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1.  Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture 
Estrada, Karol | Styrkarsdottir, Unnur | Evangelou, Evangelos | Hsu, Yi-Hsiang | Duncan, Emma L | Ntzani, Evangelia E | Oei, Ling | Albagha, Omar M E | Amin, Najaf | Kemp, John P | Koller, Daniel L | Li, Guo | Liu, Ching-Ti | Minster, Ryan L | Moayyeri, Alireza | Vandenput, Liesbeth | Willner, Dana | Xiao, Su-Mei | Yerges-Armstrong, Laura M | Zheng, Hou-Feng | Alonso, Nerea | Eriksson, Joel | Kammerer, Candace M | Kaptoge, Stephen K | Leo, Paul J | Thorleifsson, Gudmar | Wilson, Scott G | Wilson, James F | Aalto, Ville | Alen, Markku | Aragaki, Aaron K | Aspelund, Thor | Center, Jacqueline R | Dailiana, Zoe | Duggan, David J | Garcia, Melissa | Garcia-Giralt, Natàlia | Giroux, Sylvie | Hallmans, Göran | Hocking, Lynne J | Husted, Lise Bjerre | Jameson, Karen A | Khusainova, Rita | Kim, Ghi Su | Kooperberg, Charles | Koromila, Theodora | Kruk, Marcin | Laaksonen, Marika | Lacroix, Andrea Z | Lee, Seung Hun | Leung, Ping C | Lewis, Joshua R | Masi, Laura | Mencej-Bedrac, Simona | Nguyen, Tuan V | Nogues, Xavier | Patel, Millan S | Prezelj, Janez | Rose, Lynda M | Scollen, Serena | Siggeirsdottir, Kristin | Smith, Albert V | Svensson, Olle | Trompet, Stella | Trummer, Olivia | van Schoor, Natasja M | Woo, Jean | Zhu, Kun | Balcells, Susana | Brandi, Maria Luisa | Buckley, Brendan M | Cheng, Sulin | Christiansen, Claus | Cooper, Cyrus | Dedoussis, George | Ford, Ian | Frost, Morten | Goltzman, David | González-Macías, Jesús | Kähönen, Mika | Karlsson, Magnus | Khusnutdinova, Elza | Koh, Jung-Min | Kollia, Panagoula | Langdahl, Bente Lomholt | Leslie, William D | Lips, Paul | Ljunggren, Östen | Lorenc, Roman S | Marc, Janja | Mellström, Dan | Obermayer-Pietsch, Barbara | Olmos, José M | Pettersson-Kymmer, Ulrika | Reid, David M | Riancho, José A | Ridker, Paul M | Rousseau, François | Slagboom, P Eline | Tang, Nelson LS | Urreizti, Roser | Van Hul, Wim | Viikari, Jorma | Zarrabeitia, María T | Aulchenko, Yurii S | Castano-Betancourt, Martha | Grundberg, Elin | Herrera, Lizbeth | Ingvarsson, Thorvaldur | Johannsdottir, Hrefna | Kwan, Tony | Li, Rui | Luben, Robert | Medina-Gómez, Carolina | Palsson, Stefan Th | Reppe, Sjur | Rotter, Jerome I | Sigurdsson, Gunnar | van Meurs, Joyce B J | Verlaan, Dominique | Williams, Frances MK | Wood, Andrew R | Zhou, Yanhua | Gautvik, Kaare M | Pastinen, Tomi | Raychaudhuri, Soumya | Cauley, Jane A | Chasman, Daniel I | Clark, Graeme R | Cummings, Steven R | Danoy, Patrick | Dennison, Elaine M | Eastell, Richard | Eisman, John A | Gudnason, Vilmundur | Hofman, Albert | Jackson, Rebecca D | Jones, Graeme | Jukema, J Wouter | Khaw, Kay-Tee | Lehtimäki, Terho | Liu, Yongmei | Lorentzon, Mattias | McCloskey, Eugene | Mitchell, Braxton D | Nandakumar, Kannabiran | Nicholson, Geoffrey C | Oostra, Ben A | Peacock, Munro | Pols, Huibert A P | Prince, Richard L | Raitakari, Olli | Reid, Ian R | Robbins, John | Sambrook, Philip N | Sham, Pak Chung | Shuldiner, Alan R | Tylavsky, Frances A | van Duijn, Cornelia M | Wareham, Nick J | Cupples, L Adrienne | Econs, Michael J | Evans, David M | Harris, Tamara B | Kung, Annie Wai Chee | Psaty, Bruce M | Reeve, Jonathan | Spector, Timothy D | Streeten, Elizabeth A | Zillikens, M Carola | Thorsteinsdottir, Unnur | Ohlsson, Claes | Karasik, David | Richards, J Brent | Brown, Matthew A | Stefansson, Kari | Uitterlinden, André G | Ralston, Stuart H | Ioannidis, John P A | Kiel, Douglas P | Rivadeneira, Fernando
Nature genetics  2012;44(5):491-501.
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.
PMCID: PMC3338864  PMID: 22504420
2.  Placing epidemiological results in the context of multiplicity and typical correlations of exposures 
Epidemiological studies evaluate multiple exposures, but the extent of multiplicity often remains non-transparent when results are reported. There is extensive debate in the literature on whether multiplicity should be adjusted for in the design, analysis, and reporting of most epidemiological studies, and, if so, how this should be done. The challenges become more acute in an era where the number of exposures that can be studied (the exposome) can be very large. Here, we argue that it can be very insightful to visualize and describe the extent of multiplicity by reporting the number of effective exposures for each category of exposures being assessed, and to describe the distribution of correlation between exposures and/or between exposures and outcomes in epidemiological datasets. The results of new proposed associations can be placed in the context of this background information. An association can be assigned to a percentile of magnitude of effect based on the distribution of effects seen in the field. We offer an example of how such information can be routinely presented in an epidemiological study/dataset using data on 530 exposure and demographic variables classified in 32 categories in the National Health and Nutrition Examination Survey (NHANES). Effects that survive multiplicity considerations and that are large may be prioritized for further scrutiny.
PMCID: PMC4545966  PMID: 24923805
3.  Design and Analysis for Studying microRNAs in Human Disease: A Primer on -Omic Technologies 
American Journal of Epidemiology  2014;180(2):140-152.
microRNAs (miRNAs) are fundamental to cellular biology. Although only approximately 22 bases long, miRNAs regulate complex processes in health and disease, including human cancer. Because miRNAs are highly stable in circulation when compared with several other classes of nucleic acids, they have generated intense interest as clinical biomarkers in diverse epidemiologic studies. As with other molecular biomarker fields, however, miRNA research has become beleaguered by pitfalls related to terminology and classification; procedural, assay, and study cohort heterogeneity; and methodological inconsistencies. Together, these issues have led to both false-positive and potentially false-negative miRNA associations. In this review, we summarize the biological rationale for studying miRNAs in human disease with a specific focus on circulating miRNAs, which highlight some of the most challenging topics in the field to date. Examples from lung cancer are used to illustrate the potential utility and some of the pitfalls in contemporary miRNA research. Although the field is in its infancy, several important lessons have been learned relating to cohort development, sample preparation, and statistical analysis that should be considered for future studies. The goal of this primer is to equip epidemiologists and clinical researchers with sound principles of study design and analysis when using miRNAs.
PMCID: PMC4082346  PMID: 24966218
blood; cancer; circulating biomarkers; lung cancer; microRNA; review
4.  Effects of Interventions on Survival in Acute Respiratory Distress Syndrome: an Umbrella Review of 159 Published Randomized Trials and 29 Meta-analyses 
Intensive care medicine  2014;40(6):769-787.
Multiple interventions have been tested in acute respiratory distress syndrome (ARDS). We examined the entire agenda of published randomized controlled trials (RCTs) in ARDS that reported on mortality and of respective meta-analyses.
We searched PubMed, the Cochrane Library and Web of Knowledge until July 2013. We included RCTs in ARDS published in English. We excluded trials of newborns and children; and those on short-term interventions, ARDS prevention or post-traumatic lung injury. We also reviewed all meta-analyses of RCTs in this field that addressed mortality. Treatment modalities were grouped in five categories: mechanical ventilation strategies and respiratory care, enteral or parenteral therapies, inhaled / intratracheal medications, nutritional support and hemodynamic monitoring.
We identified 159 published RCTs of which 93 had overall mortality reported (n= 20,671 patients) - 44 trials (14,426 patients) reported mortality as a primary outcome. A statistically significant survival benefit was observed in 8 trials (7 interventions) and two trials reported an adverse effect on survival. Among RTCs with >50 deaths in at least 1 treatment arm (n=21), 2 showed a statistically significant mortality benefit of the intervention (lower tidal volumes and prone positioning), 1 showed a statistically significant mortality benefit only in adjusted analyses (cisatracurium) and 1 (high-frequency oscillatory ventilation) showed a significant detrimental effect. Across 29 meta-analyses, the most consistent evidence was seen for low tidal volumes and prone positioning in severe ARDS.
There is limited supportive evidence that specific interventions can decrease mortality in ARDS. While low tidal volumes and prone positioning in severe ARDS seem effective, most sporadic findings of interventions suggesting reduced mortality are not corroborated consistently in large-scale evidence including meta-analyses.
PMCID: PMC4031289  PMID: 24667919
Acute respiratory distress syndrome; treatment; survival; mortality
5.  Publication and other reporting biases in cognitive sciences: detection, prevalence and prevention 
Trends in cognitive sciences  2014;18(5):235-241.
Recent systematic reviews and empirical evaluations of the cognitive sciences literature suggest that publication and other reporting biases are prevalent across diverse domains of cognitive science. This review summarizes the various forms of publication and reporting biases and other questionable research practices, and overviews the available methods for probing into their existence. We discuss the available empirical evidence for the presence of such biases across the neuroimaging, animal, other pre-clinical, psychological, clinical trials, and genetics literature in the cognitive sciences. We also highlight emerging solutions (from study design to data analyses and reporting) to prevent bias and improve the fidelity in the field of cognitive science research.
PMCID: PMC4078993  PMID: 24656991
publication bias; reporting bias; cognitive sciences; neuroscience; bias
6.  Large-Scale Analysis of Association Between GDF5 and FRZB Variants and Osteoarthritis of the Hip, Knee, and Hand 
Arthritis and rheumatism  2009;60(6):1710-1721.
GDF5 and FRZB have been proposed as genetic loci conferring susceptibility to osteoarthritis (OA); however, the results of several studies investigating the association of OA with the rs143383 polymorphism of the GDF5 gene or the rs7775 and rs288326 polymorphisms of the FRZB gene have been conflicting or inconclusive. To examine these associations, we performed a large-scale meta-analysis of individual-level data.
Fourteen teams contributed data on polymorphisms and knee, hip, and hand OA. For rs143383, the total number of cases and controls, respectively, was 5,789 and 7,850 for hip OA, 5,085 and 8,135 for knee OA, and 4,040 and 4,792 for hand OA. For rs7775, the respective sample sizes were 4,352 and 10,843 for hip OA, 3,545 and 6,085 for knee OA, and 4,010 and 5,151 for hand OA, and for rs288326, they were 4,346 and 8,034 for hip OA, 3,595 and 6,106 for knee OA, and 3,982 and 5,152 for hand OA. For each individual study, sex-specific odds ratios (ORs) were calculated for each OA phenotype that had been investigated. The ORs for each phenotype were synthesized using both fixed-effects and random-effects models for allele-based effects, and also for haplotype effects for FRZB.
