot studies or incomplete studies were not eligible for full data abstraction.Table S4.The prevalence of genetic association studies in the literature has increased exponentially over the past decade. Most are cross-sectional studies that present unique methodological challenges and risks of bias and therefore such studies were appraised accordingly when included in systematic reviews and meta-analyses. To assess the risk of bias for individual studies in this investigation, a modified Newcastle Ottawa Scale (NOS) instrument was used All observational studies meeting the inclusion criteria for full text extraction were subjected to a methodological quality assessment. The two raters  independently assessed the methodological quality of each article using an amended Newcastle-Ottawa Scale for observational studies To understand whether or not we can be confident in the significant estimates, we constructed a series of GRADE evidence profiles in an effort to rank the quality of evidence presented in the summary statistics.Due to the variability of how MMT response is defined in the literature, this review has looked at multiple MMT response outcomes. The MMT response outcomes focused on in this review include: methadone dose, continued illicit opioid abuse, and methadone metabolism or methadone plasma concentrations. Currently, methadone dose is defined in the literature as an average or maximum daily dose during the first year of treatment, where it is treated as a continuous variable that can be measured through self-report or chart review in mg/day Full text extraction forms were created for the purpose of this systematic review and are available upon request. Information abstracted from the individual studies includes; study design, number of participants, ethnicity of participants, genes assessed, SNPs assessed, methadone outcome, statistical measurement, statistical association, p-values, confidence intervals, handling of missing data, handling of multiple testing error, and information on covariates tested in each model. Any disagreements that arose during the data extraction stage were resolved by discussion between the raters, or if no solution was reached, by consulting a third party . All studies eligible for full text extraction are presented in detail in ABCB1 (rs1045642) SNP and the CYP2B6*6 haplotype and trough (R) and (S) methadone plasma concentrations, the standardized mean difference between genotypes was used. The standardized mean difference was also used when pooling the results of studies investigating the association between the SNPs of interest and methadone dose. When pooling results of studies investigating methadone response by genotype, we were able to use a dichotomous outcome and use response as an event among participants, resulting in a pooled odds ratio for the included studies. Assessing for publication bias among the pooled studies using Egger's plot for each of the forest plots generated for this review resulted in limited findings, arguably due to the small sample size and limited number of studies eligible for pooling.The results of this study are synthesized in both a narrative and statistical manner. We conducted several meta-analyses using a random-effects model to address each of the outcomes of interest; methadone dose, methadone trough (R) and (S) plasma concentration, and response to methadone treatment defined as abstinence from illicit substance abuse. All statistical analyses were completed using Review Manager 5.0. For the meta analyses pooling the results from studies investigating the association between the When combining results of the dichotomous data (response to treatment) into a summary odds ratio, we implemented the Mantel-Haenszel method, in which the model is able to estimate between study variation through an evaluation of each study's final results to a Mantel-Haenszel fixed effect meta analysis result. This is a random effects approach available through Review Manager, Version 5 2 statistic has been used to determine whether there is heterogeneity in the results of the studies or if the actual difference in the results is attributable to chance alone 2 test statistic of 40% or greater is considered to be an indication of the presence of important heterogeneity among studies Each SNP and its associated MMT outcome of interest are displayed in separate forest plots. All studies suitable for inclusion in the meta-analysis are weighted by the inverse of the variance. Presenting the data in forest plots with the associated confidence intervals allows us to also determine whether or not there is heterogeneity in the results, however we will need to address the a priori hypotheses about heterogeneity to determine the possible reasons for result differences across studies. We anticipate possible differences between studies based on influencing factors such as outcome measurement and study design. It is also known that allelic frequencies are influenced by ethnicity. In addition, some variability is anticipated based on the study quality . For example, some studies may use self-report to determine concomitant opioid abuse, while other studies may use urine toxicology screening to determine