A review of common statistical methods for dealing with multiple pollutant mixtures and multiple exposures

Traditional environmental epidemiology has consistently focused on studying the impact of single exposures on specific health outcomes, considering concurrent exposures as variables to be controlled. However, with the continuous changes in environment, humans are increasingly facing more complex exposures to multi-pollutant mixtures. In this context, accurately assessing the impact of multi-pollutant mixtures on health has become a central concern in current environmental research. Simultaneously, the continuous development and optimization of statistical methods offer robust support for handling large datasets, strengthening the capability to conduct in-depth research on the effects of multiple exposures on health. In order to examine complicated exposure mixtures, we introduce commonly used statistical methods and their developments, such as weighted quantile sum, bayesian kernel machine regression, toxic equivalency analysis, and others. Delineating their applications, advantages, weaknesses, and interpretability of results. It also provides guidance for researchers involved in studying multi-pollutant mixtures, aiding them in selecting appropriate statistical methods and utilizing R software for more accurate and comprehensive assessments of the impact of multi-pollutant mixtures on human health

Effects of Exercise Training on Cardiorespiratory Fitness and Biomarkers of Cardiometabolic Health: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

BACKGROUND: Guidelines recommend exercise for cardiovascular health, although evidence from trials linking exercise to cardiovascular health through intermediate biomarkers remains inconsistent. We performed a meta-analysis of randomized controlled trials to quantify the impact of exercise on cardiorespiratory fitness and a variety of conventional and novel cardiometabolic biomarkers in adults without cardiovascular disease. METHODS AND RESULTS: Two researchers selected 160 randomized controlled trials (7487 participants) based on literature searches of Medline, Embase, and Cochrane Central (January 1965 to March 2014). Data were extracted using a standardized protocol. A random-effects meta-analysis and systematic review was conducted to evaluate the effects of exercise interventions on cardiorespiratory fitness and circulating biomarkers. Exercise significantly raised absolute and relative cardiorespiratory fitness. Lipid profiles were improved in exercise groups, with lower levels of triglycerides and higher levels of high-density lipoprotein cholesterol and apolipoprotein A1. Lower levels of fasting insulin, homeostatic model assessment-insulin resistance, and glycosylated hemoglobin A1c were found in exercise groups. Compared with controls, exercise groups had higher levels of interleukin-18 and lower levels of leptin, fibrinogen, and angiotensin II. In addition, we found that the exercise effects were modified by age, sex, and health status such that people aged <50 years, men, and people with type 2 diabetes, hypertension, dyslipidemia, or metabolic syndrome appeared to benefit more. CONCLUSIONS: This meta-analysis showed that exercise significantly improved cardiorespiratory fitness and some cardiometabolic biomarkers. The effects of exercise were modified by age, sex, and health status. Findings from this study have significant implications for future design of targeted lifestyle interventions

Autistic clinical profiles, age at first concern, and diagnosis among children with autism spectrum disorder

BackgroundTo explore the relationship between autistic clinical profiles and age at first concern and diagnosis among children with autism spectrum disorder. The clinical profiles included the severity of autism, cognition, adaptability, language development, and regression.MethodsThe multivariate linear regression model was used to examine the association of diagnostic age and first-concern age with autistic clinical profiles and with further stratification analysis.ResultsA total of 801 autistic children were included. Language delay and regression were associated with earlier diagnostic age (language delay: crudeβ: −0.80, 95%CI%: −0.92–−0.68; regression: crudeβ: −0.21, 95%CI%: −0.43–−0.00) and the age of first concern of autistic children (language delay: crudeβ: −0.55, 95%CI%: −0.65–−0.45; regression: crudeβ: −0.17, 95%CI%: −0.34–−0.00). After stratification by sex, language delay tended to be more associated with the earlier diagnostic age among boys (crudeβ: −0.85, 95%CI%: −0.98–−0.72) than among girls (crudeβ: −0.46, 95%CI%: −0.77–−0.16). After stratification by maternal education level or family income level, language delay was most associated with the earlier diagnostic age in autistic children from families with higher socioeconomic levels.ConclusionLanguage delay, rather than other symptoms, promoted an earlier diagnostic age. Among male autistic children or children from families with higher socioeconomic levels, language delay was most significantly associated with an earlier age of diagnosis. Cognitive delay, or adaptive delay, was associated with a later age at diagnosis and presented only in autistic children from families with lower socioeconomic levels. There may be sex or socioeconomic inequality in the diagnostic age for autistic children. More publicity and public education about the diversity of autistic symptoms are urgently needed in the future, especially for low-socioeconomic families

Generation of host-directed and virus-specific antivirals using targeted protein degradation promoted by small molecules and viral RNA mimics.

Targeted protein degradation (TPD), as exemplified by proteolysis-targeting chimera (PROTAC), is an emerging drug discovery platform. PROTAC molecules, which typically contain a target protein ligand linked to an E3 ligase ligand, recruit a target protein to the E3 ligase to induce its ubiquitination and degradation. Here, we applied PROTAC approaches to develop broad-spectrum antivirals targeting key host factors for many viruses and virus-specific antivirals targeting unique viral proteins. For host-directed antivirals, we identified a small-molecule degrader, FM-74-103, that elicits selective degradation of human GSPT1, a translation termination factor. FM-74-103-mediated GSPT1 degradation inhibits both RNA and DNA viruses. Among virus-specific antivirals, we developed viral RNA oligonucleotide-based bifunctional molecules (Destroyers). As a proof of principle, RNA mimics of viral promoter sequences were used as heterobifunctional molecules to recruit and target influenza viral polymerase for degradation. This work highlights the broad utility of TPD to rationally design and develop next-generation antivirals

N-of-1 Trial of Jianpiqingrehuashi Granular Decoction with Mesalamine in the Treatment of Ulcerative Colitis in Remission with Spleen Deficiency-induced Damp-heat Syndrome

BackgroundThe patient with ulcerative colitis (UC) in remission has a long course of disease, and needs a long-term maintenance treatment. Traditional Chinese medicine (TCM) has proved to be partially effective in treating UC in remission, but the efficacy of Jianpiqingrehuashi granular decoction (JPQRHSGD) against UC in remission is not yet clear.ObjectiveTo evaluate the efficacy and safety of JPQRHSGD with mesalamine versus mesalamine in the treatment of UC in remission using an N-of-1 trial.MethodsAn N-of-1 trial was conducted between June 2020 and March 2021. Participant was an outpatient with UC in remission with spleen deficiency-induced dampness-heat syndrome who was selected from the First Affiliated Hospital, Guangzhou University of Chinese Medicine. The patient received a treatment program, namely four rounds of treatment without washout consisting of eight cycles〔each round includes two cycles, that was, one-month intervention treatment (use of JPQRHSGD with mesalamine) alternating with one-month control treatment (taking mesalamine only) 〕. Efficaciesof two types of treatment were evaluated by of the TCM Syndrome Score (TCMSS) , Bristol Stool Form Scale (BSFS) , visual analogue scale (VAS) for abdominal pain and diarrhea, and Short Health Scale (SHS) . Safety was also compared between the two treatments.ResultsThe total TCMSS in intervention period was significantly lower than that in control period (P&lt;0.05) . In particular, the symptoms of diarrhea, abdominal distension and fatigue of the limbs were improved more obviouslyin intervention period (P&lt;0.05) . The improvements of total BSFS score, and diarrhea VAS score in intervention period were better than those in control period (P&lt;0.05) . However, abdominal pain VAS score in intervention period was worse than that in control period (P&lt;0.05) . The improvement of SHS score in intervention period was better than those in control period (P&lt;0.05) . No treatment-related adverse events were reported.ConclusionThe JPQRHSGD with mesalamine improved the clinical symptoms of the UC patient in remission with spleen deficiency-induced dampness-heat syndrome, with relatively high safety

Risk Factors for Incident Hospitalized Heart Failure With Preserved Versus Reduced Ejection Fraction in a Multiracial Cohort of Postmenopausal WomenClinical Perspective

BACKGROUND: Heart failure is an important and growing public health problem in women. Risk factors for incident hospitalized heart failure with preserved ejection fraction (HFpEF) compared with heart failure with reduced ejection fraction (HFrEF) in women and differences by race/ethnicity are not well characterized. METHODS AND RESULTS: We prospectively evaluated the risk factors for incident hospitalized HFpEF and HFrEF in a multiracial cohort of 42 170 postmenopausal women followed up for a mean of 13.2 years. Cox regression models with time-dependent covariate adjustment were used to define risk factors for HFpEF and HFrEF. Differences by race/ethnicity about incidence rates, baseline risk factors, and their population-attributable risk percentage were analyzed. Risk factors for both HFpEF and HFrEF were as follows: older age, white race, diabetes mellitus, cigarette smoking, and hypertension. Obesity, history of coronary heart disease (other than myocardial infarction), anemia, atrial fibrillation, and more than one comorbidity were associated with HFpEF but not with HFrEF. History of myocardial infarction was associated with HFrEF but not with HFpEF. Obesity was found to be a more potent risk factor for African American women compared with white women for HFpEF (P for interaction=0.007). For HFpEF, the population-attributable risk percentage was greatest for hypertension (40.9%) followed by obesity (25.8%), with the highest population-attributable risk percentage found in African Americans for these risk factors. CONCLUSIONS: In this multiracial cohort of postmenopausal women, obesity stands out as a significant risk factor for HFpEF, with the strongest association in African American women. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00000611

Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. Video Abstract [Figure presented] Keywords: type 2 diabetes (T2D); genetics; disease mechanism; SLC16A11; MCT11; solute carrier (SLC); monocarboxylates; fatty acid metabolism; lipid metabolism; precision medicin

Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed

Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value OBFC1indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated our TL polygenic trait scores (PTS) were associated with increased risk of cancer-related phenotypes

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic