Development of a key performance indicator system to benchmark relative paratransit performance

The Americans with Disabilities Act of 1990 prohibits discrimination against people with disabilities. US transit agencies are therefore required to offer services to eligible customers that complement the mobility opportunities provided to the general public on fixed-route public transit. While these paratransit services are necessary and just, they represent a proportionally large cost to agencies: approximately eight times the cost per boarding compared to fixed-route bus service. To be able to identify opportunities for (cost) efficiencies, and to further improve the quality of paratransit services offered, the twenty agencies of the American Bus Benchmarking Group (ABBG) decided to benchmark their relative performance in paratransit management and operations. To ensure comparability of agencies’ performance and hence ensure the usefulness of the benchmarking program, a key performance indicator system was developed and associated data items were defined in detail. The scope of this system went beyond the data already provided to the National Transit Database, both in amount and granularity of data collected, as well as the detail of definitions. This paper describes the challenges, respective solutions, and other lessons identified during four years of paratransit benchmarking development led by Imperial College London, the ABBG facilitators. The paper provides transit agencies and authorities as well as benchmarking practitioners and academics an opportunity to apply these lessons for the further benefit of paratransit services and their customers around the U.S

Novel Genetic Loci Underlying Human Intracranial Volume Identified through Genome-Wide Association

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five novel loci for intracranial volume and confirmed two known signals. Four of the loci are also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic=0.748), which indicated a similar genetic background and allowed for the identification of four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, Parkinson’s disease, and enriched near genes involved in growth pathways including PI3K–AKT signaling. These findings identify biological underpinnings of intracranial volume and provide genetic support for theories on brain reserve and brain overgrowth

Replication of LDL SWAs hits in PROSPER/PHASE as validation for future (pharmaco)genetic analyses

<p><b>Background:</b> The PHArmacogenetic study of Statins in the Elderly at risk (PHASE) is a genome wide association study in the PROspective Study of Pravastatin in the Elderly at risk for vascular disease (PROSPER) that investigates the genetic variation responsible for the individual variation in drug response to pravastatin. Statins lower LDL-cholesterol in general by 30%, however not in all subjects. Moreover, clinical response is highly variable and adverse effects occur in a minority of patients. In this report we first describe the rationale of the PROSPER/PHASE project and second show that the PROSPER/PHASE study can be used to study pharmacogenetics in the elderly.</p> <p><b>Methods:</b> The genome wide association study (GWAS) was conducted using the Illumina 660K-Quad beadchips following manufacturer's instructions. After a stringent quality control 557,192 SNPs in 5,244 subjects were available for analysis. To maximize the availability of genetic data and coverage of the genome, imputation up to 2.5 million autosomal CEPH HapMap SNPs was performed with MACH imputation software. The GWAS for LDL-cholesterol is assessed with an additive linear regression model in PROBABEL software, adjusted for age, sex, and country of origin to account for population stratification.</p> <p><b>Results:</b> Forty-two SNPs reached the GWAS significant threshold of p = 5.0e-08 in 5 genomic loci (APOE/APOC1; LDLR; FADS2/FEN1; HMGCR; PSRC1/CELSR5). The top SNP (rs445925, chromosome 19) with a p-value of p = 2.8e-30 is located within the APOC1 gene and near the APOE gene. The second top SNP (rs6511720, chromosome 19) with a p-value of p = 5.22e-15 is located within the LDLR gene. All 5 genomic loci were previously associated with LDL-cholesterol levels, no novel loci were identified. Replication in WOSCOPS and CARE confirmed our results.</p> <p><b>Conclusion:</b> With the GWAS in the PROSPER/PHASE study we confirm the previously found genetic associations with LDL-cholesterol levels. With this proof-of-principle study we show that the PROSPER/PHASE study can be used to investigate genetic associations in a similar way to population based studies. The next step of the PROSPER/PHASE study is to identify the genetic variation responsible for the variation in LDL-cholesterol lowering in response to statin treatment in collaboration with other large trials.</p&gt

Genetic risk prediction of atrial fibrillation

Background—Atrial fibrillation (AF) has a substantial genetic basis. Identification of individuals at greatest AF risk could minimize the incidence of cardioembolic stroke. Methods—To determine whether genetic data can stratify risk for development of AF, we examined associations between AF genetic risk scores and incident AF in five prospective studies comprising 18,919 individuals of European ancestry. We examined associations between AF genetic risk scores and ischemic stroke in a separate study of 509 ischemic stroke cases (202 cardioembolic [40%]) and 3,028 referents. Scores were based on 11 to 719 common variants (≥5%) associated with AF at P-values ranging from <1x10-3 to <1x10-8 in a prior independent genetic association study. Results—Incident AF occurred in 1,032 (5.5%) individuals. AF genetic risk scores were associated with new-onset AF after adjusting for clinical risk factors. The pooled hazard ratio for incident AF for the highest versus lowest quartile of genetic risk scores ranged from 1.28 (719 variants; 95%CI, 1.13-1.46; P=1.5x10-4) to 1.67 (25 variants; 95%CI, 1.47-1.90; P=9.3x10-15). Discrimination of combined clinical and genetic risk scores varied across studies and scores (maximum C statistic, 0.629-0.811; maximum ΔC statistic from clinical score alone, 0.009-0.017). AF genetic risk was associated with stroke in age- and sex-adjusted models. For example, individuals in the highest versus lowest quartile of a 127-variant score had a 2.49-fold increased odds of cardioembolic stroke (95%CI, 1.39-4.58; P=2.7x10-3). The effect persisted after excluding individuals (n=70) with known AF (odds ratio, 2.25; 95%CI, 1.20-4.40; P=0.01). Conclusions—Comprehensive AF genetic risk scores were associated with incident AF beyond associations for clinical AF risk factors, though offered small improvements in discrimination. AF genetic risk was also associated with cardioembolic stroke in age- and sex-adjusted analyses. Efforts are warranted to determine whether AF genetic risk may improve identification of subclinical AF or help distinguish between stroke mechanisms

