We compared linkage analysis results for an alcoholism trait, ALDX1 (DSM-III-R and Feigner criteria) using a nonparametric linkage analysis method, which takes into account allele sharing among several affected persons, for both microsatellite and single-nucleotide polymorphism (SNP) markers (Affymetrix and Illumina) in the Collaborative Study on the Genetics of Alcoholism (COGA) dataset provided to participants at the Genetic Analysis Workshop 14 (GAW14). The two sets of linkage results from the dense Affymetrix SNP markers and less densely spaced Illumina SNP markers are very similar. The linkage analysis results from microsatellite and SNP markers are generally similar, but the match is not perfect. Strong linkage peaks were found on chromosome 7 in three sets of linkage analyses using both SNP and microsatellite marker data. We also observed that for SNP markers, using the given genetic map and using the map by converting 1 megabase pair (1 Mb) to 1 centimorgan (cM), did not change the linkage results. We recommend the use of the 1 Mb-to-1 cM converted map in a first round of linkage analysis with SNP markers in which map integration is an issue. Using single-nucleotide polymorphisms (SNP) for linkage analysis is a relatively new strategy. With only two alleles, the homozygosity rate for SNP markers is high. Homozygous parents are not informative for linkage. SNP-based linkage analyses using a single SNP may not be as successful as linkage analyses using microsatellite markers. However, SNP-based linkage analyses may work better when several neighboring markers are combined together . These SNP combinations can be considered as one composite marker with more alleles . HoweverEven though on a single marker basis SNP markers are not as informative as microsatellite markers, technological advantages have pushed SNP-based linkage analysis forward and SNPs can now be used both for linkage and association studies. This advance is possible because SNPs are relatively inexpensive, have high-throughput production, and dense coverage of the genome. The Affymetrix 10 k chip ,4, for eComparisons between linkage analyses using SNPs and microsatellite markers have recently been reported in the literature . This woThe 143 families  were included in the pedigree data, though only roughly 1,300–1,400 people are genotyped with microsatellite markers, Affymetrix SNP, or Illumina SNP markers (the exact number of genotyped samples is given in the papers describing the data provided to GAW participants). The numbers of microsatellite markers, Illumina SNP markers, and Affymetrix SNP markers are 315 , 4,596 , and 10,805 . We used the same set of individuals for the microsatellite marker, Illumina SNP, and Affymetrix SNP genome scans.The phenotype we used was ALDX1, where affectation includes both DSM-III-R alcohol dependence and Feighner alcohol dependence. We coded an individual as affected if he or she was an alcoholic (ALDX1 = 5), as unaffected if they never drank or if they were unaffected with some symptoms , and as unknown if there was no information about their symptoms (ALDX1 = 0).MERLIN  is curreWe ran MERLIN twice on the microsatellite markers: once for single-point analysis and again for multipoint analyses. MERLIN was run twice for the Illumina SNP data also. The first time we used a genetic map that was converted from physical (base pair) position information (1 Mb is converted to 1 cM); and the second time we used the genetic map position provided by GAW14, but manually added an arbitrary small distance when two or more SNPs had the same position in centimorgans. MERLIN was run three times for the Affymetrix SNP data: 1) using the genetic map with the 1 Mb-to-1 cM conversion, 2) using the genetic map given by the GAW14, and 3) using the genetic map given by Affymetrix . We investigated the 1 Mb-to-1 cM map conversion because there may be other cases in which the genetic map information is not available. We were interested to see whether this simple method was successful with the COGA data.MERLIN (version 0.10.2) was run with 24 bits (a measure of the pedigree complexity), on a computer with 8 gigabytes of memory. Even with this upper memory limit, 9 pedigrees  were skipped by MERLIN. We used the same program, and the same individuals in the sample, for all analyses. As a result, the same exact set of 134 families  was analyzed in each case. Even with extended computer hardware and a moderately restricted sample, for an average size chromosome, the computing time was in excess of 2 to 3 hours for each SNP dataset. The total computing time for results included in this paper was in the range of 300 hours.10 curve with the p-value from the NPLall test is very similar to Figures 10 roughly equal to the maximum value of LOD plus 1 .Figures Figure Figure There are three sets of KC-LOD scores shown in Figure To compare linkage analyses from different types of markers, we plot the 3 sets of KC-LOD results for chromosome 7 in Figure This study addresses two questions: first, are the results consistent when comparing microsatellite marker and SNP-based linkage analyses? Second, for SNP-based linkage analysis, can the 1 Mb-to-1 cM genetic map be used when only the physical location is provided for the SNP markers instead of genetic map distance? The answer to the first question seems to be that the two linkage results match on a crude level, but do not match on a finer level. For all three sets of marker data, the highest linkage peaks appear in chromosome 7. This indicates that on the genome-wide level, microsatellite and SNP markers do lead to consistent results. On the other hand, for intermediate linkage peaks , three sets of marker data do not match. For example, a peak on chromosome 12 for Illumina and Affymetrix SNP data does not appear in the microsatellite data.One strategy to explain the discrepancy between the two sets of markers is to examine the information content. Evans et al.  simulateThe answer to the second question seems to be that we can indeed use the simple 1 Mb-to-1 cM rule to generate a genetic map for linkage analysis. Using the 1 Mb-to-1 cM conversion rule is equivalent to the assumption that the recombination rate was homogeneous along a chromosome, which is known to be unrealistic. The reason that this simplistic map is still able to reproduce the linkage result based on a more detailed genetic map is perhaps that the inter-marker distances are relatively short. If we consider Affymetrix's 10 k chip for example, as 10,000 SNP covers the whole human genome with 3000 Mb, the inter-marker distance is on average 300 kb, or roughly 0.3 cM. Even with a large variation in local recombination rate, the range of the absolute value of the inter-SNP distance is small. Our findings showed that the cM/Mb = 1 rule may prove to be a useful tool in situations when the genetic marker map is missing or incomplete.In conclusion, we have carried out genome-wide NPL multipoint analyses seven times using both microsatellite and Illumina or Affymetrix SNP markers, on the same pedigree data with identical affection status definition. The linkage signals obtained from the Illumina SNP data and Affymetrix SNP data are more similar than those obtained from the microsatellite markers. However, all three datasets point to chromosome 7 as having the strongest linkage signal. We also compare linkage analyses with SNP markers using the given genetic map and using the map derived from the simple rule of 1 Mb-to-1 cM. We showed that the linkage signals obtained from these two genetic maps are essentially the same.COGA: Collaborative Study on the Genetics of AlcoholismGAW14: Genetic Analysis Workshop 14KC-LOD: Kong-Cox LODNPL: Nonparametric linkageSNP: Single-nucleotide polymorphismsAU conducted the MERLIN runs on the microsatellite data, and WL conducted the MERLIN runs on SNP markers. Both authors read and approved the final manuscript.


A landmark randomised trial of male circumcision (MC) in Orange Farm, South Africa recently showed a large and significant reduction in risk of HIV infection, reporting MC effectiveness of 61% (95% CI: 34%–77%). Additionally, two further randomised trials of MC in Kisumu, Kenya and Rakai, Uganda were recently stopped early to report 53% and 48% effectiveness, respectively. Since MC may protect against both HIV and certain sexually transmitted infections (STI), which are themselves cofactors of HIV infection, an important question is the extent to which this estimated effectiveness against HIV is mediated by the protective effect of circumcision against STI. The answer lies in the trial data if the appropriate statistical analyses can be identified to estimate the separate efficacies against HIV and STI, which combine to determine overall effectiveness.Focusing on the MC trial in Kisumu, we used a stochastic prevention trial simulator (1) to determine whether statistical analyses can validly estimate efficacy, (2) to determine whether MC efficacy against STI alone can produce large effectiveness against HIV and (3) to estimate the fraction of all HIV infections prevented that are attributable to efficacy against STI when both efficacies combine.Valid estimation of separate efficacies against HIV and STI as well as MC effectiveness is feasible with available STI and HIV trial data, under Kisumu trial conditions. Under our parameter assumptions, high overall effectiveness of MC against HIV was observed only with a high MC efficacy against HIV and was not possible on the basis of MC efficacy against STI alone. The fraction of all HIV infections prevented which were attributable to MC efficacy against STI was small, except when efficacy of MC specifically against HIV was very low. In the three MC trials which reported between 48% and 61% effectiveness (combining STI and HIV efficacies), the fraction of HIV infections prevented in circumcised males which were attributable to STI was unlikely to be more than 10% to 20%.Estimation of efficacy, attributable fraction and effectiveness leads to improved understanding of trial results, gives trial results greater external validity and is essential to determine the broader public health impact of circumcision to men and women. The role of male circumcision (MC) in protecting against HIV infection in sub-Saharan Africa has been controversial since the beginning of the HIV epidemic. This is because evidence derived from observational studies is prone to bias due to confounding risk factors and because MC as a HIV prevention strategy can be seen as unethical -3. ThereThe role of male circumcision as a HIV prevention tool is now supported by a landmark randomised trial that showed a large and significant effectiveness against HIV  among a sample of adult men in Orange Farm, South Africa . RecentlThese questions can be answered if the appropriate statistical analyses can be identified. This involves estimation of the efficacies of MC against HIV and STI separately, as well as the usual estimation of overall effectiveness from randomised trials. These efficacy and effectiveness estimates can then be combined to deduce the fraction of HIV infections prevented by MC which are attributable to STI.In this paper we use a prevention trial simulator of circumcision, using data from the Kisumu MC trial, where HIV and STI both circulate (1) to demonstrate which statistical analyses validly estimate efficacy against HIV and STI; (2) to examine whether the efficacy of MC on STI alone can result in a large overall estimates of HIV effectiveness a in randomised trial when MC does not have a direct protective effect against HIV; and (3) to examine when both efficacies combine, what is the attributable fraction of all HIV infections prevented by efficacy against STI in a MC trial. The results of our modelling study will facilitate and improve interpretation of the results of the three MC trials. In turn, this will eventually lead to better understanding of the population-level effectiveness and cost-effectiveness of circumcision in settings with different STI and HIV epidemiology.F, estimates the total difference in HIV