VA Office of Research and Development

BACKGROUND: The effects of intensive glucose control on cardiovascular events in patients with long-standing type 2 diabetes mellitus remain uncertain. METHODS: We randomly assigned 1791 military veterans (mean age, 60.4 years) who had a suboptimal response to therapy for type 2 diabetes to receive either intensive or standard glucose control. Other cardiovascular risk factors were treated uniformly. The mean number of years since the diagnosis of diabetes was 11.5, and 40% of the patients had already had a cardiovascular event. The goal in the intensive-therapy group was an absolute reduction of 1.5 percentage points in the glycated hemoglobin level, as compared with the standard-therapy group. The primary outcome was the time from randomization to the first occurrence of a major cardiovascular event, a composite of myocardial infarction, stroke, death from cardiovascular causes, congestive heart failure, surgery for vascular disease, inoperable coronary disease, and amputation for ischemic gangrene. RESULTS: The median follow-up was 5.6 years. Median glycated hemoglobin levels were 8.4% in the standard-therapy group and 6.9% in the intensive-therapy group. The primary outcome occurred in 264 patients in the standard-therapy group and 235 patients in the intensive-therapy group (hazard ratio in the intensive-therapy group, 0.88; 95% confidence interval [CI], 0.74 to 1.05; P=0.14). There was no significant difference between the two groups in any component of the primary outcome or in the rate of death from any cause (hazard ratio, 1.07; 95% CI, 0.81 to 1.42; P=0.62). No differences between the two groups were observed for microvascular complications. The rates of adverse events, predominantly hypoglycemia, were 17.6% in the standard-therapy group and 24.1% in the intensive-therapy group. CONCLUSIONS: Intensive glucose control in patients with poorly controlled type 2 diabetes had no significant effect on the rates of major cardiovascular events, death, or microvascular complications with the exception of progression of albuminuria (P = 0.01) [added]. (ClinicalTrials.gov number, NCT00032487.)

Abstract The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes) 1 . In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

BACKGROUND: The movement of evidence-based practices (EBPs) into routine clinical usage is not spontaneous, but requires focused efforts. The field of implementation science has developed to facilitate the spread of EBPs, including both psychosocial and medical interventions for mental and physical health concerns. DISCUSSION: The authors aim to introduce implementation science principles to non-specialist investigators, administrators, and policymakers seeking to become familiar with this emerging field. This introduction is based on published literature and the authors' experience as researchers in the field, as well as extensive service as implementation science grant reviewers. Implementation science is "the scientific study of methods to promote the systematic uptake of research findings and other EBPs into routine practice, and, hence, to improve the quality and effectiveness of health services." Implementation science is distinct from, but shares characteristics with, both quality improvement and dissemination methods. Implementation studies can be either assess naturalistic variability or measure change in response to planned intervention. Implementation studies typically employ mixed quantitative-qualitative designs, identifying factors that impact uptake across multiple levels, including patient, provider, clinic, facility, organization, and often the broader community and policy environment. Accordingly, implementation science requires a solid grounding in theory and the involvement of trans-disciplinary research teams. The business case for implementation science is clear: As healthcare systems work under increasingly dynamic and resource-constrained conditions, evidence-based strategies are essential in order to ensure that research investments maximize healthcare value and improve public health. Implementation science plays a critical role in supporting these efforts.

Mental health encompasses a range of mental, emotional, social, and behavioral functioning and occurs along a continuum from good to poor. Previous research has documented that mental health among children and adolescents is associated with immediate and long-term physical health and chronic disease, health risk behaviors, social relationships, education, and employment. Public health surveillance of children's mental health can be used to monitor trends in prevalence across populations, increase knowledge about demographic and geographic differences, and support decision-making about prevention and intervention. Numerous federal data systems collect data on various indicators of children's mental health, particularly mental disorders. The 2013-2019 data from these data systems show that mental disorders begin in early childhood and affect children with a range of sociodemographic characteristics. During this period, the most prevalent disorders diagnosed among U.S. children and adolescents aged 3-17 years were attention-deficit/hyperactivity disorder and anxiety, each affecting approximately one in 11 (9.4%-9.8%) children. Among children and adolescents aged 12-17 years, one fifth (20.9%) had ever experienced a major depressive episode. Among high school students in 2019, 36.7% reported persistently feeling sad or hopeless in the past year, and 18.8% had seriously considered attempting suicide. Approximately seven in 100,000 persons aged 10-19 years died by suicide in 2018 and 2019. Among children and adolescents aged 3-17 years, 9.6%-10.1% had received mental health services, and 7.8% of all children and adolescents aged 3-17 years had taken medication for mental health problems during the past year, based on parent report. Approximately one in four children and adolescents aged 12-17 years reported having received mental health services during the past year. In federal data systems, data on positive indicators of mental health (e.g., resilience) are limited. Although no comprehensive surveillance system for children's mental health exists and no single indicator can be used to define the mental health of children or to identify the overall number of children with mental disorders, these data confirm that mental disorders among children continue to be a substantial public health concern. These findings can be used by public health professionals, health care providers, state health officials, policymakers, and educators to understand the prevalence of specific mental disorders and other indicators of mental health and the challenges related to mental health surveillance.

