The long-term genetic stability and individual specificity of the human gut microbiome.

By following up the gut microbiome, 51 human phenotypes and plasma levels of 1,183 metabolites in 338 individuals after 4 years, we characterize microbial stability and variation in relation to host physiology. Using these individual-specific and temporally stable microbial profiles, including bacterial SNPs and structural variations, we develop a microbial fingerprinting method that shows up to 85% accuracy in classifying metagenomic samples taken 4 years apart. Application of our fingerprinting method to the independent HMP cohort results in 95% accuracy for samples taken 1 year apart. We further observe temporal changes in the abundance of multiple bacterial species, metabolic pathways, and structural variation, as well as strain replacement. We report 190 longitudinal microbial associations with host phenotypes and 519 associations with plasma metabolites. These associations are enriched for cardiometabolic traits, vitamin B, and uremic toxins. Finally, mediation analysis suggests that the gut microbiome may influence cardiometabolic health through its metabolites.

Linking the Human Gut Microbiome to Inflammatory Cytokine Production Capacity.

Gut microbial dysbioses are linked to aberrant immune responses, which are often accompanied by abnormal production of inflammatory cytokines. As part of the Human Functional Genomics Project (HFGP), we investigate how differences in composition and function of gut microbial communities may contribute to inter-individual variation in cytokine responses to microbial stimulations in healthy humans. We observe microbiome-cytokine interaction patterns that are stimulus specific, cytokine specific, and cytokine and stimulus specific. Validation of two predicted host-microbial interactions reveal that TNFα and IFNγ production are associated with specific microbial metabolic pathways: palmitoleic acid metabolism and tryptophan degradation to tryptophol. Besides providing a resource of predicted microbially derived mediators that influence immune phenotypes in response to common microorganisms, these data can help to define principles for understanding disease susceptibility. The three HFGP studies presented in this issue lay the groundwork for further studies aimed at understanding the interplay between microbial, genetic, and environmental factors in the regulation of the immune response in humans. PAPERCLIP.

Multi-cohort analysis of host immune response identifies conserved protective and detrimental modules associated with severity across viruses.

Viral infections induce a conserved host response distinct from bacterial infections. We hypothesized that the conserved response is associated with disease severity and is distinct between patients with different outcomes. To test this, we integrated 4,780 blood transcriptome profiles from patients aged 0 to 90 years infected with one of 16 viruses, including SARS-CoV-2, Ebola, chikungunya, and influenza, across 34 cohorts from 18 countries, and single-cell RNA sequencing profiles of 702,970 immune cells from 289 samples across three cohorts. Severe viral infection was associated with increased hematopoiesis, myelopoiesis, and myeloid-derived suppressor cells. We identified protective and detrimental gene modules that defined distinct trajectories associated with mild versus severe outcomes. The interferon response was decoupled from the protective host response in patients with severe outcomes. These findings were consistent, irrespective of age and virus, and provide insights to accelerate the development of diagnostics and host-directed therapies to improve global pandemic preparedness.

Promoting a MOSAIC future in science.

Discoveries at the frontiers of science and finding solutions to pressing biomedical problems will be accelerated when talent, which is widely distributed, is better aligned with opportunities. Strategies to enhance a MOSAIC (Maximizing Opportunities for Scientific and Academic Independent Careers) professoriate and diversify the biomedical landscape are discussed.

A Molecular Signature in Blood Reveals a Role for p53 in Regulating Malaria-Induced Inflammation.

