Autism Spectrum Conditions (ASCs) are characterized by a high degree of clinical heterogeneity, but the extent to which this variation represents a severity gradient versus discrete phenotypes is unclear. This issue has complicated genetic studies seeking to investigate the genetic basis of the high hereditability observed clinically in those with an ASC. The aim of this study was to examine the possible clustering of symptoms associated with ASCs to determine whether the observed distribution of symptom type and severity supported either a severity or a symptom subgroup model to account for the phenotypic variation observed within the ASCs.a priori assumptions about any underlying factor structure of constituent items. The responses obtained were analyzed using complete linkage hierarchical cluster analysis. For the members of each cluster identified the mean score on each Autism Spectrum Quotient question was calculated.We investigated the responses of a group of adults with higher functioning ASCs on the fifty clinical features examined in the Autism Spectrum Quotient, a screening questionnaire used in the diagnosis of higher functioning ASCs. In contrast to previous studies we have used this instrument with no Autism Spectrum Quotient responses from a total of 333 individuals between the ages of 16.6 and 78.0 years were entered into the hierarchical cluster analysis. The four cluster solution was the one that generated the largest number of clusters that did not also include very small cluster sizes, defined as a membership comprising 10 individuals or fewer. Examination of these clusters demonstrated that they varied in total Autism Spectrum Quotient but that the profiles across the symptoms comprising the Autism Spectrum Quotient did not differ independently of this severity factor.These results are consistent with a unitary spectrum model, suggesting that the clinical heterogeneity observed in those with an autistic spectrum condition at the higher-IQ end of the spectrum is associated with a gradient in the overall severity of the ASC rather than with the presence of different specific symptom profiles in different individuals. The implications of this for genetic research are considered. Autism and the related disorders Asperger Syndrome (AS) and Pervasive Developmental Disorder Not Otherwise Specified (PDDNOS) are characterised by qualitative impairments of social interaction and communication, and restricted and repetitive patterns of behaviour of early childhood onset. They are now widely accepted as forming a spectrum of disorders, the so-called autism spectrum of conditions (ASCs), with the term 'spectrum' indicating the variation in the clinical phenotype observed . Twin anUnfortunately, however, the genetic research has been plagued with a failure to replicate findings, and with regions of linkage seemingly occurring on the majority of chromosomes. Recent research has taken two different approaches to address this. First, pooling data to increase sample sizes, such as with the Autism Genetic Resource Exchange  databaseThis latter approach is predicated on a model in which the spectrum is not a unitary concept, but, instead, consists of subgroups with unique but overlapping genetic influences ,8. At itper se, or is a reflection of another factor, such as the impact of cognitive function on the expression of the phenotype.In contrast, however, other researchers have argued for a severity gradient ,13, withThere are a number of considerations that might explain the discrepancies between studies. An important consideration is the design of the studies. For example, Spiker's and Silverman's examined clustering according to the Autism Diagnostic Interview (ADI-R), whilst Constantino's  examineda priori assumptions about the underlying factor structure of this questionnaire and the clinical features it identifies. Our aim was to examine the possible clustering of responses within our study population and to determine whether the data obtained supported either a severity or a subgroup model to account for the phenotypic variation observed within the ASCs. Previous studies have sampled children with ASCs, but this is the first to examine an adult sample in this way. There is evidence that for a significant minority the ASC symptoms improve with age [per se on clustering are relatively reduced.In this current study, adult singletons with higher functioning ASCs are examined for their clustering on the fifty clinical features examined in the Autism Spectrum Quotient , a screewith age , suggestThe individuals comprising the study population were drawn from across the UK and had either been referred to a specialist diagnostic clinic  for clarification of a possible diagnosis of Asperger's syndrome or high functioning autism or had contacted the University of Cambridge Autism Research Centre (ARC) volunteer database. All participating individuals were aged at least 16 years and met diagnostic criteria for an ASC according to DSM-IV. Altogether 213 individuals were ascertained from the ARC volunteer database and 175 from the diagnostic clinic (CLASS), making a total of 388.ibid.). Moreover, the AQ has been found to be strongly predictive of a clinical diagnosis of AS according to DSM-IV criteria [The characteristics entered into this study were those endorsed by each of the participants on the Autism Spectrum Quotient . The AQ criteria ; and hascriteria ).For the purpose of this study, for each item a score of 0,1,2 or 3 was assigned along the spectrum 'definitely agree', 'slightly agree', 'slightly disagree', and 'definitely disagree' for items worded to produce a 'disagree' response in a high scoring person with AS, and 3,2,1 and 0 for items worded to produce an 'agree' response. Therefore, each individual's scores ranged from 0 to 3 for each of the 50 AQ items, and 0 to 150 for the complete questionnaire, with higher scores indicative of traits more typical of ASCs. Subsequently, complete linkage cluster analysis was employed , using SAQ responses from a total of 388 individuals between the ages of 16.6 and 78.0 years were initially considered. Of these, 127 were female and 261 were male. There was no difference in mean AQ score between those recruited from the ARC volunteer database and those seen in the CLASS clinic . Mean ages  in the two populations were similar. Considering gender distribution , the preponderance of males with respect to females attending the diagnostic clinic was significantly greater than was the case for members of the ARC volunteer data base. Although IQs were unfortunately not available, all participants had attended mainstream school. In 55 participants some AQ responses were missing and these individuals were excluded, leaving questionnaires from 333 individuals to be included in the cluster analysis.Whilst the 2, 3 and 4 cluster solutions produced groups each with more than 10 participants, in contrast, solutions with more than four clusters included one or more groups with very small numbers (i.e. with less than 10). The significance of groups with very small numbers such as these is unclear, and therefore only the 2, 3 and 4 cluster solutions were examined further. For each AQ item, the group mean was calculated, allowing comparison between groups for each of the 50 AQ items. By way of illustration, Table Strikingly, each of these solutions was consistent with a severity gradient. Considering the 4 cluster model for example, although not all AQ items demonstrate a clear severity gradient, 64% of the AQ items are consistent with gradient of severity with Group 1 representing 'severe' cases, Group 2 'moderately severe', Group 3 'moderate' and Group 4 'mild'. Similar results were found for the 2 and 3 cluster models.In summary, the results of this current analysis support a unitary spectrum model, with clustering according to severity. This study therefore seems primarily to agree with that of Spiker and colleagues , who havThere are several limitations to the current study that should also be considered. The lack of IQ data precluded us from examining the impact of cognitive functioning on AQ scores. The spread of ages within the participant population, though excluding children below the age of 16, was large. The smaller male excess in the ARC sample with respect to the CLASS Clinic sample was unexpected. The sex ratio in the clinic participants resembled that recorded in many other studies of people with ASC. The clinic population were referred by other doctors  who may have been influenced in their willingness to refer to a specialist service by expectations that autism-like symptoms when seen in males may be autism but when seen in females may have some non-autistic cause. The observation that both the ARC-ascertained and the clinic-ascertained samples had similar age profiles and similar scores on the AQ suggests that people with conditions of similar severity presented to both.Although these various factors may have influenced the results, it remains possible that a gradient of severity is an independent observation and explains the variation between people's clinical phenotype. Such a gradient may not necessarily be the result of differences in autism symptoms per se, but might instead reflect the modifying effect of another continuously distributed factor (or factors). For example, IQ is continuously distributed in the population and differences in IQ between participants may have mediated the gradient observed. Unfortunately, IQ scores were not available for the participants of this study, and so to examine this hypothesis further data are needed. Similarly, personality traits vary quite considerably in the general population and these may have a modifying effect on the expression of the phenotype. This too needs further investigation. However, the variation in severity observed in this and previous studies may be due to a variation in severity of autism itself, and, if so, this may be the result of an additive genetic effect for autism related genes. This model proposes that there are several susceptibility genes for autism, and that the more of these genes a person has, the more severe will be the phenotype. These genes may be conceptualised as conferring a general susceptibility to autism rather than comprising different genes that contribute to different aspects of the phenotype such as social interaction, communication, rigidity and so forth. The results of the current study and previous ones ,13 suppoThese analyses should be considered as exploratory. The ideas developed in this paper need to be tested further for replication, and examined across a wider spectrum of disability. Clearly what is now needed is the exploration of factors that might contribute to the existence of a severity gradient, and more specifically whether this can best be explained by the modifying effect of another continuously distributed factor, such as IQ, or whether it is indicative of ASCs being inherited as a single, continuous severity dimension. Ultimately, examination of inter versus intrafamilial clustering, both in affected sib-pairs, and within their unaffected parents, will be able to investigate the hypothesis that the severity gradient is the result of the modifying effect of another non-ASC factor, such as IQ. Until this is clearer, difficulties in identifying ASC susceptibility genes may continue.The clinical heterogeneity observed in people with ASCs, together with the strong hereditability recognised in these conditions, has led to a debate as to whether this variation in manifestation is associated with either distinct genetic sub-types with quite different clinical symptoms or with a common basis but with clinical variability originating as a result of an overall variation in severity between individuals. Examination of the responses of over 300 individuals with Asperger's syndrome or high functioning autism to the 50 items of a questionnaire rating the occurrence of a wide range of behaviors characteristic of ASC provides evidence that the observed clinical spectrum is associated with a gradient in the overall severity of the ASC rather than with the presence of different specific symptom profiles in different individuals. The possible causes for this variation in severity however remain to be established.CLASS: Cambridge lifespan asperger syndrome service; AQ : Autism spectrum quotient questionnaire; ARC : University of cambridge autism research centre; ASCs : Autism spectrum conditionsNone of the authors have any competing financial interests. The AQ was developed by Sally Wheelwright and Simon Baron-Cohen but it is freely available and they do not derive any financial benefit from its use.The study was devised by HR and MWS. SW and SBC prepared the data for analysis and advised on interpretation of the results. PW carried out the statistical analysis. HR and MWS wrote the first draft of the paper and all the authors contributed to modifications in subsequent drafts.


Studies examining the association of apolipoprotein A5 (APOA5) gene -1131 T>C polymorphism with blood lipids produced inconsistent results. In this meta-analysis encompassing all the relevant studies, we aimed to investigate the association of the -1131 T>C polymorphism with fasting blood lipids.We limited our analysis to the following four blood lipid variables: total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). Subjects were confined to adults who were at least 18 years old. A dominant model was used for this meta-analysis. 37 studies with 37859 subjects were included in this meta-analysis.P < 0.00001, Pheterogeneity = 0.42, and SMD = 0.31, 95% CI , P < 0.00001, Pheterogeneity = 0.0003, respectively. Significant association between the -1131 T>C polymorphism and lower blood HDL-C was also detected under the dominant model: SMD = -0.17, 95% CI , P < 0.00001, Pheterogeneity = 0.003.The results showed that the carriers of -1131C allele have higher blood TC and TG than the non-carriers: standardized mean difference (SMD) = 0.08, 95% confidence interval , Our meta-analysis supports the strong association of the APOA5 -1131 T>C polymorphism with higher levels of TC and TG, and lower levels of HDL-C. Hyperlipidemia, which is considered to be one of the most important risk factors for coronary heart disease (CHD) and stroke, is characterized by the derangements of one or many of the lipids: elevations of total cholesterol (TC), low density lipoprotein cholesterol (LDL-C) and/or triglycerides (TG), or low levels of high-density lipoprotein cholesterol (HDL-C) . AlthougMore recently, apolipoprotein A5 (APOA5) was identified as a strong modulator of blood lipids . The APOThe APOA5 gene is located on chromosome 11q23 within the APOA1/C3/A4/A5 gene cluster, and comprises 4 exons encoding 366 amino acids . A numbeWe identified all articles published before November 2009 on the APOA5 -1131 T>C polymorphism and its association with blood lipids. A systematic search of the literature was carried out by using PubMed and HugeNavigator. The language was limited to English. The keywords used for this search were "APOAV OR APOA-V OR apolipoprotein A-V OR apolipoprotein AV OR apolipoprotein A5 OR APOA5 OR APO A5" concatenated with "polymorphism OR variant OR SNP OR mutation". We limited our analysis to the following four blood lipid variables: TC, TG, LDL-C, and HDL-C. The selection criteria for studies to be considered for this meta-analysis were as follows: (1) data were reported on at least 1 of the four blood lipid variables; (2) data reported on fasting blood lipid; (3) in case of interventional studies, we used pre-intervention baseline data; (4) we only included studies in which mean blood lipid levels and standard deviations (SD) or standard errors by genotype were available; (5) subjects were confined to adults who were at least 18 years old. All references cited in the studies were also reviewed in order to find other published work that was not indexed by PubMed and HugeNavigator. Animal studies, case reports, review articles, abstracts, reports with incomplete data, and studies based on pedigree data were excluded.Two investigators independently reviewed the articles to exclude irrelevant and overlapping studies. The results were compared, and disagreements were discussed and resolved by consensus. When overlapping articles were found, we only included the publication that reported the most extensive information. From each study, the following information was extracted: journal, year of publication, first author, demographics, racial background of the study population, fasting status, age, sex, health condition, sample size, mean and SD or standard error by genotypes, genotyping and lipid assay methods, unit of the four lipid variables.All data in this analysis were presented as mean ± SD. When the standard error was reported in the original article, the value of the SD was calculated. Review Manager 5.0 software  was used for the meta-analysis. Because the frequencies of the minor allele homozygous were low, to ensure adequate statistical power, we employed a dominant model [(TC+CC) versus TT] for this meta-analysis. When information was reported for more than one subpopulation  in one study, each subpopulation was treated as a separate comparison in our meta-analysis. In addition, we conducted subgroup analyses by ethnicity, gender, and health condition. Ethnic subgroups were defined as European descendents, East Asian, or populations of other ethnic origins. Considering that the effects of APOA 5 gene on blood lipids may be influenced by lipid-lowering therapy, we also performed a subgroup analysis in subjects without taking lipid-lowering medication. The healthy subjects  and the subjects who ceased lipid-lowering therapy at least 1 month were also included in this subgroup. For TG, we also conducted a larger study (with sample size more than five hundreds) subgroup analysis. To ensure adequate statistical power, we only performed the meta-analysis on the subgroup with at least four studies.P < 0.1. A pooled standardized mean difference (SMD), together with 95% confidence interval (CI), was used for this meta-analysis. The SMD was chosen because the blood lipids were measured using different scanners [The existence of heterogeneity between studies was ascertained by Q-statistic. Heterogeneity was considered significant for scanners . Becausescanners . The ranAll populations described in the studies were tested for Hardy-Weinberg equilibrium (HWE). We repeatedly performed the meta-analysis via excluding the studies not in HWE to test the stability of the results.Galbraith plot, made by MIX 1.7 software , was used to detect potential sources of heterogeneity ,46. The P < 0.1 indicates the presence of publication bias.Funnel plot was performed to look for evidence of publication bias. The funnel plot should be asymmetric when there is publication bias and symmetric in case of no publication bias. Egger's test, estimated by MIX 1.7 software was performed to measure the funnel plot asymmetry -47. A siAdditional file The selected study characteristics were summarized in Table S1 of additional file We distinguished 66 comparisons on the basis of categories like ethnicity, gender, and health condition. Of these, 60, 42, 37, and 48 comparisons were included for comparing the difference in blood TG, TC, LDL-C, and HDL-C, respectively , P = 0.05, respectively (Table P>0.05) , P = 0.11, Pheterogeneity = 0.09. The other results were similar to those when the studies not in HWE were included.We next conducted the analyses excluding the studies not in HWE Table . The assP < 0.00001, Pheterogeneity = 0.0003 (Table P < 0.0001) , 7, 0.34, There was significant heterogeneity among the available studies. However, the heterogeneity was effectively decreased or removed in the subgroups stratified by the characteristics of the subjects Table .P>0.05)  except that the association between the APOA5 -1131 T>C polymorphism and lower blood HDL-C under dominant model was marginally significant in CHD subjects: SMD = -0.21, 95% CI , P = 0.06, Pheterogeneity = 0.003 , P = 0.05, Pheterogeneity = 0.41. The remaining results from these analyses were similar to those when the studies not in HWE were included.We next conducted the analyses excluding the studies not in HWE Table . The assP = 0.04, Pheterogeneity = 0.61, and for the analysis excluding the studies not in HWE: SMD = -0.12, 95% CI , P = 0.04, Pheterogeneity = 0.42 , P = 0.6544, and Intercept = 0.0825, 95% CI , P = 0.8458, respectively. The funnel plot comparing the difference in TG showed asymmetry that suggested the existence of publication bias [Additional file P = 0.0031. To further evaluate the relationship between the APOA5 -1131 T>C polymorphism and blood TG, we carried the subgroup analysis only including the studies with sample size more than five hundreds. The funnel plot for these studies was basically symmetric [Additional file P = 0.9421.Publication bias was assayed by visual funnel plot inspection and Egger's test. The funnel plots comparing the differences in TC, LDL-C, and HDL-C were all basically symmetric [Additional file The APOA5 -1131 T>C polymorphism has been suggested as a possible genetic factor associated with hyperlipidemia ,5. HowevIn this meta-analysis, we investigated the association of the APOA5 -1131 T>C polymorphism with fasting blood lipids. Because the frequencies of the minor allele homozygous were low, most of the studies included in this meta-analysis only provided mean blood lipid levels of all allele C carriers and did not respectively provide mean blood lipid levels of homozygote CC and heterozygote CT. To ensure adequate statistical power, we employed a dominant model for this meta-analysis. The results suggest that the APOA5 -1131 T>C polymorphism under dominant model is significantly associated with fasting blood lipids. The carriers of -1131C allele have higher levels of TC and TG, and lower levels of HDL-C than the non-carriers. In the eligible studies, some studies clearly stated that the overall populations or one/several subpopulations did not take lipid-lowering medication. Because the effects of APOA5 gene on blood lipids may be influenced by lipid-lowering therapy, we performed the subgroup analyses in subjects without taking lipid-lowering medication. The similar association between the -1131 T>C polymorphism and the three blood lipid variables was also detected in these subjects. Since gender, ethnicity, and health condition probably were important variables in determining associative risk with hyperlipidemia, we performed subgroup analyses of gender, ethnicity, and health condition. The effect of this polymorphism on TC especially exists in East Asians, and the effect on TG exists in all subpopulations included in this meta-analysis. For the association of the -1131 T>C polymorphism with lower levels of HDL-C, all findings from this meta-analysis were significant except that the association was marginally significant in male subjects. More studies should be conducted to further examine the association of this polymorphism with HDL-C in male subjects. The association of the -1131 T>C polymorphism with blood HDL-C, TG, and TC was very robust, which did not vary materially when the analyses that removed the studies not in HWE were performed. The significant association of the APOA5 -1131 T>C polymorphism with blood HDL-C was also supported by the results from the meta-analysis performed after removal of the outlier studies. However, our meta-analysis does not suggest the significant association of the APOA5 -1131 T>C polymorphism with blood LDL-C under dominant model. Genome-wide association studies have suggested that the polymorphisms in or near the APOA5 gene are among the strongest known genetic determinants of triglyceride concentration ,49. Our Significant heterogeneity was respectively found across the studies for TG, LDL-C, and HDL-C. Prominent sources of heterogeneity include: differences in ancestry, different study design, gender difference, and healthy status of the subjects included in the meta-analysis, etc. To explore the potential source of the observed heterogeneity, we performed subgroup analyses stratified by the characteristics of the subjects. For TG, the heterogeneity was effectively decreased or removed in the subgroup analyses. For LDL-C and HDL-C, significant heterogeneity was still observed in some subgroups. The sources of heterogeneity were further evaluated by Galbraith plot. Outlier studies were identified as the main contributors of heterogeneity by using the plot. The heterogeneity was effectively removed or decreased after exclusion of these outlier studies.Significant publication bias was present in the studies on TG. Any meta-analysis carries the risk of publication bias caused by the fact that small studies with positive results are more likely to be published than those with negative results . TherefoThe association of the APOA5 -1131 T>C polymorphism with blood TC, TG, and HDL-C is not likely to be due to type I errors . First, the random effects model was used in our meta-analysis. Because the random effects model provides a more conservative evaluation of the significance of the association than one based on fixed effects, the results from our meta-analysis are based on a more conservative evaluation, which was expected to avoid false-positive results. Second, 37 studies with 37859 subjects were included in this meta-analysis. Among the subjects, 36% of them were carriers of -1131C allele. If the incidence of the Thr 54 carriers was sufficiently high, this may have prevented the type I error.APOA1/C3/A4/A5 gene cluster which is key components in modulating lipid metabolism [APOA1/C3/A4/A5 gene cluster [The possible mechanism by which -1131 T>C polymorphism modulates lipids metabolism has not yet been investigated in detail. Study has shown that APOA5 knockout mice develop hypertriglyceridemia, whereas transgenic mice overexpressing APOA5 have low triglyceride levels . It is wtabolism ,24. Stud cluster .The current meta-analysis has several limitations which should be noted. First, hyperlipidemia originates from the interactions of multiple genes, environmental factors, and behavior. Lacking of the original data of the included studies limited our further evaluation of potential interactions because the interactions among gene-gene, gene-environment and even different polymorphic loci of the same gene may modulate blood lipid levels. For example, we did not perform the stratification analyses by environmental factors such as diet, exercise, and smoking. A more precise analysis could be conducted if more detailed individual data were available, which would allow for an adjusted estimate. Second, we did not perform a meta-analysis for haplotype analysis of the APOA5 gene, because a very limited number of studies were available. Third, for LDL-C, a relative small number of subjects were included in this meta-analysis, which may lead to lower statistic power and type II errors . More studies with larger population will be required to further examine the association. Fourth, because it was very difficult to get the full papers published in various languages, we only included the studies published in English. Thus the limitations mentioned may affect our final conclusions.In conclusion, our meta-analysis supports the strong association of the APOA5 -1131 T>C polymorphism with higher levels of TC and TG, and lower levels of HDL-C.The authors declare that they have no competing interests.TFZ participated in the design, data acquisition and analysis, interpretation of results, and manuscript writing. JPZ participated in the data acquisition and analysis. Both authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2350/11/120/prepubA figure describing the flow of candidate and eligible papers.Click here for fileFigure legends of additional file 1, additional file 4, and additional file Click here for fileSupplementary tables. Two supplementary tables including: Table S1. Characteristics of individual studies included in the meta-analysis. Table S2. Blood lipid levels by genotypes of individual studies included in the meta-analysis.Click here for fileGalbraith plot detecting potential sources of heterogeneity.Click here for fileFunnel plot detecting potential publication bias.Click here for file


LIPC) gene was found to be significantly related to advanced age-related macular degeneration (AMD) in our genome-wide association study. We evaluated its association and interaction with previously identified genetic variants and modifiable factors.A novel locus in the hepatic lipase  or no AMD (n=275 controls) were evaluated. AMD status was determined using fundus photography. Covariates included cigarette smoking, body mass index (BMI), and dietary lutein. Individuals were genotyped for the rs10468017 polymorphism in LIPC variant was associated with a reduced risk of AMD, with odds ratios (OR) of 0.50  0.20–0.90) and p=0.014 for the TT genotype versus the CC genotype, controlling for age, gender, smoking, body mass index (BMI), and nutritional factors. Controlling for seven other AMD genetic variants, the OR was 0.50, 95% . The magnitude of the effect was similar for both atrophic and neovascular forms of AMD. Cigarette smoking and higher BMI increased the risk, while higher dietary lutein reduced the risk of advanced AMD, adjusting for genetic variants. There were no significant interactions between LIPC and smoking, BMI, or lutein. There was a possible association between LIPC and complement factor H (CFH) rs1410996, and a possible interaction effect between LIPC and both CFH rs10033900 and the complement factor I (CFI) variants in terms of risk of AMD.The TT genotype of the LIPC is associated with reduced risk of advanced AMD, independent of demographic and environmental variables. Both genetic susceptibility and behavioral and lifestyle factors modify the risk of developing AMD. The links between genetics, environment and age-related macular degeneration (AMD) have been assessed in several previous studies. The US twin study of AMD quantified the proportions of variance in early, intermediate, and advanced forms of this disease due to genetic and environmental factors as 46%–71% and 19%–37%, respectively . SeveralLIPC) in the high-density lipoprotein cholesterol (HDL) pathway as a novel locus for AMD risk, with a protective effect for the minor T allele. A separate GWAS corroborated the LIPC association with AMD [LIPC encodes hepatic triglyceride lipase, which is expressed in the liver. One of the principal functions of the enzyme hepatic lipase is to convert HDL to LDL. LIPC performs the dual functions of triglyceride hydrolase and ligand bridging factors for receptor-mediated lipoprotein uptake [LIPC locus and found that the association was strongest at the functional variant in the promoter region (single nucleotide polymorphism (SNP) rs10468017), which influences LIPC expression [In an attempt to identify other susceptibility loci and to explain the remaining heritability of AMD, we conducted a large genome-wide association study (GWAS) of 979 cases of advanced AMD and 1709 controls, with replication of our top results in independent cohorts with a total of 5789 cases and 4234 controls . Our scawith AMD . LIPC enn uptake . We furtpression .LIPC gene by evaluating the association between the LIPC genetic variant and other genes related to advanced AMD, exploring the relationship between this gene and the two distinct advanced “dry and wet” phenotypes, and assessing LIPC gene-environment associations and interactions with demographic, personal and lifestyle factors.In this report, we expanded upon the results of the GWAS discovery of the The Age-Related Eye Disease Study (AREDS) included a randomized clinical trial to assess the effect of antioxidant and mineral supplements on risk of AMD and cataract as well as a longitudinal study of progression of AMD that ended in December, 2005 . Based ors10468017, which is a functional variant of the LIPC gene on chromosome 15q22, was assessed. In addition, variants in seven other known AMD genes were also determined: 1) the common SNP in exon 9 of the complement factor H (CFH) gene on chromosome 1q31 (rs1061170), a change 1277T>C, resulting in a substitution of histidine for tyrosine at codon 402 of the CFH protein, Y402H; 2) CFH rs1410996, an independently associated SNP variant within intron 14 of CFH; 3) SNP rs10490924 in the ARMS2/HTRA1 region of chromosome 10, a non-synonymous coding SNP variant in exon 1, resulting in a substitution of the amino acid serine for alanine at codon 69; 4) Complement component 2 or C2 E318D (rs9332739), the non-synonymous coding SNP variant in exon 7 of C2 resulting in the amino acid glutamic acid changing to aspartic acid at codon 318; 5) Complement Factor B or CFB R32Q (rs641153), the non-synonymous coding SNP variant in exon 2 of CFB, resulting in the amino acid glutamine changing to arginine at codon 32; 6) Complement component 3 or C3 R102G (rs2230199), the non-synonymous coding SNP variant in exon 3 of C3, resulting in the amino acid glycine to arginine at codon 102 on chromosome 19; and 7) Complement Factor I or CFI (rs10033900) on chromosome 4. The genetic variant on chromosome 10, ARMS2/HTRA1, remains a subject of debate as to whether the gene HTRA1 adjacent to it may in fact be the AMD-susceptibility gene on 10q26 [rs10490924 used in this study can be considered a surrogate for the causal variant that resides in this region. For the C2/CFB genes, there are two independent associations to the C2/CFB locus, but because of linkage disequilibrium, we do not know which of the two genes or if in fact both are functionally affected.All genotyping was performed using primer mass extension and MALDI-TOF MS analysis according to the MassEXTEND methodology of Sequenom  at the Broad Institute Center for Genotyping and Analysis, Cambridge, MA . The sinLIPC genotypes and other risk factors. Individuals with advanced AMD, as well as the GA and NV subtypes, were compared to the control group of persons with no AMD in regards to genotype and risk factor data. Multivariate unconditional logistic regression analyses were performed to evaluate the relationships between AMD and LIPC, controlling for age ; gender; education ; cigarette smoking ; BMI, which was calculated as the weight in kilograms divided by the square of the height in meters ; dietary lutein (micrograms), which was determined from food frequency questionnaires, divided into tertiles, and adjusted for sex and calorie intake because men tend to have a higher calorie intake than women; and assignment to a supplement containing antioxidants or a supplement not containing antioxidants. We included dietary lutein in our models because it is related to AMD [LIPC gene increases HDL [Logistic regression was used to determine the association between d to AMD ,33 and bases HDL –36.LIPC gene and these variants was assessed. Tests for multiplicative interactions between genes and between genes and environmental factors were performed using cross-product terms according to genotype and the individual risk factors [A separate statistical model including all of the above factors, plus the seven other genetic variants, was also evaluated. The association between the  factors . Odds raLIPC genotypes for controls and cases with geographic atrophy and neovascular disease. There were no significant differences in gender, education, smoking, BMI, antioxidant supplements, or calorie-adjusted dietary lutein among the LIPC genotypes. There was a significant association between the number of T alleles and age for the NV group, which was not seen in the other groups.The distributions of demographic, personal, and lifestyle variables, previously shown to be associated with AMD in studies of this cohort ,33,38,39LIPC and other known AMD genetic loci are shown in LIPC and CFH rs1410996 in the GA subgroup (p=0.035). There were no other significant associations between the LIPC gene and other AMD genetic loci among the controls or in the advanced AMD phenotypes.The associations between LIPC variant, while adjusting for demographic and behavioral risk factors. Controlling for age, gender, education, smoking, BMI, AREDS treatment, and dietary lutein in multivariate model 1 (MV1), the OR was 0.5  0.2–0.9) comparing the TT genotype to the CC genotype for advanced AMD (p=0.014), which suggests a protective effect for the TT genotype. Controlling for the other seven genotypes (multivariate model 2), did not alter the magnitude of the effect of this new genetic variant , although this was not statistically significant possibly due to small numbers. There were minimal differences between GA and NV for this locus. For GA in model 1, the OR was 0.5 (95% CI 0.2–1.3) for the TT genotype, and for NV, the OR was 0.4 (95% CI 0.2–0.9).LIPC genotype. Cigarette smoking was associated with a statistically significant increased risk of advanced AMD for both subtypes, controlling for genotype and other factors. ORs in the multivariate model 1  range from 3.9 to 4.0 for current smoking and 1.5–1.8 for past smoking. A body mass index of 30 kg/m2 or higher increased the risk for advanced AMD for both neovascular cases  and for geographic atrophy . Higher lutein intake tended to reduce the risk of AMD, with OR 0.6 (95% CI 0.4–1.0) for the third tertile versus the first tertile. Additional adjustment for the other seven genetic loci (multivariate model 2) did not alter these associations. There were no substantial differences between GA and NV in the analyses of these covariates.LIPC genotypes and lifestyle factors on risk of AMD; results are shown in We assessed the effect of interactions between LIPC genotypes and other genes on risk of advanced AMD. There was a borderline significant interaction between LIPC and the CFI rs10033900 and CFH rs1410996 genotypes. LIPC appears to be more protective when CFI rs10033900 is CC or CT as opposed to TT. LIPC is more protective when CFH rs1410996 is CT or TT versus CC.Shown in LIPC functional variant and advanced AMD while controlling for demographic and behavioral factors including BMI, smoking, and dietary factors, as well as previously identified AMD genes. LIPC and environmental factors were independently associated with advanced AMD, the leading cause of visual impairment and vision-related reduced quality of life among elderly individuals. Controlling for the LIPC genotype, modifiable lifestyle factors, including higher BMI, smoking, and lower dietary lutein, were significantly associated with increased risk of advanced AMD. Similar to our previous findings with other genetic variants [LIPC and CFH rs1410996, and a possible interaction effect between LIPC and both CFH rs1410996 and CFI rs10033900 variants in terms of risk of AMD, but no other associations or interactions were seen between LIPC and the other known AMD genes.To our knowledge, this is the first evaluation of the relationship between the variants –41, therLIPC polymorphisms and AMD is biologically plausible because this gene is involved with the HDL cholesterol pathway, and cardiovascular disease (CVD) risk factors are associated with AMD [LIPC and AMD, and found an inverse (protective) association between HDL and AMD, and a positive (adverse) association with higher LDL and total cholesterol [LIPC and HDL together, the level of serum lipid did not appear to modify the effect of LIPC on AMD [LIPC regulates level of HDL, this may not be the direct mechanism whereby LIPC reduces risk of AMD. HDL transports lutein and zeaxanthin and these carotenoids are also associated with reduced risk of AMD [LIPC genetic variation could be related to AMD [LIPC and the HDL pathway in the pathogenesis of AMD are needed.The association between with AMD . It has with AMD . Modifiawith AMD ,44 and Awith AMD ,44. In alesterol . When weC on AMD , suggestk of AMD –10,34–36d to AMD .  FurtheLIPC genotype. Furthermore, the biologic effects of LIPC and the modifiable factors are not likely to differ in major ways among various European populations with AMD. This study of moderate sample size may not have sufficient power to detect small to intermediate interaction effects between genes or between genes and environmental factors. Larger studies, as well as prospective studies, are needed to confirm and expand upon these findings.Strengths of the study include the large, well characterized population of patients with and without advanced AMD from various geographic regions around the US, the standardized collection of risk factor information, direct measurements of height and weight, and classification of maculopathy by ophthalmologic examinations and fundus photography. Misclassification was unlikely, since grades were assigned without knowledge of risk factors or genotype. We controlled for known AMD risk factors, including age and education, as well as antioxidant status, in the assessment of BMI, smoking, dietary lutein, and genotype. The environmental and genetic risk factors were independently associated with AMD, when considered simultaneously. There may be some other unmeasured factors that might still be confounding these relationships, but they would have to be highly related to genotype, smoking and BMI, and a strong risk factor for AMD to explain these results. Although this is a selected population, cases likely represent the typical patient with AMD seen in clinical setting. The overall population is similar to others in this age range in terms of smoking and prevalence of obesity, as well as the distribution of the LIPC is independently associated with reduced risk of advanced AMD, adjusting for demographic and environmental variables. Both genetic susceptibility and behavioral and lifestyle factors modify risk of developing AMD.


This is a retrospective analysis of poorly-differentiated head and neck malignancies at University College Hospital, Ibadan.Eighty-six poorly-differentiated neoplasms were categorized as carcinomas, sarcomas, lymphomas or neuroendocrine cancers with a panel of 7 antibodies . Immunohistochemical and original hematoxylin-eosin diagnoses were contrasted.The male: female ratio was 2.5:1, with mean age of 38.9 years. Nasopharynx, nose and maxillofacial bones were the most common locations. Immunohistochemistry confirmed 54.8% of carcinomas, 70.6% of sarcomas and 80% of lymphomas.Hematoxylin-eosin was able to distinguish between sarcoma and lymphoma but differentiation between a carcinoma and neuroendocrine lesion was poor. Further studies are required to maximize the role of immunohistochemistry as an ancillary diagnostic tool in the West African sub-region. Histological examination plays a central role in diagnosis, classification, grading and staging of malignancy. Difficulties arise from the subjective nature of histological analysis that are influenced by the practitioner's experience, bias and training. With poorly-differentiated neoplasms, inter- and intra-observer variability can be high . ImmunohIn some undifferentiated tumors, subtle features of epithelial versus mesenchymal differentiation can often be appreciated, which assist the immunohistochemical approach to these tumors. Some tumors, however, may not fit into either of these two categories because of their overlapping histological features . NeverthThe immunohistochemical evaluation of undifferentiated tumors should first aim at a broad lineage determination of the neoplasia. Based on the result of the screening panel, a more detailed or specific panel should then be applied to further sub classify the tumor or to confirm a particular diagnosis . The thr1192 head and neck malignancies  were retrieved from the archives of the Pathology and Oral Pathology departments of the University College Hospital, Ibadan, Nigeria between 1990 and 2008. 142 poorly-differentiated and undifferentiated neoplasms including anaplastic (undifferentiated) or poorly-differentiated carcinomas, anaplastic large cell lymphomas, pleomorphic sarcomas, malignant fibrous histiocytoma, esthesioneuroblastoma and spindle cell sarcomas were selected. Cases where the original paraffin block could not be obtained were excluded from analysis. Only 86 of the 142 undifferentiated and poorly-differentiated head and neck malignancies diagnosed during the study period satisfied the inclusion criteria.Freshly prepared sections from each case were stained with hematoxylin-eosin (H&E) and a panel of antibodies to leukocyte common antigen (CD45), cytokeratin AE1/AE3, vimentin, desmin, myogenin and neuron-specific enolase (NSE) using the specifications of the manufacturer .The sections for immunohistochemistry were de-paraffinized, hydrated and then rinsed in Phosphate Buffered Solution (PBS). They were immersed in heat induced epitope retrieval citrate buffer diluted to 1:10 with distilled water and incubated at 90°C for 1 hour. They were then placed in fresh citrate, cooled in water for 20 minutes and then rinsed in PBS. Positive controls  and negative controls were employed for each antibody. 3% hydrogen peroxide was added to each section for 10 minutes and the sections were rinsed in 0.1% PBS. The specimens were incubated for an hour with 40-130 μl of appropriately diluted Dako mouse primary antibody, followed by incubation with undiluted labeled polymer Horse Radish Peroxidase conjugated antimouse secondary antibody for 30 minutes. One ml of Diaminobenzidene solution was added to cover the specimen, followed by incubation in a humidity chamber for 15 minutes. The sections were then immersed in aqueous hematoxylin and rinsed in distilled water. The tissue was then dehydrated and subsequently rinsed with xylene. DPX  mounting fluid was then applied and a cover slip placed.All the seven antibodies used in the panel for one specimen were reviewed sequentially and the pattern and intensity of staining was observed and scored as: negative (0), weakly positive (+1), moderately positive (+2) and strongly positive (+3) . The sliThe data was analyzed using version 16 of the Statistical Package for Social Sciences (SPSS16). Qualitative data were compared using chi-square statistics. Quantitative data were summarized using mean, standard deviation and confidence interval and compared using student t- and/or one-way analysis of variance test. The level of significance was set at p < 0.05. Sensitivity and specificity were calculated using immunohistochemistry as the gold standard to which the original H&E diagnosis was compared. The positive predictive value, negative predictive value, accuracy and degree of agreement were also determined. For degree of agreement, Kappa value >0.75 = excellent agreement, 0.4-0.75 = fair to good agreement and <0.4 = moderate to poor agreement .The cases comprised 62 (72.1%) males and 24 (27.9%) females. The mean age was 38.9 (SD ± 15.9) with peak occurrence between 25-44 years. The nasopharynx (47.7%), nose (12.8%) and maxillofacial bones (12.8%) were the most common locations.The original hematoxylin-eosin diagnoses are shown in figure Table The sensitivity of histology was highest for carcinomas (97.1%) and least for neuroendocrine lesions (14.2%). Specificity of histology was highest for neuroendocrine lesions (98.6%) and lymphomas (98.4%) and least for carcinomas (47.7%). The positive predictive values of histology was highest for sarcomas and lymphomas (80% each), while the negative predictive value was highest for carcinomas (95.4%). Accuracy of histology was highest for the neuroendocrine tumors (91.1%). The level of agreement between histology and immunohistochemistry, given by the kappa values, was highest for sarcomas (54%) Table .et al in Italy [In the present study, the original histological diagnosis of 62 lesions was carcinoma, but only 34 (54.8%) were confirmed by immunohistochemistry. This proportion is higher than the 27.9% confirmation rate of carcinomas in a study by Bianchini in Italy  also repEighty percent of lymphomas diagnosed by histology in this study were confirmed by immunohistochemistry and this is comparable to the 66% reported confirmation of lymphomas in another study .After the immunohistochemical analysis, almost 10% of the lesions thought to be undifferentiated carcinomas were revised to neuroendocrine carcinomas. More than 60% of these revised lesions were found either in the nose or