this outcome. Hence, the possible differences in the continued opioid abuse (response) outcome results between studies may be explained by the influence of social desirability bias. An Ist 2013. After applying theoutlined search strategy defined in Table S3 to the Medline, EMBASE, CINAHL, PsycINFO, and Web of Science databases, we obtained an initial yield of 182 articles after duplicate screening. Please refer to The search was performed from inception of databases to April 1The observed quadratic weighted kappa agreement between the two independent raters for the title, abstract, and full text screening was found to be 0.82 , 0.43 , and 0.43 , respectively. The decline in agreement for the abstract and full-text screening is arguably due to the limited number of studies available for screening in the later phases.The study designs found in this review were cross-sectional (n = 5) and case-control (n = 2). The studies included in this review were performed on a predominantly male patient population, with the percentage of males ranging from 65.3 to 78.8 percent Table 3.ABCB1 (rs1045642) and CYP2B6  genetic polymorphisms and patient response to methadone maintenance therapy ( and ABCB1 genetic polymorphism (rs1045642) and trough (R) and (S) methadone plasma concentrations. While we were able to extract data on five articles investigating the association between the CYP2B6*6 haplotype  and trough (R) and (S) methadone plasma concentrations, one of the articles was an interim analysis CYP2B6*6 haplotype or the ABCB1 (rs1045642) SNP and continued illicit substance abuse among MMT patients, only two articles provided data on each gene of interest CYP2B6*6 haplotype and four articles ABCB1 (rs1045642) SNP which provided data.A total of seven studies were reviewed to determine the association between the apy  and Table 5Table S5). Five (100%) of the cross sectional studies evaluated did not report whether or not there was blinding during the outcome or exposure assessment (kappa = 1.0). In addition to the poor reporting quality surrounding the blinding of assessors when discerning the outcome or exposure, there was also poor reporting quality for the genetic methodological analysis section, with only 40% (n = 2) of studies explicitly detailing high quality methods for genetic analysis . It is important to also note that of these studies (n = 2) with good reporting and quality in genetic analysis methodology, one is an interim analysis of the other, meaning that the second study is the completed genetic analysis of the first with a greater number of participants and different planned genotyping analysis.When evaluating the risk of bias in cross-sectional genetic studies (n = 5) In addition, only 60% of the cross-sectional genetic studies had <10% of data missing, meaning only 60% of the cross-sectional studies were ranked with a low risk of bias when evaluated on missing data (kappa = 1.0). All but one study  had a detailed description of their outcome measurements, such as trough (R) and (S) plasma concentration assessment using plasma analysis or urine toxicology screening to asses illicit substance abuse/response to treatment (kappa = 1.0). All but one study , had study samples that were representative of the cohort of interest (n = 4), where the Uhelinger (2007) study was limited by strict inclusion/exclusion criteria due to the strict outcome being assessed (effect of quetiapine on methadone dose). When assessing whether the cohorts were drawn from the same population, 60% of studies were able to fulfill the criteria for low risk of bias, as demonstrated by patients being selected from a similar population . The studies that failed to meet this criteria , were limited by their larger dispersion of source MMT sites due to their inability to adjust for other confounding variables which could be influenced by site of administration .When assessing whether studies controlled for important confounding variables such as concurrent medication, concurrent treatment, body mass index (BMI), or duration of MMT, 60% (n = 4) of the cross-sectional studies evaluated had a low risk of bias Table S6). Of the two studies evaluated only one  was considered to be at low risk of bias, receiving a score of 8/9 stars. One limitation of the Hung (2011) study was their inability to adequately report whether cases and controls had the same method of assessment for the genetic risk allele (exposure), due to the lack of explicit reporting of the genotyping methods for both cases and controls. The second case control study  was evaluated as being subject to a high risk of bias, receiving a low score of 4/9 stars. The Coller (2006) study had very limited reporting quality for the sections considered in the assessment, including; definitions of cases, selection of participants, and statistical adjustment.The modified Newcastle Ottawa scale was also used to asses the two case control studies that were evaluated during this review S2) pooled results of studies examining the association between the ABCB1 (rs1045642) genetic polymorphism and the trough (R) methadone plasma concentrations. The SMD is the difference in mean effects across the comparator genotype groups divided by the pooled standard deviation of participants mean trough (R) methadone plasma concentrations. In this meta-analysis we see a comparison of the mean trough (R) methadone plasma concentration between participants with the ABCB1 (rs1045642) CC versus TT genotypes and CC versus CT genotypes. To estimate the effect of the standardized mean difference many refer to Cohen's (1988) statistical criteria, which dictates that a standardized mean difference of 0.2 represents a small effect, 0.5 a moderate effect, and 0.8 a large effect S2), while not significant, we see a small effect of 0.23, p = 0.41  and 0.07, p = 0.61 , for the pooled results of CC versus TT and CC versus CT respectively, indicating that trough (R) methadone plasma concentrations do not differ widely amongst participants with different genotypes. There was minimal observed heterogeneity among the pooled results for the comparisons of the CC versus TT and CC versus CT respectively .Our first meta-analysis (ABCB1 (rs1045642) CC versus TT genotypes  and CC versus CT genotypes . In the meta-analyses of trough (S) methadone plasma concentrations, while not significant, we again see small effects of 0.3, p = 0.22  and 0.17, p = 0.41 , for the pooled results of CC versus TT and CC versus CT respectively, indicating again that trough (S) methadone plasma concentration does not differ based on this SNP genotype. There was minimal observed heterogeneity among these pooled results for the comparisons of the CC versus TT and CC versus CT respectively .In the second grouping of meta-analyses we see a comparison of the mean trough (S) methadone plasma concentration between participants with the ABCB1 CC versus TT genotypes  and CC versus CT genotypes . Within this analysis the number of events are considered the number of participants who have “responded” to methadone maintenance therapy, meaning the number of participants who are abstaining from illicit substances. A resulting non-significant odds ratio of 0.86, p = 0.81  and 0.85, p = 0.7  is observed for the comparison of the CC versus TT and CC versus CT genotypes respectively. These results indicate that there is no difference in methadone response between participants with different genotype profiles for the rs1045642 SNP. The confidence in the estimates for this meta-analysis is low, largely due to the heterogeneity among pooled studies, where both I2 calculations exceeded 51%.In the third set of meta-analyses, we are comparing the differences in response to treatment (illicit drug use) among participants with the ABCB1 SNP pooled results of studies examining the association between the ABCB1 (rs1045642) polymorphism and methadone dose. In the meta analyses of methadone dose, while not significant, we see a large effect of 0.76, p = 0.24,  and −0.02, p = 0.88, , for the pooled results of CC versus TT  and CC versus CT  respectively, indicating that methadone dose is not significantly associated with this genetic variant. There was a considerable amount of heterogeneity observed among the pooled results for the comparisons of the CC versus TT (I2 = 92%), but not the CC versus CT genotypes (I2 = 0%).Our final grouping of meta-analyses for the CYP2B6 *6 haplotype. In the meta-analyses determining the association between the *6 haplotype and trough (R) methadone plasma concentration, we see a significant SMD between genotyped groups. When comparing homozygous carriers of the *6 haplotype with non-carriers  methadone plasma concentration between homozygous *6 and non *6 carriers as well as the heterozygous *6 and non *6 carriers of the carriers Figure 22 values of 69 percent for both analyses.In the meta-analyses determining the association between the *6 haplotype and trough (S) methadone plasma concentration, we see a significant SMD between genotyped groups. When comparing homozygous carriers of the *6 haplotype with non-carriers Figure 4Figure S9). Within this analysis the number of events are considered the number of participants who have “responded” to methadone maintenance therapy, meaning the number of participants who are not continuing to abuse illicit substances. Observed heterogeneity in this meta analysis was minimal, with an I2 value of zero percent.When comparing the differences in response to treatment (illicit drug use) among participants who are homozygous carriers of the *6 haplotype against participants who are non-carriers of this haplotype (*1/*1), we see a resulting non-significant odds ratio of 1.05, p = 0.93 , indicating that response to treatment is not affected by the presence or absence of the *6 haplotype  haplotype . When comparing homozygous carriers of the *6 haplotype to non-carriers, we see an SMD effect of −0.21, p = 0.37 , which can be considered by Cohen's criteria as a very small effect. This analysis while not significant, does show a trend that indicates that carriers of the *6 variant are more likely to have lower doses then participants without the *6 haplotype. As shown earlier, carriers of the *6 haplotype have been demonstrated to have higher (R) and statistically significant higher (S) methadone plasma concentrations, indicating that the individuals with the *6 haplotype are slower metabolizers of