Voting behavior during FDA Medical Device Advisory Committee panel meetings

OBJECTIVES: During premarket review, the US Food and Drug Administration may ask its Medical Device Advisory Committee (MDAC) Panels to assess the safety and effectiveness of medical devices being considered for approval. The objective of this study is to assess the relationship, if any, between individual votes and Panel recommendations and: (1) the composition of Panels, specifically the expertise and demographic features of individual members; or (2) Panel members\u27 propensity to speak during Panel deliberations. METHODS: This was a retrospective cohort study of routinely collected data from voting members of MDAC panels convened between January 2011 to June 2016 to consider premarket approval. Data sources were verbatim transcripts available publicly from the FDA. Number of words spoken, directionality of votes on device approval, profession, and demographics were collected. RESULTS: 658,954 words spoken by 536 members during 49 meetings of 11 Panels were analyzed. Based on multivariate analysis, biostatisticians spoke more (+373 words; P = 0.0002), and women (-187 words; P = 0.0184) and other non-physician voting members less (-213 words; P = 0.0306), than physicians. Speaking more was associated with abstaining (P = 0.0179), and with voting against the majority (P = 0.0153). Non-physician, non-biostatistician members (P = 0.0109), and those having attended more meetings as a voting member (P = 0.0249) were more likely to vote against approval. In bivariable analysis, unanimous Panels had a greater proportion of biostatisticians (mean 0.1580; 95% CI 0.1237-0.1923) than non-unanimous Panels (0.1107; 95% CI 0.0912-0.1301; p = 0.0201). CONCLUSIONS: Panelists likely to vote against the majority include non-physician, non-biostatisticians; experienced Panelists; and more talkative members. The increased presence of biostatisticians on Panels leads to greater voting consensus. Having a diversity of opinions on Panels, including in sufficient numbers those members likely to dissent from majority views, may help ensure that a diversity of opinions are aired before decision-making

Voting behavior during FDA Medical Device Advisory Committee panel meetings

Objectives During premarket review, the US Food and Drug Administration may ask its Medical Device Advisory Committee (MDAC) Panels to assess the safety and effectiveness of medical devices being considered for approval. The objective of this study is to assess the relationship, if any, between individual votes and Panel recommendations and: (1) the composition of Panels, specifically the expertise and demographic features of individual members; or (2) Panel members’ propensity to speak during Panel deliberations. Methods This was a retrospective cohort study of routinely collected data from voting members of MDAC panels convened between January 2011 to June 2016 to consider premarket approval. Data sources were verbatim transcripts available publicly from the FDA. Number of words spoken, directionality of votes on device approval, profession, and demographics were collected. Results 658,954 words spoken by 536 members during 49 meetings of 11 Panels were analyzed. Based on multivariate analysis, biostatisticians spoke more (+373 words; P = 0.0002), and women (-187 words; P = 0.0184) and other non-physician voting members less (-213 words; P = 0.0306), than physicians. Speaking more was associated with abstaining (P = 0.0179), and with voting against the majority (P = 0.0153). Non-physician, non-biostatistician members (P = 0.0109), and those having attended more meetings as a voting member (P = 0.0249) were more likely to vote against approval. In bivariable analysis, unanimous Panels had a greater proportion of biostatisticians (mean 0.1580; 95% CI 0.1237–0.1923) than non-unanimous Panels (0.1107; 95% CI 0.0912–0.1301; p = 0.0201). Conclusions Panelists likely to vote against the majority include non-physician, non-biostatisticians; experienced Panelists; and more talkative members. The increased presence of biostatisticians on Panels leads to greater voting consensus. Having a diversity of opinions on Panels, including in sufficient numbers those members likely to dissent from majority views, may help ensure that a diversity of opinions are aired before decision-making

Protocol for development of a core outcome set for clinical trials in melasma

INTRODUCTION: Melasma is a pigmentation disorder of the skin. Characterised by brown to gray-brown patches on the face and neck, the condition predominantly affects women and has been associated with pregnancy, hormonal variation and sun exposure. Melasma can be disfiguring and anxiety-provoking, and quality of life is often adversely impacted. Management includes sun protection, laser and energy device therapy, topical and oral skin-bleaching agents and chemical peels. While clinical trials of melasma exist, there is a lack of consistency in reported outcomes, which has been a barrier to the aggregation of data in systematic reviews and meta-analyses. This protocol describes a planned process for development of a minimum set of outcomes (ie, ‘core outcome set’) that should be measured in all clinical trials of melasma. METHODS AND ANALYSIS: An exhaustive list of potential outcomes will be extracted from four sources: (1) systematic literature review of outcomes in clinical trials; (2) semistructured patient interviews; (3) brochures, pamphlets, clinical trial registries, and other published and unpublished sources and documentation; and (4) interviews with non-patient, non-physician stakeholders, including federal regulators, industry scientists and non-physician providers. An international two-round Delphi process will then be performed to identify the outcomes deemed most important to patients and physicians. Subsequently, a consensus meeting will be convened to review and process the results, and to vote on a final set of core outcomes. ETHICS AND DISSEMINATION: Ethics approval was provided by the Northwestern University Institutional Review Board (protocol ID: STU00201637). This study is registered with both the Core Outcome Measures in Effectiveness Trials and Cochrane Skin-Core Outcome Set Initiative initiatives, and this protocol is in accordance with the guidelines for protocol development of both groups. All findings from the study described in this protocol will be disseminated to all stakeholders involved in the development process and will be submitted for publication in peer-reviewed journals. PROSPERO REGISTRATION NUMBER: CRD42020214189

Biological, clinical and population relevance of 95 loci for blood lipids.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD

Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche.

Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

Identification of biomolecule mass transport and binding rate parameters in living cells by inverse modeling

BACKGROUND: Quantification of in-vivo biomolecule mass transport and reaction rate parameters from experimental data obtained by Fluorescence Recovery after Photobleaching (FRAP) is becoming more important. METHODS AND RESULTS: The Osborne-Moré extended version of the Levenberg-Marquardt optimization algorithm was coupled with the experimental data obtained by the Fluorescence Recovery after Photobleaching (FRAP) protocol, and the numerical solution of a set of two partial differential equations governing macromolecule mass transport and reaction in living cells, to inversely estimate optimized values of the molecular diffusion coefficient and binding rate parameters of GFP-tagged glucocorticoid receptor. The results indicate that the FRAP protocol provides enough information to estimate one parameter uniquely using a nonlinear optimization technique. Coupling FRAP experimental data with the inverse modeling strategy, one can also uniquely estimate the individual values of the binding rate coefficients if the molecular diffusion coefficient is known. One can also simultaneously estimate the dissociation rate parameter and molecular diffusion coefficient given the pseudo-association rate parameter is known. However, the protocol provides insufficient information for unique simultaneous estimation of three parameters (diffusion coefficient and binding rate parameters) owing to the high intercorrelation between the molecular diffusion coefficient and pseudo-association rate parameter. Attempts to estimate macromolecule mass transport and binding rate parameters simultaneously from FRAP data result in misleading conclusions regarding concentrations of free macromolecule and bound complex inside the cell, average binding time per vacant site, average time for diffusion of macromolecules from one site to the next, and slow or rapid mobility of biomolecules in cells. CONCLUSION: To obtain unique values for molecular diffusion coefficient and binding rate parameters from FRAP data, we propose conducting two FRAP experiments on the same class of macromolecule and cell. One experiment should be used to measure the molecular diffusion coefficient independently of binding in an effective diffusion regime and the other should be conducted in a reaction dominant or reaction-diffusion regime to quantify binding rate parameters. The method described in this paper is likely to be widely used to estimate in-vivo biomolecule mass transport and binding rate parameters

Rare coding variants and X-linked loci associated with age at menarche.

More than 100 loci have been identified for age at menarche by genome-wide association studies; however, collectively these explain only ∼3% of the trait variance. Here we test two overlooked sources of variation in 192,974 European ancestry women: low-frequency protein-coding variants and X-chromosome variants. Five missense/nonsense variants (in ALMS1/LAMB2/TNRC6A/TACR3/PRKAG1) are associated with age at menarche (minor allele frequencies 0.08-4.6%; effect sizes 0.08-1.25 years per allele; P<5 × 10(-8)). In addition, we identify common X-chromosome loci at IGSF1 (rs762080, P=9.4 × 10(-13)) and FAAH2 (rs5914101, P=4.9 × 10(-10)). Highlighted genes implicate cellular energy homeostasis, post-transcriptional gene silencing and fatty-acid amide signalling. A frequently reported mutation in TACR3 for idiopathic hypogonatrophic hypogonadism (p.W275X) is associated with 1.25-year-later menarche (P=2.8 × 10(-11)), illustrating the utility of population studies to estimate the penetrance of reportedly pathogenic mutations. Collectively, these novel variants explain ∼0.5% variance, indicating that these overlooked sources of variation do not substantially explain the 'missing heritability' of this complex trait.UK sponsors (see article for overseas ones): This work made use of data and samples generated by the 1958 Birth Cohort (NCDS). Access to these resources was enabled via the 58READIE Project funded by Wellcome Trust and Medical Research Council (grant numbers WT095219MA and G1001799). A full list of the financial, institutional and personal contributions to the development of the 1958 Birth Cohort Biomedical resource is available at http://www2.le.ac.uk/projects/birthcohort. Genotyping was undertaken as part of the Wellcome Trust Case-Control Consortium (WTCCC) under Wellcome Trust award 076113, and a full list of the investigators who contributed to the generation of the data is available at www.wtccc.org.uk ... The Fenland Study is funded by the Wellcome Trust and the Medical Research Council, as well as by the Support for Science Funding programme and CamStrad. ... SIBS - CRUK ref: C1287/A8459 SEARCH - CRUK ref: A490/A10124 EMBRACE is supported by Cancer Research UK Grants C1287/A10118, C1287/A16563 and C1287/A17523. Genotyping was supported by Cancer Research - UK grant C12292/A11174D and C8197/A16565. Gareth Evans and Fiona Lalloo are supported by an NIHR grant to the Biomedical Research Centre, Manchester. The Investigators at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust are supported by an NIHR grant to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. Ros Eeles and Elizabeth Bancroft are supported by Cancer Research UK Grant C5047/A8385. ... Generation Scotland - Scottish Executive Health Department, Chief Scientist Office, grant number CZD/16/6. Exome array genotyping for GS:SFHS was funded by the Medical Research Council UK. 23andMe - This work was supported in part by NIH Award 2R44HG006981-02 from the National Human Genome Research Institute.This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/ncomms875

The Molecular Genetic Architecture of Self-Employment

Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable-entrepreneurship-that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg2/σP2= 25%, h2= 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10-5were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases