| 1. |
- Turcot, Valerie, et al.
(författare)
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Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity
- 2018
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 50:1, s. 26-41
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are similar to 10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed similar to 7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
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| 2. |
- Paluch, Amanda E., et al.
(författare)
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Daily steps and all-cause mortality : a meta-analysis of 15 international cohorts
- 2022
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Ingår i: The Lancet Public Health. - : Elsevier. - 2468-2667. ; 7:3, s. e219-e228
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Although 10 000 steps per day is widely promoted to have health benefits, there is little evidence to support this recommendation. We aimed to determine the association between number of steps per day and stepping rate with all-cause mortality.METHODS: In this meta-analysis, we identified studies investigating the effect of daily step count on all-cause mortality in adults (aged ≥18 years), via a previously published systematic review and expert knowledge of the field. We asked participating study investigators to process their participant-level data following a standardised protocol. The primary outcome was all-cause mortality collected from death certificates and country registries. We analysed the dose-response association of steps per day and stepping rate with all-cause mortality. We did Cox proportional hazards regression analyses using study-specific quartiles of steps per day and calculated hazard ratios (HRs) with inverse-variance weighted random effects models.FINDINGS: We identified 15 studies, of which seven were published and eight were unpublished, with study start dates between 1999 and 2018. The total sample included 47 471 adults, among whom there were 3013 deaths (10·1 per 1000 participant-years) over a median follow-up of 7·1 years ([IQR 4·3-9·9]; total sum of follow-up across studies was 297 837 person-years). Quartile median steps per day were 3553 for quartile 1, 5801 for quartile 2, 7842 for quartile 3, and 10 901 for quartile 4. Compared with the lowest quartile, the adjusted HR for all-cause mortality was 0·60 (95% CI 0·51-0·71) for quartile 2, 0·55 (0·49-0·62) for quartile 3, and 0·47 (0·39-0·57) for quartile 4. Restricted cubic splines showed progressively decreasing risk of mortality among adults aged 60 years and older with increasing number of steps per day until 6000-8000 steps per day and among adults younger than 60 years until 8000-10 000 steps per day. Adjusting for number of steps per day, comparing quartile 1 with quartile 4, the association between higher stepping rates and mortality was attenuated but remained significant for a peak of 30 min (HR 0·67 [95% CI 0·56-0·83]) and a peak of 60 min (0·67 [0·50-0·90]), but not significant for time (min per day) spent walking at 40 steps per min or faster (1·12 [0·96-1·32]) and 100 steps per min or faster (0·86 [0·58-1·28]).INTERPRETATION: Taking more steps per day was associated with a progressively lower risk of all-cause mortality, up to a level that varied by age. The findings from this meta-analysis can be used to inform step guidelines for public health promotion of physical activity.FUNDING: US Centers for Disease Control and Prevention.
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| 3. |
- Paluch, Amanda E., et al.
(författare)
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Prospective association of daily steps with cardiovascular disease : a harmonized meta-analysis
- 2023
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Ingår i: Circulation. - 0009-7322 .- 1524-4539. ; 147:2, s. 122-131
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Taking fewer than the widely promoted "10 000 steps per day" has recently been associated with lower risk of all-cause mortality. The relationship of steps and cardiovascular disease (CVD) risk remains poorly described. A meta-analysis examining the dose-response relationship between steps per day and CVD can help inform clinical and public health guidelines.METHODS: Eight prospective studies (20 152 adults [ie, ≥18 years of age]) were included with device-measured steps and participants followed for CVD events. Studies quantified steps per day and CVD events were defined as fatal and nonfatal coronary heart disease, stroke, and heart failure. Cox proportional hazards regression analyses were completed using study-specific quartiles and hazard ratios (HR) and 95% CI were meta-analyzed with inverse-variance-weighted random effects models.RESULTS: The mean age of participants was 63.2±12.4 years and 52% were women. The mean follow-up was 6.2 years (123 209 person-years), with a total of 1523 CVD events (12.4 per 1000 participant-years) reported. There was a significant difference in the association of steps per day and CVD between older (ie, ≥60 years of age) and younger adults (ie, <60 years of age). For older adults, the HR for quartile 2 was 0.80 (95% CI, 0.69 to 0.93), 0.62 for quartile 3 (95% CI, 0.52 to 0.74), and 0.51 for quartile 4 (95% CI, 0.41 to 0.63) compared with the lowest quartile. For younger adults, the HR for quartile 2 was 0.79 (95% CI, 0.46 to 1.35), 0.90 for quartile 3 (95% CI, 0.64 to 1.25), and 0.95 for quartile 4 (95% CI, 0.61 to 1.48) compared with the lowest quartile. Restricted cubic splines demonstrated a nonlinear association whereby more steps were associated with decreased risk of CVD among older adults.CONCLUSIONS: For older adults, taking more daily steps was associated with a progressively decreased risk of CVD. Monitoring and promoting steps per day is a simple metric for clinician-patient communication and population health to reduce the risk of CVD.
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| 4. |
- ODonnell, Michael, et al.
(författare)
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Registered Replication Report: Dijksterhuis and van Knippenberg (1998)
- 2018
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Ingår i: Perspectives on Psychological Science. - : SAGE PUBLICATIONS LTD. - 1745-6916 .- 1745-6924. ; 13:2, s. 268-294
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Tidskriftsartikel (refereegranskat)abstract
- Dijksterhuis and van Knippenberg (1998) reported that participants primed with a category associated with intelligence (professor) subsequently performed 13% better on a trivia test than participants primed with a category associated with a lack of intelligence (soccer hooligans). In two unpublished replications of this study designed to verify the appropriate testing procedures, Dijksterhuis, van Knippenberg, and Holland observed a smaller difference between conditions (2%-3%) as well as a gender difference: Men showed the effect (9.3% and 7.6%), but women did not (0.3% and -0.3%). The procedure used in those replications served as the basis for this multilab Registered Replication Report. A total of 40 laboratories collected data for this project, and 23 of these laboratories met all inclusion criteria. Here we report the meta-analytic results for those 23 direct replications (total N = 4,493), which tested whether performance on a 30-item general-knowledge trivia task differed between these two priming conditions (results of supplementary analyses of the data from all 40 labs, N = 6,454, are also reported). We observed no overall difference in trivia performance between participants primed with the professor category and those primed with the hooligan category (0.14%) and no moderation by gender.
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| 5. |
- Clark, Andrew G., et al.
(författare)
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Evolution of genes and genomes on the Drosophila phylogeny
- 2007
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 450:7167, s. 203-218
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Tidskriftsartikel (refereegranskat)abstract
- Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.
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| 6. |
- Jones, Benedict C, et al.
(författare)
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To which world regions does the valence-dominance model of social perception apply?
- 2021
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Ingår i: Nature Human Behaviour. - : Springer Science and Business Media LLC. - 2397-3374. ; 5:1, s. 159-169
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Tidskriftsartikel (refereegranskat)abstract
- Over the past 10 years, Oosterhof and Todorov's valence-dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov's methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov's original analysis strategy, the valence-dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence-dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 5 November 2018. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.7611443.v1 .
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| 7. |
- Sjölander, Arvid, et al.
(författare)
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Bias results for nondifferential mismeasurement of a binary confounder
- 2022
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Ingår i: Statistics and Probability Letters. - : Elsevier. - 0167-7152 .- 1879-2103. ; 186
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Tidskriftsartikel (refereegranskat)abstract
- Suppose we want to estimate the causal effect of an exposure on an outcome, while adjusting for a binary confounder. Suppose that the confounder is measured with error, but that the measurement error is nondifferential. We show that, under certain assumptions, adjusting for the mismeasured confounder produces a biased parameter that lies between the corresponding true and crude parameters. We further show how these assumptions can be tested empirically. We finally show that the bias when adjusting for the mismeasured confounder decreases with the sensitivity and specificity of the mismeasured confounder, provided that the sum of the sensitivity and specificity is at least one. These results have been shown previously for binary exposures and for specific effect measures. We generalize the results for exposures of any class (e.g. continuous and multilevel categorical) and for a wide range of effect measures that includes, but is not limited to, those considered previously.
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| 8. |
- Ciocanea-Teodorescu, Iuliana, et al.
(författare)
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Causal inference in survival analysis under deterministic missingness of confounders in register data
- 2023
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Ingår i: Statistics in Medicine. - : John Wiley & Sons. - 0277-6715 .- 1097-0258. ; 42:12, s. 1946-1964
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Tidskriftsartikel (refereegranskat)abstract
- Long-term register data offer unique opportunities to explore causal effects of treatments on time-to-event outcomes, in well-characterized populations with minimum loss of follow-up. However, the structure of the data may pose methodological challenges. Motivated by the Swedish Renal Registry and estimation of survival differences for renal replacement therapies, we focus on the particular case when an important confounder is not recorded in the early period of the register, so that the entry date to the register deterministically predicts confounder missingness. In addition, an evolving composition of the treatment arms populations, and suspected improved survival outcomes in later periods lead to informative administrative censoring, unless the entry date is appropriately accounted for. We investigate different consequences of these issues on causal effect estimation following multiple imputation of the missing covariate data. We analyse the performance of different combinations of imputation models and estimation methods for the population average survival. We further evaluate the sensitivity of our results to the nature of censoring and misspecification of fitted models. We find that an imputation model including the cumulative baseline hazard, event indicator, covariates and interactions between the cumulative baseline hazard and covariates, followed by regression standardization, leads to the best estimation results overall, in simulations. Standardization has two advantages over inverse probability of treatment weighting here: it can directly account for the informative censoring by including the entry date as a covariate in the outcome model, and allows for straightforward variance computation using readily available software.
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| 9. |
- Crippa, Alessio, et al.
(författare)
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The ProBio trial : molecular biomarkers for advancing personalized treatment decision in patients with metastatic castration-resistant prostate cancer
- 2020
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Ingår i: Trials. - : BioMed Central. - 1745-6215. ; 21:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Multiple therapies exist for patients with metastatic castration-resistant prostate cancer (mCRPC). However, their improvement on progression-free survival (PFS) remains modest, potentially explained by tumor molecular heterogeneity. Several prognostic molecular biomarkers have been identified for mCRPC that may have predictive potential to guide treatment selection and prolong PFS. We designed a platform trial to test this hypothesis.Methods: The Prostate-Biomarker (ProBio) study is a multi-center, outcome-adaptive, multi-arm, biomarker-driven platform trial for tailoring treatment decisions for men with mCRPC. Treatment decisions in the experimental arms are based on biomarker signatures defined as mutations in certain genes/pathways suggested in the scientific literature to be important for treatment response in mCRPC. The biomarker signatures are determined by targeted sequencing of circulating tumor and germline DNA using a panel specifically designed for mCRPC.Discussion: Patients are stratified based on the sequencing results and randomized to either current clinical practice (control), where the treating physician decides treatment, or to molecularly driven treatment selection based on the biomarker profile. Outcome-adaptive randomization is implemented to early identify promising treatments for a biomarker signature. Biomarker signature-treatment combinations graduate from the platform when they demonstrate 85% probability of improving PFS compared to the control arm. Graduated combinations are further evaluated in a seamless confirmatory trial with fixed randomization. The platform design allows for new drugs and biomarkers to be introduced in the study.Conclusions: The ProBio design allows promising treatment-biomarker combinations to quickly graduate from the platform and be confirmed for rapid implementation in clinical care.
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| 10. |
- Gabriel, Erin E., et al.
(författare)
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Bias attenuation results for dichotomization of a continuous confounder
- 2022
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Ingår i: Journal of Causal Inference. - : DE GRUYTER POLAND SP Z O O. - 2193-3677 .- 2193-3685. ; 10:1, s. 515-526
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Tidskriftsartikel (refereegranskat)abstract
- It is well-known that dichotomization can cause bias and loss of efficiency in estimation. One can easily construct examples where adjusting for a dichotomized confounder causes bias in causal estimation. There are additional examples in the literature where adjusting for a dichotomized confounder can be more biased than not adjusting at all. The message is clear, do not dichotomize. What is unclear is if there are scenarios where adjusting for the dichotomized confounder always leads to lower bias than not adjusting. We propose several sets of conditions that characterize scenarios where one should always adjust for the dichotomized confounder to reduce bias. We then highlight scenarios where the decision to adjust should be made more cautiously. To our knowledge, this is the first formal presentation of conditions that give information about when one should and potentially should not adjust for a dichotomized confounder.
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| 11. |
- Gabriel, Erin E., et al.
