Two recent studies identified a mutation (p.Asp620Asn) in the vacuolar protein sorting 35 gene as a cause for an autosomal dominant form of Parkinson disease . Although additional missense variants were described, their pathogenic role yet remains inconclusive.
Methods and results
We performed the largest multi-center study to ascertain the frequency and pathogenicity of the reported vacuolar protein sorting 35 gene variants in more than 15,000 individuals worldwide. p.Asp620Asn was detected in 5 familial and 2 sporadic PD cases and not in healthy controls, p.Leu774Met in 6 cases and 1 control, p.Gly51Ser in 3 cases and 2 controls. Overall analyses did not reveal any significant increased risk for p.Leu774Met and p.Gly51Ser in our cohort.
Our study apart from identifying the p.Asp620Asn variant in familial cases also identified it in idiopathic Parkinson disease cases, and thus provides genetic evidence for a role of p.Asp620Asn in Parkinson disease in different populations worldwide.
Parkinson-s disease; Genome-wide; Genetics; Genetic epidemiology; Complex traits
Pain influences sleep and vice versa. We performed an umbrella review of meta-analyses on treatments for diverse conditions in order to examine whether diverse medical treatments for different conditions have similar or divergent effects on pain and sleep.
We searched published systematic reviews with meta-analyses in the Cochrane Database of Systematic Reviews until October 20, 2011. We identified randomized trials (or meta-analyses thereof, when >1 trial was available) where both pain and sleep outcomes were examined. Pain outcomes were categorized as headache, musculoskeletal, abdominal, pelvic, generic or other pain. Sleep outcomes included insomnia, sleep disruption, and sleep disturbance. We estimated odds ratios for all outcomes and evaluated the concordance in the direction of effects between sleep and various types of pain and the correlation of treatment effects between sleep and pain outcomes.
151 comparisons with 385 different trials met our eligibility criteria. 96 comparisons had concordant direction of effects between each pain outcome and sleep, while in 55 the effect estimates were in opposite directions (P<0.0001). In the 20 comparisons with largest amount of evidence, the experimental drug always had worse sleep outcomes and tended to have worse pain outcomes in 17/20 cases. For headache and musculoskeletal pain, 69 comparisons showed concordant direction of effects with sleep outcomes and 36 showed discordant direction (P<0.0001). For the other 4 pain types there were overall 27 vs. 19 pairs with concordant vs. discordant direction of effects (P = 0.095). There was a weak correlation of the treatment effect sizes for sleep vs. headache/musculoskeletal pain (r = 0.17, P = 0.092).
Medical interventions tend to have effects in the same direction for pain and sleep outcomes, but exceptions occur. Concordance is primarily seen for sleep and headache or musculoskeletal pain where many drugs may both disturb sleep and cause pain.
Fifteen meta-analyses have been published between 1995 and 2011 to evaluate the efficacy/effectiveness and harms of diverse influenza vaccines—seasonal, H5N1 and 2009(H1N1) —in various age-classes (healthy children, adults or elderly). These meta-analyses have often adopted different analyses and study selection criteria. Because it is difficult to have a clear picture of vaccine benefits and harms examining single systematic reviews, we compiled the main findings and evaluated which could be the most reasonable explanations for some differences in findings (or their interpretation) across previously published meta-analyses. For each age group, we performed analyses that included all trials that had been included in at least one relevant meta-analysis, also exploring whether effect sizes changed over time. Although we identified several discrepancies among the meta-analyses on seasonal vaccines for children and elderly, overall most seasonal influenza vaccines showed statistically significant efficacy/effectiveness, which was acceptable or high for laboratory-confirmed cases and of modest magnitude for clinically-confirmed cases. The available evidence on parenteral inactivated vaccines for children aged < 2 y remains scarce. Pre-pandemic “avian” H5N1 and pandemic 2009 (H1N1) vaccines can achieve satisfactory immunogenicity, but no meta-analysis has addressed H1N1 vaccination impact on clinical outcomes. Data on harms are overall reassuring, but their value is diminished by inconsistent reporting.
Meta-analysis; influenza vaccine; vaccine efficacy; vaccine immunogenicity; vaccine safety
Since 2007, genome-wide association (GWA) studies have identified numerous well-supported, novel genetic risk loci for common cancers; however, there are concerns that this technology is reaching its limits. We provide an overview of GWA-identified genetic associations with solid tumors. We simulated the distribution of population risk alleles for colorectal, prostate, testicular, and thyroid cancers based on genetic variants identified in GWA studies. We also evaluated whether statistical power to detect typical genetic effects could be improved with studies performing GWA analyses of all available samples rather than multistage designs. Fifty-six eligible articles yielded 92 eligible associations between cancer phenotypes and genetic variants with a median per-allele odds ratio (OR) of 1.22 (interquartile range = 1.15–1.36). Half of the associations pertained to prostate, colorectal, or breast cancer. Individuals at the upper quartile of simulated risk had only 2.1- to 4.2-fold higher relative risk than those in the lower quartile. Comprehensive evaluation of currently available samples with GWA platforms would yield few additional variants with per-allele OR = 1.4, but many more variants with OR = 1.2 could be detected; statistical power to detect weak associations (OR = 1.07) would still be negligible. The GWA approach is effective in identifying common genetic variants with moderate effect; however, identifying loci with very small effects and rare variants will require major new efforts. At present, the utility of GWA-identified risk loci in risk stratification for cancer is limited.
Black box warnings (BBWs) are the strongest medication-related safety warnings in a drug’s labeling information and highlight major risks. Absence of a BBW or asynchronous addition of a BBW among same-class drugs could have major implications.
We identified the 20 top-selling drugs in 2008 (10 with BBWs and 10 without BBWs on their label) that belonged to different drug classes. We collected labeling information on all drugs belonging in these 20 classes, and recorded differences in the presence and timing of acquisition of BBWs for same-class drugs.
Across the 20 evaluated drug classes, we identified 176 different agents, of which 7 had been withdrawn for safety reasons. The reasons for the withdrawals became BBWs in other same-class agents only in two of the seven cases. Differences were identified in 9 of the 20 classes corresponding to 15 BBWs that were not present in all drugs of the same class. The information for 10 of the 15 different BBWs were included in the labels of same-class drugs as simple warnings or text, while it was absent entirely in 5 BBWs. The median interval from the time the BBW had appeared in another drug of the same class was 66 months.
Differences in BBW labeling in same-class drugs are common and shape impressions about the safety of similar agents. BBW labeling needs to become more systematic.
Electronic supplementary material
The online version of this article (doi:10.1007/s11606-011-1633-9) contains supplementary material, which is available to authorized users.
black-box warning; FDA; adverse events; harms
We studied the independent and joint effects of the genes encoding alpha-synuclein (SNCA) and microtubule associated protein tau (MAPT) in Parkinson's disease (PD) as part of a large meta-analysis of individual data from case-control studies participating in the Genetic Epidemiology of Parkinson's Disease (GEO-PD) consortium.
Participants of Caucasian ancestry were genotyped for a total of four SNCA (rs2583988, rs181489, rs356219, rs11931074) and two MAPT (rs1052553, rs242557) SNPs. Individual and joint effects of SNCA and MAPT SNPs were investigated using fixed- and random-effects logistic regression models. Interactions were studied both on a multiplicative and an additive scale, and using a case-control and case-only approach.
Fifteen GEO-PD sites contributed a total of 5302 cases and 4161 controls. All four SNCA SNPs and the MAPT H1-haplotype defining SNP (rs1052553) displayed a highly significant marginal association with PD at the significance level adjusted for multiple comparisons. For SNCA, the strongest associations were observed for SNPs located at the 3′ end of the gene. There was no evidence of statistical interaction between any of the four SNCA SNPs and rs1052553 or rs242557, neither on the multiplicative nor on the additive scale.
This study confirms the association between PD and both SNCA SNPs and the H1 MAPT haplotype. It shows, based on a variety of approaches, that the joint action of variants in these two loci is consistent with independent effects of the genes without additional interacting effects.
Parkinson disease; SNCA; MAPT; genetics; interaction; case-control
Proposed molecular classifiers may be overfit to idiosyncrasies of noisy genomic and proteomic data. Cross-validation methods are often used to obtain estimates of classification accuracy, but both simulations and case studies suggest that, when inappropriate methods are used, bias may ensue. Bias can be bypassed and generalizability can be tested by external (independent) validation. We evaluated 35 studies that have reported on external validation of a molecular classifier. We extracted information on study design and methodological features, and compared the performance of molecular classifiers in internal cross-validation versus external validation for 28 studies where both had been performed. We demonstrate that the majority of studies pursued cross-validation practices that are likely to overestimate classifier performance. Most studies were markedly underpowered to detect a 20% decrease in sensitivity or specificity between internal cross-validation and external validation [median power was 36% (IQR, 21–61%) and 29% (IQR, 15–65%), respectively]. The median reported classification performance for sensitivity and specificity was 94% and 98%, respectively, in cross-validation and 88% and 81% for independent validation. The relative diagnostic odds ratio was 3.26 (95% CI 2.04–5.21) for cross-validation versus independent validation. Finally, we reviewed all studies (n = 758) which cited those in our study sample, and identified only one instance of additional subsequent independent validation of these classifiers. In conclusion, these results document that many cross-validation practices employed in the literature are potentially biased and genuine progress in this field will require adoption of routine external validation of molecular classifiers, preferably in much larger studies than in current practice.
predictive medicine; genes; gene expression; proteomics
The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice.The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality.Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction.A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines.These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
Genetic effects for common variants affecting complex disease risk are subtle. Single genome-wide association (GWA) studies are typically underpowered to detect these effects, and combination of several GWA data sets is needed to enhance discovery. The authors investigated the properties of the discovery process in simulated cumulative meta-analyses of GWA study-derived signals allowing for potential genetic model misspecification and between-study heterogeneity. Variants with null effects on average (but also between-data set heterogeneity) could yield false-positive associations with seemingly homogeneous effects. Random effects had higher than appropriate false-positive rates when there were few data sets. The log-additive model had the lowest false-positive rate. Under heterogeneity, random-effects meta-analyses of 2–10 data sets averaging 1,000 cases/1,000 controls each did not increase power, or the meta-analysis was even less powerful than a single study (power desert). Upward bias in effect estimates and underestimation of between-study heterogeneity were common. Fixed-effects calculations avoided power deserts and maximized discovery of association signals at the expense of much higher false-positive rates. Therefore, random- and fixed-effects models are preferable for different purposes (fixed effects for initial screenings, random effects for generalizability applications). These results may have broader implications for the design and interpretation of large-scale multiteam collaborative studies discovering common gene variants.
epidemiology; genetics; genome-wide association study; Human Genome Project; meta-analysis; models, genetic; polymorphism, single nucleotide
elderly; clopidogrel; glycoprotein IIb/IIIa blockers
Genetic and molecular epidemiology covers a vast area of research. Given the rapid changes in this field, discussing a research agenda is a precarious and ambitious task. A representative set of high‐priority concepts will be presented here, each of which alone could be the topic of a long series of essays. The wish list includes issues of full transparency and integration of information, dealing efficiently with complex multidimensional biology, juxtaposing the genome and environmental exposures, and using robust randomised trials to advance our knowledge and its application in this field.
Randomized evidence for vaccine immunogenicity and safety is urgently needed in the setting of pandemics with new emerging infectious agents. We carried out an observational survey to evaluate how many randomized controlled trials testing 2009 H1N1 vaccines were published among those registered, and what was the time lag from their start to publication and from their completion to publication.
PubMed, EMBASE and 9 clinical trial registries were searched for eligible randomized controlled trials. The units of the analysis were single randomized trials on any individual receiving influenza vaccines in any setting.
73 eligible trials were identified that had been registered in 2009–2010. By June 30, 2011 only 21 (29%) of these trials had been published, representing 38% of the randomized sample size (19905 of 52765). Trials starting later were published less rapidly (hazard ratio 0.42 per month; 95% Confidence Interval: 0.27 to 0.64; p<0.001). Similarly, trials completed later were published less rapidly (hazard ratio 0.43 per month; 95% CI: 0.27 to 0.67; p<0.001). Randomized controlled trials were completed promptly (median, 5 months from start to completion), but only a minority were subsequently published.
Most registered randomized trials on vaccines for the H1N1 pandemic are not published in the peer-reviewed literature.
Valentina Gallo and colleagues provide detailed guidance to authors to help more accurately report the findings of epidemiological studies involving biomarkers. Their guidance covers issues regarding collection, handling and storage of biological samples; laboratory methods, validity and reliability of biomarkers; specificities of study design; and ethical considerations.
There is an overwhelming abundance of genetic association studies available in the literature, which often can be collectively difficult to interpret. To address this issue, the Venice interim guidelines were established for determining the credibility of the cumulative evidence. The objective of this report is to evaluate the literature on the association of common GST variants (GSTM1 null, GSTT1 null and GSTP1 Ile105Val polymorphism) and lung cancer, and to assess the credibility of the associations using the newly proposed cumulative evidence guidelines. Information from the literature was enriched with an updated meta-analysis and a pooled analysis using data from the Genetic Susceptibility to Environmental Carcinogens (GSEC) database. There was a significant association between GSTM1 null and lung cancer for the meta- (meta OR = 1.17, 95% CI: 1.10–1.25) and pooled analysis (adjusted OR = 1.10, 95% CI: 1.04–1.16), although substantial heterogeneity was present. No overall association between lung cancer and GSTT1 null or GSTP1 Ile105Val was found. When the Venice criteria was applied, cumulative evidence for all associations were considered “weak”, with the exception of East Asian carriers of the G allele of GSTP1 Ile105Val, which was graded as “moderate” evidence. In spite of large amounts of studies, and several statistically significant summary estimates produced by meta-analyses, the application of the Venice criteria suggests extensive heterogeneity and susceptibility to bias for the studies on association of common genetic polymorphisms, such as with GST variants and lung cancer.
meta-analysis; pooled analysis; GSTM1; GSTT1; GSTP1; lung cancer; evidence
Eleven genetic loci have reached genome-wide significance in a recent meta-analysis of genome-wide association studies in Parkinson disease (PD) based on populations of Caucasian descent. The extent to which these genetic effects are consistent across different populations is unknown.
Investigators from the Genetic Epidemiology of Parkinson's Disease Consortium were invited to participate in the study. A total of 11 SNPs were genotyped in 8,750 cases and 8,955 controls. Fixed as well as random effects models were used to provide the summary risk estimates for these variants. We evaluated between-study heterogeneity and heterogeneity between populations of different ancestry.
In the overall analysis, single nucleotide polymorphisms (SNPs) in 9 loci showed significant associations with protective per-allele odds ratios of 0.78–0.87 (LAMP3, BST1, and MAPT) and susceptibility per-allele odds ratios of 1.14–1.43 (STK39, GAK, SNCA, LRRK2, SYT11, and HIP1R). For 5 of the 9 replicated SNPs there was nominally significant between-site heterogeneity in the effect sizes (I2 estimates ranged from 39% to 48%). Subgroup analysis by ethnicity showed significantly stronger effects for the BST1 (rs11724635) in Asian vs Caucasian populations and similar effects for SNCA, LRRK2, LAMP3, HIP1R, and STK39 in Asian and Caucasian populations, while MAPT rs2942168 and SYT11 rs34372695 were monomorphic in the Asian population, highlighting the role of population-specific heterogeneity in PD.
Our study allows insight to understand the distribution of newly identified genetic factors contributing to PD and shows that large-scale evaluation in diverse populations is important to understand the role of population-specific heterogeneity. Neurology® 2012;79:659–667
Genetic association studies have revealed numerous polymorphisms conferring susceptibility to melanoma. We aimed to replicate previously discovered melanoma-associated single-nucleotide polymorphisms (SNPs) in a Greek case-control population, and examine their predictive value.
Based on a field synopsis of genetic variants of melanoma (MelGene), we genotyped 284 patients and 284 controls at 34 melanoma-associated SNPs of which 19 derived from GWAS. We tested each one of the 33 SNPs passing quality control for association with melanoma both with and without accounting for the presence of well-established phenotypic risk factors. We compared the risk allele frequencies between the Greek population and the HapMap CEU sample. Finally, we evaluated the predictive ability of the replicated SNPs.
Risk allele frequencies were significantly lower compared to the HapMap CEU for eight SNPs (rs16891982 – SLC45A2, rs12203592 – IRF4, rs258322 – CDK10, rs1805007 – MC1R, rs1805008 - MC1R, rs910873 - PIGU, rs17305573- PIGU, and rs1885120 - MTAP) and higher for one SNP (rs6001027 – PLA2G6) indicating a different profile of genetic susceptibility in the studied population. Previously identified effect estimates modestly correlated with those found in our population (r = 0.72, P<0.0001). The strongest associations were observed for rs401681-T in CLPTM1L (odds ratio [OR] 1.60, 95% CI 1.22–2.10; P = 0.001), rs16891982-C in SCL45A2 (OR 0.51, 95% CI 0.34–0.76; P = 0.001), and rs1805007-T in MC1R (OR 4.38, 95% CI 2.03–9.43; P = 2×10−5). Nominally statistically significant associations were seen also for another 5 variants (rs258322-T in CDK10, rs1805005-T in MC1R, rs1885120-C in MYH7B, rs2218220-T in MTAP and rs4911442-G in the ASIP region). The addition of all SNPs with nominal significance to a clinical non-genetic model did not substantially improve melanoma risk prediction (AUC for clinical model 83.3% versus 83.9%, p = 0.66).
Overall, our study has validated genetic variants that are likely to contribute to melanoma susceptibility in the Greek population.
There is increasing interest to make primary data from published research publicly available. We aimed to assess the current status of making research data available in highly-cited journals across the scientific literature.
Methods and Results
We reviewed the first 10 original research papers of 2009 published in the 50 original research journals with the highest impact factor. For each journal we documented the policies related to public availability and sharing of data. Of the 50 journals, 44 (88%) had a statement in their instructions to authors related to public availability and sharing of data. However, there was wide variation in journal requirements, ranging from requiring the sharing of all primary data related to the research to just including a statement in the published manuscript that data can be available on request. Of the 500 assessed papers, 149 (30%) were not subject to any data availability policy. Of the remaining 351 papers that were covered by some data availability policy, 208 papers (59%) did not fully adhere to the data availability instructions of the journals they were published in, most commonly (73%) by not publicly depositing microarray data. The other 143 papers that adhered to the data availability instructions did so by publicly depositing only the specific data type as required, making a statement of willingness to share, or actually sharing all the primary data. Overall, only 47 papers (9%) deposited full primary raw data online. None of the 149 papers not subject to data availability policies made their full primary data publicly available.
A substantial proportion of original research papers published in high-impact journals are either not subject to any data availability policies, or do not adhere to the data availability instructions in their respective journals. This empiric evaluation highlights opportunities for improvement.
Unfavorable results of major studies have led to a large shrinkage of the market for hormone replacement therapy (HRT) in the last 6 years. Some scientists continue to strongly support the use of HRT.
We analyzed a sample of partisan editorializing articles on HRT to examine their arguments, the reporting of competing interests, the journal venues and their sponsoring societies.
Through Thomson ISI database, we selected articles without primary data written by the five most prolific editorialists that addressed clinical topics pertaining to HRT and that were published in regular journal issues in 2002–2008.
We recorded the number of articles with a partisan stance and their arguments, the number of partisan articles that reported conflicting interests, and the journal venues and their sponsoring societies publishing the partisan editorials.
We analyzed 114 eligible articles (58 editorials, 16 guidelines, 37 reviews, 3 letters), of which 110 (96%) had a partisan stance favoring HRT. Typical arguments were benefits for menopausal and related symptoms (64.9%), criticism of unfavorable studies (78.9%), preclinical data that showed favorable effects of HRT (50%), and benefits for major outcomes such as osteoporosis and fractures (49.1%), cardiovascular disease (31.6%), dementia (24.6%) or colorectal cancer (20.2%), but also even breast cancer (4.4%). All 5 prolific editorialists had financial relationships with hormone manufacturers, but these were reported in only 6 of the 110 partisan articles. Four journals published 15–37 partisan articles each. The medical societies of these journals reported on their websites that several pharmaceutical companies sponsored them or their conferences.
There is a considerable body of editorializing articles favoring HRT use and very few of these articles report conflicts of interest. Full disclosure of conflicts of interest is needed, especially for articles without primary data.
Electronic supplementary material
The online version of this article (doi:10.1007/s11606-010-1360-7) contains supplementary material, which is available to authorized users.
hormone replacement therapy; menopause; postmenopausal women
John Ioannidis and Alan Garber discuss how to use incremental cost-effectiveness ratios (ICER) and related metrics so they can be useful for decision-making at the individual level, whether used by clinicians or individual patients.
Genome-wide association studies (GWASs) have created a paradigm shift in discovering genetic associations for common diseases and phenotypes, but it is unclear whether the thousands of candidate genetic association studies performed in the pre-GWAS era had found any reliable associations for common diseases and phenotypes. We aimed to systematically evaluate whether loci proposed to harbor candidate associations before the advent of GWASs are replicated in GWASs. The GWAS data published through August, 2008 and included in the NHGRI catalog were screened and variants in candidate loci were selected on the basis of statistical significance (P<0.05) to create a list of independent, non-redundant associations. Altogether, 159 articles on GWASs were evaluated, 100 of which addressed past proposed candidate loci. A total of 291 independent, nominally significant (P<0.05) candidate gene associations were assembled after keeping only the SNP with lowest P-value for each locus and each phenotype; 108 of those had P<10−3 for association and 41 had P<10−7. A total of 22 of these 41 candidate gene associations pertained to binary phenotypes with a median odds ratio=2.91 (IQR: 1.82–4.6) and median minor allele frequency=0.17 (IQR: 0.12–0.29) in Caucasians; for comparison, 60 new associations of binary outcomes with P<10−7 discovered in the same GWASs had much smaller effects (median odds ratio 1.30, IQR: 1.18–1.58) and modestly larger minor allele frequencies (median 0.27, IQR: 0.15–0.43). Overall, few of the numerous genetic associations proposed in the candidate gene era have been replicated in GWASs, but those that have been conclusively replicated have large genetic effects that should not be discarded.
genome-wide association studies; candidate loci; single nucleotide polymorphisms; common diseases/phenotypes; replication
Heterogeneous data are a common problem in meta-analysis. John Ioannidis, Nikolaos Patsopoulos, and Hannah Rothstein show that final synthesis is possible and desirable in most cases