A significant random-effects summary OR for knee OA was demonstrated for rs143383 (1.15 [95% confidence interval 1.09–1.22]) (P = 9.4 × 10−7), with no significant between-study heterogeneity. Estimates of effect sizes for hip and hand OA were similar, but a large between-study heterogeneity was observed, and statistical significance was borderline (for OA of the hip [P = 0.016]) or absent (for OA of the hand [P = 0.19]). Analyses for FRZB polymorphisms and haplotypes did not reveal any statistically significant signals, except for a borderline association of rs288326 with hip OA (P = 0.019).
Evidence of an association between the GDF5 rs143383 polymorphism and OA is substantially strong, but the genetic effects are consistent across different populations only for knee OA. Findings of this collaborative analysis do not support the notion that FRZB rs7775 or rs288326 has any sizable genetic effect on OA phenotypes.
PMCID: PMC4412885  PMID: 19479880
7.  Unscientific Beliefs about Scientific Topics in Nutrition123 
Advances in Nutrition  2014;5(5):563-565.
Humans interact with food daily. Such repeated exposure creates a widespread, superficial familiarity with nutrition. Personal familiarity with nutrition from individual and cultural perspectives may give rise to beliefs about food not grounded in scientific evidence. In this summary of the session entitled “Unscientific Beliefs about Scientific Topics in Nutrition,” we discuss accumulated work illustrating and quantifying potentially misleading practices in the conduct and, more so, reporting of nutrition science along with proposed approaches to amelioration. We begin by defining “unscientific beliefs” and from where such beliefs may come, followed by discussing how large bodies of nutritional epidemiologic observations not only create highly improbable patterns of association but implausible magnitudes of implied effect. Poor reporting practices, biases, and methodologic issues that have distorted scientific understandings of nutrition are presented, followed by potential influences of conflicts of interest that extend beyond financial considerations. We conclude with recommendations for improving the conduct, reporting, and communication of nutrition-related research to ground discussions in evidence rather than solely on beliefs.
PMCID: PMC4188234  PMID: 25469397
8.  Endgame: engaging the tobacco industry in its own elimination 
A billion deaths from tobacco are expected by 2100. Many policy interventions such as increased taxation, restrictions on advertisement, smoking bans, as well as behavioral interventions, such as pharmacological and psychological treatments for smoking cessation, decrease tobacco use, but they reach their limits. Endgame scenarios focusing on tobacco supply rather than demand are increasingly discussed, but meet with resistance by the industry and even by many tobacco control experts. A main stumbling block that requires more attention is what to do with the tobacco industry in endgame scenarios. This industry has employed notoriously talented experts in law, business, organization, marketing, advertising, strategy, policy, and statistics and has tremendous lobbying power. Performance-based regulatory approaches can pose a legal obligation on manufacturers to decrease – and eventually – eliminate tobacco products according to specified schedules. Penalties and rewards can make such plans both beneficial for public health and attractive to the companies that do the job well. We discuss caveats and reality checks of engaging the tobacco industry to eliminate its current market and change focus. Brainstorming is warranted to entice the industry to abandon tobacco for other profit goals. To get the dialogue started, we propose the wild possibility of hiring former tobacco companies to reduce the costs of healthcare, thereby addressing concurrently two major challenges to public health.
PMCID: PMC4038649  PMID: 24117211
9.  Corrigendum: Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example 
Frontiers in Genetics  2015;6:231.
PMCID: PMC4493401  PMID: 26217377
risk prediction; genetic risk score (GRS); electronic health records; cardiovascular diseases; coronary disease; biomarkers
10.  How to Make More Published Research True 
PLoS Medicine  2014;11(10):e1001747.
In a 2005 paper that has been accessed more than a million times, John Ioannidis explained why most published research findings were false. Here he revisits the topic, this time to address how to improve matters.
Please see later in the article for the Editors' Summary
PMCID: PMC4204808  PMID: 25334033
11.  Geometry of the Randomized Evidence for Treatments of Pulmonary Hypertension 
Cardiovascular therapeutics  2013;31(6):e138-e146.
We studied the entire agenda of randomized clinical trials in pulmonary hyper-tension (PH) using sociological methods. We explored the geometry of the PH network to interpret the evidence on multiple competing treatments for the same indication.
We searched MEDLINE, Embase and Cochrane Library Databases for published studies. We queried and WHO International Clinical Trials Registry platform for non-published studies.
We found 75 randomized trials (41 published [n = 4136 participants] and 34 registered unpublished [planned n = 3470 participants]). Of the published randomized studies, all used placebo as the comparator arm except for two nonindustry-sponsored comparisons between phosphodiestearase-5 (PDE-5) inhibitors and endothelin receptor antagonists (ERA), and one study comparing two different regimens of treprostinil. Similarly, only five unpublished/ongoing trials used an active PH treatment as comparator (PDE-5 inhibitors versus ERA (n = 3), different doses of sildenafil (n = 1) and two formulations of epoprostenol (n = 1). Of the 75 trials, 47 were sponsored by the manufacturer of the tested active product(s), and only two trials were sponsored by two companies comparing their products.
The relative merits of different treatment options are not directly known, as there are very few head-to-head comparisons. A limited number of ongoing studies are using active FDA-approved PH-treatments for comparison. This lack of information can be overcome by carefully designing comparative effectiveness trials.
PMCID: PMC4480770  PMID: 24112824
Pulmonary hypertension; Treatment
12.  Correction: Geographic and Temporal Trends in the Molecular Epidemiology and Genetic Mechanisms of Transmitted HIV-1 Drug Resistance: An Individual-Patient- and Sequence-Level Meta-Analysis 
Rhee, Soo-Yon | Blanco, Jose Luis | Jordan, Michael R. | Taylor, Jonathan | Lemey, Philippe | Varghese, Vici | Hamers, Raph L. | Bertagnolio, Silvia | de Wit, Tobias F. Rinke | Aghokeng, Avelin F. | Albert, Jan | Avi, Radko | Avila-Rios, Santiago | Bessong, Pascal O. | Brooks, James I. | Boucher, Charles A. B. | Brumme, Zabrina L. | Busch, Michael P. | Bussmann, Hermann | Chaix, Marie-Laure | Chin, Bum Sik | D’Aquin, Toni T. | De Gascun, Cillian F. | Derache, Anne | Descamps, Diane | Deshpande, Alaka K. | Djoko, Cyrille F. | Eshleman, Susan H. | Fleury, Herve | Frange, Pierre | Fujisaki, Seiichiro | Harrigan, P. Richard | Hattori, Junko | Holguin, Africa | Hunt, Gillian M. | Ichimura, Hiroshi | Kaleebu, Pontiano | Katzenstein, David | Kiertiburanakul, Sasisopin | Kim, Jerome H. | Kim, Sung Soon | Li, Yanpeng | Lutsar, Irja | Morris, Lynn | Ndembi, Nicaise | Kee, Peng NG | Paranjape, Ramesh S. | Peeters, Martine | Poljak, Mario | Price, Matt A. | Ragonnet-Cronin, Manon L. | Reyes-Terán, Gustavo | Rolland, Morgane | Sirivichayakul, Sunee | Smith, Davey M. | Soares, Marcelo A. | Soriano, Vincent V. | Ssemwanga, Deogratius | Stanojevic, Maja | Stefani, Mariane A. | Sugiura, Wataru | Sungkanuparph, Somnuek | Tanuri, Amilcar | Tee, Kok Keng | Truong, Hong-Ha M. | van de Vijver, David A. M. C. | Vidal, Nicole | Yang, Chunfu | Yang, Rongge | Yebra, Gonzalo | Ioannidis, John P. A. | Vandamme, Anne-Mieke | Shafer, Robert W.
PLoS Medicine  2015;12(6):e1001845.
PMCID: PMC4452696  PMID: 26030872
13.  Studying the Elusive Environment in Large Scale 
PMCID: PMC4110965  PMID: 24893084
14.  A Nutrient-Wide Association Study on Blood Pressure 
Circulation  2012;126(21):2456-2464.
A nutrient-wide approach may be useful comprehensively to test and validate associations between nutrients (derived from foods and supplements) and blood pressure (BP) in an unbiased manner.
Methods and Results
Data from 4,680 participants ages 40–59 in the cross-sectional International Study of Macro/Micro-nutrients and Blood Pressure (INTERMAP) were stratified randomly into training and testing sets. NHANES cross-sectional cohorts of 1999–2000 to 2005–2006 were used for external validation. We performed multiple linear regression analyses associating each of 82 nutrients and 3 urine electrolytes with systolic and diastolic BP in the INTERMAP training set. Significant findings were validated in the INTERMAP testing set and further in the NHANES cohorts (False Discovery Rate <5% in training, p<0.05 for internal and external validation). Among the validated nutrients, alcohol and urinary sodium-to-potassium ratio were directly associated with systolic BP, and dietary phosphorus, magnesium, iron, thiamin, folacin, and riboflavin were inversely associated with systolic BP. In addition, dietary folacin, and riboflavin were inversely associated with diastolic BP. The absolute effect sizes in the validation data (NHANES) ranged from 0.97 mmHg lower systolic BP (phosphorus) to 0.39 mmHg lower systolic BP (thiamin) per 1SD difference in nutrient variable. Inclusion of nutrient intake from supplements in addition to foods gave similar results for some nutrients, though it attenuated the associations of folacin, thiamin and riboflavin intake with BP.
We identified significant inverse associations between B vitamins and BP, relationships hitherto poorly investigated. Our analyses represent a systematic unbiased approach to the evaluation and validation of nutrient-BP associations.
PMCID: PMC4105584  PMID: 23093587
lood pressure; diet; epidemiology; nutrition
15.  Quantifying rare, deleterious variation in 12 human cytochrome P450 drug-metabolism genes in a large-scale exome dataset 
Human Molecular Genetics  2013;23(8):1957-1963.
The study of genetic influences on drug response and efficacy (‘pharmacogenetics’) has existed for over 50 years. Yet, we still lack a complete picture of how genetic variation, both common and rare, affects each individual's responses to medications. Exome sequencing is a promising alternative method for pharmacogenetic discovery as it provides information on both common and rare variation in large numbers of individuals. Using exome data from 2203 AA and 4300 Caucasian individuals through the NHLBI Exome Sequencing Project, we conducted a survey of coding variation within 12 Cytochrome P450 (CYP) genes that are collectively responsible for catalyzing nearly 75% of all known Phase I drug oxidation reactions. In addition to identifying many polymorphisms with known pharmacogenetic effects, we discovered over 730 novel nonsynonymous alleles across the 12 CYP genes of interest. These alleles include many with diverse functional effects such as premature stop codons, aberrant splicesites and mutations at conserved active site residues. Our analysis considering both novel, predicted functional alleles as well as known, actionable CYP alleles reveals that rare, deleterious variation contributes markedly to the overall burden of pharmacogenetic alleles within the populations considered, and that the contribution of rare variation to this burden is over three times greater in AA individuals as compared with Caucasians. While most of these impactful alleles are individually rare, 7.6–11.7% of individuals interrogated in the study carry at least one newly described potentially deleterious alleles in a major drug-metabolizing CYP.
PMCID: PMC3959810  PMID: 24282029
16.  Geographic and Temporal Trends in the Molecular Epidemiology and Genetic Mechanisms of Transmitted HIV-1 Drug Resistance: An Individual-Patient- and Sequence-Level Meta-Analysis 
Rhee, Soo-Yon | Blanco, Jose Luis | Jordan, Michael R. | Taylor, Jonathan | Lemey, Philippe | Varghese, Vici | Hamers, Raph L. | Bertagnolio, Silvia | de Wit, Tobias F. Rinke | Aghokeng, Avelin F. | Albert, Jan | Avi, Radko | Avila-Rios, Santiago | Bessong, Pascal O. | Brooks, James I. | Boucher, Charles A. B. | Brumme, Zabrina L. | Busch, Michael P. | Bussmann, Hermann | Chaix, Marie-Laure | Chin, Bum Sik | D’Aquin, Toni T. | De Gascun, Cillian F. | Derache, Anne | Descamps, Diane | Deshpande, Alaka K. | Djoko, Cyrille F. | Eshleman, Susan H. | Fleury, Herve | Frange, Pierre | Fujisaki, Seiichiro | Harrigan, P. Richard | Hattori, Junko | Holguin, Africa | Hunt, Gillian M. | Ichimura, Hiroshi | Kaleebu, Pontiano | Katzenstein, David | Kiertiburanakul, Sasisopin | Kim, Jerome H. | Kim, Sung Soon | Li, Yanpeng | Lutsar, Irja | Morris, Lynn | Ndembi, Nicaise | NG, Kee Peng | Paranjape, Ramesh S. | Peeters, Martine | Poljak, Mario | Price, Matt A. | Ragonnet-Cronin, Manon L. | Reyes-Terán, Gustavo | Rolland, Morgane | Sirivichayakul, Sunee | Smith, Davey M. | Soares, Marcelo A. | Soriano, Vincent V. | Ssemwanga, Deogratius | Stanojevic, Maja | Stefani, Mariane A. | Sugiura, Wataru | Sungkanuparph, Somnuek | Tanuri, Amilcar | Tee, Kok Keng | Truong, Hong-Ha M. | van de Vijver, David A. M. C. | Vidal, Nicole | Yang, Chunfu | Yang, Rongge | Yebra, Gonzalo | Ioannidis, John P. A. | Vandamme, Anne-Mieke | Shafer, Robert W.
PLoS Medicine  2015;12(4):e1001810.
Regional and subtype-specific mutational patterns of HIV-1 transmitted drug resistance (TDR) are essential for informing first-line antiretroviral (ARV) therapy guidelines and designing diagnostic assays for use in regions where standard genotypic resistance testing is not affordable. We sought to understand the molecular epidemiology of TDR and to identify the HIV-1 drug-resistance mutations responsible for TDR in different regions and virus subtypes.
Methods and Findings
We reviewed all GenBank submissions of HIV-1 reverse transcriptase sequences with or without protease and identified 287 studies published between March 1, 2000, and December 31, 2013, with more than 25 recently or chronically infected ARV-naïve individuals. These studies comprised 50,870 individuals from 111 countries. Each set of study sequences was analyzed for phylogenetic clustering and the presence of 93 surveillance drug-resistance mutations (SDRMs). The median overall TDR prevalence in sub-Saharan Africa (SSA), south/southeast Asia (SSEA), upper-income Asian countries, Latin America/Caribbean, Europe, and North America was 2.8%, 2.9%, 5.6%, 7.6%, 9.4%, and 11.5%, respectively. In SSA, there was a yearly 1.09-fold (95% CI: 1.05–1.14) increase in odds of TDR since national ARV scale-up attributable to an increase in non-nucleoside reverse transcriptase inhibitor (NNRTI) resistance. The odds of NNRTI-associated TDR also increased in Latin America/Caribbean (odds ratio [OR] = 1.16; 95% CI: 1.06–1.25), North America (OR = 1.19; 95% CI: 1.12–1.26), Europe (OR = 1.07; 95% CI: 1.01–1.13), and upper-income Asian countries (OR = 1.33; 95% CI: 1.12–1.55). In SSEA, there was no significant change in the odds of TDR since national ARV scale-up (OR = 0.97; 95% CI: 0.92–1.02). An analysis limited to sequences with mixtures at less than 0.5% of their nucleotide positions—a proxy for recent infection—yielded trends comparable to those obtained using the complete dataset. Four NNRTI SDRMs—K101E, K103N, Y181C, and G190A—accounted for >80% of NNRTI-associated TDR in all regions and subtypes. Sixteen nucleoside reverse transcriptase inhibitor (NRTI) SDRMs accounted for >69% of NRTI-associated TDR in all regions and subtypes. In SSA and SSEA, 89% of NNRTI SDRMs were associated with high-level resistance to nevirapine or efavirenz, whereas only 27% of NRTI SDRMs were associated with high-level resistance to zidovudine, lamivudine, tenofovir, or abacavir. Of 763 viruses with TDR in SSA and SSEA, 725 (95%) were genetically dissimilar; 38 (5%) formed 19 sequence pairs. Inherent limitations of this study are that some cohorts may not represent the broader regional population and that studies were heterogeneous with respect to duration of infection prior to sampling.
Most TDR strains in SSA and SSEA arose independently, suggesting that ARV regimens with a high genetic barrier to resistance combined with improved patient adherence may mitigate TDR increases by reducing the generation of new ARV-resistant strains. A small number of NNRTI-resistance mutations were responsible for most cases of high-level resistance, suggesting that inexpensive point-mutation assays to detect these mutations may be useful for pre-therapy screening in regions with high levels of TDR. In the context of a public health approach to ARV therapy, a reliable point-of-care genotypic resistance test could identify which patients should receive standard first-line therapy and which should receive a protease-inhibitor-containing regimen.
In this individual patient and sequence-level meta-analysis, Soo-Yon Rhee and colleagues measure regional trends in HIV-1 transmitted drug resistance prevalence and investigate the specific mutations responsible for TDR in different regions and in different virus subtypes.
