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Pharmacogenomic testing has emerged to aid medication selection for patients with major depressive disorder (MDD) by identifying potential gene-drug interactions (GDI). Many pharmacogenomic tests are available with varying levels of supporting evidence, including direct-to-consumer and physician-ordered tests. We retrospectively evaluated the safety of using a physician-ordered combinatorial pharmacogenomic test (GeneSight) to guide medication selection for patients with MDD in a large, randomized, controlled trial (GUIDED).
Materials and Methods
Patients diagnosed with MDD who had an inadequate response to ≥1 psychotropic medication were randomized to treatment as usual (TAU) or combinatorial pharmacogenomic test-guided care (guided-care). All received combinatorial pharmacogenomic testing and medications were categorized by predicted GDI (no, moderate, or significant GDI). Patients and raters were blinded to study arm, and physicians were blinded to test results for patients in TAU, through week 8. Measures included adverse events (AEs, present/absent), worsening suicidal ideation (increase of ≥1 on the corresponding HAM-D17 question), or symptom worsening (HAM-D17 increase of ≥1). These measures were evaluated based on medication changes [add only, drop only, switch (add and drop), any, and none] and study arm, as well as baseline medication GDI.
Most patients had a medication change between baseline and week 8 (938/1,166; 80.5%), including 269 (23.1%) who added only, 80 (6.9%) who dropped only, and 589 (50.5%) who switched medications. In the full cohort, changing medications resulted in an increased relative risk (RR) of experiencing AEs at both week 4 and 8 [RR 2.00 (95% CI 1.41–2.83) and RR 2.25 (95% CI 1.39–3.65), respectively]. This was true regardless of arm, with no significant difference observed between guided-care and TAU, though the RRs for guided-care were lower than for TAU. Medication change was not associated with increased suicidal ideation or symptom worsening, regardless of study arm or type of medication change. Special attention was focused on patients who entered the study taking medications identified by pharmacogenomic testing as likely having significant GDI; those who were only taking medications subject to no or moderate GDI at week 8 were significantly less likely to experience AEs than those who were still taking at least one medication subject to significant GDI (RR 0.39, 95% CI 0.15–0.99, p=0.048). No other significant differences in risk were observed at week 8.
These data indicate that patient safety in the combinatorial pharmacogenomic test-guided care arm was no worse than TAU in the GUIDED trial. Moreover, combinatorial pharmacogenomic-guided medication selection may reduce some safety concerns. Collectively, these data demonstrate that combinatorial pharmacogenomic testing can be adopted safely into clinical practice without risking symptom degradation among patients.
Emerging from the warehouse of knowledge about terrestrial ecosystem functioning and the application of the systems ecology paradigm, exemplified by the power of simulation modeling, tremendous strides have been made linking the interactions of the land, atmosphere, and water locally to globally. Through integration of ecosystem, atmospheric, soil, and more recently social science interactions, plausible scenarios and even reasonable predictions are now possible about the outcomes of human activities. The applications of that knowledge to the effects of changing climates, human-caused nitrogen enrichment of ecosystems, and altered UV-B radiation represent challenges addressed in this chapter. The primary linkages addressed are through the C, N, S, and H2O cycles, and UV-B radiation. Carbon dioxide exchanges between land and the atmosphere, N additions and losses to and from lands and waters, early studies of SO2 in grassland ecosystem, and the effects of UV-B radiation on ecosystems have been mainstays of research described in this chapter. This research knowledge has been used in international and national climate assessments, for example the IPCC, US National Climate Assessment, and Paris Climate Accord. Likewise, the knowledge has been used to develop concepts and technologies related to sustainable agriculture, C sequestration, and food security.
Clarifying the relationship between depression symptoms and cardiometabolic and related health could clarify risk factors and treatment targets. The objective of this study was to assess whether depression symptoms in midlife are associated with the subsequent onset of cardiometabolic health problems.
The study sample comprised 787 male twin veterans with polygenic risk score data who participated in the Harvard Twin Study of Substance Abuse (‘baseline’) and the longitudinal Vietnam Era Twin Study of Aging (‘follow-up’). Depression symptoms were assessed at baseline [mean age 41.42 years (s.d. = 2.34)] using the Diagnostic Interview Schedule, Version III, Revised. The onset of eight cardiometabolic conditions (atrial fibrillation, diabetes, erectile dysfunction, hypercholesterolemia, hypertension, myocardial infarction, sleep apnea, and stroke) was assessed via self-reported doctor diagnosis at follow-up [mean age 67.59 years (s.d. = 2.41)].
Total depression symptoms were longitudinally associated with incident diabetes (OR 1.29, 95% CI 1.07–1.57), erectile dysfunction (OR 1.32, 95% CI 1.10–1.59), hypercholesterolemia (OR 1.26, 95% CI 1.04–1.53), and sleep apnea (OR 1.40, 95% CI 1.13–1.74) over 27 years after controlling for age, alcohol consumption, smoking, body mass index, C-reactive protein, and polygenic risk for specific health conditions. In sensitivity analyses that excluded somatic depression symptoms, only the association with sleep apnea remained significant (OR 1.32, 95% CI 1.09–1.60).
A history of depression symptoms by early midlife is associated with an elevated risk for subsequent development of several self-reported health conditions. When isolated, non-somatic depression symptoms are associated with incident self-reported sleep apnea. Depression symptom history may be a predictor or marker of cardiometabolic risk over decades.
The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.
To conduct a pilot study implementing combined genomic and epidemiologic surveillance for hospital-acquired multidrug-resistant organisms (MDROs) to predict transmission between patients and to estimate the local burden of MDRO transmission.
Pilot prospective multicenter surveillance study.
The study was conducted in 8 university hospitals (2,800 beds total) in Melbourne, Australia (population 4.8 million), including 4 acute-care, 1 specialist cancer care, and 3 subacute-care hospitals.
All clinical and screening isolates from hospital inpatients (April 24 to June 18, 2017) were collected for 6 MDROs: vanA VRE, MRSA, ESBL Escherichia coli (ESBL-Ec) and Klebsiella pneumoniae (ESBL-Kp), and carbapenem-resistant Pseudomonas aeruginosa (CRPa) and Acinetobacter baumannii (CRAb). Isolates were analyzed and reported as routine by hospital laboratories, underwent whole-genome sequencing at the central laboratory, and were analyzed using open-source bioinformatic tools. MDRO burden and transmission were assessed using combined genomic and epidemiologic data.
In total, 408 isolates were collected from 358 patients; 47.5% were screening isolates. ESBL-Ec was most common (52.5%), then MRSA (21.6%), vanA VRE (15.7%), and ESBL-Kp (7.6%). Most MDROs (88.3%) were isolated from patients with recent healthcare exposure.
Combining genomics and epidemiology identified that at least 27.1% of MDROs were likely acquired in a hospital; most of these transmission events would not have been detected without genomics. The highest proportion of transmission occurred with vanA VRE (88.4% of patients).
Genomic and epidemiologic data from multiple institutions can feasibly be combined prospectively, providing substantial insights into the burden and distribution of MDROs, including in-hospital transmission. This analysis enables infection control teams to target interventions more effectively.
Extracorporeal membrane oxygenation (ECMO) has accelerated rapidly for patients in severe cardiac or respiratory failure. As a result, ECMO networks are being developed across the world using a “hub and spoke” model. Current guidelines call for all patients transported on ECMO to be accompanied by a physician during transport. However, as ECMO centers and networks grow, the increasing number of transports will be limited by this mandate.
The aim of this study was to compare rates of adverse events occurring during transport of ECMO patients with and without an additional clinician, defined as a physician, nurse practitioner (NP), or physician assistant (PA).
This is a retrospective cohort study of all adults transported while cannulated on ECMO from 2011-2018 via ground and air between 21 hospitals in the northeastern United States, comparing transports with and without additional clinicians. The primary outcome was the rate of major adverse events, and the secondary outcome was minor adverse events.
Over the seven-year study period, 93 patients on ECMO were transported. Twenty-three transports (24.7%) were accompanied by a physician or other additional clinician. Major adverse events occurred in 21.5% of all transports. There was no difference in the total rate of major adverse events between accompanied and unaccompanied transports (P = .91). Multivariate analysis did not demonstrate any parameter as being predictive of major adverse events.
In a retrospective cohort study of transports of ECMO patients, there was no association between the overall rate of major adverse events in transport and the accompaniment of an additional clinician. No variables were associated with major adverse events in either cohort.
There is evidence that environmental and genetic risk factors for schizophrenia spectrum disorders are transdiagnostic and mediated in part through a generic pathway of affective dysregulation.
We analysed to what degree the impact of schizophrenia polygenic risk (PRS-SZ) and childhood adversity (CA) on psychosis outcomes was contingent on co-presence of affective dysregulation, defined as significant depressive symptoms, in (i) NEMESIS-2 (n = 6646), a representative general population sample, interviewed four times over nine years and (ii) EUGEI (n = 4068) a sample of patients with schizophrenia spectrum disorder, the siblings of these patients and controls.
The impact of PRS-SZ on psychosis showed significant dependence on co-presence of affective dysregulation in NEMESIS-2 [relative excess risk due to interaction (RERI): 1.01, p = 0.037] and in EUGEI (RERI = 3.39, p = 0.048). This was particularly evident for delusional ideation (NEMESIS-2: RERI = 1.74, p = 0.003; EUGEI: RERI = 4.16, p = 0.019) and not for hallucinatory experiences (NEMESIS-2: RERI = 0.65, p = 0.284; EUGEI: −0.37, p = 0.547). A similar and stronger pattern of results was evident for CA (RERI delusions and hallucinations: NEMESIS-2: 3.02, p < 0.001; EUGEI: 6.44, p < 0.001; RERI delusional ideation: NEMESIS-2: 3.79, p < 0.001; EUGEI: 5.43, p = 0.001; RERI hallucinatory experiences: NEMESIS-2: 2.46, p < 0.001; EUGEI: 0.54, p = 0.465).
The results, and internal replication, suggest that the effects of known genetic and non-genetic risk factors for psychosis are mediated in part through an affective pathway, from which early states of delusional meaning may arise.
This study attempted to replicate whether a bias in probabilistic reasoning, or ‘jumping to conclusions’(JTC) bias is associated with being a sibling of a patient with schizophrenia spectrum disorder; and if so, whether this association is contingent on subthreshold delusional ideation.
Data were derived from the EUGEI project, a 25-centre, 15-country effort to study psychosis spectrum disorder. The current analyses included 1261 patients with schizophrenia spectrum disorder, 1282 siblings of patients and 1525 healthy comparison subjects, recruited in Spain (five centres), Turkey (three centres) and Serbia (one centre). The beads task was used to assess JTC bias. Lifetime experience of delusional ideation and hallucinatory experiences was assessed using the Community Assessment of Psychic Experiences. General cognitive abilities were taken into account in the analyses.
JTC bias was positively associated not only with patient status but also with sibling status [adjusted relative risk (aRR) ratio : 4.23 CI 95% 3.46–5.17 for siblings and aRR: 5.07 CI 95% 4.13–6.23 for patients]. The association between JTC bias and sibling status was stronger in those with higher levels of delusional ideation (aRR interaction in siblings: 3.77 CI 95% 1.67–8.51, and in patients: 2.15 CI 95% 0.94–4.92). The association between JTC bias and sibling status was not stronger in those with higher levels of hallucinatory experiences.
These findings replicate earlier findings that JTC bias is associated with familial liability for psychosis and that this is contingent on the degree of delusional ideation but not hallucinations.
Within the Biostatistics, Epidemiology, and Research Design (BERD) component of the Northwestern University Clinical and Translational Sciences Institute, we created a mentoring program to complement training provided by the associated Multidisciplinary Career Development Program (KL2). Called Research design Analysis Methods Program (RAMP) Mentors, the program provides each KL2 scholar with individualized, hands-on mentoring in biostatistics, epidemiology, informatics, and related fields, with the goal of building multidisciplinary research teams. From 2015 to 2019, RAMP Mentors paired 8 KL2 scholars with 16 individually selected mentors. Mentors had funded/protected time to meet at least monthly with their scholar to provide advice and instruction on methods for ongoing research, including incorporating novel techniques. RAMP Mentors has been evaluated through focus groups and surveys. KL2 scholars reported high satisfaction with RAMP Mentors and confidence in their ability to establish and maintain methodologic collaborations. Compared with other Northwestern University K awardees, KL2 scholars reported higher confidence in obtaining research funding, including subsequent K or R awards, and selecting appropriate, up-to-date research methods. RAMP Mentors is a promising partnership between a BERD group and KL2 program, promoting methodologic education and building multidisciplinary research teams for junior investigators pursuing clinical and translational research.
Outbreaks of cyclosporiasis, a food-borne illness caused by the coccidian parasite Cyclospora cayetanensis have increased in the USA in recent years, with approximately 2300 laboratory-confirmed cases reported in 2018. Genotyping tools are needed to inform epidemiological investigations, yet genotyping Cyclospora has proven challenging due to its sexual reproductive cycle which produces complex infections characterized by high genetic heterogeneity. We used targeted amplicon deep sequencing and a recently described ensemble-based distance statistic that accommodates heterogeneous (mixed) genotypes and specimens with partial genotyping data, to genotype and cluster 648 C. cayetanensis samples submitted to CDC in 2018. The performance of the ensemble was assessed by comparing ensemble-identified genetic clusters to analogous clusters identified independently based on common food exposures. Using these epidemiologic clusters as a gold standard, the ensemble facilitated genetic clustering with 93.8% sensitivity and 99.7% specificity. Hence, we anticipate that this procedure will greatly complement epidemiologic investigations of cyclosporiasis.
Radiocarbon (14C) ages cannot provide absolutely dated chronologies for archaeological or paleoenvironmental studies directly but must be converted to calendar age equivalents using a calibration curve compensating for fluctuations in atmospheric 14C concentration. Although calibration curves are constructed from independently dated archives, they invariably require revision as new data become available and our understanding of the Earth system improves. In this volume the international 14C calibration curves for both the Northern and Southern Hemispheres, as well as for the ocean surface layer, have been updated to include a wealth of new data and extended to 55,000 cal BP. Based on tree rings, IntCal20 now extends as a fully atmospheric record to ca. 13,900 cal BP. For the older part of the timescale, IntCal20 comprises statistically integrated evidence from floating tree-ring chronologies, lacustrine and marine sediments, speleothems, and corals. We utilized improved evaluation of the timescales and location variable 14C offsets from the atmosphere (reservoir age, dead carbon fraction) for each dataset. New statistical methods have refined the structure of the calibration curves while maintaining a robust treatment of uncertainties in the 14C ages, the calendar ages and other corrections. The inclusion of modeled marine reservoir ages derived from a three-dimensional ocean circulation model has allowed us to apply more appropriate reservoir corrections to the marine 14C data rather than the previous use of constant regional offsets from the atmosphere. Here we provide an overview of the new and revised datasets and the associated methods used for the construction of the IntCal20 curve and explore potential regional offsets for tree-ring data. We discuss the main differences with respect to the previous calibration curve, IntCal13, and some of the implications for archaeology and geosciences ranging from the recent past to the time of the extinction of the Neanderthals.
Heavy alcohol consumption is associated with poorer cognitive function in older adults. Although understudied in middle-aged adults, the relationship between alcohol and cognition may also be influenced by genetics such as the apolipoprotein (ApoE) ε4 allele, a risk factor for Alzheimer’s disease. We examined the relationship between alcohol consumption, ApoE genotype, and cognition in middle-aged adults and hypothesized that light and/or moderate drinkers (≤2 drinks per day) would show better cognitive performance than heavy drinkers or non-drinkers. Additionally, we hypothesized that the association between alcohol use and cognitive function would differ by ApoE genotype (ε4+ vs. ε4−).
Participants were 1266 men from the Vietnam Era Twin Study of Aging (VETSA; M age = 56; range 51–60) who completed a neuropsychological battery assessing seven cognitive abilities: general cognitive ability (GCA), episodic memory, processing speed, executive function, abstract reasoning, verbal fluency, and visuospatial ability. Alcohol consumption was categorized into five groups: never, former, light, moderate, and heavy.
In fully adjusted models, there was no significant main effect of alcohol consumption on cognitive functions. However, there was a significant interaction between alcohol consumption and ApoE ε4 status for GCA and episodic memory, such that the relationship of alcohol consumption and cognition was stronger in ε4 carriers. The ε4+ heavy drinking subgroup had the poorest GCA and episodic memory.
Presence of the ε4 allele may increase vulnerability to the deleterious effects of heavy alcohol consumption. Beneficial effects of light or moderate alcohol consumption were not observed.
We describe 14 yr of public data from the Parkes Pulsar Timing Array (PPTA), an ongoing project that is producing precise measurements of pulse times of arrival from 26 millisecond pulsars using the 64-m Parkes radio telescope with a cadence of approximately 3 weeks in three observing bands. A comprehensive description of the pulsar observing systems employed at the telescope since 2004 is provided, including the calibration methodology and an analysis of the stability of system components. We attempt to provide full accounting of the reduction from the raw measured Stokes parameters to pulse times of arrival to aid third parties in reproducing our results. This conversion is encapsulated in a processing pipeline designed to track provenance. Our data products include pulse times of arrival for each of the pulsars along with an initial set of pulsar parameters and noise models. The calibrated pulse profiles and timing template profiles are also available. These data represent almost 21 000 h of recorded data spanning over 14 yr. After accounting for processes that induce time-correlated noise, 22 of the pulsars have weighted root-mean-square timing residuals of
in at least one radio band. The data should allow end users to quickly undertake their own gravitational wave analyses, for example, without having to understand the intricacies of pulsar polarisation calibration or attain a mastery of radio frequency interference mitigation as is required when analysing raw data files.
We describe an ultra-wide-bandwidth, low-frequency receiver recently installed on the Parkes radio telescope. The receiver system provides continuous frequency coverage from 704 to 4032 MHz. For much of the band (
), the system temperature is approximately 22 K and the receiver system remains in a linear regime even in the presence of strong mobile phone transmissions. We discuss the scientific and technical aspects of the new receiver, including its astronomical objectives, as well as the feed, receiver, digitiser, and signal processor design. We describe the pipeline routines that form the archive-ready data products and how those data files can be accessed from the archives. The system performance is quantified, including the system noise and linearity, beam shape, antenna efficiency, polarisation calibration, and timing stability.
The Genomics Used to Improve DEpresssion Decisions (GUIDED) trial assessed outcomes associated with combinatorial pharmacogenomic (PGx) testing in patients with major depressive disorder (MDD). Analyses used the 17-item Hamilton Depression (HAM-D17) rating scale; however, studies demonstrate that the abbreviated, core depression symptom-focused, HAM-D6 rating scale may have greater sensitivity toward detecting differences between treatment and placebo. However, the sensitivity of HAM-D6 has not been tested for two active treatment arms. Here, we evaluated the sensitivity of the HAM-D6 scale, relative to the HAM-D17 scale, when assessing outcomes for actively treated patients in the GUIDED trial.
Outpatients (N=1,298) diagnosed with MDD and an inadequate treatment response to >1 psychotropic medication were randomized into treatment as usual (TAU) or combinatorial PGx-guided (guided-care) arms. Combinatorial PGx testing was performed on all patients, though test reports were only available to the guided-care arm. All patients and raters were blinded to study arm until after week 8. Medications on the combinatorial PGx test report were categorized based on the level of predicted gene-drug interactions: ‘use as directed’, ‘moderate gene-drug interactions’, or ‘significant gene-drug interactions.’ Patient outcomes were assessed by arm at week 8 using HAM-D6 and HAM-D17 rating scales, including symptom improvement (percent change in scale), response (≥50% decrease in scale), and remission (HAM-D6 ≤4 and HAM-D17 ≤7).