nasopharynx and occurred more commonly in males (66.7%). Histopathological differentiation of undifferentiated carcinoma from neuroendocrine carcinoma is challenging and is significantly aided by immunohistochemistry .et al reported 18.6% and Gatter reported 6.7% inconclusive results. This could be due to technique differences, different antigen retrieval methods or the absence of the antigen suspected. Use of inappropriate antibodies may also be responsible for absence of immunoreactivity. In addition, some poorly-differentiated tumors might require other techniques such as electron microscopy and molecular studies before an accurate diagnosis can be achieved [The present study had inconclusive diagnosis by immunohistochemistry in 8.1% of cases, Bianchini achieved ,13.In this study, histology, to a reasonable extent is able to determine if a sarcoma or lymphoma is present or if they are absent. However it cannot, with a good degree of certainty, determine if a carcinoma or a neuroendocrine tumor is present, although it can exclude them fairly accurately. The high number of carcinomas seen in this study therefore suggests an over-diagnosis of carcinomas by histology. For correct management to be instituted for any malignant lesion it must be diagnosed accurately. In this study the diagnostic accuracy of histology for carcinomas is 69.6%. This means that almost 70% of the time, histology will diagnose carcinomas accurately. The diagnostic accuracy for sarcomas, lymphomas and neuroendocrine tumors is 83.5%, 86% and 91.1% respectively. Therefore further ancillary tests will be needed to resolve diagnostic doubts.The level of agreement in this study between morphological classification by histology and immunohistochemical assessment was fair for sarcomas (kappa = 0.54), moderate for carcinomas and lymphomas (kappa = 0.42), and poor for neuroendocrine tumors (kappa = 0.18). However, a larger sample of neuroendocrine tumors will be required before any affirmative deductions can be made about them.et al [et al [Undifferentiated carcinomas were the most prevalent group in this study constituting 64% of the undifferentiated malignancies and 7.6% of all head and neck malignancies. A study by Gatter et al  in the Ul [et al  however l [et al . In pracIn this study, test of sensitivity and specificity show that histology is able to determine the presence or absence of a sarcoma or lymphoma to a good extent but confirmation of a carcinoma or neuroendocrine lesion is poor, although it is able to exclude them fairly accurately. This study has also shown that the use of antibodies in immunohistochemistry greatly assist in the identification of tumors which cannot be accurately identified using routine histopathological procedures.More detailed studies for specific pathological conditions need to be carried out in order to maximize immunohistochemistry as an ancillary diagnostic tool and expand its versatility in Nigeria and the West African sub-region.The authors declare that they have no competing interests.AO, AO and JO conceived of the study, and participated in its design and coordination and helped to draft the manuscript. EEU, BF and B participated in the design of the study, drafting of the manuscript and performed the statistical analysis. AO, AO and EEU participated in the revision and reporting of the cases. All authors read and approved the final manuscript.


Policy decisions often require synthesis of evidence from multiple sources, and the source studies typically vary in rigour and in relevance to the target question. We present simple methods of allowing for differences in rigour  and relevance  in evidence synthesis. The methods are developed in the context of reanalysing a UK National Institute for Clinical Excellence technology appraisal in antenatal care, which includes eight comparative studies. Many were historically controlled, only one was a randomized trial and doses, populations and outcomes varied between studies and differed from the target UK setting. Using elicited opinion, we construct prior distributions to represent the biases in each study and perform a bias-adjusted meta-analysis. Adjustment had the effect of shifting the combined estimate away from the null by approximately 10%, and the variance of the combined estimate was almost tripled. Our generic bias modelling approach allows decisions to be based on all available evidence, with less rigorous or less relevant studies downweighted by using computationally simple methods. Standard methods for meta-analysis assume that all studies have addressed the same question in a similar way and therefore provide information on common parameters of interest. In practice, however, the studies vary in degree of rigour and in relevance to the research question. Rigour  reflects how well a study estimates its intended parameters and varies according to use of randomization, adequacy of allocation concealment, degree of blinding and attrition levels. Relevance  is defined with respect to a target question. For example, in a typical comparison of two interventions, the objective is to compare the effect of the interventions on a specified primary outcome in a particular population. The source studies that are available may differ from this target setting, with respect to study population, outcomes measured and details of interventions. This paper is motivated primarily by meta-analyses that were carried out to inform policy decisions, where a target question is predefined, but varying relevance also affects the interpretation of any meta-analysis.Differences in rigour and relevance between studies which are potentially eligible in a systematic review are typically addressed by choosing a minimum threshold for inclusion. This introduces an arbitrary division and valuable evidence may be discarded . Of addiIf a bias affecting a particular study were of known magnitude, bias adjustment could be achieved simply by shifting the study effect estimate and interval. Typically, however, the internal and external biases are of unknown magnitude, and this uncertainty should be acknowledged in the analysis, resulting in a wider interval as well as a shift of location. It is misleading to report confidence intervals (CIs) which reflect only the extent of possible random error when systematic biases are suspected . The uncSeveral methods of adjusting for biases in meta-analysis have been proposed. Weighting the analysis by quality scores is known to be inadequate ; among oOur objective in this paper is to provide simple generic methods for allowing for internal and external biases in meta-analysis and evidence synthesis. The term ‘evidence synthesis’ refers to a broader class of analyses, encompassing synthesis of results from diverse sources, e.g. different study designs, different treatment comparisons and different clinical end points . Our appWe develop our methods in the context of an example in antenatal care, which concerns the effectiveness of routine anti-D prophylaxis in pregnant women who are Rhesus negative. The purpose of anti-D prophylaxis is to prevent ‘sensitization’ of the mother, to avoid haemolytic disease of the newborn in subsequent pregnancies. A technology appraisal  and the outcome of interest.When identifying the biases that are present in a study, it is not trivial to distinguish external from internal biases. For example, consider a study which recruited different populations in the intervention and control arms, neither identical to the target population. It is clear that differences between populations will cause both internal and external bias with respect to the target question, but unclear how to determine the extent of each bias. To address this problem, we first envisage an idealized version of each source study and write down a miniprotocol for it. The idealized study can be viewed as a repeat of the original study by using a design which eliminates all sources of internal bias. In the miniprotocol, we specify the population which the researchers planned to study, their planned comparison and the outcome which they planned to measure. This information is usually easily extracted from the abstract and early sections of the study publication. In the idealized study, the population recruited and the outcome measured would be identical in the intervention and control arms. It may be helpful to think of the idealized study as a perfect randomized controlled trial, but note that this design need not be practicable, for instance where ethical issues prevent use of randomization or blinding.The process of identifying internal and external biases is now much simpler . To idenTo reiterate our approach proposed above, the steps are as follows.Define the target question.Write down a miniprotocol for an idealized version of each study.Identify internal biases by comparing the original study against the idealized study.Identify external biases by comparing the idealized study against the target question.Tools for completion of steps (c) and (d) are provided in Section 4.For bias modelling, we would like to group individual biases into broader categories of bias, which may be assumed to be independent see . For intFor external bias, the bias categories represent the differences between the idealized studies and the four components of the target question: population bias; intervention bias; control bias; outcome bias. For example, population bias may reflect differences in age, sex or health status of the idealized study participants, compared with the target population. Intervention bias refers to differences in dose, timing or delivery method of the idealized study intervention compared with the target intervention, and similarly control bias refers to differences in the control strategy. When the target question is a comparison of two active interventions, intervention bias and control bias would be relabelled appropriately. Outcome bias may represent differences in the definition, timing or method of measurement of the idealized study outcome compared with the target.There may be some flexibility over how to define the idealized study, e.g. where a study has measured several outcomes and none is identical to the target outcome. The aim is to maximize the information that is supplied by the study with respect to the target question and this could mean weighing up relevance against the extent of missing data. We do not here address publication bias or selective reporting of outcomes, for which methods have been discussed elsewhere . These iθ, which is the ‘true’ intervention effect in our target setting. For a two-arm comparison, θ represents the difference in the target end point between the target intervention and control policies, when assessed within the target population. The intervention effect is defined on a scale on which it is reasonable to assume that most biases act additively.In this section, we propose a simple method of adjusting for internal and external biases in meta-analysis. We wish to estimate some underlying quantity k studies, i=1,…,k, and each provides a statistic yi  represents a general distribution with mean μ and variance σ2. We assume also that, if there were no external biases, all the studies would be measuring the target quantity so θi=θ. Thus internal biases reflect that the above sampling distribution is not a correct assumption, whereas external biases reflect that θi is not equal to θ. All the development below carries through by using moments and does not require assumptions of normality.Suppose that there are The method of adjustment that is proposed here is appropriate only for biases which may be regarded as independent of the magnitude of the intervention effect, and we refer to these as additive biases. Examples are given in Section 4.1, and in Section 6 we discuss methods of adjusting for biases which are proportional to the intervention effect.j=1,…,JI of internal bias, we write j on the estimated intervention effect in study i. ith study is We use superscripts I and E to distinguish internal and external biases. For multiple independent sources αi can be interpreted as a quality weight for rigour, representing the proportion of within-study variability that is unrelated to internal biases  and (2), we obtain a model which incorporates internal and external biases, θ is The inverse variance estimator of with approximate standard error θ is Assuming approximate normality for the estimator τ2 is required and it is convenient to use a method-of-moments estimate that is based on the heterogeneity statistic Q  might be induced by this bias?The assessor is given a copy of an elicitation scale  for eachThe relative risk scale that is shown is symmetric with respect to the study arms, so a doubling of risk in the control group compared with the intervention group is marked as 0.5 on the left-hand half of the scale, whereas a doubling of risk in the intervention group is marked as 0.5 on the right-hand half. Range limits marked symmetrically around 1 represent a belief that the bias is equally likely to be in favour of the control as in favour of the intervention. Relative risk values are marked on a log-scale, since this will be used when constructing probability distributions.To ease the process of choosing numerical limits for each bias, we recommend that assessors first make a qualitative judgement of the severity of bias, before quantifying their opinion as a 67% range. Assessors write down their judgement of the severity of bias  in favour of the intervention and, separately, the severity of bias in favour of the control. We suggest the following correspondence between qualitative judgements of severity and choices for the range limit: none (1); low (0.9–1); medium (0.7–0.9); high (less than 0.7). These divisions are guided by consideration of the effect of different ranges of bias on the CI for a log-odds-ratio . For conFor each external bias category, the assessor is asked to consider the following question, taking into account the information that is extracted in Even if there were no effect in a study addressing the target question, what effect might there be in an idealized version of the present study ?For each external bias in every study, the assessor is asked to mark a 67% range on an elicitation scale , as descj in study i, the range limits aij on the left-hand half of the elicitation scale and bij on the right-hand half correspond to range limits log (aij), log (1/bij) on a scale representing the log-relative-risk for intervention compared with control. For convenience, we assume that the 67% range represents approximately μij±σij, as it would under normality, and obtain the following elicited values for μij and σij: To construct a probability distribution from the range estimate that is chosen for each bias, we work on the log-scale. For bias μij and http://rsb.info.nih.gov/ij/download.html)In this way, parameters Our example concerns the antenatal care of women who are Rhesus negative, i.e. women who have no D antigen on their red blood cells. When a Rhesus negative woman is pregnant with a Rhesus positive fetus, there is a danger of ‘sensitization’, where contact between fetal blood and maternal blood causes the mother to produce antibodies to the D antigens in the fetal red blood cells . In any primigravidae (women who are pregnant for the first time) in the UK. This analysis provided strong evidence in favour of routine antenatal injection of anti-D immunoglobulin, with the odds ratio of sensitization estimated as 0.37 . The policy proposed was also considered to be cost effective and, in 2002, the NICE recommended that it should be implemented across the UK.The NICE technology appraisal  for two groups of Rhesus negative women who were delivered of Rhesus positive babies in a Swedish hospital  and r0 and r1 represent the number of observed events in the control and treated arms. For a given To help those viewing the results to interpret the effect of bias adjustment, we convert the odds ratio results into numbers of events that would be observed in each arm of a study of rare events. Failure to allow for bias can be viewed as similar to overcounting rare events. In a large study with similar sample sizes in each arm, the estimated log-odds-ratio 2=0.05.Our original aim in the anti-D immunoglobulin example was to perform a bias-adjusted meta-analysis of the 11 relevant studies that were identified by the NICE appraisal , 1987. Wet al. (1984) study in Section 5.2, we elicited distributions for the additive biases in the other seven anti-D immunoglobulin studies. Under the assumptions of model (3), we adjust the study estimates and standard errors and perform a bias-adjusted meta-analysis. The unadjusted and additive bias-adjusted study results are shown in As described for the Hermann τ2 is estimated as 0. There remains strong evidence for the effectiveness of routine antenatal anti-D treatment, but the uncertainty has increased , and the between-study variance ncreased . The effncreased .Through adjusting for internal and external additive biases, we have reduced the estimated heterogeneity to 0 and appear to have explained the systematic differences between the studies. The reduction in heterogeneity is caused partly by a decrease in variability of the study estimates, and partly by an increase in within-study uncertainty. After adjustment for additive biases, the variance of the log-odds-ratio estimates has decreased by 27%, whereas a measure of the typical within-study variance  has apprWe now consider biases which depend on the magnitude of the intervention effect. Examples include the external bias that is caused by a study delivering the intervention to only a subset of the target population, and the internal bias due to a study excluding non-compliers who did not receive the intervention. The first of these reduces the intervention effect in the idealized study compared with the target, whereas the second exaggerates the effect in the actual study compared with the idealized study. These biases cannot be modelled by using additive bias models, and we assume that they reduce or increase the intervention effect multiplicatively.k=1,…,KI of internal proportional bias, we write k on the estimated intervention effect in study i, and similarly we write Assuming multiple independent sources i is βik and deriving The total internal proportional bias in study δ. Using the distribution of the product of independent variables  might this bias induce?The assessor is given a copy of an elicitation scale  for eachk in study i, assuming that the 67% range represents approximately λik±ωik on the log-scale. To find moments for total internal proportional bias and total external proportional bias, which are products of multiple proportional biases on the original scale, we assume log-normality .In The effect of adjusting the As described for the In a meta-analysis that is adjusted for additive and proportional bias, the odds ratio of sensitization is estimated as 0.25 . In comparison with the unadjusted results, the estimate has shifted from the null value by just over 10%, whereas the variance has almost tripled . The effτ2 is again estimated as 0. In comparison with the unadjusted analysis, the variance of the log-odds-ratio estimates has decreased by 61% and the typical within-study variance . We chose this approach in preference to the linear opinion pool or the logarithmic opinion pool, where the pooled opinion from multiple assessors represents weakened or strengthened knowledge respectively compared with a single assessor . Individual biases are likely to be positively correlated across trials. Since we do not take this into account, we expect our degree of variance adjustment to be conservative, meaning that the study results should be downweighted further.The decision to assume a direct form for the biases affecting the intervention effect was based on the view that constructing separate models for every bias would be unrealistic in most practical settings. We also chose to model biases as either additive or proportional, as a simplification which we expect to be adequate in many circumstances. Within our approach, it would be possible to incorporate more complex forms of adjustment for certain biases, by adjusting for these before the other biases. In observational studies, it may be desirable to use a detailed model of adjustment for uncontrolled confounding  required at least three hours.If carrying out analyses to inform politically sensitive decisions concerning availability of particular treatments, it would be important for stakeholders to approve the set of bias assessors in advance. Completed bias checklists and summaries of bias distributions that were elicited for each included study could subsequently be made publicly available. In the event of conflict over the bias-adjusted results, stakeholders could look for cases of disagreement between assessors and undertake sensitivity analyses accordingly by using software made publicly available on the Web. This process would promote transparency in the synthesis of available evidence.The quantification of biases by assessors on elicitation scales would benefit enormously from the availability of interactive elicitation software, as recommended by If the aim of a meta-analysis is to summarize the literature rather than to address a target question, there is no need to adjust for external biases since differences between the  studies are accepted as diversity. The need to adjust for internal biases remains and our method can be applied directly to these.In the anti-D immunoglobulin example, it was previously unclear how to make best use of the information that is available from studies which showed clear evidence of internal bias and which varied in relevance to the target UK setting. Our bias-adjusted meta-analysis was carried out to exemplify the methods rather than as a definitive analysis of these data. It would be preferable to involve assessors from several disciplines at the elicitation stage rather than only two (biostatistics and obstetric medicine), including at least one assessor with specialist knowledge of transfusion medicine. We place least confidence in our assessments of the external biases due to differences in dose and frequency of anti-D immunoglobulin.Our methods for bias adjustment are presented in the context of a two-arm comparison of a binary outcome, but they could be modified for other settings. Other types of outcome could be addressed by adapting the elicitation scales and questions. For a non-comparative target setting, such as estimation of a prevalence, changes to the bias checklists would also be required.When deciding how to handle biases in evidence synthesis, researchers should consider whether their aim is to answer a specific target question by using the evidence which is currently available, or to summarize the literature. Our methods have been developed with the first of these aims in mind. When a decision must be taken on the basis of the evidence that is available, it is essential to exploit fully the information in the studies and, for this, detailed bias assessment and elicitation are worthwhile. The element of judgement could be considered controversial, but we feel that even stronger judgements are always made, when eliminating evidence on somewhat arbitrary grounds and treating the evidence included as ‘perfect’. Our approach makes judgements explicit, transparent and open to sensitivity analysis. This can only increase the accountability of decisions that are made by organizations such as the NICE.