Effective rehabilitative therapies are needed for patients with long-term deficits after stroke.In this multicenter, randomized, controlled trial involving 127 patients with moderate-to-severe upper-limb impairment 6 months or more after a stroke, we randomly assigned 49 patients to receive intensive robot-assisted therapy, 50 to receive intensive comparison therapy, and 28 to receive usual care. Therapy consisted of 36 1-hour sessions over a period of 12 weeks. The primary outcome was a change in motor function, as measured on the Fugl-Meyer Assessment of Sensorimotor Recovery after Stroke, at 12 weeks. Secondary outcomes were scores on the Wolf Motor Function Test and the Stroke Impact Scale. Secondary analyses assessed the treatment effect at 36 weeks.At 12 weeks, the mean Fugl-Meyer score for patients receiving robot-assisted therapy was better than that for patients receiving usual care (difference, 2.17 points; 95% confidence interval [CI], -0.23 to 4.58) and worse than that for patients receiving intensive comparison therapy (difference, -0.14 points; 95% CI, -2.94 to 2.65), but the differences were not significant. The results on the Stroke Impact Scale were significantly better for patients receiving robot-assisted therapy than for those receiving usual care (difference, 7.64 points; 95% CI, 2.03 to 13.24). No other treatment comparisons were significant at 12 weeks. Secondary analyses showed that at 36 weeks, robot-assisted therapy significantly improved the Fugl-Meyer score (difference, 2.88 points; 95% CI, 0.57 to 5.18) and the time on the Wolf Motor Function Test (difference, -8.10 seconds; 95% CI, -13.61 to -2.60) as compared with usual care but not with intensive therapy. No serious adverse events were reported.In patients with long-term upper-limb deficits after stroke, robot-assisted therapy did not significantly improve motor function at 12 weeks, as compared with usual care or intensive therapy. In secondary analyses, robot-assisted therapy improved outcomes over 36 weeks as compared with usual care but not with intensive therapy. (ClinicalTrials.gov number, NCT00372411.)

BACKGROUND: Over the past 10-15 years, a substantial amount of work has been done by the scientific, regulatory, and business communities to elucidate the effects and risks of pharmaceuticals and personal care products (PPCPs) in the environment. OBJECTIVE: This review was undertaken to identify key outstanding issues regarding the effects of PPCPs on human and ecological health in order to ensure that future resources will be focused on the most important areas. DATA SOURCES: To better understand and manage the risks of PPCPs in the environment, we used the "key question" approach to identify the principle issues that need to be addressed. Initially, questions were solicited from academic, government, and business communities around the world. A list of 101 questions was then discussed at an international expert workshop, and a top-20 list was developed. Following the workshop, workshop attendees ranked the 20 questions by importance. DATA SYNTHESIS: The top 20 priority questions fell into seven categories: a) prioritization of substances for assessment, b) pathways of exposure, c) bioavailability and uptake, d) effects characterization, e) risk and relative risk, f ) antibiotic resistance, and g) risk management. CONCLUSIONS: A large body of information is now available on PPCPs in the environment. This exercise prioritized the most critical questions to aid in development of future research programs on the topic.

Despite a growing body of research about mentoring, definitional, theoretical, and methodological deficiencies reduce the usefulness of existing research. This article provides a critical review of the literature on mentoring, with an emphasis on the links between mentoring and undergraduate academic success. The first section describes a variety of ways in which mentoring has been defined within higher education, management, and psychology. Issues related to developing a standard operational definition of mentoring within higher education are discussed. The second section provides a critical review of empirical research about mentoring and undergraduate education. The third section describes four different theoretical perspectives that could be used in future research about mentoring. Finally, future directions for research, including methodological issues and substantive concerns, are addressed.