At week 8, the guided-care arm demonstrated statistically significant symptom improvement over TAU using HAM-D6 scale (Δ=4.4%, p=0.023), but not using the HAM-D17 scale (Δ=3.2%, p=0.069). The response rate increased significantly for guided-care compared with TAU using both HAM-D6 (Δ=7.0%, p=0.004) and HAM-D17 (Δ=6.3%, p=0.007). Remission rates were also significantly greater for guided-care versus TAU using both scales (HAM-D6 Δ=4.6%, p=0.031; HAM-D17 Δ=5.5%, p=0.005). Patients taking medication(s) predicted to have gene-drug interactions at baseline showed further increased benefit over TAU at week 8 using HAM-D6 for symptom improvement (Δ=7.3%, p=0.004) response (Δ=10.0%, p=0.001) and remission (Δ=7.9%, p=0.005). Comparatively, the magnitude of the differences in outcomes between arms at week 8 was lower using HAM-D17 (symptom improvement Δ=5.0%, p=0.029; response Δ=8.0%, p=0.008; remission Δ=7.5%, p=0.003).
Combinatorial PGx-guided care achieved significantly better patient outcomes compared with TAU when assessed using the HAM-D6 scale. These findings suggest that the HAM-D6 scale is better suited than is the HAM-D17 for evaluating change in randomized, controlled trials comparing active treatment arms.
Terrestrial plant macrofossils from the sedimentary record of Lake Suigetsu, Japan, provide the only quasi-continuous direct atmospheric record of radiocarbon (14C) covering the last 50 ka cal BP (Bronk Ramsey et al. 2012). Since then, new high precision data have become available on U-Th dated speleothems from Hulu Cave China, covering the same time range (Cheng et al. 2018). In addition, an updated varve-based chronology has also been published for the 2006 core from Lake Suigetsu (SG06) based on extended microscopic analysis of the sediments and improved algorithms for interpolation (Schlolaut et al. 2018). Here we reanalyze the radiocarbon dataset from Suigetsu based on the new varve counting information and the constraints imposed by the speleothem data. This enables the new information on the calendar age scale of the Suigetsu dataset to be used in the construction of the consensus IntCal calibration curve. Comparison of the speleothem and plant macrofossil records provides insight into the mechanisms underlying the incorporation of carbon into different types of record and the relative strengths of different types of archive for calibration purposes.
We present a detailed overview of the cosmological surveys that we aim to carry out with Phase 1 of the Square Kilometre Array (SKA1) and the science that they will enable. We highlight three main surveys: a medium-deep continuum weak lensing and low-redshift spectroscopic HI galaxy survey over 5 000 deg2; a wide and deep continuum galaxy and HI intensity mapping (IM) survey over 20 000 deg2 from
$z = 0.35$
to 3; and a deep, high-redshift HI IM survey over 100 deg2 from
$z = 3$
to 6. Taken together, these surveys will achieve an array of important scientific goals: measuring the equation of state of dark energy out to
$z \sim 3$
with percent-level precision measurements of the cosmic expansion rate; constraining possible deviations from General Relativity on cosmological scales by measuring the growth rate of structure through multiple independent methods; mapping the structure of the Universe on the largest accessible scales, thus constraining fundamental properties such as isotropy, homogeneity, and non-Gaussianity; and measuring the HI density and bias out to
$z = 6$
. These surveys will also provide highly complementary clustering and weak lensing measurements that have independent systematic uncertainties to those of optical and near-infrared (NIR) surveys like Euclid, LSST, and WFIRST leading to a multitude of synergies that can improve constraints significantly beyond what optical or radio surveys can achieve on their own. This document, the 2018 Red Book, provides reference technical specifications, cosmological parameter forecasts, and an overview of relevant systematic effects for the three key surveys and will be regularly updated by the Cosmology Science Working Group in the run up to start of operations and the Key Science Programme of SKA1.