infection rates between trial arms. In a phase 3 trial, the estimated effectiveness will depend on several factors. These include the direct reduction in female-to-male HIV transmission probability due to circumcision, the direct reduction in female-to-male STI transmission, prevalence of STI in trial participants and their partners, and strength of the HIV-STI epidemiological interaction. Since STI prevalence can change with time in trial participants, effectiveness estimates can also depend on the duration of follow-up. Thus, effectiveness is an estimate of the aggregate effects of several factors whose interpretation is limited to the trial context in which it is estimated and is a time-dependent quantity. We use the term effectiveness in its clinical trial sense which is more limited than its epidemiological sense where it would represent impact of MC in a general population. In particular, the effectiveness estimated in a clinical trial says nothing about the herd effect of MC benefiting females.It is crucial to distinguish between efficacy and effectiveness as they are used in phase 3 HIV prevention trials. Effectiveness, denoted EH, represents the direct reduction in female-to-male HIV transmission probability due to circumcision, just one of the factors determining effectiveness. Similarly, efficacy against STI, denoted ES, represents the reduction in female-to-male STI transmission probability. Thus, efficacy gives a more 'canonical' description of the effect of circumcision which is independent of setting and time and has a biological interpretation which is more generalisable and simpler to interpret than effectiveness.Efficacy against HIV, denoted AF, as the proportion of all HIV infections prevented that are mediated by MC efficacy against STI. This quantity describes how much of the overall effectiveness of MC against HIV is due to the indirect effect mediated by MC efficacy against STI. The AF can be approximated using estimates of F and EH (see later).We also define attributable fraction, denoted Dynamic stochastic models simulating trial designs are well suited to study this type of question and have been used successfully in the past to evaluate the quality of epidemiological studies on the STI and HIV interaction and to validate statistical analyses for HIV vaccine trials -29. Our The model generates simulated trial data which are then analysed to estimate efficacy against HIV, STI and overall effectiveness against HIV. The efficacy estimates are valid when they agree with the true values embedded in the simulation.The base-case model parameter values were selected according to trial design parameters from the UNIM circumcision trial in Kisumu District of Kenya ,16, were-1 and loss to follow-up is 15%. Given these trial parameters, 63 infection events would be expected in the control arm of the trial. This implies a 70% probability (power) of declaring an efficacy better than zero when the true effectiveness is 40%, or 90% power when true effectiveness is 50%. HIV prevalence in Luo men at screening was 7.4% and HIV incidence is estimated at 2.5%. The Kenya Demographic and Health Survey (DHS) [The Kenyan circumcision study is an unblinded randomized controlled trial which began recruiting uncircumcised, HIV seronegative Luo men aged 18–24 years in February 2002. The Luo are a homogenous traditionally non-circumcising ethnic group in western Kenya. The primary objective is the determination of reduction in incidence of HIV infection, interpreted as effectiveness. Estimation of reduction in incidence of STI is a secondary objective. A total of 2784 participants are equally randomized to each arm of the trial and followed for 24 months. The estimated annual HIV infection rate in the control group is 2.5% yrey (DHS)  also repey (DHS) .Model parameters for sample size, follow-up duration and randomisation ratio were chosen according to the trial's design characteristics. The size of the population hosting the trial was assumed to be much larger than the sample size of the study. The sexual behaviour parameters  in the model were chosen to reproduce trial data and Kenyan DHS data on HIV prevalence, HIV incidence and STI prevalence. This parameter selection also ensured the simulated power, as determined by number of expected endpoints, were closely matched to the trial's actual power. Under base-case parameter values, the model's HIV prevalence in the general population averaged 18.0% over the time of the trial, HIV incidence rate in the simulated trials was 2.5% per year in control subjects, and STI prevalence in simulations averaged 8.2% in controls. Over the trial period HIV and STI prevalence remained unchanged. The simulated trials produced an average of 66 HIV infection events in the control arm.α1 = 4), while STI in the HIV-susceptible increases HIV transmission by a factor of 3 (α1 = 3). This compares with a review on the increased susceptibility to HIV due to STIs [Remaining parameters for HIV and STI transmission probabilities, duration of the different HIV states and duration of STI infection were estimated based on other published studies. In particular, the strength of interaction modelled between HIV and STI under base-case assumptions is assumed to be medium; presence of STI in the HIV-infected sexual partner increases the per partnership probability of HIV transmission by a factor of 4  with robust variance estimates is the most suitable method for estimation of EH [ES. Estimation of F is based on comparison of HIV infection times between control and treated arms without stratification for STI infection. The proportion of HIV infections prevented which are attributable to MC efficacy against STI is approximated by We denote estimated values of on of EH ,32. The sion 8.1 .EH, modelled as a reduction in susceptibility upon exposure varied between 0% and 70%. Similarly, values for ES between 0% to 80% were explored. Low ES (~0–20%) reflects the efficacy of MC on Chlamydia and HSV while high ES (~60–80%) reflects efficacy against chancroid and syphilis [EH and ES were simulated 100 times and analysed individually, giving 4000 simulated trials under base-case parameter values. The first objective was addressed by comparing the estimated H against the true value for EH embedded in the 4,000 simulated trials. The second objective was addressed by examining the 5 scenarios where true EH = 0%. The third objective was addressed by the examining attributable fraction AF in the 4,000 simulated trials.Values for α1 = 6, α2 = 6) and a weaker HIV-STI interaction . Bivariate sensitivity analyses were additionally performed by varying the above parameters with compensating changes in HIV transmission probabilities in order to maintain annual HIV incidence in the trial constant at 2.5%, thus maintaining the power of the simulated study at a realistic level.Further simulations to test the robustness of our conclusions were performed by univariate and bivariate sensitivity analyses . Table H where true EH varies from 0–70% and true ES varies from 0–80%. The estimates of EH reflect the true value embedded in each simulation, given that the median H estimate over 100 simulations falls within ± 2.9% of the true value in all scenarios. Furthermore the H estimates and their confidence limits were unchanged by efficacy against STI (reading down columns), contrary to the corresponding effectiveness estimates In order to understand the relative importance of STIs in the prevention of HIV infections in phase 3 circumcision trials, we must be sure that the efficacy estimator of H and H and S estimates  increases. For example, when true ES = 40% the predicted trial effectiveness is around 6% . In these simulations, the effectiveness is due entirely to the indirect protection against HIV achieved by MC efficacy against STI, but this can be ascertained only by observing the H and S estimates, which reflect their true values of EH and ES (e.g. H = -0.4% and S = 78.8%). These results suggest that, under our parameter assumptions, even if MC has a very high efficacy against STI, it is unlikely to produce a large overall HIV effectiveness if circumcision does not also protect against HIV.When MC efficacy against HIV is zero  and increasing the follow-up period to five years. This resulted in STI prevalence of 0.7% at five years in circumcised men and an estimated To further explore why STIs play a small role in preventing HIV infection, we approximate the fraction of all HIV infections attributable to the STI in the trial. We do this by 'removing' the HIV-STI interaction effect in circumcised men by simulating perfect efficacy against STI and zero efficacy against HIV , the interpretation of effectiveness becomes more complex. Different combinations of true EH and true ES can produce similar EH = 40% and ES = 0–20% or EH = 30% and ES = 60–80%  while S reflected true ES (S = -0.8 and 79.3%). The validity of the efficacy estimates make apparent when the majority of HIV infections averted in the circumcised arm of the trial were due to protection against STI, and this can be quantified in the AF.We also note that the greater the true H and EH and ES and under base-case parameter assumptions. The lightest purple region indicates when EH must be below 20% for a substantial proportion of HIV infections to be prevented via STI. For example, if efficacy against HIV and STI are 10% and 80%, respectively, then about 60% of HIV infections would be prevented in the circumcised arm due to MC efficacy against STI. The EH increases. If EH is above 40%, then at most 21% of HIV cases prevented in the circumcised arm could be expected to be due to STI, even if true ES is as high as 100%. Figure EH and ES in a two year MC trial. The lightest gold region shows when total effectiveness will be 0–10%, while the darkest indicates when EH = 15%, EH = 60% and true ES = 60%, then Figure Figure AF, but this change was only moderate. For example, when true EH = 50% and ES = 80%, the Simulations performed for sensitivity analyses showed that conditions which increase STI prevalence or the strength of STI cofactor effect increase, predictably, the EH was very small (between 0 to 20%). Under scenarios of lessened importance of STI, H estimates generally did not differ by more than 3%. Closeness of H and ES or to weak STI-HIV interaction.Under conditions which lessen the importance of STI , the EH ~ 0–20%). A corollary is if a MC trial demonstrates a moderate to high effectiveness  can produce equivalent effectiveness estimates in a trial context but not equivalent impact in a general population. Second, effectiveness estimated in a randomised trial does not correspond exactly to epidemiological effectiveness. In particular, the herd effect of MC benefiting females cannot be captured by trial estimates. By separately estimating EH and ES, transmission dynamic models can project better the potential epidemiological impact of MC. Further simulations with our model illustrated this point. For example, if MC had 40% efficacy against HIV and reached 75% of males in Kisumu, then after 10 years a 23% decline in HIV prevalence is possible in men compared to 7% in women, assuming MC does not protect against STI. However, if MC is also efficacious against STI, these declines in HIV prevalence are 29% for males and 14% in females, indicating the incremental benefit of STI efficacy is larger for women than men. This is essentially due to the fact that MC efficacy impact on male STI prevalence more rapidly than on HIV prevalence, and women's exposure to STI is consequently reduced quickly. Such insights would not be possible with effectiveness estimates alone. Thus, in terms of evaluating the public health potential of MC for both men and women, it will be essential to accurately estimate both EH and ES, even if high HIV effectiveness is observed.Public health decision makers are unlikely to be interested in circumcision if effectiveness is low (< ~ 30%). On the basis of our findings, the usefulness of circumcision against HIV when effectiveness is high (> ~ 50%) may not be questioned since a small fraction of