Warfarin treatment has a narrow therapeutic range, requiring meticulous monitoring and dosage titration. Individual dosage requirement has recently partly been explained by genetic variation of the warfarin metabolizing enzyme CYP2C9 and the Vitamin K-activating enzyme VKORC1. In the WARIS-II study, comparing three different antithrombotic regimens after myocardial infarction, warfarin treatment reduced thrombotic events, but was associated with more frequent bleeding than use of acetylsalisylic acid (ASA) alone.The primary aim of the present study was to investigate the relation between genotypes of CYP2C9 and VKORC1 and warfarin maintenance dose in myocardial infarction. The secondary aim was to relate the genotypes to international normalized ratio (INR).Genotyping was performed in 212 myocardial infarction patients from the WARIS-II study by robotic isolation of DNA from EDTA whole blood (MagNa Pure LC) before PCR amplification (LightCycler) and melting point analysis.The 420 C>T substitution of CYP2C9*2, the 1075 A>C substitution of CYP2C9*3 and the 1173 C>T substitution of VKORC1 had minor allele frequencies of, 11.3%, 5.7% and 36.6% respectively. Warfarin weekly dose varied between 17 mg and 74 mg among the patients. INR did not vary between genotypes. Warfarin dosage requirement was significantly associated with CYP2C9 and VKORC1 genotypes, treatment group and age. The VKORC1 genotype contributed 24.5% to the interindividual variation in warfarin dosage, whereas the combined CYP2C9 genotypes were only responsible for 7.2% of the dose variation.CYP2C9 and VKORC1 genotype frequencies in myocardial infarction patients appear similar to other patient groups and have similar impact on warfarin maintenance dose. Warfarin and aspirin (ASA) have a well established role in secondary prevention of atherothrombotic disease, reducing new thromboembolic events -4. Howevet al. [Warfarin antagonizes the vitamin K-dependent activation of a range of coagulation factors  and anticoagulants , and INR is used as an indicator of coagulation status. Two gene products known to influence warfarin dose are the enzymes Cytochrom P 450 subtype 2C9 (CYP2C9) and the Vitamin K Epoxide Reductase 1 (VKORC1), which are involved in drug metabolism and vitamin K activation, respectively. Common gene polymorphisms exist for both enzymes, resulting in marked alteration of enzyme activity, and several studies have characterized the role of these polymorphisms in explaining a substantial part of the variation in warfarin dosage requirement -15. In tet al. , carrierIn the WARIS-II study, warfarin alone or in combination with low dose ASA (75 mg daily) were superior to 160 mg ASA in prevention of new thrombotic events after acute myocardial infarction, but was also associated with higher risk of bleeding . Thus, 1The primary aim of the present study was to investigate the relation between genotypes of CYP2C9 and VKORC1 and warfarin maintenance dose in myocardial infarction patients (from the WARIS-II study). The secondary aim was to relate the genotypes to international normalized ratio (INR).This substudy was established from the Warfarin Aspirin Reinfarction Study (WARIS-II), a Norwegian multicenter study, comparing three different antithrombotic regimens on clinical end-points of mortality, reinfarction and cerebral stroke after acute myocardial infarction . All pat2 and 50–100 ng genomic DNA.DNA was isolated from 200 μl EDTA whole blood by MagNA Pure LC robot  accordinAY702706) was performed essentially as described by others [Genotyping the two functional sequence variants CYP2C9* 2 and CYP2C9*3 in the human CYP2C9 gene , we selected one SNP (rs9934438/1173 C>T) localized in the first intron of VKORC1, reported to have a minor allele frequency (MAP) of about 40% [et al. [From common and publicly available sequence variants in the human VKORC1 gene . Univariate and stepwise multiple regression analyses were performed to evaluate the impact of polymorphisms in VKORC1 and CYP2C9 genes on mean warfarin dose, after adjustment for the covariates age, sex and treatment group. The significance level of A total of 212 Caucasian patients, divided into three different anticoagulation regimens  were genotyped for common VKORC1 and CYP2C9 polymorphisms in this study. One hundred and five patients were included in the two warfarin groups. The treatment groups were similar as to baseline characteristics . Noteworthy, there was a statistically significant  difference in mean warfarin dose between the warfarin and warfarin +ASA groups . This difference reflects the differences in observed INR values 2.4–3.6 (mean 3.1) and 1.9–2.9 (mean 2.2) for warfarin and warfarin +ASA groups, respectively and in INR target values of 2.8–4.2 and 2.0–2.5, respectively.Genotype distributions of CYP2C9*2, CYP2C9*3 and VKORC1 1173 C>T polymorphisms in 212 patients from the Oslo subset of the WARIS-II study are summarized in Table Relation between warfarin dose and CYP2C9 and VKORC1 genotypes is illustrated in Figure INR values did not vary significantly between different genotypes as shown in Table This study was designed to investigate the frequency of CYP2C9 and VKORC1 gene polymorphisms and their relation to warfarin dose and INR in patients with myocardial infarction from the Norwegian WARIS-II study. The genotype and allele frequencies of CYP2C9 and VKORC1 polymorphisms for the whole group of 212 patients investigated were in accordance with recent reports from studies in Caucasians. The relation observed between polymorphisms of CYP2C9 and VKORC1 and variation in warfarin dose requirement was as previously reported in other patient groups.The minor allele frequencies (MAF) of 37% for the VKORC1 polymorphism 1173C>T, 11% for the CYP2C9*2 and 6% for the CYP2C9*3 were all slightly lower than those reported by Takahashi, who found MAF of 42, 14 and 10% for the respective polymorphisms in Caucasians . Anotheret al. [A meta-analysis of 33 studies showed that major and fatal bleedings occurred at rates of 7.2 and 1.3, respectively, per 100 patients years during oral anticoagulant therapy . Aithal et al.  found thet al. . A meta-et al. . This suet al. . When coet al. found a higher risk of myocardial infarction in individuals carrying the *2 or *3 variants of CYP2C9 [et al. [et al. [The possible impact of the warfarin dose-related polymorphisms on risk of myocardial infarction has recently been studied. Yasar f CYP2C9 , whereas [et al.  found th [et al.  found a In conclusion, the observed genotype frequencies of CYP2C9 and VKORC1 in patients with myocardial infarction are similar to those previously reported in other patient groups and healthy subjects in Caucasians, as is the relation between warfarin dosage and genotypes. Genotyping would be of value for secondary stratification of patients into comparable study groups when testing different treatment regimens. The relation between gene polymorphisms and bleeding frequency during warfarin treatment needs to be further investigated in larger studies with sufficient statistical power.ASA: aspirin; CYP: cytochrom P 450; INR: international normalized ratio; MAF: minor allele frequencies; SNP: single nucleotide polymorphism; VKORC1: vitamin K epoxide reductase 1; WARIS-II: Warfarin Aspirin Reinfarction Study.The authors declare that they have no competing interests.KBFH participated in the study design, developed and followed up the genetic analysis and drafted the manuscriptMNS participated in the study design, performed the statistical analysis and drafted the manuscriptMKK participated in the study design, performed the statistical analysis and drafted the manuscriptSN participated in the study designSTS performed the genotypingPWJ participated in the study design and drafted the manuscriptPK participated in the study design and drafted the manuscriptIS contributed with the WARIS-II materialHA contributed with the the WARIS-II materialOB participated in the study design and drafted the manuscriptAll authors read and approved the final manuscript.


CALM1 gene encodes calmodulin (CaM), an important and ubiquitous eukaryotic Ca2+-binding protein. Several studies have indicated that a deficient CaM function is likely to be involved in the pathogenesis of osteoarthritis (OA). Using a convincing genome-wide association study, a Japanese group has recently demonstrated a genetic association between the CALM1 core promoter polymorphism  and OA susceptibility. However, the subsequent association studies failed to provide consistent results in OA patients of differently selected populations. The present study is to evaluate the association of the -16C/T polymorphism with knee OA in a Chinese Han population.A case-control association study was conducted. The polymorphism was genotyped in 183 patients who had primary symptomatic knee OA with radiographic confirmation and in 210 matched controls. Allelic and genotypic frequencies were compared between patients and control subjects.P > 0.05). The association was also negative even after stratification by sex. Furthermore, no association between the -16C/T SNP genotype and the clinical variables age, sex, BMI (body mass index) and K/L (Kellgren/Lawrence) score was observed in OA patients.No significant difference was detected in genotype or allele distribution between knee OA and control groups (all The present study suggests that the CALM1 core promoter polymorphism -16C/T is not a risk factor for knee OA susceptibility in the Chinese Han population. Further studies are needed to give a global view of this polymorphism in pathogenesis of OA. Osteoarthritis (OA) is a common musculoskeletal disease among the elderly, characterized by the degradation of articular cartilage and formation of abnormal bone (osteophyte). It is a multifactorial disorder in which aging, genetic, hormonal and mechanical factors are all major contributors to its onset and progression . ResultsCALM1) encodes calmodulin (CaM), a ubiquitous eukaryotic Ca2+-binding protein which regulates many Ca2+-dependent cellular events by interacting with a heterogeneous group of target proteins [2+-calmodulin signal may be involved in the pathogenesis of OA.Calmodulin 1 gene  were recruited consecutively at the Center of Diagnosis and Treatment for Joint Disease, Drum Tower Hospital, affiliated to the Medical School of Nanjing University and 210 healthy control subjects (142 women and 68 men) were recruited at the Center of Physical Examination. All subjects included in the study were Han Chinese living in or around Nanjing. The study was approved by the ethics review committee of the Medical School of Nanjing University and written informed consent was obtained from all participants. The ascertainment criteria for both OA patients and control subjects were according to the previously published study by Jiang et al . In the GT3'. The italic and boldfaced nucleotide in the reverse primer is a G as opposed to the C that exists in the CALM1 sequence in order to create a APAL‡T restriction enzyme site in the T-allele of the SNP which is absent in the C-allele. The amplification solution system was supplemented with 5% dimethyl sulfoxide (DMSO) [Genomic DNA was extracted from peripheral blood leukocytes using the Chelex-100 method  or from e (DMSO) . Amplifi2 tests to determine the significance of differences in allelic and genotypic frequencies between OA patients and control subjects. P < 0.05 was considered statistically significant. Allele and genotype proportions were tested for Hardy-Weinberg equilibrium. Clinical variables age, sex, BMI (body mass index) and K/L score of OA patients with different genotype were compared using χ2 tests or Kruskal-Wallis tests. Power estimates were calculated using the software R.For this case-control association study, we used standard χP = 0.023 and 0.064) but not to those of UK Caucasians [P = 0.000 and 0.000). In the association study, no significant differences between cases and controls were observed either in allele (P = 0.996) or genotype (P = 0.802) frequencies, and the allele frequencies were even the same between the two groups. Stratifying the samples by sex did not result in any significant association  which may represent a severe phenotype of congenital hip disease.Moreover, Hoaglund  has receCALM1 core promoter polymorphism (-16C/T) and susceptibility to knee OA in the Chinese Han population. Further studies are necessary to identify the association of this polymorphism with hip OA in our population and with OA in other different populations on different joint sites to give a global view of this polymorphism in pathogenesis of OA.The present study did not find any significant association between the The authors declare that they have no competing interests.HN carried out the molecular genetic studies, performed the statistical analysis and drafted the manuscript. JD, JQ, YX, CY, LZ participated in sample collection and DNA extraction. LY participated in the design of the study and help to carry out the molecular genetic studies. QJ and DS conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