methadone. The analysis above indicates there is a trend for *6 carriers to have lower methadone doses, which is consistent with the findings that these *6 carriers are slower metabolizers, hence their requirement for lower doses of methadone for a stable drug effectiveness. Observed heterogeneity in this meta-analysis was minimal, with an I2 value of 0 percent.In this final meta-analysis, we see a comparison of the mean methadone dose between homozygous *6 carriers and non *6 carriers of the Genetic variants are known to influence an individuals' vulnerability to develop a disorder such as addiction After an extensive investigation of the genetic determinants of individual patient response to MMT, we only found seven studies that investigated a SNP of interest within a patient population on methadone treatment for opioid addition in relation to one of the outcomes of interest .ABCB1 (rs1045642) risk allele (T) do not significantly differ from patients without this risk allele on outcomes (ABCB1 (rs1045642) SNP for all outcomes of interest. However, one study by Crettol et al. (2006) suggests that carriers of the T allele metabolize methadone at a faster rate than non-carriers (p<0.01) ABCB1 genotype, we looked into the study presented by Crettol (2006). This study was the largest contributor to magnitude of association witnessed in each meta-analysis , requiring us to look further into the risk of bias this study posed and inevitably influence our confidence in the estimates.Individually, these studies suggest that 1) carriers of the outcomes Table 4.Table S5). The major limitations affecting the Crettol (2006) study was their inability to account for blinding of assessors during the exposure and outcome assessment periods. However, it is not anticipated that a lack of blinding would influence the risk of bias in this study, primarily due to the objective nature of the outcome measurement for both methadone plasma concentration and dose. The other main limitations are the small sample size and risk for type 1 error. Another important study requiring attention is by Uehlinger et al. (2007), arguably due to the inconsistency witnessed between the Uehlinger (2007) results and the other results of the pooled studies. A large limitation of the Uehlinger (2007) study was the small sample size (n = 14), with some estimates comparing genotype groups with only 3 participants in each . In addition, the primary objective in the Uehlinger (2007) investigation was not to determine the influence of genotype on methadone response, but actually the influence of genotype in quetiapine metabolism within methadone patients.The Crettol (2006) study was not limited by a serious risk of bias during the methodological quality review where it received a ranking of 20/27  the CYP2B6*6 haplotype does not influence methadone dose or response to treatment . However, it is important to be cautious of the significant estimates presented in the CYP2B6 series of meta-analyses, due to the poor confidence we have in the obtained estimates.Individually these studies also suggest that 1) The reatment Table 5.CYP2B6 haplotype may influence methadone plasma concentration, however it is not found to be associated with drug doses or clinical outcomes. These results may be due to the influence of other CYP450 genetic variations involved in the methadone N demethylation processes. For example, the CYP3A4/5, and CYP2D6 genetic polymorphisms are known variants that may also contribute to this reaction CYP3A5 variant have been shown to have high levels of CYP3A5 activity CYP3A5 variant is also known to represent 50% of the total CYP3A hepatic content CYP450 polymorphisms may be a large influence on the results suggesting a null effect of CYP2B6 on modifying methadone dose, begging the need for further research into this area.Results from this systematic review suggest that the CYP2B6 genetic variants preferentially metabolize the (S) enantiomer, with S-methadone resulting as a potent inhibitor of R-methadone N- demethylation Ethere àe goe goT Related Gene) current 3.5fold more potently than (R), with homozygous *6 carriers having an increased risk of prolonged QTc interval  Invitro studies have consistently demonstrated that the Figures S11, S12, S13, S14, S15, S16, S17, S18, S19, S20, S21, S22, S23, S24) In an effort to understand whether or not we can be confident in the significant estimates in this meta-analysis, we constructed a series of 14 GRADE evidence profiles  study, which was discussed earlier as being limited by the small sample size, and in addition this study bears a small weight on the total estimate of effect. When establishing the confidence in the estimates as very low for the outcome of methadone response, we noted that not all of the pooled studies adjusted for concurrent medication use, duration on MMT, or BMI. It is important to consider that dose or metabolism may vary among patients with different BMI's CYP2B6*6 homozygous carriers and slower methadone metabolism (p<0.05) should be interpreted cautiously, particularly because we did not adjust for multiple testing error using the Bonferroni correction.While our meta-analyses did bring us to some significant results, it is clear there are major limitations within the studies that ultimately influence our confidence in these estimates. In addition, the association we have found to be significant, that is the association between Understanding the combination of factors that contribute to inter-individual variability in methadone response is a paramount task when attempting to enhance the treatment and MMT outcomes in opioid addiction patients. Numerous factors influence the inter-individual variability in methadone response including methadone dose (increased response with doses ≥60 mg/day S6). Consequently, this large inter-individual variability poses uncertainty among physicians when deciding on an adequate dose of methadone for new patients. The importance of dose is inherent, since a dose too low can allow for breakthrough withdrawal symptoms, which can ultimately influence a patients propensity to relapse A major limitation of this systematic review is the selection of studies contributing to magnitude of association, especially since a majority of these studies did not account for the aforementioned factors contributing to patient response (ABCB1 (rs1045642) and CYP2B6*6 haplotype, it is important to address the possibility that these genes may have complimentary roles in the metabolic disposition of methadone, where one is involved in metabolite formation and another in metabolite elimination or drug absorption. Due to the limited available information, and lack of studies investigating both genes in tandem, we were unable to explore this is association further. It is plausible an interaction between these genes may exist and should be explored further in a primary investigation.When reviewing the available literature on both the ABCB1 (rs1045642) SNP has no significant effect on methadone metabolism, dose, and response to treatment, while the CYP2B6*6 haplotype has a significant effect on methadone metabolism but a minimal effect on patient response and dose of methadone. While there is inherent importance in this study, mainly because it is the first meta-analysis to be performed on the genetic determinants of methadone response, we still strongly caution the reader that our confidence in these estimates is very low, arguably because of the serious risk of bias and imprecision within all of the meta-analyses.Investigations on methadone patient health outcomes have consistently demonstrated the importance of understanding high-risk factors for MMT patients. By identifying important risk factors for methadone response, clinicians will be able to properly manage patients more successfully and in some cases prevent mortality. Methadone response is a pertinent issue for the study of opioid addiction and understanding patient characteristics that predict response can: 1) enhance patient centered treatment, 2) prevent risk of death and opioid overdose, 3) reduce health expenditure, 4) impact patient surveillance, 5) promote multi-therapy approaches to addiction, and 6) impact dosing requirements. This systematic review has shown that that Checklist S1PRISMA Checklist.(PDF)Click here for additional data file.Figure S1ABCB1 (rs1045642) CC versus TT Trough (R) Methadone Plasma Concentrations.(TIFF)Click here for additional data file.Figure S2ABCB1 (rs1045642) CC versus CT Trough (R) Methadone Plasma Concentrations.(TIFF)Click here for additional data file.Figure S3ABCB1 (rs1045642) CC versus TT Trough (S) Methadone Plasma Concentrations.(TIFF)Click here for additional data file.Figure S4ABCB1 (rs1045642) CC versus CT Trough (S) Methadone Plasma Concentrations.(TIFF)Click here for additional data file.Figure S5Influence of ABCB1 Genotype (CC versus TT) on Methadone Maintenance Therapy Response to Treatment.(TIFF)Click here for additional data file.Figure S6Influence of ABCB1 Genotype (CC versus CT) on Methadone Maintenance Therapy Response to Treatment.(TIFF)Click here for additional data file.Figure S7Influence of ABCB1 Genotype (CC versus TT) on Methadone Dose.(TIFF)Click here for additional data file.Figure S8Influence of ABCB1 Genotype (CC versus CT) on Methadone Dose.(TIFF)Click here for additional data file.Figure S9Influence of CYP2B6 *6 Haplotype on Methadone Maintenance Therapy Response to Treatment.(TIFF)Click here for additional data file.Figure S10Influence of Homozygous *6 Carriers Versus Homozygous *1/*1 Non-carriers on Methadone Dose.(TIFF)Click here for additional data file.Figure S11GRADE ABCB1 Trough (R) Methadone Plasma Concentration (CC vs TT).(TIFF)Click here for additional data file.Figure S12GRADE ABCB1 Trough (R) Methadone Plasma Concentration (CC vs CT).(TIFF)Click here for additional data file.Figure S13GRADE ABCB1 Trough (S) Methadone Plasma Concentration (CC vs TT).(TIFF)Click here for additional data file.Figure S14GRADE ABCB1 Trough (S) Methadone Plasma Concentration (CC vs CT).(TIFF)Click here for additional data file.Figure S15GRADE CYP2B6 Trough (R) Methadone Plasma Concentration (Homozygous *6 Carriers Versus Non-Carriers).(TIFF)Click here for additional data file.Figure S16GRADE CYP2B6 Trough (R) Methadone Plasma Concentration (Heterozygous *6 Carriers Versus Non-Carriers).