Subclinical Thyroid Dysfunction and the Risk of Cognitive Decline: a Meta-Analysis of Prospective Cohort Studies.

Although both overt hyper- and hypothyroidism are known to lead to cognitive impairment, data on the association between subclinical thyroid dysfunction and cognitive function are conflicting. This study sought to determine the risk of dementia and cognitive decline associated with subclinical thyroid dysfunction among prospective cohorts. We searched in MEDLINE and EMBASE from inception until November 2014. Two physicians identified prospective cohorts that assessed thyroid function and cognitive outcomes (dementia; Mini-Mental State Examination [MMSE]). Data were extracted by one reviewer following standardized protocols and verified by a second reviewer. The primary outcome was dementia and decline in cognitive function was the secondary outcome. Eleven prospective cohorts followed 16,805 participants during a median followup of 44.4 months. Five studies analyzed the risk of dementia in subclinical hyperthyroidism (SHyper) (n = 6410), six in subclinical hypothyroidism (SHypo) (n = 7401). Five studies analyzed MMSE decline in SHyper (n = 7895), seven in SHypo (n = 8960). In random-effects models, the pooled adjusted risk ratio for dementia in SHyper was 1.67 (95% confidence interval, 1.04; 2.69) and 1.14 (95% confidence interval, 0.84; 1.55) in SHypo vs euthyroidism, both without evidence of significant heterogeneity (I(2) = 0.0%). The pooled mean MMSE decline from baseline to followup (mean 32 mo) did not significantly differ between SHyper or SHypo vs euthyroidism. SHyper might be associated with an elevated risk for dementia, whereas SHypo is not, and both conditions are not associated with faster decline in MMSE over time. Available data are limited, and additional large, high-quality studies are needed

Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: a pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD

Calibration of NOMAD on ESA's ExoMars Trace Gas Orbiter: Part 2 – The Limb, Nadir and Occultation (LNO) channel

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).The Nadir and Occultation for MArs Discovery (NOMAD) instrument is a 3-channel spectrometer suite on the ESA ExoMars Trace Gas Orbiter. Since April 2018, when the nominal science mission began, it has been measuring the constituents of the Martian atmosphere. NOMAD contains three separate spectrometers, two of which operate in the infrared: the Solar Occultation (SO) channel makes only solar occultation observations, and therefore has the best resolving power (∼20,000) and a wider spectral region covering 2.2–4.3 ​μm. The Limb, Nadir and Occultation (LNO) channel covers the 2.2–3.8 ​μm spectral region and can operate in limb, nadir or solar occultation pointing modes. The Ultraviolet–VISible (UVIS) channel operates in the UV–visible region, from 200 to 650 ​nm, and can measure in limb, nadir or solar occultation modes like LNO. The LNO channel has a lower resolving power (∼10,000) than the SO channel, but is still typically an order of magnitude better than previous instruments orbiting Mars. The channel primarily operates in nadir-viewing mode, pointing directly down to the surface to measure the narrow atmospheric molecular absorption lines, clouds and surface features in the reflected sunlight. From the depth and position of the observed atmospheric absorption lines, the constituents of the Martian atmosphere and their column densities can be derived, leading to new insights into the processes that govern their distribution and transport. Surface properties can also be derived from nadir observations by observing the shape of the spectral continuum. Many calibration measurements were made prior to launch, on the voyage to Mars, and continue to be made in-flight during the science phase of the mission. This work, part 2, addresses the aspects of the LNO channel calibration that are not covered elsewhere, namely: the LNO ground calibration setup, the LNO occultation and nadir boresight pointing vectors, LNO detector characterisation and nadir/limb illumination pattern, instrument temperature effects, and finally the radiometric calibration of the LNO channel. An accompanying paper, part 1 (Thomas et al., 2021, this issue), addresses similar aspects for SO, the other infrared channel in NOMAD. A further accompanying paper (Cruz-Mermy et al., 2021, this issue) investigated the LNO radiometric calibration in more detail, approaching the work from a theoretical perspective. The two calibrations agree with each other to within 3%, validating each calibration method. © 2022 The Authors. Published by Elsevier Ltd.This project acknowledges funding by the Belgian Science Policy Office (BELSPO), with the financial and contractual coordination by the ESA Prodex Office (PEA 4000103401, 4000121493), by Spanish Ministry of Science and Innovation (MCIU) and by European funds under grants PGC2018-101836-B-I00 and ESP2017-87143-R (MINECO/FEDER), as well as by the UK Space Agency through grants ST/V002295/1, ST/V005332/1 and ST/S00145X/1 and ST/R001405/1 and Italian Space Agency through grant 2018-2-HH.0. This work was supported by the Belgian Fonds de la Recherche Scientifique – FNRS under grant number 30442502 (ET_HOME). The IAA/CSIC team acknowledges financial support from the State Agency for Research of the Spanish MCIU through the ‘Center of Excellence Severo Ochoa’ award for the Instituto de Astrofísica de Andalucía (SEV-2017-0709). SR thanks BELSPO for the FED-tWIN funding (Prf-2019-077 - RT-MOLEXO)

Life expectancy associated with different ages at diagnosis of type 2 diabetes in high-income countries:23 million person-years of observation

Background:The prevalence of type 2 diabetes is increasing rapidly, particularly among younger age groups. Estimates suggest that people with diabetes die, on average, 6 years earlier than people without diabetes. We aimed to provide reliable estimates of the associations between age at diagnosis of diabetes and all-cause mortality, cause-specific mortality, and reductions in life expectancy. Methods:For this observational study, we conducted a combined analysis of individual-participant data from 19 high-income countries using two large-scale data sources: the Emerging Risk Factors Collaboration (96 cohorts, median baseline years 1961–2007, median latest follow-up years 1980–2013) and the UK Biobank (median baseline year 2006, median latest follow-up year 2020). We calculated age-adjusted and sex-adjusted hazard ratios (HRs) for all-cause mortality according to age at diagnosis of diabetes using data from 1 515 718 participants, in whom deaths were recorded during 23·1 million person-years of follow-up. We estimated cumulative survival by applying age-specific HRs to age-specific death rates from 2015 for the USA and the EU. Findings: For participants with diabetes, we observed a linear dose–response association between earlier age at diagnosis and higher risk of all-cause mortality compared with participants without diabetes. HRs were 2·69 (95% CI 2·43–2·97) when diagnosed at 30–39 years, 2·26 (2·08–2·45) at 40–49 years, 1·84 (1·72–1·97) at 50–59 years, 1·57 (1·47–1·67) at 60–69 years, and 1·39 (1·29–1·51) at 70 years and older. HRs per decade of earlier diagnosis were similar for men and women. Using death rates from the USA, a 50-year-old individual with diabetes died on average 14 years earlier when diagnosed aged 30 years, 10 years earlier when diagnosed aged 40 years, or 6 years earlier when diagnosed aged 50 years than an individual without diabetes. Using EU death rates, the corresponding estimates were 13, 9, or 5 years earlier. Interpretation: Every decade of earlier diagnosis of diabetes was associated with about 3–4 years of lower life expectancy, highlighting the need to develop and implement interventions that prevent or delay the onset of diabetes and to intensify the treatment of risk factors among young adults diagnosed with diabetes.</p

Subclinical thyroid dysfunction and depressive symptoms: protocol for a systematic review and individual participant data meta-analysis of prospective cohort studies

INTRODUCTION: Prospective cohort studies on the association between subclinical thyroid dysfunction and depressive symptoms have yielded conflicting findings, possibly because of differences in age, sex, thyroid-stimulating hormone cut-off levels or degree of baseline depressive symptoms. Analysis of individual participant data (IPD) may help clarify this association. METHODS AND ANALYSIS: We will conduct a systematic review and IPD meta-analysis of prospective studies on the association between subclinical thyroid dysfunction and depressive symptoms. We will identify studies through a systematic search of the literature in the Ovid Medline, Ovid Embase, Cochrane Central Register of Controlled Trials (CENTRAL) and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases from inception to April 2019 and from the Thyroid Studies Collaboration. We will ask corresponding authors of studies that meet our inclusion criteria to collaborate by providing IPD. Our primary outcome will be depressive symptoms at the first available individual follow-up, measured on a validated scale. We will convert all the scores to the Beck Depression Inventory scale. For each cohort, we will estimate the mean difference of depressive symptoms between participants with subclinical hypothyroidism or hyperthyroidism and control adjusted for depressive symptoms at baseline. Furthermore, we will adjust our multivariable linear regression analyses for age, sex, education and income. We will pool the effect estimates of all studies in a random-effects meta-analysis. Heterogeneity will be assessed by I2. Our secondary outcomes will be depressive symptoms at a specific follow-up time, at the last available individual follow-up and incidence of depression at the first, last and at a specific follow-up time. For the binary outcome of incident depression, we will use a logistic regression model. ETHICS AND DISSEMINATION: Formal ethical approval is not required as primary data will not be collected. Our findings will have considerable implications for patient care. We will seek to publish this systematic review and IPD meta-analysis in a high-impact clinical journal. PROSPERO REGISTRATION NUMBER: CRD42018091627