prevented HIV infections will be expected to be due to the indirect effect of circumcision against STI. It could be argued that separate estimates of efficacy against HIV and STI are most essential when effectiveness is moderate (~30%–50%), as public health decisions would have to give greater consideration to the role of STI in the prevention of HIV with MC. However, we argue that efficacy estimation of MC against STI and HIV is important in all cases because effectiveness estimates do not give the full picture for the longer-term community-level impact of MC. This is for two reasons. First, different combinations of efficacies . At one extreme, analyses could define STI-positive person-time on the basis of infection with any of the above and STI-negative person-time on basis of no STI infection of any type. At the other extreme, one could attempt to control individually for each of the different STIs in the statistical analyses, but how well this may work needs to be validated. If feasible, this would offer even greater value to the phase 3 trial by indicating the specific categories of STIs against which circumcision is beneficial.F – effectiveness of male circumcisionFEH – efficacy of male circumcision against HIVH – estimate of EHES – efficacy of male circumcision against STIS – estimate of ESAF – attributable fraction (fraction of HIV infections prevented due to MC efficacy against HIV)HIV – human immunodeficiency virusMC – male circumcisionSTI – sexually transmitted infectionThe author(s) declare they have no competing interestst). HIV susceptibles are labelled with the superscript h = 1, full blown AIDS patients with h = 5, and HIV infecteds in three stages of HIV infection (having different degrees of infectiousness) with h = 2,3,4. Individuals infected with STI are denoted by s = 1 and those not infected with STI by s = 0. The sexually active population is stratified by sex  and by sexual activity class defined by the rate of sexual partner acquisition. Six activity classes are defined  where at one extreme are individuals of low sexual activity  and at the other are high activity individuals . Transition events between states occur by infection, progression to disease, departure from the sexually active population or immigration into the population. Given a stratification of two sexes and six sexual activity classes, 336 possible events can occur (2 sexes × 6 classes × 28 possible events) in the absence a clinical trial, as defined in Figure The model consists of ten disease states  representing five different stages of HIV infection and two states of STI infection . The number circumcised at time t of disease state h, state i, sex k and activity class i is given by t). The number of possible events after the trial begins is 984 (2 sexes × 6 activity classes × 82 events), as given in Table Upon commencement of the clinical trial in the defined population, a sample of individuals is randomized between control and treated arms. As defined in Figure S-1(t). The time of occurrence s of chosen event r can be determined by choosing a random number from a uniform distribution and setting it equal to F(s) in the equation F(s) = 1-exp(-S(t)s) and solving for s. Thus by an iterative process, a sequence of events and their time of occurrence is generated. With each new event all rates including forces of infection are automatically updated.In the stochastic simulations, a random sequence of individual events is generated where each of the 984 possible events occurs with probability t) and t)) and STI infection (t) and t)). The effect of treatment is assumed to reduce these forces of infection by an amount EffHIV and EffSTI, respectively. The force of HIV infection for sex k and activity class i at time t in the general population and controls is given by:Key event flows in the model include force of HIV infection  is the annual rate of partner acquisition of persons of sex k and class i, and φk,i,j(t) describes the mixing matrix elements. This is essentially the probability that an individual of sex k and class i chooses a partner of opposite sex k* and class j  is the total sexually active population of sex k* and class j. The term a1 is a multiplicative factor increasing the probability of transmission of HIV when the HIV infected partner is also infected with STI. Thus, t) is a function of the rate of sexual partner change, the HIV transmission probability, HIV prevalence and epidemiological interaction between HIV and STI.Here mai et al  for moret) = a2t), where a2 is a multiplicative factor increasing the probability of transmission of HIV when the HIV susceptible is infected with STI. Values for the above parameters used in the simulations are given in Table The force of HIV infection in an STI infected individual is t) = (1 - EH)t) and t) = (1 - EH)t), where EH is the reduction in susceptibility to HIV due to circumcision.The force of HIV infection for the circumcised group is given by The force of STI infection in HIV susceptibles of sex k and class i is given by:ξk*,j,i is the per partnership transmission probability of STI from sex k* and sexual activity class j to opposite sex k and class i. Unlike for HIV transmission probabilities, the values for STI transmission probabilities do not change by sexual activity class. We have chosen these values because STI transmission probabilities for bacterial STIs are high and are less affected by number of sex acts within a partnership. In addition, we are not trying to represent the exact biology of a given STI, and the STI needs to reflect a number of different aetiologies. The parameter b1 is a multiplicative factor increasing the probability of STI transmission when the STI-positive partner is also HIV positive. In our model we set b1 = b2 = 1.Here t) = b2t), where b2 is a multiplicative factor increasing the probability of STI transmission when the STI susceptible individual is HIV positive. The force of STI infection for the circumcised group is given by t) = (1 - ES)t) and t) = (1 - ES)t), where ES is the reduction in susceptibility to STI due to circumcision.The force of STI infection in a HIV positive individual of sex k and class i is given by KD and MCB contributed to the elaboration of the research objectives, development of the mathematical model, computer simulations, statistical analysis of simulated trial data, and manuscript preparation. GPG contributed to the elaboration of the research objectives and manuscript preparation. BRM contributed to the elaboration of the research objectives, statistical analyses of simulated trial data, and manuscript preparation. SM and RCB are co-principal investigators of the UNIM male circumcision study in Kisumu Kenya. They contributed to the elaboration of research objectives, design of the UNIM MC study, statistical analysis of field data to inform the mathematical model, and manuscript preparation. All authors read and approved the final manuscript.


PARK2 gene. Deletions and duplications of single exons or exon groups account for a large proportion of the gene mutations. Direct detection of these mutations can be used for the diagnosis of Parkinson's disease.One of the causes of Parkinson's disease is mutations in the PARK2 gene exons by comparing the intensity of the amplification signals from some exon of this gene with that of the β-globin gene .To detect these mutations, we developed an effective technique based on the real-time TaqMan PCR system, which allows us to evaluate the copynumbers of the PARK2 gene in 64 patients from Russia with early-onset Parkinson's disease. The frequency of these mutations in our patients was 14%.We analyzed rearrangements in exons 1–12 of the PARK2 gene. It is suitable for the analysis of large patient groups, and it may become the basis for a diagnostic test.We have developed a simple, accurate, and reproducible method applicable to the rapid detection of exon rearrangements in the  PARK2, which encodes parkin  - [ΔCt β-globin (patient sample) - ΔCt PARK2 (patient sample)]. All positive results were confirmed at least twice, and the average ratio was calculated. All samples with homozygous or heterozygous exon rearrangements affecting only one exon were confirmed with an independent set of primers to avoid any false positive results caused by primer mismatch associated with undetected polymorphisms.where ΔΔCt = [ΔCt PARK2 exon dosage. With this method, it is possible to analyze the deletions and duplications of exons 1–12.We performed relative quantitative real-time PCR amplification based on TaqMan technology to analyze PARK2 exon deletions have been identified in some of them [Exon dosage analysis was performed for nine genomic DNA samples from patients with autosomal recessive juvenile PD. These patients have been described elsewhere, and heterozygous  of them .PARK2 to the β-globin gene concentration was calculated for all DNA samples . Homozygous deletions were found in two: patients 2 (exon 4) and 5 (exon 3). Heterozygous deletion of a single exon was found in one patient (exon 3 in patient 6) and of several exons in four patients . We also studied 64 Russian patients with EOPD and found exon rearrangements in nine of them using this method. Our method is suitable for the rapid detection and screening of exon rearrangements in the parkin gene. However, for heterozygous contiguous deletions of neighboring exons, it cannot distinguish between a large contiguous deletion on a single chromosome and a combination of two deletions on both chromosomes. This method is not applicable to the detection of point mutations or small sequence changes.Here, we describe a cost-effective technique for the rapid and accurate detection of exon rearrangements in the PARK2 using different approaches [PARK2 gene exon dosage and the method described here are based on real-time PCR, which provides a precise measurement of the cycle threshold [PARK2 and the β-globin gene) are necessary for each DNA sample. However, application of the LightCycler  or TaqMan system allows us to carry out only one multiplex amplification reaction for each DNA sample [To date, several studies have addressed the question of exon dosage in proaches ,8,20-22.proaches  performeA sample ,22. ThisBoth the TaqMan and the LightCycler systems allow the application of quantitative real-time PCR assays by using labeled oligonucleotide probes, which generate sequence-specific signals. In the TaqMan system, only one probe is used for each locus, whereas in the LightCycler system, two hybridization probes are necessary, so it is more complicated.Two other groups have measured exon dosage based on TaqMan technology ,22. MaruAll these methods are based on different types of real-time PCR. Recently, a new approach has been described, called multiplex ligation-dependent probe amplification (MLPA). MLPA is based on the combination of a ligation reaction and standard PCR followed by electrophoresis. It has been shown that this method is also applicable to exon dosage analysis . HoweverPARK2 gene in patients with PD. It analyzes all relevant deletions and duplications of exons 1–12. The determination of the TaqMan-based cycle threshold is more precise than earlier methods based on SYBR Green I labeling. A very precise measurement of exon dosage is possible using a second-derivative value of the real-time fluorescence intensity curve. This method is applicable to the analysis of large patient groups and may become the basis for a diagnostic test.This TaqMan real-time PCR methodology can be applied to the rapid and precise screening of exon rearrangements in the PD: Parkinson's diseaseEOPD: early-onset Parkinson's diseasePCR: polymerase chain reactionCT: cycle thresholdSD: standard deviationThe author(s) declare that they have no competing interests.MIS and EVS designed and executed all the experiments. MIS and EVS analyzed the data and wrote the paper. GHB, SNI and III-S participated in the acquisition of data and helped draft the manuscript. PAS and SAL were involved in study design and helped draft the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Clustering analysis of microarray data is often criticized for giving ambiguous results because of sensitivity to data perturbation or clustering techniques used. In this paper, we describe a new method based on principal component analysis and ensemble consensus clustering that avoids these problems.We illustrate the method on a public microarray dataset from 36 breast cancer patients of whom 31 were diagnosed with at least two of three pathological stages of disease , ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC). Our method identifies an optimum set of genes and divides the samples into stable clusters which correlate with clinical classification into Luminal, Basal-like and Her2+ subtypes. Our analysis reveals a hierarchical portrait of breast cancer progression and identifies genes and pathways for each stage, grade and subtype. An intriguing observation is that the disease phenotype is distinguishable in ADH and progresses along distinct pathways for each subtype. The genetic signature for disease heterogeneity across subtypes is greater than the heterogeneity of progression from DCIS to IDC within a subtype, suggesting that the disease subtypes have distinct progression pathways.Our method identifies six disease subtype and one normal clusters. The first split separates the normal samples from the cancer samples. Next, the cancer cluster splits into low grade  and high grade  while the normal cluster is unchanged. Further, the low grade cluster splits into two subclusters and the high grade cluster into four. The final six disease clusters are mapped into one Luminal A, three Luminal B, one Basal-like and one Her2+.We confirm that the cancer phenotype can be identified in early stage because the genes altered in this stage progressively alter further as the disease progresses through DCIS into IDC. We identify six subtypes of disease which have distinct genetic signatures and remain separated in the clustering hierarchy. Our findings suggest that the heterogeneity of disease across subtypes is higher than the heterogeneity of the disease progression within a subtype, indicating that the subtypes are in fact distinct diseases. One out of ten women who reaches the age of ninety will have had breast cancer in her lifetime. Most tumors are treated with a combination of surgery, radiation therapy, and adjuvant systemic therapy . 60–80% of tumors express the estrogen receptor ER and respond to treatment with hormonal agents such as aromatase inhibitors or Tamoxifen ,2. 20–40k-clustering technique, which averages over several clustering methods and many data perturbations, to identify strong, stable clusters. We also define a simple criterion to find the optimum number of clusters and a method to identify robust markers for disease progression within each cluster.Microarrays have the potential to shed light on this picture because of their ability to provide a snapshot of the genetic state of the cell. In principal, they should be able to identify the genes and pathways altered in cancer initiation, progression and metastasis. This promise has resulted in microarray technology being aggressively pursued by researchers, hospitals and pharmaceutical companies to get an improved understanding of the disease process, better diagnostic protocols, new drugs, and new treatment regimens. However, the success of these efforts has been limited by practical considerations. The biggest limitation is that the results from microarray studies are sensitive to noise and analysis method . This ofductal carcinoma in-situ to IDC or invasive ductal carcinoma. The clusters paint a portrait of the disease at varying levels of granularity. When the data is divided into two clusters, the normal samples form one cluster and the disease samples form another. At the next level of clustering, the low grade and high grade samples separate. The optimal number of clusters is seven, corresponding to two sub-clusters (LG1 and LG2) of the low grade samples and four (HG1-HG4) of the high grade samples. These sub-clusters are well separated by a strong set of markers which are able to distinguish them with sensitivity and specificity in the 80–100% range. We identify the genes and pathways that mark disease progression in each sub-cluster. A major result of our analysis is that each sub-cluster contains samples from non-invasive and invasive tumors from the same patient. This suggests that within each grade of breast cancer, different groups of patients progress to the same final phenotype along different pathways. This result suggests that the sub-clusters identified here are distinct diseases. If validated on larger datasets with larger gene-sets, it would have significant implications for disease identification and treatment.Applied to a breast cancer microarray data set, our method results in stable lists of genes and pathways that distinguish high and low grade tumors. It also identifies other robust gene sets which mark progression of disease from DCIS or Using the genes specific to each cluster and ER, PR, Her2+ levels in the data, we can place the clusters into the standard categories used to classify breast cancer as defined in . We findin situ or DCIS and invasive ductal carcinoma or IDC respectively. The remaining 5 patients were diagnosed to have pre-invasive disease (ADH) only. Microarray analysis was also done for samples collected from normal breast epithelial tissue extracted from three healthy women during routine mammoplasty. From the cancer patients, normal as well as disease samples were collected from as many different stages of disease  as possible. These samples were harvested in triplicate using laser capture micro-dissection , taking care to avoid contamination between cells of different stages from the same patient. Each sample was analyzed in duplicate with a 12,000 gene cDNA microarray. It was determined that the "normal cells" from cancer patients were highly similar to the normal epithelium of the three disease free patients. This suggested that the normal samples from cancer patients could be used as a baseline to determine disease state and progression.The data was obtained from  and consThe data provided in  consistekopt in the data was estimated using gap statistics [kopt clusters.The flow chart of our analysis method is presented in Figure atistics  and silhatistics . Next a kmax = 7. This range is compared to the optimum number of clusters provided by the EM mixture modeling approach. . We thek, we integrate the clustering results across clustering methods and perturbations into an agreement matrix. To obtain a global optimum clustering solution, we apply simulated annealing to the agreement matrix at each k to sort the samples into the best k clusters, which appear as blocks along the diagonal in the sorted agreement matrix. The agreement matrix cost function used in simulated annealing optimizes between the similarity inside the clusters and the dissimilarity between different clusters for each k. Once the data is clustered by simulated annealing into k pieces, we compute the silhouette scores for these k clusters  using the fpc package from R.For each k = kopt clusters beyond which the "quality" of the clusters obtained from the agreement matrix begins to deteriorate. This is assessed by analyzing the accuracy of cluster membership assignments using weighted voting and kNN on single and multiple gene markers (patterns) which distinguish the clusters. We stop clustering when the accuracy of such an assignment falls below 75%.We stop at PCA showed that 50% of the variation in the data was represented by the first 5 PCs and 85% by the first 32 PCs. We identified 207 genes as those with highest absolute value (top 1st quartile) in the coefficients of the first 32 eigenvectors as representative of most of the data variation. These thresholds were estimated through a calibration step whose aim was to optimize the overall cluster membership assignment for the optimal number of clusters identified in the data restricted to the selected genes.k = 7 as the optimal value for the number of clusters in the data. The data was divided into k = 2, 3,...,7 clusters by using the 207 genes identified by PCA and by applying Consensus Ensemble k-clustering (see the Methods section below).Gap statistic and the silhouette scores ,12 estimk = 2, the samples separated into a "normal" (N) group, which contained all the normal samples and one ADH sample (from patient id 210), and a "breast cancer" (BCA) group, which contained all the remaining breast cancer samples. At k = 3, the normal group was unaltered but the BCA group split into a low grade (LG) tumor group containing 18 samples labeled grade 1 and 9 samples labeled grade 2, and a high grade (HG) tumor group containing 13 samples labeled grade 2 and 19 samples labeled grade 3. As k increased progressively from 4 through 7, the LG group split into 2 distinct subgroups  classification models. The models trained on these 10 markers produced only 1 false positive error (DCIS #79) and 1 false negative error (DCIS #183) in leave-one-out experiments.Using a non-stringent Signal-to-Noise-Ratio (SNR) test  we found 223 gene markers which distinguish the group LG from HG. A subset of 10 markers was selected based on their performance on leave-one-out cross-validation experiments for weighted voting (WV) and Using the SNR test and leave-one-out experiments for the WV and kNN models, we identified 10 markers which distinguish the LG samples from all others (HG and N) with 90% accuracy. We find that RBSK, Homo sapiens cDNA FLJ12924 fis, clone NT2RP2004709 and CRIP1 are up-regulated in the LG group, and EYA2, ANXA1, RUNX3, DKFZp762A227, GPRC5B are down-regulated in the LG group.For the high grade cluster, the classification accuracy was 97% with 3 false positive and zero false negative errors. The top markers up-regulated in HG are TRAM, HSPC150, TACC3, CDKN3, UBE2C, and top markers down-regulated in HG are X123, GNG7, SH3BGRL2, LOH11CR2A and Homo sapiens, clone IMAGE:3917549 mRNA, partial cds.Table As seen in Table The HG3 markers, include a group of down-regulated genes in chromosomal region 17q23-25 which harbors the ERBB2 amplicon 17q 22.24. These genes are KPNA2 (17q23.1-q23.3), amplified in breast cancer 1 , Bcl-2 inhibitor of transcription , hypothetical protein TANC2 (17q23.3), and two proteosome protein PSMC5 (17q23-Q25) and PSMD12 (17q24.2). This suggests the possibility that patients in the HG3 subgroup might have a re-arrangement or deletion of genes around the Her2 gene leading to loss of regulation or function for these genes which might explain why only 15% of HG3 patients are Her2+, while 53% are Her2- and 15% are undetermined. Since IHC data for the ERBB2 gene was not made available in , the dowThe most notable HG4 marker was a down-regulation in the transforming growth factor beta receptor II (TGFBR2). Mutations in this gene have been associated with the development of various types of tumors. The over-expression of this gene was found to be associated with poor prognosis breast tumors. Overall, gene markers and clinical parameters lead to the conclusion that among the high grade subgroups HG4 is probably the best prognosis group composed of Grade II tumors that are all ER+ and PR+.Based on these observations, we identify HG1 as Basal-like ,6, HG2 aFigure Figures k-clustering. Hierarchical clustering by itself would separate the samples into clusters but the stratification would be very sensitive to bootstrap, indicating that the clusters are unstable to data perturbation. Robustness of clustering is only obtained by averaging over many clustering techniques and data perturbations as is done in the ensemble consensus clustering technique used here.The use of ensemble consensus clustering is absolutely critical to distinguish the subtypes. PCA by itself could identify a collection of useful markers, but could not identify the rich stratification discovered by consensus ensemble Our results show that progression of the disease from non-invasive to invasive status occurs along different pathways. Progression in the low-grade groups