(TIFF)Click here for additional data file.Figure S17GRADE CYP2B6 Trough (S) Methadone Plasma Concentration (Homozygous *6 Carriers Versus Non-Carriers).(TIFF)Click here for additional data file.Figure S18GRADE CYP2B6 Trough (S) Methadone Plasma Concentration (Heterozygous *6 Carriers Versus Non-Carriers).(TIFF)Click here for additional data file.Figure S19GRADE ABCB1 Response to Methadone Maintenance Therapy (Illicit Substance Abuse Behaviors) CC vs TT.(TIFF)Click here for additional data file.Figure S20GRADE ABCB1 Response to Methadone Maintenance Therapy (Illicit Substance Abuse Behaviors) CC vs CT.(TIFF)Click here for additional data file.Figure S21GRADE CYP2B6 Response to Methadone Maintenance Therapy (Illicit Substance Abuse Behaviors) Homozygous *6 Carriers Versus Non-Carriers.(TIFF)Click here for additional data file.Figure S22GRADE ABCB1 Methadone Dose Requirements by Genotype (CC vs TT).(TIFF)Click here for additional data file.Figure S23GRADE ABCB1 Methadone Dose Requirements by Genotype (CC vs CT).(TIFF)Click here for additional data file.Figure S24GRADE CYP2B6 Methadone Dose Requirements by *6 Genotype.(TIFF)Click here for additional data file.Table S1The Genetic Determinants for MMT Response.(DOCX)Click here for additional data file.Table S2Outline of PICO Questions for Individual SNPs and Outcomes.(DOCX)Click here for additional data file.Table S3Full Search Strategy for Systematic Review and Meta-Analysis on the Genetic Determinants of Methadone Maintenance Therapy Response.(DOCX)Click here for additional data file.Table S4Modified Newcastle Ottawa Scale Tool to Asses Risk of Bias in Cross-Sectional Genetic Research.(DOCX)Click here for additional data file.Table S5Risk of Bias Table for Individual Cross-Sectional Genetic Studies.(DOCX)Click here for additional data file.Table S6Risk of Bias Table using the Modified Newcastle Ottawa Scale for Genetic Case Control Studies.(DOCX)Click here for additional data file.


Tumor necrosis factor-α (TNF-α) may play an important role in the recalcitrant inflammatory and hyperproliferative dermatosis of psoriasis, and there may be a relationship between TNF-α polymorphisms and psoriasis risk. We performed a meta-analysis to evaluate the associations between TNF-α polymorphisms and psoriasis. Electronic searches of Pubmed, Embase, and Web of Science were performed for all publications on the associations between TNF-α polymorphisms and psoriasis through September 26, 2012. The pooled odds ratios (ORs) with their 95% confidence interval (95%CIs) were calculated to assess the associations.AA/AG versus GG: fixed-effects OR 0.67, 95%CI 0.58-0.78, P < 0.001). In addition, TNF-α 238 G/A polymorphism was associated with increased risk of psoriasis under three genetic models . Subgroup analysis by ethnicity identified a significant association between TNF-α 308 G/A polymorphism and decreased risk of psoriasis in both Caucasians and Asians and a significant association between TNF-α 238 G/A polymorphism and increased risk of psoriasis in Caucasians.Sixteen case-control studies with a total of 2,253 psoriasis cases and 1,947 controls on TNF-α 308 G/A polymorphism and fourteen studies on TNF-α 238 G/A polymorphism with 2,104 cases and 1,838 controls were finally included into the meta-analysis. Overall, TNF-α 308 G/A polymorphism was significantly associated with decreased risk of psoriasis under three genetic comparison models (for A versus G: fixed-effects OR 0.71, 95%CI 0.62-0.82, P < 0.001; for AG versus GG: fixed-effects OR 0.67, 95%CI 0.57-0.78, P < 0.001; for The meta-analysis suggests that TNF-α 308 G/A polymorphism is associated with decreased risk of psoriasis, while TNF-α 238 G/A is associated with increased risk of psoriasis. Psoriasis is a very common inflammatory skin disease which affects about 3% total populations in the world ,2. CurreElectronic searches of Pubmed, Embase, and Web of Science were performed for all publications on the associations of TNF-α 308 G/A and 238 G/A polymorphisms with psoriasis risk through September 26, 2012. We used the keywords and subject terms: (“psoriasis” or “psoriatic”) and (“polymorphism” or “variant” or “genotype” or “polymorphism”) and (“tumor necrosis factor” or “TNF 238 G/A” or “TNF 308 G/A” or “TNF-α” or “rs1800629”). There was no language limitation in the literature search. All eligible studies were retrieved, and their bibliographies were checked for other relevant publications. The following criteria were used to select the eligible studies: (1) case-control studies involving the associations of TNF-α 308 G/A and 238 G/A polymorphisms with psoriasis risk; (2) reporting genotype frequencies of TNF-α 308 G/A polymorphism for estimating an odds ratio (OR) with 95% confidence interval (95%CI) (3) Confirmation of Hardy-Weinberg equilibrium (HWE) in the controls. If two or more studies reported the same patients populations, only the most recent or complete study was included into this meta-analysis.The final eligible articles selected for meta-analysis were carefully evaluated independently by two reviewers, and discrepancies were adjudicated by the consensus among all reviewers. Data retrieved from the reports included first author’s name, publication year, ethnicity of study population (categorized as Caucasians and Asians), study-design (sources of controls), genotyping method, types of cancer, number of cases and controls, and genotype frequencies of TNF-α 308 G/A or 238 G/A polymorphisms in cases and controls.AA/AG versus GG), and the recessive genetic model (AA versus AG/GG). The I2 statistic to quantify the proportion of the total variation due to heterogeneity were calculated, and a I2 value of more than 50% was interpreted as significant heterogeneity among studies [HWE in the controls was tested by a Chi-square test which compared the observed and expected genotype frequencies of the controls . The poo studies . When th studies . If obvi studies . To vali studies . Potenti studies . All anaThe study selection was shown in 2 < 50%), thus the fixed-effects model was used to calculated pooled ORs with the corresponding 95%CIs  when all 16 studies were pooled into the meta-analysis (2 < 50%), thus the fixed-effects model was used to calculated pooled ORs with the corresponding 95%CIs (2 = 0.0%), thus the fixed-effects model was used to calculated pooled ORs with the corresponding 95%CIs  when all 14 studies were pooled into the meta-analysis  indicating low risk of publication bias . BesidesAA/AG versus GG: fixed-effects OR 2.68, 95%CI 2.20-3.26, P < 0.001). Therefore, the meta-analysis suggests that TNF-α 308 G/A polymorphism is associated with decreased risk of psoriasis, while TNF-α 238 G/A is associated with increased risk of psoriasis.Psoriasis is an autoimmune and inflammatory disease, and genetic susceptibility factors also play an important role in the inflammatory and immune actions of psoriatic skin . In presSingle nucleotide conversion from guanine (G) to adenine (A) at position -308 is the most common in general populations. This transition has been shown to influence the expression of TNF-α, and a position -308 allele A is associated with a about 6 fold increased transcriptional activity and higher levels of TNF-α. TNF-α stimulates the release of interleukin 8 (IL-8) by keratinocytes and fibroblasts and transforming growth factor by keratinocytes, which may be involved in autocrine stimulation of keratinocytes proliferation in psoriatic lesions . TherefoSeveral limitations should be considered when interpreting the findings from this meta-analysis. Currently, there were only 3 case-control studies published to investigate the associations of TNF-α 308 G/A and 238 G/A polymorphisms with psoriasis risk in Asians, and no one studies were published to assess the association in Africans. The limited numbers of eligible studies could cause the relatively small sample size, and further resulted in poor validation and increased the risk of random error in the subgroup analysis of Asians. Therefore, more well-designed studies with large sample sizes are needed to further identify the association among Asians and Africans. Besides, the associations of TNF-α 308 G/A and 238 G/A polymorphisms with psoriasis risk in other races also need further studies.Another limitation in the meta-analysis was that it was based on unadjusted estimates owing to the lack of adjusted estimates. Currently, several risk factors have been identified, such as family history, viral and bacterial infections, and smoking. A more precise analysis could be performed if the estimates adjusted for those possible risk factors were available. However, none of those studies reported the adjusted estimates, and to get a more precise analysis of this association, more studies with adjusted estimates are needed.Finally, gene-gene interactions were not fully addressed in the meta-analysis for the lack of relevant data. There are several polymorphisms associated with risk of psoriasis, including signal transducer and activator of transcription 4 (STAT4), TaqI polymorphisms in vitamin D receptor (VDR) gene, interleukin-10 (IL-10) polymorphisms and LCE3B genes ,36. But In summary, this meta-analysis suggests TNF-α 308 G/A polymorphism is associated with decreased risk of psoriasis, while TNF-α 238 G/A is associated with increased risk of psoriasis. More studies with adjusted estimates are needed to assess the association among Asians and Africans.Checklist S1PRISMA checklist in this meta-analysis.(DOC)Click here for additional data file.Figure S1PRISMA 2009 flow diagram in this meta-analysis.(TIF)Click here for additional data file.


There was no difference in the frequency of deficient AAT alleles (Pi Z and Pi S) between patients and control. However, we found a significantly higher frequency of PiM1M1 homozygote and PiM1 allele in HM patients than in control . In addition, PiM homozygotes in HM-patients were more numerous than in controls . PiM1 alleles and PiM1 homozygotes are both associated with hematological malignancies, although this is considered a functionally normal AAT variant. Alpha-1-antitrypsin (AAT) or serine protease inhibitor A1 (SERPINA1) is an important serine protease inhibitor in humans. The main physiological role of AAT is to inhibit neutrophil elastase (NE) released from triggered neutrophils, with an additional lesser role in the defense against damage inflicted by other serine proteases, such as cathepsin G and proteinase 3. Although there is a reported association between AAT polymorphism and different types of cancer, this association with hematological malignancies (HM) is, as yet, unknown. We identified AAT phenotypes by isoelectric focusing (in the pH 4.2-4.9 range) in 151 serum samples from patients with HM . Healthy blood-donors constituted the control group (n = 272). The evaluated population of patients as well as the control group, were at Hardy-Weinberg equilibrium for the AAT gene (χ Hematological malignancies are clinically and biochemically diverse disorders of unknown etiology and characterized by the disproportionate proliferation of one clone of B and/or T cells.ine Proteinase INhibitor).Alpha-1-antitrypsin (AAT) is a highly polymorphic plasma glycoprotein (53 kD), synthesized in hepatocytes  in the lower respiratory tract, so as to protect the connective tissue against NE released from triggered neutrophils , with a The AAT protein is encoded by the protease inhibitor (Pi) locus on chromosome 14q31-32.3. Through the technique of isoelectric focusing, about 100 genetic variants of AAT have been identified to date.The most common alleles are the M variants, which are subdivided into six M subtypes, homozygous or heterozygous for the M1, M2, M3 and M4 alleles. When M variants are inherited in homozygous or heterozygous form, AAT serum levels are supposed to be normal , with Hodgkins lymphomas , non-Hodgkins lymphomas  and malignant monoclonal gammopathies , and which had been admitted to the Institute of Oncology and Radiology of Serbia and the Military Medical Academy, Belgrade.Diagnosis and typisation of malignant lymphomas was made by histological examination of biopsied material stained by HE and/or the MGG technique, with additional immunohistochemical determination of at least LCA, CD3, CD5, CD10, CD20, CD23 and CD45. Additional immunohistochemistry was carried out as required. Malignant monoclonal gammopathies were revealed with monoclonal immunoglobulin or Bence Jones protein in serum and/or urine by electrophoresis and immunofixation.The control group consisted of 272 healthy blood-donors without any type of malignancies . Investigated populations, both control and patents, were proportional to the ethnic background.The protocol was approved by local research ethics committees, and informed consent was obtained from all the participants.Pi phenotyping of serum samples was carried out by isoelectric focusing (pH range 4.2-4.9) according to the method by 2 test was used to assess whether control and patient groups were in Hardy-Weinberg equilibrium for the AAT gene. Investigation of differences in the frequencies of AAT phenotypes and alleles, as well as the frequency of M homozygote and M heterozygote between patients and controls, were investigated, also by using the χ2 test (2 x 2 contingency table). The Fisher exact test was used when n < 5. P values of < 0.05 were considered significant. For statistical analysis, we used STATISTICA 6.0®software.The χ2 = 4.71, d.f.11, p = 0.97 for control; χ2 = 4.42, d.f.11, p = 0.96 for HM patients).There was no deviation from Hardy-Weinberg equilibrium in either study group .Although PiM subtypes are not linked to any disease, there are some studies in which a distinct association between a lowered M3 allele and monoclonal gammopathies and acute myeloid leukemia has been observed (araproteinemias and lymphomas (It is generally accepted that AATD phenotypes are clinically important due to a firm linkage with liver and lung diseases. Several mutations of AAT are associated with low plasma level of AAT and the most common are Z and S variants. To date, few studies have been dedicated to examining the correlation of AAT polymorphism with hematological malignancies, although two such studies have described the association between the PiMZ phenotype and pThe mechanism that leads to an increase in PiM homozygosity in hematological malignancies is unknown. We believe that enlightenment on this will contribute to a better understanding of HM pathogenesis. Although it is considered that PiM subtypes are not related to diseases, we will present a hypothesis regarding their connection with HM.1-antitrypsin activity. Based on these studies, we assumed that increased PiM homozygote frequency in patients with HM may be due to their slightly reduced concentration and functional activity, which could lead to perturbation of the protease-antiprotease balance. In fact, imbalance between neutrophil elastase and alpha-1-antitrypsin is generally considered to be the cause of tissue damage, thereby creating a favorable tissue environment for carcinogens and tumor progression (The discrepancy regarding PiM homozygosity between patients and control could be due to certain advantages arising from PiM heterozygotes in healthy individuals. Two articles have been published which reported quantitative differences between PiM homozygotes and PiM heterozygotes. From the Beckman study , it was gression . Having To conclude, the higher frequency of PiM1 homozygotes and PiM1 allele in patients with hematological malignancies could be a consequence of a so far unknown association between the main serine protease inhibitor and hematological malignancies.