The variability of maternal serum biochemical markers for Down syndrome, free β-hCG and PAPP-A can have a different impact on false-positive rates between the 10+0 and 13+6 week of gestation. The study population comprised 2883 unaffected, singleton, spontaneously conceived pregnancies in Croatian women, who delivered apparently healthy child at term. Women were separated in 4 groups, dependently on the gestational week when the analyses of biochemical markers were performed. The concentrations of free β-hCG and PAPP-A in maternal serum were determined by solid-phase, enzyme-labeled chemiluminiscent immunometric assay (Siemens Immulite). Concentrations were converted to MoMs, according to centre-specific weighted regression median curves for both markers in unaffected pregnancies. The individual risks for trisomies 21, 18 and 13 were computed by Prisca 4.0 software.10 MoM free β-hCG values, between the 11th and 12th gestational week, was significant (p = 0.002). The difference in log10 MoM PAPP-A values between the 11th and 12th, and between 12th and 13th week of gestation was significant . False-positive rates of biochemical risk for trisomies were 16.1% before the 11th week, 12.8% in week 12th, 11.9% in week 13th and 9.9% after week 13th. The differences were not statistically significant.There were no significant differences between the sub-groups, regarding maternal age, maternal weight and the proportion of smokers. The difference in log10 MoMs) showed gestation related variations in the first-trimester unaffected pregnancies, although the variations could not be attributed either to the inaccuracy of analytical procedures or to the inappropriately settled curves of median values for the first-trimester biochemical markers.Biochemical markers (log The first-trimester screening for trisomies 21, 18 and 13, combining maternal age, fetal nuchal translucency thickness (NT), maternal serum free β-human chorionic gonadotropin (free β-hCG) and pregnancy associated plasma protein-A (PAPP-A) has revealed a highly potential possibility of an early detection of fetal aneuploidies .Various co-variables influence the specificity and sensitivity of the first-trimester biochemical markers have been studied . Correctth week [th week, ongoing towards the second trimester of pregnancy [Several studies have focused on the optimal timing for analysis of biochemical markers, predominantly concerning their sensitivity for fetal trisomies ,17. The th week . Clinicaregnancy .To our knowledge, there has been a lack of publications, which presume the precision of the applied analytical methods to the physiological variations of maternal serum markers across the first trimester. This retrospective study in Croatian women with unaffected pregnancies has the aim to: (a) assess the specificity of free β-hCG and PAPP-A across the first-trimester in terms of the false-positive rate (FPR) for trisomy 21 in particular weeks and (b), to examine the analytical accuracy of the methods applied for the measurement of biochemical markers.In Croatia, combined screening for fetal trisomies has been performed from February 2006. Our Laboratory has been the only centre, which has conducted the analyses for biochemical markers according to the recommendations of the Fetal Medicine Foundation . Also, we have been included in external proficiency testing program (UK NEQAS First Trimester Down Syndrome Screening) since August 2006.Out of total 3118 pregnant women who underwent the combined screening for chromosomal abnormalities till May 2008, a cohort of 2883 subjects was retrospectively recruited from the entire population. The selection criteria included non-diabetic, Caucasian women, with singleton, spontaneously conceived pregnancy, who delivered apparently healthy child at term. Pregnancies with abnormal fetal karyotype and those spontaneously aborted were excluded, on the basis of the data supplemented from health-care providers and delivery records in maternity units, respectively.All pregnant women had an ultrasound examination between weeks 10+0 and 13+6, which included the crown-rump (CRL) measurement for pregnancy dating and the correspondent NT value, respectively. The obstetrician filled the form with all the clinical data relevant for the pregnancy and the mother. The Hospital Ethics Committee approved the accessibility of the first-trimester screening to all pregnant women (E.C. No.19-1/2006). Each woman signed informed consent for the combined screening.The concentrations of maternal serum free β-hCG and PAPP-A were determined by solid-phase, enzyme-labelled chemiluminiscent immunometric assay . Assays were performed on automated platform Immulite 1000. Median levels of free β-hCG and PAPP-A in unaffected pregnancies were calculated from weighted regression of observed medians for each gestational day. For that purpose, pregnancies achieved by the methods of assisted conception, twins, diabetic pregnant women and pregnancies with confirmed fetal aneuploidies were excluded from the database. The data fitted the exponential equation well; observed medians were close to those predicted from the model. Regressed medians were used to generate multiples of the median (MoM) for each case. MoM values of markers were corrected for maternal weight and smoking cigarettes and individual risks for trisomies 21, 18 and 13 for each of the pregnant women were calculated using the Prisca 4.0 software .To assess the accuracy of the analytical procedures, specimens of Siemens control modules LPCCM and LFBCM were run in a day-routine . To examine the within-run precision, 15 replicates of each control were analyzed sequentially. To evaluate the between-day precision, an aliquot of the same lot of control specimen was run along with daily routine measurements. In addition, an aliquot of pooled pregnant women sera was run with daily batch of unknown samples.The impact of variability of biochemical marker MoM values on the risk for trisomy 21 was assessed using the appropriate 15 paired concentrations of free β-hCG and PAPP-A in controls and in human pooled sera as well, in combination with a fixed clinical pattern  and the relevant risks were computed.® software and descriptive statistics using Excel 7.0, respectively. The normality of distributions of log10 MoMs of biochemical markers was ascertained using Kolgomorov-Smirnov test. Proportions of smokers and FPR in particular weeks were determined by χ2 test. The differences in maternal age and maternal weight, between particular weeks, were assessed by one-way ANOVA. The level of p < 0.05 was considered statistically significant.Statistical analyses were performed using MedCalcThe data concerning within-run and between-day analytical precision for the biochemical markers are presented in table To investigate a possible gestation-dependent biological variability of biochemical markers, the pregnant women were classified in 4 groups, according to gestational age at blood sampling. There were no significant differences between the sub-groups, regarding maternal age, maternal weight and the proportion of smokers table .10 MoM values fitted the Gaussian distribution, with overall standard deviation for free β-hCG of 0.2600, and 0.2307 for PAPP-A, respectively.The distribution of maternal serum free β-hCG and PAPP-A MoM values, according to gestational age, are presented in table 10 MoM values of free β-hCG between the 11th and 12th gestational week (p = 0.002). In addition, significant differences were scertained for log10 MoM PAPP-A between the 11th and 12th, as well as between 12th and 13th week of gestation . Post-hoc Student-Newman-Keuls test was used to assess the significance of the difference between subgroups.Table th week, 12.8% between weeks 11 and 11+6, 11.9% between weeks 12 and 12+6, and 9.9% between weeks 13 and 13+6, respectively. The differences in proportions were not statistically significant, neither for the risks concerning trisomy 21 nor for trisomies 18/13.In table 10 MoM values of both markers fits a Gaussian curve, with SDs comparable with the results of much greater series in the literature [Introducing the first-trimester screening for fetal trisomies in Croatian pregnant women has been the opportunity for the improvement of prenatal care in our country ,21. Prevterature . Our resterature . He estaterature . In lineterature . We haveFrom the point of clinical interest, the most important is the discriminatory power of both biochemical markers across the first-trimester. The impact of variability of free β-hCG and PAPP-A on their clinical sensitivity was clearly demonstrated in studies of Spencer and his co-workers ,27.χ2 test. The compliance of log10 MoM values with normal distributions, and insignificant changes of SDs of both markers in particular weeks did not show any significant oscillations of the values of free β-hCG and PAPP-A. When we compared log-transformed MoM values between weeks by ANOVA, statistically significant differences were found for free β-hCG MoM values between the first two weeks. On the other side, significant differences for PAPP-A MoM values were established between sub-groups in later weeks of the first trimester.To examine biological variations in normal pregnancies, we studied the variability of marker concentrations and their MoM values across the first trimester. The uniformity of sub-groups in particular weeks was proved by means of ANOVA and th week [Spencer and co-workers determined the optimal time for PAPP-A measurement between 8-10 weeks' gestation, while its detection efficiency gradually decreased from 10 to 13 weeks' gestation. On the other side, the discriminatory power of free β-hCG was the best after the 12th week . Our stuWe think that it is important to get better insight in possible physiological variations of the first-trimester biochemical markers in particular weeks and to study the degree of the oscillations of mean marker values between the constant ranges of respective standard deviations. Although the number of our pregnant women was not large enough to form representative sub-groups, we have clearly shown that the observed variations are not caused by inaccuracy of analytical procedures or by a bias produced by inappropriate median values of biochemical markers across the gestational range. Considering the prevailing standards for analytical laboratories, this is of value for correct interpretation of the results of biochemical markers, particularly concerning their specificity.10 MoM values for biochemical markers, across the first-trimester weeks in unaffected pregnancies. According to our results, it seems unlikely that the observed variations could be attributed either to inaccuracy of analytical procedures or to inappropriately settled curves of median values for the first-trimester biochemical markers. Improvement of the screening strategy implies, on one side, following the guidelines of the Fetal Medicine Foundation and, on the other, a better setting of the timing for the biochemical parameters, for it can contribute to a higher specificity of the screening.We have shown the gestation related variations of logThe authors declare that they have no competing interests. Patients' data relevant for this study were retrospectively extracted from the routine praxis and no other financial funds were employed.DTM has been the main co-ordinator of screening and conceived the study. IZ carried out analytical procedures and performed all statistical analyses. AMS participated in design of study and revised the manuscript. SSR and MK performed most of ultrasound examinations. ZBM helped in acquisition of data. All authors read and approved the final version of manuscript.