Abstract Noroviruses are major agents of viral gastroenteritis worldwide. The infectivity of Norwalk virus, the prototype norovirus, has been studied in susceptible human volunteers. A new variant of the hit theory model of microbial infection was developed to estimate the variation in Norwalk virus infectivity, as well as the degree of virus aggregation, consistent with independent (electron microscopic) observations. Explicit modeling of viral aggregation allows us to express virus infectivity per single infectious unit (particle). Comparison of a primary and a secondary inoculum showed that passage through a human host does not change Norwalk virus infectivity. We estimate the average probability of infection for a single Norwalk virus particle to be close to 0.5, exceeding that reported for any other virus studied to date. Infected subjects had a dose‐dependent probability of becoming ill, ranging from 0.1 (at a dose of 10 3 NV genomes) to 0.7 (at 10 8 virus genomes). A norovirus dose response model is important for understanding its transmission and essential for development of a quantitative risk model. Norwalk virus is a valuable model system to study virulence because genetic factors are known for both complete and partial protection; the latter can be quantitatively described as heterogeneity in dose response models. J. Med. Virol. 80:1468–1476, 2008. © 2008 Wiley‐Liss, Inc.

Abstract. Recent field and laboratory evidence indicates that the oxidation of isoprene, (2-methyl-1,3-butadiene, C5H8) forms secondary organic aerosol (SOA). Global biogenic emissions of isoprene (600 Tg yr−1) are sufficiently large that the formation of SOA in even small yields results in substantial production of atmospheric particulate matter, likely having implications for air quality and climate. Here we present a review of field measurements, experimental work, and modeling studies aimed at understanding the mechanisms, yield, and atmospheric importance of isoprene-derived SOA. SOA yields depend on a number of factors, including organic aerosol loading (Mo), NOx level (RO2 chemistry), and, because of the importance of multigenerational chemistry, the degree of oxidation. These dependences are not always included in SOA modules used in atmospheric transport models, and instead most yield parameterizations rely on a single set of chamber experiments (carried out over a limited range of conditions); this may lead to very different estimates of the atmospheric importance of isoprene SOA. New yield parameterizations, based on all available laboratory data (Mo=0–50 μg m−3), are presented here, so that SOA formation may be computed as a function of Mo, NOx level, and temperature. Current research needs and future research directions are identified.

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies.

The new version of EPA's positive matrix factorization (EPA PMF) software, 5.0, includes three error estimation (EE) methods for analyzing factor analytic solutions: classical bootstrap (BS), displacement of factor elements (DISP), and bootstrap enhanced by displacement (BS-DISP). These methods capture the uncertainty of PMF analyses due to random errors and rotational ambiguity. To demonstrate the utility of the EE methods, results are presented for three data sets: (1) speciated PM2.5 data from a chemical speciation network (CSN) site in Sacramento, California (2003-2009); (2) trace metal, ammonia, and other species in water quality samples taken at an inline storage system (ISS) in Milwaukee, Wisconsin (2006); and (3) an organic aerosol data set from high-resolution aerosol mass spectrometer (HR-AMS) measurements in Las Vegas, Nevada (January 2008). We present an interpretation of EE diagnostics for these data sets, results from sensitivity tests of EE diagnostics using additional and fewer factors, and recommendations for reporting PMF results. BS-DISP and BS are found useful in understanding the uncertainty of factor profiles; they also suggest if the data are over-fitted by specifying too many factors. DISP diagnostics were consistently robust, indicating its use for understanding rotational uncertainty and as a first step in assessing a solution's viability. The uncertainty of each factor's identifying species is shown to be a useful gauge for evaluating multiple solutions, e.g., with a different number of factors.

Twitter is an electronic medium that allows a large user populace to communicate with each other simultaneously. Inherent to Twitter is an asymmetrical relationship between friends and followers that provides an interesting social network like structure among the users of Twitter. Twitter messages, called tweets, are restricted to 140 characters and thus are usually very focused. We investigate the use of Twitter to build a news processing system, called TwitterStand, from Twitter tweets. The idea is to capture tweets that correspond to late breaking news. The result is analogous to a distributed news wire service. The difference is that the identities of the contributors/reporters are not known in advance and there may be many of them. Furthermore, tweets are not sent according to a schedule: they occur as news is happening, and tend to be noisy while usually arriving at a high throughput rate. Some of the issues addressed include removing the noise, determining tweet clusters of interest bearing in mind that the methods must be online, and determining the relevant locations associated with the tweets.