Editors' Summary
About 35 million people are currently infected with HIV, the virus that causes AIDS by destroying immune system cells and leaving infected individuals susceptible to other infections. Early in the AIDS epidemic, most HIV-infected individuals died within ten years of infection. Then, in 1996, effective antiretroviral (ARV) therapy—drug combinations that suppress HIV replication by inhibiting reverse transcriptase and other essential viral enzymes—became available. For people living in affluent countries, HIV/AIDS became a chronic condition, but because ARV therapy was expensive, HIV/AIDS remained fatal in low- and middle-income countries (LMICs). In 2003, the international community began to work towards achieving universal access to ARV therapy. Now, more than 10 million HIV-positive individuals in LMICs receive ARV therapy, usually as a fixed-dose combination of two nucleoside reverse transcriptase inhibitors (NRTIs), such as tenofovir and lamivudine, plus a non-nucleoside reverse transcriptase inhibitor (NNRTI), such as efavirenz or nevirapine.
Why Was This Study Done?
The global scale-up of ARV therapy has reduced deaths from HIV/AIDS and the incidence of HIV infection in LMICs, but the development of resistance to ARV therapy is threatening these advances. HIV rapidly accumulates genetic changes (mutations), some of which make HIV resistant to ARV therapy. Up to 30% of patients receiving a fixed-dose NRTI/NNRTI combination develop virological failure, and a high proportion of these patients develop mutations associated with resistance to the ARVs in their regimen. Moreover, the proportion of newly infected, ARV-naïve individuals with transmitted drug resistance (TDR) is also increasing. Organizations involved in HIV/AIDS control need to understand the regional and temporal mutational patterns of TDR to inform the development of guidelines for first-line ARV therapy and of inexpensive resistance mutation assays for use in LMICs. Here, using a statistical approach called meta-analysis to combine information from individual patients about the resistance mutations they carry, the researchers investigate the molecular epidemiology of TDR (the patterns of molecular changes underlying TDR in populations) and identify the HIV drug-resistance mutations most responsible for TDR in different world regions.
What Did the Researchers Do and Find?
The researchers identified 287 studies published between 2000 and 2013 from 111 countries that included the reverse transcriptase sequences of HIV viruses from 50,870 ARV-naïve, HIV-positive individuals. The researchers analyzed each virus sequence for the presence of 93 surveillance drug-resistance mutations (SDRMs) previously shown to be specific indicators of TDR. Meta-analysis of these data indicated that the average overall prevalence of TDR (the proportion of ARV-naïve, HIV-positive individuals infected with a virus carrying one or more SDRMs) ranged from 2.8% in sub-Saharan Africa to 11.5% in North America. In sub-Saharan Africa, the odds (chance) of TDR increased 1.09-fold per year following national ARV scale-up; this increase was attributable to an increase in NRTI- and NNRTI-associated resistance. By contrast, in LMICs in south/southeast Asia, the odds of TDR remained unchanged following ARV scale-up. In Latin America/Caribbean, North America, Europe, and upper-income Asian countries, the odds of TDR have increased by around 1.10-fold per year since 1995, mainly as a result of increased NNRTI resistance. Four NNRTI-associated and 16 NRTI-associated SDRMs accounted for most NNRTI- and NRTI-associated TDR, respectively, in all regions. Notably, in sub-Saharan Africa and south/southeast Asia, most of the NNRTI-associated SDRMs detected were associated with high-level resistance to nevirapine or efavirenz. Finally, the researchers report that 95% of TDR viruses in sub-Saharan Africa and south/southeast Asia were unrelated and had therefore arisen independently.
What Do These Findings Mean?
Because many drug-resistance mutations reduce HIV’s fitness and tend to be lost rapidly in individuals not exposed to ARV therapy, differences among the datasets used in this meta-analysis with respect to how long each ARV-naïve patient had been infected with HIV before virus sampling may limit the accuracy of these findings. Nevertheless, the finding that most of the TDR strains detected in sub-Saharan Africa and south/southeast Asia arose independently suggests that improved patient adherence to ARV therapy and the use of ARV regimens that contain drugs to which HIV rarely develops resistance (regimens with a high genetic barrier to resistance) should reduce the generation of new ARV-resistant strains and mitigate TDR increases. In addition, the finding that a few NNRTI-resistance mutations were responsible for most cases of transmitted high-level resistance suggests that an inexpensive assay that detects these specific mutations may be useful for pre-therapy screening in LMICs with high TDR levels.
Additional Information
Please access these websites via the online version of this summary at
Information is available from the US National Institute of Allergy and Infectious Diseases on HIV infection and AIDS
NAM/aidsmap provides basic information about HIV/AIDS, summaries of recent research findings on HIV care and treatment, and personal stories about living with HIV/AIDS
Information is available from Avert, an international AIDS charity, on many aspects of HIV/AIDS, including information on antiretroviral drugs and on universal access to ARV therapy; Avert also provides personal stories about living with HIV/AIDS
The World Health Organization provides information on all aspects of HIV/AIDS (in several languages), including its guidelines on the use of antiretroviral therapy for treating and preventing HIV infection
The UNAIDS World AIDS Day Report 2014 provides up-to-date information about the AIDS epidemic and efforts to halt it, including progress towards universal access to antiretroviral therapy
The Stanford University HIV Drug Resistance Database includes information about surveillance drug-resistant mutations (SDRMs) and an interactive map displaying HIV drug resistance in ARV-naïve populations
PMCID: PMC4388826  PMID: 25849352
18.  Clinical Interpretation and Implications of Whole-Genome Sequencing 
Whole-genome sequencing (WGS) is increasingly applied in clinical medicine and is expected to uncover clinically significant findings regardless of sequencing indication.
To examine coverage and concordance of clinically relevant genetic variation provided by WGS technologies; to quantitate inherited disease risk and pharmacogenomic findings in WGS data and resources required for their discovery and interpretation; and to evaluate clinical action prompted by WGS findings.
An exploratory study of 12 adult participants recruited at Stanford University Medical Center who underwent WGS between November 2011 and March 2012. A multidisciplinary team reviewed all potentially reportable genetic findings. Five physicians proposed initial clinical follow-up based on the genetic findings.
Genome coverage and sequencing platform concordance in different categories of genetic disease risk, person-hours spent curating candidate disease-risk variants, interpretation agreement between trained curators and disease genetics databases, burden of inherited disease risk and pharmacogenomic findings, and burden and interrater agreement of proposed clinical follow-up.
Depending on sequencing platform, 10% to 19% of inherited disease genes were not covered to accepted standards for single nucleotide variant discovery. Genotype concordance was high for previously described single nucleotide genetic variants (99%-100%) but low for small insertion/deletion variants (53%-59%). Curation of 90 to 127 genetic variants in each participant required a median of 54 minutes (range, 5-223 minutes) per genetic variant, resulted in moderate classification agreement between professionals (Gross κ, 0.52; 95%CI, 0.40-0.64), and reclassified 69%of genetic variants cataloged as disease causing in mutation databases to variants of uncertain or lesser significance. Two to 6 personal disease-risk findings were discovered in each participant, including 1 frameshift deletion in the BRCA1 gene implicated in hereditary breast and ovarian cancer. Physician review of sequencing findings prompted consideration of a median of 1 to 3 initial diagnostic tests and referrals per participant, with fair interrater agreement about the suitability of WGS findings for clinical follow-up (Fleiss κ, 0.24; P < 001).
In this exploratory study of 12 volunteer adults, the use of WGS was associated with incomplete coverage of inherited disease genes, low reproducibility of detection of genetic variation with the highest potential clinical effects, and uncertainty about clinically reportable findings. In certain cases, WGS will identify clinically actionable genetic variants warranting early medical intervention. These issues should be considered when determining the role of WGS in clinical medicine.
PMCID: PMC4119063  PMID: 24618965
19.  Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson’s disease 
Nature genetics  2014;46(9):989-993.
We conducted a meta analysis of Parkinson’s disease genome-wide association studies using a common set of 7,893,274 variants across 13,708 cases and 95,282 controls. Twenty-six loci were identified as genome-wide significant; these and six additional previously reported loci were then tested in an independent set of 5,353 cases and 5,551 controls. Of the 32 tested SNPs, 24 replicated, including 6 novel loci. Conditional analyses within loci show four loci including GBA, GAK/DGKQ, SNCA, and HLA contain a secondary independent risk variant. In total we identified and replicated 28 independent risk variants for Parkinson disease across 24 loci. While the effect of each individual locus is small, a risk profile analysis revealed a substantial cummulative risk in a comparison highest versus lowest quintiles of genetic risk (OR=3.31, 95% CI: 2.55, 4.30; p-value = 2×10−16). We also show 6 risk loci associated with proximal gene expression or DNA methylation.
PMCID: PMC4146673  PMID: 25064009
20.  Concordance of effects of medical interventions on hospital admission and readmission rates with effects on mortality 
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.
PMCID: PMC3855143  PMID: 24144601
21.  Association Between Pediatric Clinical Trials and Global Burden of Disease 
Pediatrics  2014;133(1):78-87.
The allocation of research resources should favor conditions responsible for the greatest disease burden. This is particularly important in pediatric populations, which have been underrepresented in clinical research. Our aim was to measure the association between the focus of pediatric clinical trials and burden of disease and to identify neglected clinical domains.
We performed a cross-sectional study of clinical trials by using trial records in All trials started in 2006 or after and studying patient-level interventions in pediatric populations were included. Age-specific measures of disease burden were obtained for 21 separate conditions for high-, middle-, and low-income countries. We measured the correlation between number of pediatric clinical trials and disease burden for each condition.
Neuropsychiatric conditions and infectious diseases were the most studied conditions globally in terms of number of trials (874 and 847 trials, respectively), while intentional injuries (5 trials) and maternal conditions (4 trials) were the least studied. Clinical trials were only moderately correlated with global disease burden (r = 0.58, P = .006). Correlations were also moderate within each of the country income levels, but lowest in low-income countries (r = .47, P = .03). Globally, the conditions most understudied relative to disease burden were injuries (–260 trials for unintentional injuries and –160 trials for intentional injuries), nutritional deficiencies (–175 trials), and respiratory infections (–171 trials).
Pediatric clinical trial activity is only moderately associated with pediatric burden of disease, and least associated in low-income countries. The mismatch between clinical trials and disease burden identifies key clinical areas for focus and investment.
PMCID: PMC3876184  PMID: 24344112
clinical trials; burden of disease; pediatric research
22.  The protective effect of LRRK2 p.R1398H on risk of Parkinson’s disease is independent of MAPT and SNCA variants 
Neurobiology of aging  2013;35(1):10.1016/j.neurobiolaging.2013.07.013.
The best validated susceptibility variants for Parkinson’s disease (PD) are located in the alpha-synuclein (SNCA) and microtubule-associated protein tau (MAPT) genes. Recently, a protective p.N551K-R1398H-K1423K haplotype in the leucine-rich repeat kinase 2 (LRRK2) gene was identified, with p.R1398H appearing to be the most likely functional variant. To date, the consistency of the protective effect of LRRK2 p.R1398H across MAPT and SNCA variant genotypes has not been assessed. To address this, we examined four SNCA variants (rs181489, rs356219, rs11931074, rs2583988), the MAPT H1-haplotype defining variant rs1052553, and LRRK2 p.R1398H (rs7133914) in Caucasian (N=10,322) and Asian (N=2,289) series. There was no evidence of an interaction of LRRK2 p.R1398H with MAPT or SNCA variants (all P≥0.10); the protective effect of p.R1398H was observed at similar magnitude across MAPT and SNCA genotypes, and the risk effects of MAPT and SNCA variants were observed consistently for LRRK2 p.R1398H genotypes. Our results indicate that the association of LRRK2 p.R1398H with PD is independent of SNCA and MAPT variants, and vice versa, in Caucasian and Asian populations.
PMCID: PMC3829604  PMID: 23962496
Parkinson disease; LRRK2; SNCA; MAPT; interaction; genetics
23.  A Web-based database of genetic association studies in cutaneous melanoma enhanced with network-driven data exploration tools 
The publicly available online database MelGene provides a comprehensive, regularly updated, collection of data from genetic association studies in cutaneous melanoma (CM), including random-effects meta-analysis results of all eligible polymorphisms. The updated database version includes data from 192 publications with information on 1114 significantly associated polymorphisms across 280 genes, along with new front-end and back-end capabilities. Various types of relationships between data are calculated and visualized as networks. We constructed 13 different networks containing the polymorphisms and the genes included in MelGene. We explored the derived network representations under the following questions: (i) are there nodes that deserve consideration regarding their network connectivity characteristics? (ii) What is the relation of either the genome-wide or nominally significant CM polymorphisms/genes with the ones highlighted by the network representation? We show that our network approach using the MelGene data reveals connections between statistically significant genes/ polymorphisms and other genes/polymorphisms acting as ‘hubs’ in the reconstructed networks. To the best of our knowledge, this is the first database containing data from a comprehensive field synopsis and systematic meta-analyses of genetic polymorphisms in CM that provides user-friendly tools for in-depth molecular network visualization and exploration. The proposed network connections highlight potentially new loci requiring further investigation of their relation to melanoma risk.
Database URL:
PMCID: PMC4224266  PMID: 25380778
24.  The diagnostic accuracy of the Patient Health Questionnaire-2 (PHQ-2), Patient Health Questionnaire-8 (PHQ-8), and Patient Health Questionnaire-9 (PHQ-9) for detecting major depression: protocol for a systematic review and individual patient data meta-analyses 
Systematic Reviews  2014;3:124.
Major depressive disorder (MDD) may be present in 10%–20% of patients in medical settings. Routine depression screening is sometimes recommended to improve depression management. However, studies of the diagnostic accuracy of depression screening tools have typically used data-driven, exploratory methods to select optimal cutoffs. Often, these studies report results from a small range of cutoff points around whatever cutoff score is most accurate in that given study. When published data are combined in meta-analyses, estimates of accuracy for different cutoff points may be based on data from different studies, rather than data from all studies for each possible cutoff point. As a result, traditional meta-analyses may generate exaggerated estimates of accuracy. Individual patient data (IPD) meta-analyses can address this problem by synthesizing data from all studies for each cutoff score to obtain diagnostic accuracy estimates. The nine-item Patient Health Questionnaire-9 (PHQ-9) and the shorter PHQ-2 and PHQ-8 are commonly recommended for depression screening. Thus, the primary objectives of our IPD meta-analyses are to determine the diagnostic accuracy of the PHQ-9, PHQ-8, and PHQ-2 to detect MDD among adults across all potentially relevant cutoff scores. Secondary analyses involve assessing accuracy accounting for patient factors that may influence accuracy (age, sex, medical comorbidity).
Data sources will include MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, PsycINFO, and Web of Science. We will include studies that included a Diagnostic and Statistical Manual or International Classification of Diseases diagnosis of MDD based on a validated structured or semi-structured clinical interview administered within 2 weeks of the administration of the PHQ. Two reviewers will independently screen titles and abstracts, perform full article review, and extract study data. Disagreements will be resolved by consensus. Risk of bias will be assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Bivariate random-effects meta-analysis will be conducted for the full range of plausible cutoff values.
The proposed IPD meta-analyses will allow us to obtain estimates of the diagnostic accuracy of the PHQ-9, PHQ-8, and PHQ-2.
Systematic review registration
PROSPERO CRD42014010673
PMCID: PMC4218786  PMID: 25348422
Patient health questionnaire; PHQ-9; PHQ-8; PHQ-2; Depression; Screening; Diagnostic test accuracy; Systematic review; Individual patient data meta-analysis
Journal of psychiatric research  2013;47(10):1298-1303.
Mental disorders are associated with premature mortality, and the magnitudes of risk have commonly been estimated using hospital data. However, psychiatric patients who are hospitalized have more severe illness and do not adequately represent mental disorders in the general population. We conducted a national cohort study using outpatient and inpatient diagnoses for the entire Swedish adult population (N=7,253,516) to examine the extent to which mortality risks are overestimated using inpatient diagnoses only. Outcomes were all-cause and suicide mortality during 8 years of follow-up (2001–2008). There were 377,339 (5.2%) persons with any inpatient psychiatric diagnosis, vs. 680,596 (9.4%) with any inpatient or outpatient diagnosis, hence 44.6% of diagnoses were missed using inpatient data only. When including and accounting for prevalent psychiatric cases, all-cause mortality risk among persons with any mental disorder was overestimated by 15.3% using only inpatient diagnoses (adjusted hazard ratio [aHR], 5.89; 95% CI, 5.85–5.92) vs. both inpatient and outpatient diagnoses (aHR, 5.11; 95% CI, 5.08–5.14). Suicide risk was overestimated by 18.5% (aHRs, 23.91 vs. 20.18), but this varied widely by specific disorders, from 4.4% for substance use to 49.1% for anxiety disorders. The sole use of inpatient diagnoses resulted in even greater overestimation of all-cause or suicide mortality risks when prevalent cases were unidentified (~20–30%) or excluded (~25–40%). However, different methods for handling prevalent cases resulted in only modest variation in risk estimates when using both inpatient and outpatient diagnoses. These findings have important implications for the interpretation of hospital-based studies and the design of future studies.
PMCID: PMC3746500  PMID: 23806577
mental disorders; mortality; suicide

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