seems to correlate with changes in metabolic and transportation pathways, while in the high grade groups it is related to alterations in cell-cycle and signaling pathways, with distinct subsets of genes involved in each.Table k = 2,3,...7 clusters  have a strongly Luminal signature ; one subtype (HG1) had the triple negative  characteristic of the Basal-like subtype, and one subtype (HG2) had a predominantly Her2+ signature . The validation of these subtypes on a larger dataset with more genes is currently underway.k = 7, each of the six BCA clusters always contained samples in both DCIS and IDC stages from the same patient. This strong heterogeneity in the genetic signature of subtypes suggests that breast cancer is composed of distinct disease subtypes that develop early and progress along different pathways because progression within a subtype is less distinct than the subtypes themselves. Treatment decisions may benefit by taking account of these subtypes in addition to the current practice of using the markers ER, PR and Her2.At k = 2, 3,..., kopt clusters which were made insensitive to data and clustering method perturbation using consensus ensemble clustering (see below). To maintain sensitivity to subtle genetic signals, we used the full set of genes on the samples after each k level clustering to find the best pool of genes that distinguished a cluster from other clusters. This non-stringent selection was motivated by the expectation that the key genes altered in disease pathways are likely to have subtle alterations in their expression levels and may not necessarily be the same genes that are best to distinguish the clusters. On this larger set of genes for each k, we identified two sub-classes. The first set distinguished each cluster from its complement. The second set defined progression from non-invasive to invasive disease. Finally, we used annotated databases to identify the functional pathways that are most representative of the clusters identified. Each of these steps is described in detail below.Consensus ensemble clustering ,19 was akNN approach [The genes were normalized by first applying a robust nonlinear local regression method as described in  and thenapproach .Eij whose the rows were the 93 samples and whose columns were the 1927 genes that survived after robust imputation of missing data. The analysis was done by a singular value decomposition of this matrix after it was centered and scaled to mean 0 and variance 1 per column. From the eigenvectors of the largest eigenvalues that accounted for 85% of the variation in the data we selected the subset of genes with coefficients in the top 25% in absolute value in these eigenvectors. This collection of genes was further used to find robust clusters in the data.Principal Component Analysis or PCA ,21,22 wak-clustering approach  a method which generates a collection of clustering solutions using different methods applied to many perturbations of the data, and (2) a consensus function that combines the clusters found to produce a single output clustering of the data. The approach used in our paper is summarized below.Step 1. 150 datasets were created from the imputed data restricted to the 207 significant genes identified by PCA. 50 datasets came from bootstrapping the samples, 50 from bootstrapping genes and 50 by first projecting the data on bootstrapped genes and then by further bootstrapping on samples.Step 2. The optimal number of clusters koptwas inferred (a priori) using the gap statistic and silhouette scores.Step 3. k = 2,..., kopt clusters were created using representative methods from the three major classes:Partitioning: partition around medoids (PAM) [k-means [(i) ds (PAM) , k-means[k-means  and grap[k-means .(ii) Agglomerative: hierarchical clustering based on average linkage, complete linkage and Ward metric [d metric  as well d metric .(iii) Probabilistic: expectation maximization (EM) method [) method , entropy) method , cluster) method .Step 4. Each clustering method was applied 50 times with different parameter initialization on the full dataset, and once on each of the 150 datasets from Step 1. From the 200 resulting clusters, we constructed an agreement matrix of size Nsample × Nsample for each method, whose entries mij represented the fraction of times a pair of samples  occurred in the same cluster out of the number of times the pair was selected in the 200 datasets. Here Nsample denotes the number of samples in the dataset.Step 5. For each k, the agreement results of Step 4 were averaged across the clustering techniques. The samples were then sorted such that those with the highest pairwise agreement appeared along the diagonal of the agreement matrix in k blocks. We applied simulated annealing to find the k optimal clusters for which the average internal similarity (within each cluster) minus the average pairwise similarity  has a local maximum value.k by consensus ensemble clustering. The markers were chosen to discriminate between two classes: class 1 = the group of interest , class 0 = the samples not included in the group of interest . The best markers were identified in two steps.We now used the full collection of genes on each of the clusters identified at each Step 1. A large pool of genes which distinguished the two labeled classes was selected based on a variant of the t-test statistic called the signal to noise ratio (SNR) [0 - μ1)/(σ0 + σ1), where μ0 is the mean of class 0 and σ0 is the standard deviation of class 0 and so on. The t-test statistic is the same as the SNR except that the denominator is (σ02 + σ12)1/2. Since (σ0 + σ1) > (σ02 + σ12)1/2) SNR penalizes features that have higher variance in each class more than those features that have a high variance in one class and a low variance in another. This bias is particularly useful in distinguishing genes which are altered in normal/disease or stage/grade progression. For example, in the normal/disease case, the pathway in which the gene is involved is working correctly in one class, and hence is regulated strictly (has low variance) while in the other class, the pathway is compromised and the gene is less well regulated (has high variation).io (SNR)  with a pio (SNR)  of 0.5. Step 2. From the larger pool of genes from Step 1, we identified the best genes correlated with the class label using stringent criteria which combined (a) a permutation p-value of 0.05 (b) stability to sample perturbation through bootstrapping (c) stability to leave-one-out experiments in top 25% genes selected by weighted voting and kNN classifiers which distinguish the two classes with specificity and sensitivity above 0.75. This analysis was done using the software GenePattern from the Broad Institute [nstitute .We used the bioinformatics public resources DAVID , iHOP 3, and MatThe Kappa statistic can be thought of as the chance-corrected proportional agreement, and possible values range from +1 (perfect agreement) to 0 (no agreement above chance) to -1 (complete disagreement). The algorithm first generates a gene-to-gene similarity matrix  based on shared functional annotation. The matrix is made from binary entries. If a gene is annotated in a term, the term entry is 1, if not then the entry is 0. The algorithm adopts the kappa statistic to quantitatively measure the degree to which genes share similar annotation terms. The higher the value of κ, the stronger the agreement. The Fuzzy Heuristic Partition algorithm , which aAn important question is whether the gene lists found for the subtypes identified in -7 and elGSD and CD acquired the data; GSD, SG and CD provided the biological interpretation of the results. GSD and DS provided the annotations for the gene markers identified in the study. GA and GB designed the computational approach. GA performed the computational analysis. GB wrote the manuscript. GB, SG and CD supervised the research group. PT and JM worked on the GSEA and consensus clustering analysis. We thank Dr. Stefano Monti for discussions about estimating the number of clusters.Supplementary Table 1. A listing of the samples used in our study. Clinical stage and grade are as provided in the data of Ma et al (PNAS 2003). The column "Subtype" presents our classification into Normals and six disease subtypes  based on PCA and Clustering. The remaining columns list clinical information as provided in the data from Ma et al (PNAS 2003).Click here for file


The general concept of those tests is to mimic in vitro the contact between allergens and circulating basophils. The first approach to basophil functional responses was the histamine release test but this has remained controversial due to insufficient sensitivity and specificity. During recent years an increasing number of studies have demonstrated that flow cytometry is a reliable tool for monitoring basophil activation upon allergen challenge by detecting surface expression of degranulation/activation markers (CD63 or CD203c). This article reviews the recent improvements to the basophil activation test made possible by flow cytometry, focusing on the use of anti-CRTH2/DP2 antibodies for basophil recognition. On the basis of a new triple staining protocol, the basophil activation test has become a standardized tool for in vitro diagnosis of immediate allergy. It is also suitable for pharmacological studies on non-purified human basophils. Multicenter studies are now required for its clinical assessment in large patient populations and to define the cut-off values for clinical decision-making.The diagnosis of immediate allergy is mainly based upon an evocative clinical history, positive skin tests (gold standard) and, if available, detection of specific IgE. In some complicated cases, functional  The general concept of those tests is to mimic in vitro the contact between allergens and the cells responsible for symptoms . Until recently, basophils were neglected and only considered to be circulating forms of mast cells of minor importance. Furthermore, basophils represent in peripheral blood less than 0.5 percent of total leukocytes, making their purification difficult in clinical laboratories. This lack of satisfactory in vitro protocols has clearly hampered research on basophils for many years [in vitro tests for allergic reactions are focused on circulating basophils. The first approach to basophil functional studies was the histamine release test. However, its clinical benefit has remained controversial due to insufficient sensitivity and specificity [Anaphylaxis consists of an immediate IgE-dependent reaction in response to allergens. Clinical symptoms are caused by an initial systemic histamine release by mast cells and basophils that may lead to shock with laryngeal edema, lower-airway obstruction and hypotension. The most frequent allergens involved in immediate allergy are found in peanuts, fish, bee and wasp venoms, drugs and latex ,2. The iny years . Neverthny years . Consequcificity ,9,10. Thcificity -13.i.e., whole blood and vehicle without allergen). Results were considered positive when at least 2 sequential allergen dilutions induced greater than than 10% increases in CD63-positive basophils above control values. This kind of protocol has been validated for common allergens by several groups and has shown convincing results [As flow cytometry is a valuable tool for the analysis of many different cell types and can be used to identify specific populations of cells, even when present in low numbers, it seemed to be suitable for the study of allergen-induced basophil degranulation. Identification of cells was initially based both on CD45 expression, a common leukocyte antigen, and on the presence of IgE on the cell surface, since basophils express the high affinity receptor for IgE (FcεRI) ,14. In t results -24. The  results . This co results -21, this results ,25,26. I results ,25,26. CCD203c corresponds to a surface antigen expressed on human basophils recently recognized by the monoclonal antibody 97A6 . This an2 has been proposed and validated as the most reliable tool for the detection of circulating human Th2 cells [2 since it corresponds to the second receptor of prostaglandin D2 [Dermatophagoïdes pteronyssinus (d1), had a suggestive clinical history, positive skin test and/or specific IgE ≥ class III. Healthy donors, from our laboratory, were not known to be allergic and presented total IgE < 100 kU/L. In terms of clinical interpretation, sensitivity and specificity were 88% and 100%, respectively [Finally, the last drawback of the previously described protocols remained the use of an anti-IgE reagent to identify basophils. Because of its selective expression on cells associated with Th2 responses , CRTH2 (chemoattractant receptor-homologous molecule expressed on Th2 cells)/DPh2 cells ,39. CRTHandin D2 ,41. As Candin D2 . Patientectively . CRTH2 s2 was by far the most potent activator of basophils, inducing CD203c and CD11b elevation [2 with the DP1 receptor limited the activation of basophils by this prostaglandin. This suggested that the balance between DP1 and DP2 receptors may be crucial in determining the magnitude of basophil responses during allergic processes since prostaglandin D2 is known to be involved in allergic diseases and asthma. Using a similar approach, Heinemann et al. [Until recently, due to the very low number of circulating basophils in humans, pharmacological studies on these cells were difficult to perform. This required large amount of blood and / or lengthy purification procedures that may induce nonspecific activation. By the use of flow cytometry, the effects of different compounds on basophils may be examined in unfractionated human blood cells. Recently, we have been able to demonstrate that among various eicosanoids, prostaglandin Dlevation . This relevation , the intn et al.  examinedThese studies illustrate that it is now possible to perform pharmacological and drug screening studies by flow cytometry. This approach could be very useful in assessing the possible risks of inducing anaphylactoid or pseudo-anaphylactoid reactions when developing new molecules. To this end, one important task for the future will be to extend these kinds of protocols to animal models although, to our knowledge, there is no available information on CD203c in animals and monoclonal antibodies directed against human CD203c do not cross-react with other species .in vitro investigations of immediate allergy, complementary to other existing in vitro tests. It is suitable for experimental and pharmacological studies as well as allergy diagnosis in clinical practice. There is now a crucial need for inter-laboratory standardization in clinical decision-making. Each allergen has to be assessed one by one to determine its optimal concentration  as well as the definition of the threshold for positivity  since the use of an arbitrary cut-off value is likely not suitable for all allergens. The present challenge is to take advantage of the availability of improved methods to perform multicenter studies using a standardized protocol.After several improvements, the basophil activation test (using either CD203c or CD63 as activation marker) has become a robust and reliable test for The author(s) declare that they have no competing interests.RB participated as investigator and is the main author of the article.ALD participated in drafting the manuscript.GM was project leader and participated in the design of the different studies and drafting the manuscript.


The genetic regulation of variation in intra-individual fluctuations in systolic blood pressure over time is poorly understood. Analysis of the magnitude of the average fluctuation of a person's systolic blood pressure around his or her age-adjusted trend line, however, shows moderate, albeit significant, family resemblance in Cohort 1 of the Framingham Heart Study. To determine whether genomic regions affecting this phenotype could be identified, we pursued a "model-free" multipoint quantitative linkage analysis.Two different linkage methods revealed multiple nominally significant signals, two to four of which are "replicated" in Cohort 2. When both cohorts are assembled into extended pedigrees, three linkage signals remain nominally significant by one or both methods.Any or all of the genomic regions in the vicinity of D5S1456, D11S2359, and D20S470 may contain elements that regulate systolic blood pressure homeostasis. Our strategy was to: 1) document family resemblance for the variability of SBP in Cohort 1; 2) use multipoint quantitative linkage analysis to identify genomic regions that may harbor genes that affect within-person variability in SBP; and 3) replicate any findings in Cohort 2. Despite the inherent differences between the two cohorts, if one or more linkage signals are replicated, we will combine the cohorts and repeat the analysis on the extended pedigrees.We used the rich longitudinal Framingham Heart Study data to explore the hypothesis that there is a heritable component to intra-individual magnitude of the fluctuations about each individual's age-related mean SBP. Since we anticipate that different individuals may have unique age-related trends  and since we are not interested in the age-related means, per se, but rather the size of the fluctuations, we defined the phenotype as the average of absolute residual (AVGRES) obtained by regressing each person's SBP measurements on his or her age when the measurements were obtained. Because we wanted to be assured of having a sufficient number of measurements per person, we restricted our Cohort 1 analysis to subjects whose SBP was measured on a minimum of ten occasions. The mean number of SBP measurements for the subsets of Cohort 1 was 19 (SD = 3.5). See Dawber [We are particularly interested in assessing variation in the context of homeostatic regulation. It has been shown that a locus influencing age-adjusted SBP maps to chromosome 17q in these data [e Dawber  for a dep = 0.35, and for females, p = 0.46). All subsequent analyses were carried out on the transformed values of AVGRES.First we evaluated the distribution of AVGRES and found it to be significantly skewed and leptokurtotic in both males and females. A logarithmic (base 10) transformation rendered AVGRES normally distributed in both genders  were genotyped. The distribution of genotyped sibs is as follows: 38 pairs, 6 trios, and 1 quintet.To perform multipoint quantitative linkage analysis for log AVGRES, we chose two methods implemented in the GENEHUNTER linkage program: nonparametric (NP) and expectation maximization Haseman-Elston (EM-HE). The NP method performs a Wilcoxon rank-sum test by first summing the ranks of absolute trait difference from sib pairs, multiplied by a simple weight based on the number of alleles shared identically by descent (IBD). Z scores are then obtained by the usual method .The EM-HE procedure is based on the traditional Haseman-Elston method of regressing the squared sib-pair trait difference on the proportion of alleles shared IBD. In addition, when genotype information is missing, the EM algorithm infers the probability of alleles shared IBD by taking into account the allele sharing distribution as well as the regression parameters estimated from the real data points . SimilarTable The members of Cohort 2 have a maximum of only five SBP assessments (taken over a period of about 20 years). We felt that performing the regression analysis on subjects with fewer than five measurements could not adequately capture the sort of variation we are interested in. Indeed, the relative paucity of Cohort 2 measures may render it fundamentally different from Cohort 1. Restricting the analysis to genotyped sibs who were older than age 20 and had all five SBP assessments, however, yielded a much larger sample size compared to Cohort 1: 151 pairs, 84 trios, 35 quartets, 7 quintets, 4 sextets, and 2 septets.p-value < 0.05 obtained under the same weighting and statistical methodology, then there are two replications: D5S1456 for the NP approach and D11S2359 for the EM-HE approach. Two additional markers (D1S1653 and D20S470) revealed a "reversal". Both of these markers gave a nominally significant signal in Cohort 1 with the EM-HE statistic, but in Cohort 2 it was the NP statistic that achieved nominal "replication".Table Combining available individuals from both cohorts results in 17 new families that were not analyzed in either cohort. Specifically, there are two half-sib pair families, two sib-pair families (that straddle the cohorts), and 13 families with additional avuncular or cousin members. Five large pedigrees were disassembled at a marriage node into smaller units. A total of 305 families were used for the combined analyses.Table Physiological homeostasis is the process whereby a narrow range of phenotypes develops in the presence of wide variation in genotypes and environments. A classic example is the ability of homeothermic mammals to maintain a constant body temperature despite substantial genetic variation and fluctuating ambient air temperatures. The concept of physiological homeostasis bears some similarity to Waddington's notion of "canalization"  althoughDiagnostic and Statistical Manual of Mental Disorders (4th ed.) criteria for major depression are the following: a significant decrease or increase in appetite, insomnia or hypersomnia, psychomotor agitation or psychomotor retardation.That a breakdown in physiological homeostasis can result in either an increase or decrease in a phenotype — thus increasing the variance — is recognized in the operational definitions of many disorders. For example, among the While the preponderance of genetic studies concentrate on the first moment of various phenotypes — and for medical reasons are usually interested in understanding deviantly high  phenotypes — it is reasonable to suppose that the magnitude of an individual's phenotypic variation is to some extent under genetic control . Indeed,r = 0.51) and Cohort 2 (r = 0.29) in the Framingham Heart Study. This previously unrecognized relationship between the use of hypertension medication and AVGRES is likely to have confounded our linkage analysis in an unknown fashion. Second, we did not adjust the data for body mass index (BMI)-a covariate known to show familial resemblance and to affect SBP. Since our phenotype was defined as the average residual from each subject's unique regression line it is unclear what, if any, effect the failure to adjust for BMI had on our results. Third, we did not test whether curvilinear regression would have provided an improved fit compared to simple linear regression. This decision was based on two considerations. First, if for some of the subjects, a quadratic or cubic function were found to fit significantly better than the linear component, its use in a subset of the data would have created a heterogeneous definition of the phenotype. Second, we were aware that the maximum number of available SBP measures on the Cohort 2 subjects was five, and it seemed frivolous to fit a high order function to such meager data.We used the rich longitudinal Framingham Heart Study data to study the genetics of long term variation in SBP. Our findings indicate that there is moderate familial resemblance for the magnitude of the deviation of a person's SBP from his or her unique age-related trend line. At least three caveats need to be mentioned. First, we restricted our Cohort 1 analysis to individuals with 10 or more measurements. Because this cohort was relatively small, we chose to include all subjects who met the above criterion, regardless of whether they were under treatment for hypertension. Subsequent to the Genetic Analysis Workshop 13, however, we carried out an analysis to determine if there exists a relationship between medication usage and AVGRES. We quantified medication usage as the proportion of SBP assessments where the subject was reported to be medicated. Unexpectedly, there is a strong positive correlation for both cohort 1  plots . An additional two signals were found to be nominally significant by EM-HE in Cohort 1 and "replicated" with NP in Cohort 2. Three of these four signals remained nominally significant when extended pedigrees were analyzed.