(författare)
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Inverse probability of treatment weighting with generalized linear outcome models for doubly robust estimation
- 2024
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Ingår i: Statistics in Medicine. - : John Wiley & Sons. - 0277-6715 .- 1097-0258. ; 43:3, s. 534-547
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Tidskriftsartikel (refereegranskat)abstract
- There are now many options for doubly robust estimation; however, there is a concerning trend in the applied literature to believe that the combination of a propensity score and an adjusted outcome model automatically results in a doubly robust estimator and/or to misuse more complex established doubly robust estimators. A simple alternative, canonical link generalized linear models (GLM) fit via inverse probability of treatment (propensity score) weighted maximum likelihood estimation followed by standardization (the g-formula) for the average causal effect, is a doubly robust estimation method. Our aim is for the reader not just to be able to use this method, which we refer to as IPTW GLM, for doubly robust estimation, but to fully understand why it has the doubly robust property. For this reason, we define clearly, and in multiple ways, all concepts needed to understand the method and why it is doubly robust. In addition, we want to make very clear that the mere combination of propensity score weighting and an adjusted outcome model does not generally result in a doubly robust estimator. Finally, we hope to dispel the misconception that one can adjust for residual confounding remaining after propensity score weighting by adjusting in the outcome model for what remains ‘unbalanced’ even when using doubly robust estimators. We provide R code for our simulations and real open-source data examples that can be followed step-by-step to use and hopefully understand the IPTW GLM method. We also compare to a much better-known but still simple doubly robust estimator.
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| 12. |
- Gabriel, Erin E., et al.
(författare)
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Propensity weighting plus adjustment in proportional hazards model is not doubly robust
- 2024
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Ingår i: Biometrics. - 0006-341X .- 1541-0420.
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Tidskriftsartikel (refereegranskat)abstract
- Recently, it has become common for applied works to combine commonly used survival analysis modelingmethods, such as the multivariable Cox model and propensity score weighting, with the intention of forming a doublyrobust estimator of an exposure effect hazard ratio that is unbiased in large samples when either the Cox model orthe propensity score model is correctly specified. This combination does not, in general, produce a doubly robustestimator, even after regression standardization, when there is truly a causal effect. We demonstrate via simulationthis lack of double robustness for the semiparametric Cox model, the Weibull proportional hazards model, and asimple proportional hazards flexible parametric model, with both the latter models fit via maximum likelihood. Weprovide a novel proof that the combination of propensity score weighting and a proportional hazards survival model,fit either via full or partial likelihood, is consistent under the null of no causal effect of the exposure on the outcomeunder particular censoring mechanisms if either the propensity score or the outcome model is correctly specified andcontains all confounders. Given our results suggesting that double robustness only exists under the null, we outlinetwo simple alternative estimators that are doubly robust for the survival difference at a given time point (in the abovesense), provided the censoring mechanism can be correctly modeled, and one doubly robust method of estimationfor the full survival curve. We provide R code to use these estimators for estimation and inference in the supporting information.
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| 13. |
- Pena, Jose M, et al.
(författare)
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On the bias of adjusting for a non-differentially mismeasured discrete confounder
- 2021
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Ingår i: Journal of Causal Inference. - : Walter de Gruyter. - 2193-3677 .- 2193-3685. ; 9:1, s. 229-249
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Tidskriftsartikel (refereegranskat)abstract
- Biological and epidemiological phenomena are often measured with error or imperfectly captured in data. When the true state of this imperfect measure is a confounder of an outcome exposure relationship of interest, it was previously widely believed that adjustment for the mismeasured observed variables provides a less biased estimate of the true average causal effect than not adjusting. However, this is not always the case and depends on both the nature of the measurement and confounding. We describe two sets of conditions under which adjusting for a non-deferentially mismeasured proxy comes closer to the unidentifiable true average causal effect than the unadjusted or crude estimate. The first set of conditions apply when the exposure is discrete or continuous and the confounder is ordinal, and the expectation of the outcome is monotonic in the confounder for both treatment levels contrasted. The second set of conditions apply when the exposure and the confounder are categorical (nominal). In all settings, the mismeasurement must be non-differential, as differential mismeasurement, particularly an unknown pattern, can cause unpredictable results.
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