Bone mineral density (BMD) is the most important predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and East Asian ancestry. We tested the top-associated BMD markers for replication in 50,933 independent subjects and for risk of low-trauma fracture in 31,016 cases and 102,444 controls. We identified 56 loci (32 novel)associated with BMD atgenome-wide significant level (P<5×10−8). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal-stem-cell differentiation, endochondral ossification and the Wnt signalling pathways. However, we also discovered loci containing genes not known to play a role in bone biology. Fourteen BMD loci were also associated with fracture risk (P<5×10−4, Bonferroni corrected), of which six reached P<5×10−8 including: 18p11.21 (C18orf19), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.
Many clinical trials examine a composite outcome of admission to hospital and death, or infer a relationship between hospital admission and survival benefit. This assumes concordance of the outcomes “hospital admission” and “death.” However, whether the effects of a treatment on hospital admissions and readmissions correlate to its effect on serious outcomes such as death is unknown. We aimed to assess the correlation and concordance of effects of medical interventions on admission rates and mortality.
We searched the Cochrane Database of Systematic Reviews from its inception to January 2012 (issue 1, 2012) for systematic reviews of treatment comparisons that included meta-analyses for both admission and mortality outcomes. For each meta-analysis, we synthesized treatment effects on admissions and death, from respective randomized trials reporting those outcomes, using random-effects models. We then measured the concordance of directions of effect sizes and the correlation of summary estimates for the 2 outcomes.
We identified 61 meta-analyses including 398 trials reporting mortality and 182 trials reporting admission rates; 125 trials reported both outcomes. In 27.9% of comparisons, the point estimates of treatment effects for the 2 outcomes were in opposite directions; in 8.2% of trials, the 95% confidence intervals did not overlap. We found no significant correlation between effect sizes for admission and death (Pearson r = 0.07, p = 0.6). Our results were similar when we limited our analysis to trials reporting both outcomes.
In this metaepidemiological study, admission and mortality outcomes did not correlate, and discordances occurred in about one-third of the treatment comparisons included in our analyses. Both outcomes convey useful information and should be reported separately, but extrapolating the benefits of admission to survival is unreliable and should be avoided.
In 2012, the National Cancer Institute (NCI) engaged the scientific community to provide a vision for cancer epidemiology in the 21st century. Eight overarching thematic recommendations, with proposed corresponding actions for consideration by funding agencies, professional societies, and the research community emerged from the collective intellectual discourse. The themes are (i) extending the reach of epidemiology beyond discovery and etiologic research to include multilevel analysis, intervention evaluation, implementation, and outcomes research; (ii) transforming the practice of epidemiology by moving towards more access and sharing of protocols, data, metadata, and specimens to foster collaboration, to ensure reproducibility and replication, and accelerate translation; (iii) expanding cohort studies to collect exposure, clinical and other information across the life course and examining multiple health-related endpoints; (iv) developing and validating reliable methods and technologies to quantify exposures and outcomes on a massive scale, and to assess concomitantly the role of multiple factors in complex diseases; (v) integrating “big data” science into the practice of epidemiology; (vi) expanding knowledge integration to drive research, policy and practice; (vii) transforming training of 21st century epidemiologists to address interdisciplinary and translational research; and (viii) optimizing the use of resources and infrastructure for epidemiologic studies. These recommendations can transform cancer epidemiology and the field of epidemiology in general, by enhancing transparency, interdisciplinary collaboration, and strategic applications of new technologies. They should lay a strong scientific foundation for accelerated translation of scientific discoveries into individual and population health benefits.
big data; clinical trials; cohort studies; epidemiology; genomics; medicine; public health; technologies; training; translational research
Remarkable progress has been made in the last decade in new methods for biological measurements using sophisticated technologies that go beyond the established genome, proteome, and gene expression platforms. These methods and technologies create opportunities to enhance cancer epidemiologic studies. In this article, we describe several emerging technologies and evaluate their potential in epidemiologic studies. We review the background, assays, methods, and challenges, and offer examples of the use of mitochondrial DNA and copy number assessments, epigenomic profiling (including methylation, histone modification, microRNAs (miRNAs), and chromatin condensation), metabolite profiling (metabolomics), and telomere measurements. We map the volume of literature referring to each one of these measurement tools and the extent to which efforts have been made at knowledge integration (e.g. systematic reviews and meta-analyses). We also clarify strengths and weaknesses of the existing platforms and the range of type of samples that can be tested with each of them. These measurement tools can be used in identifying at-risk populations and providing novel markers of survival and treatment response. Rigorous analytical and validation standards, transparent availability of massive data, and integration in large-scale evidence are essential in fulfilling the potential of these technologies.
Epigenetics; methylation; mitochondria; risk assessment; telomerase
To investigate whether the two subtypes of advanced age-related macular degeneration (AMD), choroidal neovascularization (CNV) and geographic atrophy (GA), segregate separately in families and to identify which genetic variants are associated with these two subtypes.
Sibling correlation study and genome-wide association study (GWAS)
For the sibling correlation study, we included 209 sibling pairs with advanced AMD. For the GWAS, we included 2594 participants with advanced AMD subtypes and 4134 controls. Replication cohorts included 5383 advanced AMD participants and 15,240 controls.
Participants had AMD grade assigned based on fundus photography and/or examination. To determine heritability of advanced AMD subtypes, we performed a sibling correlation study. For the GWAS, we conducted genome-wide genotyping and imputed 6,036,699 single nucleotide polymorphism (SNPs). We then analyzed SNPs with a generalized linear model controlling for genotyping platform and genetic ancestry. The most significant associations were evaluated in independent cohorts.
Main Outcome Measures
Concordance of advanced AMD subtypes in sibling pairs and associations between SNPs with GA and CNV advanced AMD subtypes.
The difference between the observed and expected proportion of siblings concordant for the same subtype of advanced AMD was different to a statistically significant degree (P=4.2 x 10−5) meaning that siblings of probands with CNV or GA are more likely to develop CNV or GA, respectively. In the analysis comparing participants with CNV to those with GA, we observed a statistically significant association at the ARMS2/HTRA1 locus [rs10490924, odds ratio (OR)=1.47, P=4.3 ×10−9] which was confirmed in the replication samples (OR=1.38, P=7.4 x 10−14 for combined discovery and replication analysis).
Whether a patient with AMD develops CNV vs. GA is determined in part by genetic variation. In this large GWAS meta-analysis and replication analysis, the ARMS2/HTRA1 locus confers increased risk for both advanced AMD subtypes but imparts greater risk for CNV than for GA. This locus explains a small proportion of the excess sibling correlation for advanced AMD subtype. Other loci were detected with suggestive associations which differ for advanced AMD subtypes and deserve follow-up in additional studies.
MicroRNA (miR) expression may have prognostic value for many types of cancers. However, the miR literature comprises many small studies. We systematically reviewed and synthesized the evidence.
Using MEDLINE (last update December 2010), we identified English language studies that examined associations between miRs and cancer prognosis using tumor specimens for more than 10 patients during classifier development. We included studies that assessed a major clinical outcome (nodal disease, disease progression, response to therapy, metastasis, recurrence, or overall survival) in an agnostic fashion using either polymerase chain reaction or hybridized oligonucleotide microarrays.
Forty-six articles presenting results on 43 studies pertaining to 20 different types of malignancy were eligible for inclusion in this review. The median study size was 65 patients (interquartile range [IQR] = 34–129), the median number of miRs assayed was 328 (IQR = 250–470), and overall survival or recurrence were the most commonly measured outcomes (30 and 19 studies, respectively). External validation was performed in 21 studies, 20 of which reported at least one nominally statistically significant result for a miR classifier. The median hazard ratio for poor outcome in externally validated studies was 2.52 (IQR = 2.26–5.40). For all classifier miRs in studies that evaluated overall survival across diverse malignancies, the miRs most frequently associated with poor outcome after accounting for differences in miR assessment due to platform type were let-7 (decreased expression in patients with cancer) and miR 21 (increased expression).
MiR classifiers show promising prognostic associations with major cancer outcomes and specific miRs are consistently identified across diverse studies and platforms. These types of classifiers require careful external validation in large groups of cancer patients that have adequate protection from bias. –
Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed eQTL analysis and bioinformatics network analysis.
We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS-) and femoral neck (FN-) BMD, in 25,353 individuals from eight cohorts. In a second stage, we followed up the 12 top SNPs (P<1×10−5) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs.
We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 & p-value = 3.0×10−5; female effect = −0.007 & p-value=3.3×10−2) and eleven suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (P<5×10−8) gene-by-sex interaction in the joint analysis of discovery and replication cohorts.
Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found influencing BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08% of the variation in these traits per implicated SNP.
gene-by-sex; interaction; BMD; association; aging
BACKGROUND AND OBJECTIVE:
Optimal treatment decisions in children require sufficient evidence on the safety and efficacy of pharmaceuticals in pediatric patients. However, there is concern that not enough trials are conducted in children and that pediatric trials differ from those performed in adults. Our objective was to measure the prevalence of pediatric studies among clinical drug trials and compare trial characteristics and quality indicators between pediatric and adult drug trials.
For conditions representing a high burden of pediatric disease, we identified all drug trials registered in ClinicalTrials.gov with start dates between 2006 and 2011 and tracked the resulting publications. We measured the proportion of pediatric trials and subjects for each condition and compared pediatric and adult trial characteristics and quality indicators.
For the conditions selected, 59.9% of the disease burden was attributable to children, but only 12.0% (292/2440) of trials were pediatric (P < .001). Among pediatric trials, 58.6% were conducted without industry funding compared with 35.0% of adult trials (P < .001).
Fewer pediatric compared with adult randomized trials examined safety outcomes (10.1% vs 16.9%, P = .008). Pediatric randomized trials were slightly more likely to be appropriately registered before study start (46.9% vs 39.3%, P = .04) and had a modestly higher probability of publication in the examined time frame (32.8% vs 23.2%, P = .04).
There is substantial discrepancy between pediatric burden of disease and the amount of clinical trial research devoted to pediatric populations. This may be related in part to trial funding, with pediatric trials relying primarily on government and nonprofit organizations.
clinical trials; evidence-based medicine; pediatrics; medication use; research subjects
The ability of a scientist to maintain a continuous stream of publication may be important, because research requires continuity of effort. However, there is no data on what proportion of scientists manages to publish each and every year over long periods of time.
Using the entire Scopus database, we estimated that there are 15,153,100 publishing scientists (distinct author identifiers) in the period 1996–2011. However, only 150,608 (<1%) of them have published something in each and every year in this 16-year period (uninterrupted, continuous presence [UCP] in the literature). This small core of scientists with UCP are far more cited than others, and they account for 41.7% of all papers in the same period and 87.1% of all papers with >1000 citations in the same period. Skipping even a single year substantially affected the average citation impact. We also studied the birth and death dynamics of membership in this influential UCP core, by imputing and estimating UCP-births and UCP-deaths. We estimated that 16,877 scientists would qualify for UCP-birth in 1997 (no publication in 1996, UCP in 1997–2012) and 9,673 scientists had their UCP-death in 2010. The relative representation of authors with UCP was enriched in Medical Research, in the academic sector and in Europe/North America, while the relative representation of authors without UCP was enriched in the Social Sciences and Humanities, in industry, and in other continents.
The proportion of the scientific workforce that maintains a continuous uninterrupted stream of publications each and every year over many years is very limited, but it accounts for the lion’s share of researchers with high citation impact. This finding may have implications for the structure, stability and vulnerability of the scientific workforce.
personalized medicine; coronary artery disease; genotyping; SNP; preventive cardiology
Osteoarthritis (OA) is the most prevalent form of arthritis and accounts for substantial morbidity and disability, particularly in the elderly. It is characterized by changes in joint structure including degeneration of the articular cartilage and its etiology is multifactorial with a strong postulated genetic component. We performed a meta-analysis of four genome-wide association (GWA) studies of 2,371 knee OA cases and 35,909 controls in Caucasian populations. Replication of the top hits was attempted with data from additional ten replication datasets. With a cumulative sample size of 6,709 cases and 44,439 controls, we identified one genome-wide significant locus on chromosome 7q22 for knee OA (rs4730250, p-value=9.2×10−9), thereby confirming its role as a susceptibility locus for OA. The associated signal is located within a large (500kb) linkage disequilibrium (LD) block that contains six genes; PRKAR2B (protein kinase, cAMP-dependent, regulatory, type II, beta), HPB1 (HMG-box transcription factor 1), COG5 (component of oligomeric golgi complex 5), GPR22 (G protein-coupled receptor 22), DUS4L (dihydrouridine synthase 4-like), and BCAP29 (the B-cell receptor-associated protein 29). Gene expression analyses of the (six) genes in primary cells derived from different joint tissues confirmed expression of all the genes in the joint environment.
Industry involvement has been associated with more favourable cost-effectiveness ratios in cost-effectiveness analyses, but the mechanisms for this association are unclear. We evaluated whether the assumed accuracy of the Papanicolaou (Pap) test was correlated with the features of cost-effectiveness analysis studies.
We searched PubMed (last updated April 2010) for cost-effectiveness analysis studies in which at least one strategy involved the Pap test for cervical cancer. We assessed the baseline assumed diagnostic sensitivity and specificity of the Pap test in each study and the association of these values with three levels of manufacturer involvement in the study.
Among 88 analyzed cost-effectiveness analysis studies, the assumed sensitivity of the Pap test was lower in studies with manufacturer-affiliated authors, manufacturer funding or manufacturer-related competing interests versus studies without (mean sensitivity 60% v. 70%, p < 0.001). The assumed specificity of the Pap test was lower in cost-effectiveness analyses involving new screening tests (mean 93% v. 96%, p = 0.016). The assumed specificity did not differ between trials with manufacturer involvement versus those without (mean 95% v. 95%, p = 0.755).
The results of cost-effectiveness analyses may be affected by a downgrading of the assumed diagnostic accuracy of the standard Pap test against which newer tests or interventions are compared. New technology then seems to have more favourable results against a straw-man comparator.
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
For most associations of common polymorphisms with common diseases, the genetic model of inheritance is unknown. We extended and applied a Bayesian meta-analysis approach to data from 19 studies on 17 replicated associations for type 2 diabetes. For 13 polymorphisms, the data fit very well to an additive model, for 4 polymorphisms the data were consistent with either an additive or dominant model, and for 2 polymorphisms with an additive or recessive model of inheritance for the diabetes risk allele. Results were robust to using different priors and after excluding data where index polymorphisms had been examined indirectly through proxy markers. The Bayesian meta-analysis model yielded point estimates for the genetic effects that are very similar to those previously reported based on fixed or random effects models, but uncertainty about several of the effects was substantially larger. We also examined the extent of between-study heterogeneity in the genetic model and found generally small values of the between-study deviation for the genetic model parameter. Heterosis could not be excluded in 4 SNPs. Information on the genetic model of robustly replicated GWA-derived association signals may be useful for predictive modeling, and for designing biological and functional experiments.
Meta-analysis of multiple genome-wide association (GWA) studies has become common practice over the last few years. The main advantage of this technique is the maximization of power to detect the subtle genetic effects for common traits. Moreover, one can use meta-analysis to probe and identify heterogeneity in the effect sizes across the combined studies. In this review we systematically appraised and evaluated the characteristics of GWA meta-analyses with 10,000 or more subjects published until June 2012. We overview the current landscape of variants discovered by GWA meta-analyses and we discuss and assess with extrapolations from empirical data the value of larger meta-analyses for the discovery of additional genetic associations and new biology in the future. Finally, we discuss some emerging logistical and practical issues related to the conduct of meta-analysis of GWA studies.
variance explained; gene discovery; sample size; common variants; rare variants; missing heritability; consortium
The advent of genome-wide association studies has allowed considerable progress in the identification and robust replication of common gene variants that confer susceptibility to common diseases and other phenotypes of interest. These genetic effect sizes are almost invariably moderate-to-small in magnitude and single studies, even if large, are underpowered to detect them with confidence. Meta-analysis of many genome-wide association studies improves the power to detect more associations, and to investigate the consistency or heterogeneity of these associations across diverse datasets and study populations. In this review, we discuss the key methodological issues in the set-up, information gathering and processing, and analysis of meta-analyses of genome-wide association datasets. We illustrate, as an example, the application of meta-analysis methods in the elucidation of common genetic variants associated with type 2 diabetes. Finally, we discuss the prospects and caveats for future application of meta-analysis methods in the genome-wide setting.
meta-analysis; genome-wide association studies; replication; heterogeneity; methods
Leucine-rich repeat kinase 2 (LRRK2) is known to harbor highly penetrant mutations linked to familial parkinsonism. However, its full polymorphic variability in relationship to Parkinson’s disease (PD) risk has not been systematically assessed.
We examined the frequency pathogenicity of 121 exonic LRRK2 variants in three ethnic series (Caucasian [N=12,590], Asian [N=2,338] and Arab-Berber [N=612]) consisting of 8,611 patients and 6,929 control subjects from 23 separate sites of the Genetic Epidemiology of Parkinson’s Disease Consortium.
Excluding carriers of previously known pathogenic mutations, new independent risk associations were found for polymorphic variants in Caucasian (p.M1646T, OR: 1.43, 95% CI: 1.15 – 1.78, P=0.0012) and Asian (p.A419V, OR: 2.27, 95% CI: 1.35 – 3.83, P=0.0011) populations. In addition, a protective haplotype was observed at >5% frequency (p.N551K-p.R1398H-p.K1423K) in the Caucasian and Asian series’, with a similar finding in the small Arab-Berber series that requires further study (combined 3-series OR: 0.82, 95% CI: 0.72 – 0.94, P=0.0043). Of the two previously reported Asian risk variants p.G2385R was found to be associated with disease (OR: 1.73, 95% CI: 1.20 – 2.49, P=0.0026) but no association was observed for p.R1628P (OR: 0.62, 95% CI: 0.36 – 1.07, P=0.087). Also in the Arab-Berber series, p.Y2189C showed potential evidence of risk association with PD (OR: 4.48, 95% CI: 1.33 – 15.09, P=0.012). Of note, two variants (p.I1371V and p.T2356I) which have been previously proposed as pathogenic were observed in patient and control subjects at the same frequency.
LRRK2 offers an example where multiple rare and common genetic variants in the same gene have independent effects on disease risk. Lrrk2, and the pathway in which it functions, is important in the etiology and pathogenesis of a greater proportion of patients with PD than previously believed.
The present study and original funding for the GEO-PD Consortium was supported by grants from Michael J. Fox Foundation. Studies at individual sites were supported by a number of funding agencies world-wide.
Parkinson disease; LRRK2; genetics
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
To identify genes involved in osteoarthritis (OA), the most prevalent form of joint disease, we performed a genome-wide association study (GWAS) in which we tested 500,510 Single Nucelotide Polymorphisms (SNPs) in 1341 OA cases and 3496 Dutch Caucasian controls. SNPs associated with at least two OA-phenotypes were analysed in 14,938 OA cases and approximately 39,000 controls. The C-allele of rs3815148 on chromosome 7q22 (MAF 23%, 172 kb upstream of the GPR22 gene) was consistently associated with a 1.14-fold increased risk (95%CI: 1.09–1.19) for knee- and/or hand-OA (p=8×10−8), and also with a 30% increased risk for knee-OA progression (95%CI: 1.03–1.64, p=0.03). This SNP is in almost complete linkage disequilibrium with rs3757713 (located 68 kb upstream of GPR22) which is associated with GPR22 expression levels in lymphoblast cell lines (p=4×10−12). GPR22 encodes an G-protein coupled receptor with unkown ligand (orphan receptor). Immunohistochemistry experiments showed absence of GPR22 in normal mouse articular cartilage or synovium. However, GPR22 positive chondrocytes were found in the upper layers of the articular cartilage of mouse knee joints that were challenged by in vivo papain treatment or in the presence of interleukin-1 driven inflammation. GRP22 positive chondrocyte-like cells were also found in osteophytes in instability-induced OA. In addition, GPR22 is also present in areas of the brain involved in locomotor function. Our findings reveal a novel common variant on chromosome 7q22 to influence susceptibility for prevalence and progression of OA.
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.
Most studies on global health inequality consider unequal health care and socio-economic conditions but neglect inequality in the production of health knowledge relevant to addressing disease burden. We demonstrate this inequality and identify likely causes. Using disability-adjusted life years (DALYs) for 111 prominent medical conditions, assessed globally and nationally by the World Health Organization, we linked DALYs with MEDLINE articles for each condition to assess the influence of DALY-based global disease burden, compared to the global market for treatment, on the production of relevant MEDLINE articles, systematic reviews, clinical trials and research using animal models vs. humans. We then explored how DALYs, wealth, and the production of research within countries correlate with this global pattern. We show that global DALYs for each condition had a small, significant negative relationship with the production of each type of MEDLINE articles for that condition. Local processes of health research appear to be behind this. Clinical trials and animal studies but not systematic reviews produced within countries were strongly guided by local DALYs. More and less developed countries had very different disease profiles and rich countries publish much more than poor countries. Accordingly, conditions common to developed countries garnered more clinical research than those common to less developed countries. Many of the health needs in less developed countries do not attract attention among developed country researchers who produce the vast majority of global health knowledge—including clinical trials—in response to their own local needs. This raises concern about the amount of knowledge relevant to poor populations deficient in their own research infrastructure. We recommend measures to address this critical dimension of global health inequality.