Estimation of conditional average treatment effects with high-dimensional data

Ministry of Education, Singapore under its Academic Research Funding Tier

Co-variations and Clustering of Chronic Disease Behavioral Risk Factors in China: China Chronic Disease and Risk Factor Surveillance, 2007

BACKGROUND: Chronic diseases have become the leading causes of mortality in China and related behavioral risk factors (BRFs) changed dramatically in past decades. We aimed to examine the prevalence, co-variations, clustering and the independent correlates of five BRFs at the national level. METHODOLOGY/PRINCIPAL FINDINGS: We used data from the 2007 China Chronic Disease and Risk Factor Surveillance, in which multistage clustering sampling was adopted to collect a nationally representative sample of 49,247 Chinese aged 15 to 69 years. We estimated the prevalence and clustering (mean number of BRFs) of five BRFs: tobacco use, excessive alcohol drinking, insufficient intake of vegetable and fruit, physical inactivity, and overweight or obesity. We conducted binary logistic regression models to examine the co-variations among five BRFs with adjustment of demographic and socioeconomic factors, chronic conditions and other BRFs. Ordinal logistic regression was constructed to investigate the independent associations between each covariate and the clustering of BRFs within individuals. Overall, 57.0% of Chinese population had at least two BRFs and the mean number of BRFs is 1.80 (95% confidence interval: 1.78-1.83). Eight of the ten pairs of bivariate associations between the five BRFs were found statistically significant. Chinese with older age, being a male, living in rural areas, having lower education level and lower yearly household income experienced increased likelihood of having more BRFs. CONCLUSIONS/SIGNIFICANCE: Current BRFs place the majority of Chinese aged 15 to 69 years at risk for the future development of chronic disease, which calls for urgent public health programs to reduce these risk factors. Prominent correlations between BRFs imply that a combined package of interventions targeting multiple BRFs might be appropriate. These interventions should target elder population, men, and rural residents, especially those with lower SES

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Expanding the Current Imaging Toolkit With Novel Fluorescent Protein Based Biosensors

The objective of my Ph.D. study is to develop novel genetically encoded fluorescent biosensors to image and dissect biological signaling pathways in the context of live cells. I utilized protein engineering techniques to convert fluorescent proteins into fluorescent biosensors that can actively respond to specific, spatiotemporally organized cellular changes.In this thesis, we expanded the fluorescent protein toolkit by engineering one of the first red fluorescent probes⎯rxRFP1⎯for sensing general redox states in the live cells. To further extend the usage of this sensor in various subcellular domains, such as mitochondria, endoplasmic reticulum, and the cell nucleus, we developed a group of rxRFP1 mutants showing different midpoint redox potentials for studying compartmentalized redox dynamics under various pathophysiological conditions. We also developed the first genetically encoded fluorescent biosensor for thioredoxin (Trx) redox by engineering a redox relay between the active-site cysteines of human Trx1 and rxRFP1. We utilized the resultant biosensor⎯TrxRFP1⎯to selectively monitor the perturbations of Trx redox in various mammalian cell lines. We further combined TrxRFP1 with a green fluorescent Grx1-roGFP2 biosensor to simultaneously monitor the dynamics of the two major cellular antioxidant systems, Trx and glutathione, in live cells in response to chemically and physiologically relevant stimuli. We exploit another strategy which introduces reactive functional groups into circular permutated fluorescent proteins (cpFPs) using a genetic code expansion technology. Through a powerful directed protein evolution process, we were able to modulate the reactivity and chemoselectivity of an introduced p-boronophenylalanine (pBoF) in a cpRFP scaffold, resulting in fluorescent probes selectively responsive to hydrogen peroxide (H2O2) and peroxynitrite (ONOO—). Furthermore, by using boronic acid and short peptides as synergistic recognition motifs, we were able to engineer a series of reversible probes for nucleotides and carbohydrates showing surprisingly high specificity and large dynamic ranges. We have successfully utilized this new family of fluorescent probes to visualize various cellular activities

Monitoring redox dynamics in living cells with a redox-sensitive red fluorescent protein.

Redox signaling and homeostasis are important for all forms of life on Earth. There has been great interest in monitoring redox dynamics in living cells and organisms as a mean to better understand redox biology in physiological and pathological conditions. Herein we report our recent results on the development of a genetically encoded redox-sensitive red fluorescent protein (rxRFP). We first identified a circularly permuted RFP (cpRFP) scaffold, which maintained its autocatalytic fluorescence, from a red fluorescent Ca(2+) sensor, R-GECO1. We then introduced cysteine residue pairs to the N- and C- termini of the cpRFP scaffold, and subsequently optimized the length and composition of the sequences adjacent to the cysteine residues. From these libraries, we identified rxRFP, showing up to a 4-fold fluorescence increase in the oxidized state compared to the reduced state at pH 7.4. We thoroughly characterized rxRFP in vitro, and expressed it in living mammalian cells to monitor redox dynamics. With its excitation peak at 576 nm and emission peak at 600 nm, rxRFP is one of the first genetically encoded red fluorescent probes that can sense general redox states

Mean number of chronic disease BRFs among different groups of Chinese aged 15–69 years and the independent correlates of BRFs clustering (2007 China Chronic Disease and Risk Factor Surveillance^a).

a<p>All analysis were weighted to represent the total population of national disease surveillance points system with post-stratification for age and gender.</p>b<p>Confidence intervals taking into account the complex survey design.</p>c<p>Cumulative odds ratios from a multivariate ordinal logistic regression model based on complex survey design with adjustment for all covariates. The number of the BRFs was the dependent variable.</p