The unprecedented global increase in the use of herbal remedies is set to continue apace well into the foreseeable future. This raises important public health concerns, especially as it relates to safety issues including adverse effects and herb-drug interactions. Most Western-trained physicians are ignorant of the risks and benefits of this healthcare modality and assessment of acceptance and knowledge would identify appropriate intervention strategies to improve physician-patient communication in this area.de novo questionnaire at six public hospitals in Trinidad between May–July 2004. The questionnaire utilized weighed questions to quantify acceptance (maximum score = 14 points) and knowledge (maximum score = 52 points). Acceptance and knowledge scores were analyzed using the ANOVA and Tukey's tests.A cross-sectional survey was done using an interviewer-administered pilot tested Of 192 physicians interviewed, most (60.4%) believed that herbal remedies were beneficial to health. Respondents had relatively high acceptance levels  and poor knowledge . Seventy-eight physicians (40.6%) admitted having used herbs in the past, and 60 of these (76.9%) were satisfied with the outcome. Although 52 physicians (27.1%) recommended the use of herbs to their patients only 29 (15.1%) were able to identify at least one known herb-drug interaction.The use of herbal remedies is relatively high in Trinidad, as throughout the world, and most patients self-medicate with or without the knowledge of their attending physician. Surprisingly, we demonstrated relatively high acceptance levels and use of herbs among physicians in Trinidad. This interesting scenario of high acceptance levels and poor knowledge creates a situation that demands urgent intervention. We recommend educational intervention to narrow the gap between acceptance and knowledge so that physicians would be adequately equipped to communicate with their patients on this modality. The integration of herbal medicine into the curriculum of medical schools, continuing education programs and the availability of reputable pharmacopoeias for referencing at public health institutions are useful instruments that can be used to close this gap and promote improved physician-patient communication. More than 80% of the population in the developing world use traditional medicine, which includes herbal remedies, for the management of health . In the There has been an unprecedented explosion in the popularity of herbal preparations during the last few decades, especially in developed countries . This phThere is significant use of herbal remedies in the Caribbean ,14 and rFew studies report on the knowledge, attitudes and practices of physicians regarding complementary and alternative medicine, with little emphasis on herbal medicine ,19. Thisde novo pilot-tested questionnaire during the period May to July 2004. Weighted questions were used to quantitatively assess physicians' acceptance and knowledge of herbal remedies. A sample of public health sector physicians was recruited from the six public hospitals in Trinidad. The nature and purpose of the study were explained on an individual basis, and following the physicians' willingness to participate they signed their informed consent. Respondents were permitted to withdraw from the study at anytime after the interview had commenced. The study was approved by the Ethics Committee, Faculty of Medical Sciences at the University of the West Indies, Trinidad.This descriptive study was cross-sectional in design and used a The sample of physicians was recruited from the six public hospitals, namely the Port-of-Spain General Hospital (POSGH), the San Fernando General Hospital (SFGH) and the Eric Williams Medical Sciences Complex (EWMSC). These are the three major hospitals and employ most physicians in the public healthcare sector on the island. The other hospitals were the specialist obstetrics and gynecology Mount Hope Women's Hospital (MHWH), the St. Ann's Psychiatric Hospital (SAPH) and the minor Sangre Grande Regional Hospital (SGRH).Quota sampling was used to obtain the sample size; the total number of physicians required was proportionally distributed among the hospitals based on the population of physicians at each hospital; i.e. the larger hospitals represented a larger percentage of the sample size. Furthermore, at these larger general hospitals, a representative proportion of physicians from all specialized department was obtained, and this was based on the total number of physicians working at each department. At these departments physicians were interviewed by convenient sampling until the quota was achieved. At the smaller specialist hospitals convenient sampling was used, without stratification, until the quota was achieved. With this method of interviewee selection we expected a 100% response rate. For inclusion in the study physicians must have been employed at the hospital for at least three months.de novo questionnaire was interviewer-administered and determined demographic details including gender, nationality, country of study, duration of employment at the hospital, position at the hospital, years of practicing medicine and level of qualification.The pilot-tested de novo to assess these cognitive, evaluative and behavioural aspects of acceptance with a maximum possible score of 14 points. We rationalized that the behavioural component would be the best indicator of acceptance, as it is sometimes possible for beliefs and feelings to be discordant with actions. We estimated that the cognitive and evaluative aspects contributed less weight to acceptance and these items were assigned fewer points (4 out of 14 points). Items on behaviour included personal use, past recommendation and prescription of medicinal herbs to patients, and these were allocated a larger proportion of the overall points (10 out of 14 points).Acceptance (or positive attitude) was assessed using questions that evaluated beliefs, feelings and actions regarding herbal medicines (Appendix 1). Questions were developed Knowledge was evaluated using open-ended weighed questions to identify five (5) Caribbean and five (5) non-Caribbean medicinal herbs, their uses, contraindications and important herb-drug interactions, together with other questions determined knowledge of herbal pharmacopoeias and clinical studies on herbal medicines with a maximum score of 52 (Appendix 2). Established pharmacopoeias -22 and rWe postulated that most physicians in Trinidad would reject the use of herbal medicines, as did 82% of oncologists who rejected complementary and alternative medicines in the study by Hyodo et al . We usedOne hundred and ninety two 192) survey questionnaires were completed (100% response rate) and the demographic details of the sample are given in Table 92 surveyThe mean acceptance score was 5.69 ± 0.29 (maximum score = 14), Table Fifty-two respondents (27.1%) had previously recommended the use of medicinal herbs to their patients, and were also able to identify the herbs and herbal products in the treatment and management of diseases such as peptic ulcers, prostate enlargement and hepatitis, which supported their acceptance of this modality. However, only 14 physicians (7.3%) had ever advised their patients to consult an herbalist. Forty-three or 22.4% of the sample indicated that they would recommend medicinal herbs, if the option were available, to patients who were refractory to treatment with conventional allopathic medicines. Thirty physicians (15.6%) indicated that they accepted herbal medicines as a viable healthcare option, as they were aware of traditional medicinal practices, such as Ayuvedic medicine, and clinical trials that supported safety and efficacy of herbal remedies. Most physicians (58.3%) also expressed their willingness to allow their patients to participate in randomized controlled clinical trials to validate the safety and efficacy of medicinal herbs.For 73 physicians (39.1%) the primary reason for rejecting herbal medicines was due to the sparse scientific information available from clinical trials to support the safety and efficacy of medicinal herbs in healthcare management. To a much lesser extent other reasons for rejecting herbal medicines included an absence of impartation of such knowledge during their medical training, non-relevance to specific specialties and the medico-legal issues of prescribing this modality in the public healthcare delivery system in Trinidad. Other physicians indicated that they personally did not believe that herbs were either safe or beneficial and one respondent commented "... and some are not scientifically proven to work and can give patients a false hope." However, most respondents (81.3%) believed that continuing education in herbal medicine was important to facilitate greater doctor-patient interaction in this mushrooming area of healthcare management.Mean knowledge score was 7.77 ± 0.56 (maximum score = 52), Table Ninety-six respondents (50%) could identify at least two (2) Caribbean medicinal herbs and their traditional uses, whereas only 54 (28.1%) could identify at least two (2) non-Caribbean medicinal herbs and their uses. Most respondents were unable to identify at least one contraindication for either Caribbean (82.3%) or non-Caribbean herbs (87.5%) and only 29 physicians (15.1%) were able to correctly identify any known herb-drug interaction. Most physicians (55.7%) reported asking patients about their medicinal herb use in the history taking of drug use.Cymbopogon citratus DC. Stapf), noni (Morinda citrifolia Linn.) and saffron (Curcuma longa L.). Interestingly, the medicinal use of marijuana (Cannabis sativa) was recognized in third place with 26 physicians (13.5%) recognizing its usefulness.The most popular herbs identified are listed in Table Only 18 physicians (9.4%) had access to information on herbal medicine at their place of work, and 30 (15.6%) had ever attended conferences or workshops where a paper on herbal medicine was presented or discussed. Although 105 physicians (54.7%) were aware of herbal pharmacopoeias, only 13 of these 105 (or 12.4%) could name at least one.This study showed for the first time the marked disparity between acceptance and knowledge of herbal medicines by public health sector doctors in Trinidad. The mean acceptance score was about 40% of the total possible score, whereas the mean knowledge score was about 15% of the total possible score. Generally, these healthcare providers had relatively high acceptance levels with poor knowledge. The gap between acceptance and knowledge of herbal remedies by physicians may indicate the differential between traditional/cultural beliefs and the lack of access to information.We propose that this disparity could be partly explained by the origin and composition of Trinidad's 1.3 million inhabitants . More thUnlike earlier studies that used closed questions, where true-or-false responses were required for a limited number of popular medicinal herbs, most of the knowledge questions in our survey instrument were open-ended. We postulated that this approach would provide a wider breadth to assess 'true' knowledge without limiting responses and also eliminate the likelihood of respondents guessing the correct answers. Besides, our finding of poor knowledge among physicians in Trinidad was consistent with other studies assessing medical practitioners ,19 and oOver 40% of physicians interviewed reported using medicinal herbs in the past, with more than three-fourths of these being satisfied with the outcome. Our results were markedly higher than in the Norwegian study where only 12% of physicians reported the use of alternative medicines, which included herbal medicines . Our resAbout one-fifth of our sample population suggested that this therapeutic option should be explored when conventional allopathic medicines fail, and this finding was similar to that reported in a recent UK study  where phMost respondents, particularly native West Indians, were able to identify the traditional medicinal uses of Caribbean herbs; and fewer were able to identify non-Caribbean herbs and their indications. In this study, knowledge of contraindications and herb-drug interactions was very poor and was similar to a US study which also demonstrated a knowledge deficit as it related to adverse effects of herbs . We noteMore than half of the physicians interviewed reported having asked their patients specifically about herbal medicine use when taking a drug history, and this was similar to an Israeli study where 58% of physicians always or frequently asked their patients about their use of complementary medicine . Our resAs the use of medicinal herbs continues to increase worldwide, there has been a parallel surge in research to isolate pharmacologically active pure compounds from medicinal plants, and clinical investigations are being done to establish the safety profile and efficacy of some of the more popular traditionally used herbal remedies -42. The At present, formal training in herbal medicine at the regional university (The University of the West Indies) where most of our physicians are trained, does not form part of the curriculum and subsequently graduates possess no formal knowledge in the area. Our study showed that most respondents agreed that continuing education in herbal medicines was necessary for effective patient consultations. Recent studies have shown that herbal medicine educational interventions taught as structured programs via different media significantly improved physicians' knowledge, confidence and their interactions with patients ,43. FrenOur survey was conducted at public hospitals throughout Trinidad, and obviously excluded physicians who worked exclusively at private institutions and probably different responses would have been elicited from these physicians. Although the use of quota sampling with stratification was advantageous for our research purposes, interviewer bias may have been introduced by the non-random convenient selection of respondents, resulting in a sample that may not have been truly representative. Although open-ended questions were especially useful for gathering responses on knowledge, where replies were too numerous to code , there were some limitations. Open-ended questions require more thought and are taxing on the respondent and this may have affected the quality of responses. Also, responses to these open-ended items may have been summarized and the true meaning distorted by the interviewer or by the coding process used for data entry.Notwithstanding these limitations, the burden of our results suggests that there is an urgent need for educational intervention with regard to herbal medicine in the training of our physicians. We propose that there be an integration of herbal medicine into the current medical curriculum so that future physicians would be better able to communicate with their patients on this healthcare modality. Continuing education programs are also recommended so that practicing physicians would have the opportunity to upgrade their knowledge in this rapidly expanding area of significant public health concern. In the interim, public health institutions should be equipped with reputable herbal pharmacopoeias and electronic databases to answer questions that would arise during the course of clinical practice.Our findings showed that medical practitioners in the public healthcare sector in Trinidad generally accepted herbal remedies as a viable option although they lack sufficient knowledge on the uses and potential risks associated with this modality. This result directly contradicted our initial hypothesis that herbal remedies would be rejected (or poor acceptance) and that this would correlate with poor knowledge. This creates an interesting scenario where the gap between acceptance and knowledge provides an ideal opportunity to facilitate the introduction of educational programs and policies that would increase the knowledgebase of these healthcare professionals. Well-informed physicians would be more confident in their interactions with patients and this would improve the quality of healthcare delivery, as more meaningful communication on important issues such as adverse effects and herb-drug interactions would be facilitated. The increasing trend in the use of herbs is set to continue well into the foreseeable future and the enhanced knowledgebase of physicians would redound to the benefit of patients who would appreciate a non-judgmental environment when discussing healthcare needs.1. Do you believe that herbal medicines are beneficial in healthcare management? (2 points for affirmative answer)Yes □No □2. Have you ever recommended the use of herbal medicines? (2 points for affirmative answer)Yes □No □3. Have you ever prescribed herbs to patients for medicinal purposes? (2 points for affirmative answer)Yes □No □4. Have you ever recommended patients to an herbalist? (2 points for affirmative answer)Yes □No □5. Have you ever personally used herbs? (2 points for affirmative answer)Yes □No □6. Do you think that the use of herbal medicines should be limited only to patients who have failed conventional therapy? (1 point for affirmative answer)Yes □No □7. Do you think that continuing education in herbal medicines is important? (1 point for affirmative answer)Yes □No □8. Would you be willing to allow your patients to participate in clinical trials to evaluate the efficacy of Caribbean 'bush' teas?  (2 points for affirmative answer)Yes □No □1. Can you identify any five (5) Caribbean herbs and their common usages? 2. Can you list five (5) contraindications of named Caribbean herbs? (2 points for each herb and its correct contraindication(s); 10 points total)3. Can you identify any five (5) imported herbs and their common usages? 2 points for each herb and its correct use; 10 points total)4. Can you list five (5) contraindications of named imported herbs? (2 points for each herb and its correct contraindication(s); 10 points total)5. Can you list any two (2) herb-drug interactions? 6. Do you specifically ask your patients about their use of herbal medicine when taking a drug history? 1 point for affirmative answer)Yes □No □7. Are you aware that several international herbal pharmacopoeias exist? (1 point for affirmative answer)Yes □No □8. If yes, could you give at least one (1) example of a herbal pharmacopoeia? (3 points for correct pharmacopoeia)9. Are you aware that there are several completed and ongoing international clinical trials on the efficacy and safety of herbal medicines? (1 point for affirmative answer)Yes □No □10. If yes, could you identify one example? (2 points for correct example)The author(s) declare that they have no competing interests.YNC was the P.I. and was responsible for the study concept, development of methodology, coordinating of the research activities, analyzing the data, and writing the manuscript. KK, TB, SB, MF and KN were involved in methodological development, data collection, data input and analysis. OM was involved in methodological development. AFW was involved in data input and statistical analysis. CES was involved in an advisory capacity in the study concept and development of methodology phases of the research. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Over 5,000 participants attended the 10th International Conference on Alzheimer's Disease (ICAD) and Related Disorders in Madrid, Spain from July 15–20, 2006. Highlights of the conference included reports on brain imaging, the discovery of mutations in the progranulin gene that cause frontotemporal dementia, the finding that neuregulin-1 is a substrate for BACE1 and new interest in the connection between Alzheimer's disease and metabolic syndromes. More than 5,000 researchers, students and clinicians came to Madrid to present their research and learn about the findings of others. The welcome reception at Palacio Negralejo, a sprawling estate on the outskirts of Madrid, allowed attendees to meet collaborators and friends and sample some typical Spanish food: Iberic ham, seafood paella, grilled veal and various tapas. Flamenco dancers, banjo players, and plenty of sangria created a festive beginning for the conference.The 10The main conference was preceded by an imaging consortium on Alzheimer's disease (AD). Using a wide variety of methods, investigators showed correlations between AD or aging and different imaging measures. There was particular interest in white matter lesions, which several scientists noted were closely correlated with AD. Frank-Erik De Leeuw from UMC-Stradboud in the Netherlands reported that the extent of white matter lesions correlates with medial temporal atrophy in late-onset but not early-onset AD, suggesting that late-onset and early-onset AD may have some different pathological pathways . There wMAPT) gene on chromosome 17 were found to cause FTD with parkinsonism, geneticists have been stymied by families with FTD linked to the same region on chromosome 17 but having no MAPT mutations. It seemed likely that difficult-to-find mutations in MAPT accounted for these FTD cases, but the mutations could not be found despite heroic efforts. Geneticists then sequenced genes near MAPT and were rewarded by finding mutations in the progranulin gene (PGRN), which is located a mere 1.7 Mb away from MAPT. In one patient series, PGRN mutations accounted for at least 11% of all FTD cases and 26% of familial FTD cases. Interestingly, all the PRGN mutations that were reported are dominant and effectively create null alleles, meaning that the FTD phenotype results from decreased levels of progranulin in affected individuals. Additionally, the ubiquitin-positive inclusions in the brains of affected individuals do not stain with anti-progranulin antibodies, leaving the identity of the ubiquitinated protein an intriguing mystery. The discovery of PGRN mutations is a major advance in our understanding of FTD and will undoubtedly inspire intense research to discover the mechanism by which progranulin deficiency leads to FTD.Although there were hundreds of presentations at ICAD, a few stood out because of their importance and novelty. Perhaps the biggest news came from two independent groups of researchers at the Mayo Clinic and the University of Antwerp in Belgium. Both groups found mutations in the gene encoding progranulin that cause a form of frontotemporal dementia (FTD), the second most common form of dementia in individuals younger than 65 years old ,4. SinceBace1-/- mice, most likely because BACE1 is the major enzyme that cleaves neuregulin-1. Finally, they demonstrated that neuregulin-1 is cleaved by BACE1 in vitro [Another interesting story from the conference involved BACE1, the major β-secretase in the brain. Sequential cleavage of amyloid precursor protein by β-secretase and then γ-secretase produces the amyloid β-peptide (Aβ). Since inhibition of β-secretase should decrease Aβ levels in the brain, it is an attractive therapeutic target. In fact, Martin Citron from Amgen reported that over 100 patents have been filed for BACE1 inhibitors . Howeverin vitro . It is uAn area that has not been previously emphasized, the interaction between AD and metabolic syndromes such as obesity and diabetes, was discussed in multiple sessions. Miia Kivipelto from the Stockholm Gerontology Research Center presented epidemiological data showing that obesity, hypercholesterolemia and hypertension were all risk factors for AD and that when all three factors were present in the same individual the risk of AD increased 6-fold . Other iFinally, one other notable change in this conference was the plethora of drug company representatives marketing their formulations of acetylcholinesterase inhibitors and memantine. While scientists rarely get excited about increasing numbers of drug salespeople, their presence was evidence that therapeutics the Alzheimer's research and pharmaceutical community has been developing for years are finally coming to the market. Hopefully the therapeutics being marketed at the 2008 ICAD conference in Chicago will be more numerous and effective.The author(s) declares that she has no competing interests.