Abstract Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry 1,2 . Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated ( P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis 3 , and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN ) and variants (such as at GRK5 and NOS3 ). Using a three-pronged approach 4 , we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry 5 . Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.

Abstract. The EPA PMF (Environmental Protection Agency positive matrix factorization) version 5.0 and the underlying multilinear engine-executable ME-2 contain three methods for estimating uncertainty in factor analytic models: classical bootstrap (BS), displacement of factor elements (DISP), and bootstrap enhanced by displacement of factor elements (BS-DISP). The goal of these methods is to capture the uncertainty of PMF analyses due to random errors and rotational ambiguity. It is shown that the three methods complement each other: depending on characteristics of the data set, one method may provide better results than the other two. Results are presented using synthetic data sets, including interpretation of diagnostics, and recommendations are given for parameters to report when documenting uncertainty estimates from EPA PMF or ME-2 applications.

The postnatal effects of in utero exposure to perfluorooctane sulfonate (PFOS, C8F17SO3-) were evaluated in the rat and mouse. Pregnant Sprague-Dawley rats were given 1, 2, 3, 5, or 10 mg/kg PFOS daily by gavage from gestation day (GD) 2 to GD 21; pregnant CD-1 mice were treated with 1, 5, 10, 15, and 20 mg/kg PFOS from GD 1 to GD 18. Controls received 0.5% Tween-20 vehicle (1 ml/kg for rats and 10 ml/kg for mice). At parturition, newborns were observed for clinical signs and survival. All animals were born alive and initially appeared to be active. In the highest dosage groups (10 mg/kg for rat and 20 mg/kg for mouse), the neonates became pale, inactive, and moribund within 30-60 min, and all died soon afterward. In the 5 mg/kg (rat) and 15 mg/kg (mouse) dosage groups, the neonates also became moribund but survived for a longer period of time (8-12 h). Over 95% of these animals died within 24 h. Approximately 50% of offspring died at 3 mg/kg for rat and 10 mg/kg for mouse. Cross-fostering the PFOS-exposed rat neonates (5 mg/kg) to control nursing dams failed to improve survival. Serum concentrations of PFOS in newborn rats mirrored the maternal administered dosage and were similar to those in the maternal circulation at GD 21; PFOS levels in the surviving neonates declined in the ensuing days. Small but significant and persistent growth lags were detected in surviving rat and mouse pups exposed to PFOS prenatally, and slight delays in eye opening were noted. Significant increases in liver weight were observed in the PFOS-exposed mouse pups. Serum thyroxine levels were suppressed in the PFOS-treated rat pups, although triiodothyronine and thyroid-stimulating hormone [TSH] levels were not altered. Choline acetyltransferase activity (an enzyme that is sensitive to thyroid status) in the prefrontal cortex of rat pups exposed to PFOS prenatally was slightly reduced, but activity in the hippocampus was not affected. Development of learning, determined by T-maze delayed alternation in weanling rats, was not affected by PFOS exposure. These results indicate that in utero exposure to PFOS severely compromised postnatal survival of neonatal rats and mice, and caused delays in growth and development that were accompanied by hypothyroxinemia in the surviving rat pups.

Perfluorooctanoic acid (PFOA), a member of the perfluoroalkyl acids that have wide commercial applications, has recently been detected in humans and wildlife. The current study characterizes the developmental toxicity of PFOA in the mouse. Timed-pregnant CD-1 mice were given 1, 3, 5, 10, 20, or 40 mg/kg PFOA by oral gavage daily from gestational day (GD) 1 to 17; controls received an equivalent volume (10 ml/kg) of water. PFOA treatment produced dose-dependent full-litter resorptions; all dams in the 40-mg/kg group resorbed their litters. Weight gain in dams that carried pregnancy to term was significantly lower in the 20-mg/kg group. At GD 18, some dams were sacrificed for maternal and fetal examinations (group A), and the rest were treated once more with PFOA and allowed to give birth (group B). Postnatal survival, growth, and development of the offspring were monitored. PFOA induced enlarged liver in group A dams at all dosages, but did not alter the number of implantations. The percent of live fetuses was lower only in the 20-mg/kg group (74 vs. 94% in controls), and fetal weight was also significantly lower in this group. However, no significant increase in malformations was noted in any treatment group. The incidence of live birth in group B mice was significantly lowered by PFOA: ca. 70% for the 10- and 20-mg/kg groups compared to 96% for controls. Postnatal survival was severely compromised at 10 or 20 mg/kg, and moderately so at 5 mg/kg. Dose-dependent growth deficits were detected in all PFOA-treated litters except the 1-mg/kg group. Significant delays in eye-opening (up to 2-3 days) were noted at 5 mg/kg and higher dosages. Accelerated sexual maturation was observed in male offspring, but not in females. These data indicate maternal and developmental toxicity of PFOA in the mouse, leading to early pregnancy loss, compromised postnatal survival, delays in general growth and development, and sex-specific alterations in pubertal maturation.

Phosphorus (P) has been identified as the key constituent defining wetland productivity, structure, and function. Our goal was to investigate the spatial patterns of total P and three labile forms of P (labile organic, inorganic, and microbial biomass P) across a subtropical wetland located in east-central Florida, the Blue Cypress Marsh Conservation Area (BCMCA), and link spatial patterns to ecosystem processes. The wetland received a continual input of nutrients primarily from the south and intermittently from the west and east, respectively, which ceased in the mid-1990s. Since then the marsh system has been undergoing natural succession. We used (i) ordinary kriging to characterize the spatial patterns of total P and labile P forms across the wetland, (ii) local, moving spatial correlations to investigate relationships between total P and labile P forms, and (iii) a clustering technique to link the identified spatial patterns to biogeochemical processes. The spatially explicit analyses revealed patterns of total P and labile P forms as well as changing relationships between variables across the marsh. We were able to distinguish P-enriched areas from unaffected ("natural") areas and intermediate zones that are currently undergoing change as P is mobilized and translocated. We also identified areas that are at risk, showing a shift toward a more P-enriched status. Our results improve our understanding of P and its labile components within a spatially explicit context.

Abstract Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury 1–4 . These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries 5 . Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

BACKGROUND: Vascular leakage and shock are the major causes of death in patients with dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS). Thirty years ago, complement activation was proposed to be a key underlying event, but the cause of complement activation has remained unknown. METHODS: The major nonstructural dengue virus (DV) protein NS1 was tested for its capacity to activate human complement in its membrane-associated and soluble forms. Plasma samples from 163 patients with DV infection and from 19 patients with other febrile illnesses were prospectively analyzed for viral load and for levels of NS1 and complement-activation products. Blood and pleural fluids from 9 patients with DSS were also analyzed. RESULTS: Soluble NS1 activated complement to completion, and activation was enhanced by polyclonal and monoclonal antibodies against NS1. Complement was also activated by cell-associated NS1 in the presence of specific antibodies. Plasma levels of NS1 and terminal SC5b-9 complexes correlated with disease severity. Large amounts of NS1, complement anaphylatoxin C5a, and the terminal complement complex SC5b-9 were present in pleural fluids from patients with DSS. CONCLUSIONS: Complement activation mediated by NS1 leads to local and systemic generation of anaphylatoxins and SC5b-9, which may contribute to the pathogenesis of the vascular leakage that occurs in patients with DHF/DSS.

OBJECTIVES: Our objective was to compare long-term outcomes of deep brain stimulation (DBS) of the globus pallidus interna (GPi) and subthalamic nucleus (STN) for patients with Parkinson disease (PD) in a multicenter randomized controlled trial. METHODS: Patients randomly assigned to GPi (n = 89) or STN DBS (n = 70) were followed for 36 months. The primary outcome was motor function on stimulation/off medication using the Unified Parkinson's Disease Rating Scale motor subscale. Secondary outcomes included quality of life and neurocognitive function. RESULTS: Motor function improved between baseline and 36 months for GPi (41.1 to 27.1; 95% confidence interval [CI] -16.4 to -10.8; p < 0.001) and STN (42.5 to 29.7; 95% CI -15.8 to -9.4; p < 0.001); improvements were similar between targets and stable over time (p = 0.59). Health-related quality of life improved at 6 months on all subscales (all p values significant), but improvement diminished over time. Mattis Dementia Rating Scale scores declined faster for STN than GPi patients (p = 0.01); other neurocognitive measures showed gradual decline overall. CONCLUSIONS: The beneficial effect of DBS on motor function was stable and comparable by target over 36 months. Slight declines in quality of life following initial gains and gradual decline in neurocognitive function likely reflect underlying disease progression and highlight the importance of nonmotor symptoms in determining quality of life. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that improvement of motor symptoms of PD by DBS remains stable over 3 years and does not differ by surgical target. Neurology® 2012;79:55-65.