Immunity that controls parasitemia and inflammation during Plasmodium falciparum (Pf) malaria can be acquired with repeated infections. A limited understanding of this complex immune response impedes the development of vaccines and adjunctive therapies. We conducted a prospective systems biology study of children who differed in their ability to control parasitemia and fever following Pf infection. By integrating whole-blood transcriptomics, flow-cytometric analysis, and plasma cytokine and antibody profiles, we demonstrate that a pre-infection signature of B cell enrichment, upregulation of T helper type 1 (Th1) and Th2 cell-associated pathways, including interferon responses, and p53 activation associated with control of malarial fever and coordinated with Pf-specific immunoglobulin G (IgG) and Fc receptor activation to control parasitemia. Our hypothesis-generating approach identified host molecules that may contribute to differential clinical outcomes during Pf infection. As a proof of concept, we have shown that enhanced p53 expression in monocytes attenuated Plasmodium-induced inflammation and predicted protection from fever.

Epigenome-wide association study of total nicotine equivalents in multiethnic current smokers from three prospective cohorts.

The impact of tobacco exposure on health varies by race and ethnicity and is closely tied to internal nicotine dose, a marker of carcinogen uptake. DNA methylation is strongly responsive to smoking status and may mediate health effects, but study of associations with internal dose is limited. We performed a blood leukocyte epigenome-wide association study (EWAS) of urinary total nicotine equivalents (TNEs; a measure of nicotine uptake) and DNA methylation measured using the MethylationEPIC v1.0 BeadChip (EPIC) in six racial and ethnic groups across three cohort studies. In the Multiethnic Cohort Study (discovery, n = 1994), TNEs were associated with differential methylation at 408 CpG sites across >250 genomic regions (p < 9 × 10-8). The top significant sites were annotated to AHRR, F2RL3, RARA, GPR15, PRSS23, and 2q37.1, all of which had decreasing methylation with increasing TNEs. We identified 45 novel CpG sites, of which 42 were unique to the EPIC array and eight annotated to genes not previously linked with smoking-related DNA methylation. The most significant signal in a novel gene was cg03748458 in MIR383;SGCZ. Fifty-one of the 408 discovery sites were validated in the Singapore Chinese Health Study (n = 340) and the Southern Community Cohort Study (n = 394) (Bonferroni corrected p < 1.23 × 10-4). Significant heterogeneity by race and ethnicity was detected for CpG sites in MYO1G and CYTH1. Furthermore, TNEs significantly mediated the association between cigarettes per day and DNA methylation at 15 sites (average 22.5%-44.3% proportion mediated). Our multiethnic study highlights the transethnic and ethnic-specific methylation associations with internal nicotine dose, a strong predictor of smoking-related morbidities.

MagicalRsq-X: A cross-cohort transferable genotype imputation quality metric.

Since genotype imputation was introduced, researchers have been relying on the estimated imputation quality from imputation software to perform post-imputation quality control (QC). However, this quality estimate (denoted as Rsq) performs less well for lower-frequency variants. We recently published MagicalRsq, a machine-learning-based imputation quality calibration, which leverages additional typed markers from the same cohort and outperforms Rsq as a QC metric. In this work, we extended the original MagicalRsq to allow cross-cohort model training and named the new model MagicalRsq-X. We removed the cohort-specific estimated minor allele frequency and included linkage disequilibrium scores and recombination rates as additional features. Leveraging whole-genome sequencing data from TOPMed, specifically participants in the BioMe, JHS, WHI, and MESA studies, we performed comprehensive cross-cohort evaluations for predominantly European and African ancestral individuals based on their inferred global ancestry with the 1000 Genomes and Human Genome Diversity Project data as reference. Our results suggest MagicalRsq-X outperforms Rsq in almost every setting, with 7.3%-14.4% improvement in squared Pearson correlation with true R2, corresponding to 85-218 K variant gains. We further developed a metric to quantify the genetic distances of a target cohort relative to a reference cohort and showed that such metric largely explained the performance of MagicalRsq-X models. Finally, we found MagicalRsq-X saved up to 53 known genome-wide significant variants in one of the largest blood cell trait GWASs that would be missed using the original Rsq for QC. In conclusion, MagicalRsq-X shows superiority for post-imputation QC and benefits genetic studies by distinguishing well and poorly imputed lower-frequency variants.

The impact of 22q11.2 copy-number variants on human traits in the general population.

While extensively studied in clinical cohorts, the phenotypic consequences of 22q11.2 copy-number variants (CNVs) in the general population remain understudied. To address this gap, we performed a phenome-wide association scan in 405,324 unrelated UK Biobank (UKBB) participants by using CNV calls from genotyping array. We mapped 236 Human Phenotype Ontology terms linked to any of the 90 genes encompassed by the region to 170 UKBB traits and assessed the association between these traits and the copy-number state of 504 genotyping array probes in the region. We found significant associations for eight continuous and nine binary traits associated under different models (duplication-only, deletion-only, U-shape, and mirror models). The causal effect of the expression level of 22q11.2 genes on associated traits was assessed through transcriptome-wide Mendelian randomization (TWMR), revealing that increased expression of ARVCF increased BMI. Similarly, increased DGCR6 expression causally reduced mean platelet volume, in line with the corresponding CNV effect. Furthermore, cross-trait multivariable Mendelian randomization (MVMR) suggested a predominant role of genuine (horizontal) pleiotropy in the CNV region. Our findings show that within the general population, 22q11.2 CNVs are associated with traits previously linked to genes in the region, and duplications and deletions act upon traits in different fashions. We also showed that gain or loss of distinct segments within 22q11.2 may impact a trait under different association models. Our results have provided new insights to help further the understanding of the complex 22q11.2 region.

AESurv: autoencoder survival analysis for accurate early prediction of coronary heart disease.

Coronary heart disease (CHD) is one of the leading causes of mortality and morbidity in the United States. Accurate time-to-event CHD prediction models with high-dimensional DNA methylation and clinical features may assist with early prediction and intervention strategies. We developed a state-of-the-art deep learning autoencoder survival analysis model (AESurv) to effectively analyze high-dimensional blood DNA methylation features and traditional clinical risk factors by learning low-dimensional representation of participants for time-to-event CHD prediction. We demonstrated the utility of our model in two cohort studies: the Strong Heart Study cohort (SHS), a prospective cohort studying cardiovascular disease and its risk factors among American Indians adults; the Women's Health Initiative (WHI), a prospective cohort study including randomized clinical trials and observational study to improve postmenopausal women's health with one of the main focuses on cardiovascular disease. Our AESurv model effectively learned participant representations in low-dimensional latent space and achieved better model performance (concordance index-C index of 0.864 ± 0.009 and time-to-event mean area under the receiver operating characteristic curve-AUROC of 0.905 ± 0.009) than other survival analysis models (Cox proportional hazard, Cox proportional hazard deep neural network survival analysis, random survival forest, and gradient boosting survival analysis models) in the SHS. We further validated the AESurv model in WHI and also achieved the best model performance. The AESurv model can be used for accurate CHD prediction and assist health care professionals and patients to perform early intervention strategies. We suggest using AESurv model for future time-to-event CHD prediction based on DNA methylation features.

Cohort bias in predictive risk assessments of future criminal justice system involvement.

Risk assessment instruments (RAIs) are widely used to aid high-stakes decision-making in criminal justice settings and other areas such as health care and child welfare. These tools, whether using machine learning or simpler algorithms, typically assume a time-invariant relationship between predictors and outcome. Because societies are themselves changing and not just individuals, this assumption may be violated in many behavioral settings, generating what we call cohort bias. Analyzing criminal histories in a cohort-sequential longitudinal study of children, we demonstrate that regardless of model type or predictor sets, a tool trained to predict the likelihood of arrest between the ages of 17 and 24 y on older birth cohorts systematically overpredicts the likelihood of arrest for younger birth cohorts over the period 1995 to 2020. Cohort bias is found for both relative and absolute risks, and it persists for all racial groups and within groups at highest risk for arrest. The results imply that cohort bias is an underappreciated mechanism generating inequality in contacts with the criminal legal system that is distinct from racial bias. Cohort bias is a challenge not only for predictive instruments with respect to crime and justice, but also for RAIs more broadly.

Generational differences in mental health trends in the twenty-first century.

Given the observed deterioration in mental health among Australians over the past decade, this study investigates to what extent this differs in people born in different decades-i.e., possible birth cohort differences in the mental health of Australians. Using 20 y of data from a large, nationally representative panel survey (N = 27,572), we find strong evidence that cohort effects are driving the increase in population-level mental ill-health. Deteriorating mental health is particularly pronounced among people born in the 1990s and seen to a lesser extent among the 1980s cohort. There is little evidence that mental health is worsening with age for people born prior to the 1980s. The findings from this study highlight that it is the poorer mental health of Millennials that is driving the apparent deterioration in population-level mental health. Understanding the context and changes in society that have differentially affected younger people may inform efforts to ameliorate this trend and prevent it continuing for emerging cohorts.

Excess Mortality and Loss of Life Expectancy After Myocardial Infarction: A Registry-Based Matched Cohort Study.

BACKGROUND: The effect of myocardial infarction (MI) on life expectancy is difficult to study because the prevalence of MI hinders direct comparison with the life expectancy of the general population. We sought to assess this in relation to age, sex, and left ventricular ejection fraction (LVEF) by comparing individuals with MI with matched comparators without previous MI. METHODS: We included patients with a first MI between 1991 and 2022 from the nationwide SWEDEHEART registry (Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies), each matched with up to 5 comparators on age, sex, and region of residence. Flexible parametric survival models were used to estimate excess mortality and mean loss of life expectancy (LOLE) depending on index year, age, sex, and LVEF, and adjusted for differences in characteristics. RESULTS: A total of 335 748 cases were matched to 1 625 396 comparators. A higher LOLE was observed in younger individuals, women, and those with reduced LVEF (<50%). In 2022, the unadjusted and adjusted mean LOLE spanned from 11.1 and 9.5 years in 50-year-old women with reduced LVEF to 5 and 3.7 months in 80-year-old men with preserved LVEF. Between 1992 and 2022, the adjusted mean LOLE decreased by 36% to 55%: from 4.4 to 2.0 years and from 3.3 to 1.9 years in 50-year-old women and men, respectively, and from 1.7 to 1.0 years and from 1.4 to 0.9 years in 80-year-old women and men, respectively. CONCLUSIONS: LOLE is higher in younger individuals, women, and those with reduced LVEF, but is attenuated when adjusting for comorbidities and risk factors. Advances in MI treatment during the past 30 years have almost halved LOLE, with no clear sign of leveling off to a plateau.

Multiple Human Population Movements and Cultural Dispersal Events Shaped the Landscape of Chinese Paternal Heritage.

Large-scale genomic projects and ancient DNA innovations have ushered in a new paradigm for exploring human evolutionary history. However, the genetic legacy of spatiotemporally diverse ancient Eurasians within Chinese paternal lineages remains unresolved. Here, we report an integrated Y-chromosome genomic database encompassing 15,563 individuals from both modern and ancient Eurasians, including 919 newly reported individuals, to investigate the Chinese paternal genomic diversity. The high-resolution, time-stamped phylogeny reveals multiple diversification events and extensive expansions in the early and middle Neolithic. We identify four major ancient population movements, each associated with technological innovations that have shaped the Chinese paternal landscape. First, the expansion of early East Asians and millet farmers from the Yellow River Basin predominantly carrying O2/D subclades significantly influenced the formation of the Sino-Tibetan people and facilitated the permanent settlement of the Tibetan Plateau. Second, the dispersal of rice farmers from the Yangtze River Valley carrying O1 and certain O2 sublineages reshapes the genetic makeup of southern Han Chinese, as well as the Tai-Kadai, Austronesian, Hmong-Mien, and Austroasiatic people. Third, the Neolithic Siberian Q/C paternal lineages originated and proliferated among hunter-gatherers on the Mongolian Plateau and the Amur River Basin, leaving a significant imprint on the gene pools of northern China. Fourth, the J/G/R paternal lineages derived from western Eurasia, which were initially spread by Yamnaya-related steppe pastoralists, maintain their presence primarily in northwestern China. Overall, our research provides comprehensive genetic evidence elucidating the significant impact of interactions with culturally distinct ancient Eurasians on the patterns of paternal diversity in modern Chinese populations.

Helicobacter pylori Treatment and Gastric Cancer Risk After Endoscopic Resection of Dysplasia: A Nationwide Cohort Study.

BACKGROUND & AIMS: The study investigated the association between Helicobacter pylori treatment and the risk of gastric cancer after endoscopic resection of gastric dysplasia. METHODS: Patients who received endoscopic resection for gastric dysplasia between 2010 and 2020 from Korean nationwide insurance data were included. We verified the occurrence of new-onset gastric cancer and metachronous gastric neoplasm, which encompasses both cancer and dysplasia, >1 year after the index endoscopic resection. Newly diagnosed gastric cancer ≥3 years and ≥5 years was regarded as late-onset gastric cancer. A multivariable Cox regression model with H pylori treatment status as a time-dependent covariate was used to determine the risk of gastric cancer and metachronous gastric neoplasms. RESULTS: Gastric dysplasia in 69,722 patients was treated with endoscopy, and 49.5% were administered H pylori therapy. During the median 5.6 years of follow-up, gastric cancer developed in 2406 patients and metachronous gastric neoplasms developed in 3342 patients. Receiving H pylori therapy was closely related to lower gastric cancer risk (adjusted hazard ratio [aHR], 0.88; 95% confidence interval [CI], 0.80-0.96). H pylori treatment also significantly decreased metachronous gastric neoplasm development (aHR, 0.76; 95% CI, 0.70-0.82). Furthermore, H pylori therapy showed a prominent protective effect for late-onset gastric cancer development at ≥3 years (aHR, 0.84; 95% CI, 0.75-0.94) and ≥5 years (aHR, 0.80; 95% CI, 0.68-0.95). CONCLUSIONS: In this nationwide cohort, H pylori therapy after endoscopic resection of gastric dysplasia was associated with a reduced risk of gastric cancer and metachronous gastric neoplasm occurrence.

An Empirical Dietary Pattern Associated with the Gut Microbial Features in Relation to Colorectal Cancer Risk.

BACKGROUND & AIMS: Epidemiologic evidence for dietary influence on colorectal cancer (CRC) risk through the gut microbiome remains limited. METHODS: Leveraging 307 men and 212 women with stool metagenomes and dietary data, we characterized and validated a sex-specific dietary pattern associated with the CRC-related gut microbial signature (CRC Microbial Dietary Score [CMDS]). We evaluated the associations of CMDS with CRC risk according to Fusobacterium nucleatum, pks+Escherichia coli, and enterotoxigenic Bacteroides fragilis status in tumor tissue using Cox proportional hazards regression in the Health Professionals Follow-Up Study (1986-2018), Nurses' Health Study (1984-2020), and Nurses' Health Study II (1991-2019). RESULTS: The CMDS was characterized by high industrially processed food and low unprocessed fiber-rich food intakes. In 259,200 participants, we documented 3854 incident CRC cases over 6,467,378 person-years of follow-up. CMDS was associated with a higher risk of CRC (Ptrend < .001), with a multivariable hazard ratio (HRQ5 vs Q1) of 1.25 (95% CI, 1.13-1.39). The association remained after adjusting for previously established dietary patterns, for example, the Western and prudent diets. Notably, the association was stronger for tumoral F nucleatum-positive (HRQ5 vs Q1, 2.51; 95% CI, 1.68-3.75; Ptrend < .001; Pheterogeneity = .03, positivity vs negativity), pks+E coli-positive (HRQ5 vs Q1, 1.68; 95% CI, 0.84-3.38; Ptrend = .005; Pheterogeneity = .01, positivity vs negativity), and enterotoxigenic Bacteroides fragilis-positive CRC (HRQ5 vs Q1, 2.06; 95% CI, 1.10-3.88; Ptrend = .016; Pheterogeneity = .06, positivity vs negativity), compared with their negative counterparts. CONCLUSIONS: CMDS was associated with increased CRC risk, especially for tumors with detectable F nucleatum, pks+E coli, and enterotoxigenic Bacteroides fragilis in tissue. Our findings support a potential role of the gut microbiome underlying the dietary effects on CRC.

A Bayesian approach for investigating the pharmacogenetics of combination antiretroviral therapy in people with HIV.

Combination antiretroviral therapy (ART) with at least three different drugs has become the standard of care for people with HIV (PWH) due to its exceptional effectiveness in viral suppression. However, many ART drugs have been reported to associate with neuropsychiatric adverse effects including depression, especially when certain genetic polymorphisms exist. Pharmacogenetics is an important consideration for administering combination ART as it may influence drug efficacy and increase risk for neuropsychiatric conditions. Large-scale longitudinal HIV databases provide researchers opportunities to investigate the pharmacogenetics of combination ART in a data-driven manner. However, with more than 30 FDA-approved ART drugs, the interplay between the large number of possible ART drug combinations and genetic polymorphisms imposes statistical modeling challenges. We develop a Bayesian approach to examine the longitudinal effects of combination ART and their interactions with genetic polymorphisms on depressive symptoms in PWH. The proposed method utilizes a Gaussian process with a composite kernel function to capture the longitudinal combination ART effects by directly incorporating individuals' treatment histories, and a Bayesian classification and regression tree to account for individual heterogeneity. Through both simulation studies and an application to a dataset from the Women's Interagency HIV Study, we demonstrate the clinical utility of the proposed approach in investigating the pharmacogenetics of combination ART and assisting physicians to make effective individualized treatment decisions that can improve health outcomes for PWH.

Plasma metabolomic signature of healthy lifestyle, structural brain reserve and risk of dementia.

Although the association between healthy lifestyle and dementia risk has been documented, the relationship between a metabolic signature indicative of healthy lifestyle and dementia risk and the mediating role of structural brain impairment remain unknown. We retrieved 136 628 dementia-free participants from UK Biobank. Elastic net regression was used to obtain a metabolic signature that represented lifestyle behaviours. Cox proportional hazard models were fitted to explore the associations of lifestyle-associated metabolic signature with incident dementia. Causal associations between identified metabolites and dementia were investigated using Mendelian randomization. Mediation analysis was also conducted to uncover the potential mechanisms involving 19 imaging-derived phenotypes (brain volume, grey matter volume, white matter volume and regional grey matter volumes). During a follow-up of 12.55 years, 1783 incident cases of all-cause dementia were identified, including 725 cases of Alzheimer's dementia and 418 cases of vascular dementia. We identified 83 metabolites that could represent healthy lifestyle behaviours using elastic net regression. The metabolic signature was associated with a lower dementia risk, and for each standard deviation increment in metabolic signature, the hazard ratio was 0.89 [95% confidence interval (CI): 0.85, 0.93] for all-cause dementia, 0.95 (95% CI: 0.88, 1.03) for Alzheimer's dementia and 0.84 (95% CI: 0.77, 0.91) for vascular dementia. Mendelian randomization revealed potential causal associations between the identified metabolites and risk of dementia. In addition, the specific structural brain reserve, including the hippocampus, grey matter in the hippocampus, parahippocampal gyrus and middle temporal gyrus, were detected to mediate the effects of metabolic signature on dementia risk (mediated proportion ranging from 6.21% to 11.98%). The metabolic signature associated with a healthy lifestyle is inversely associated with dementia risk, and greater structural brain reserve plays an important role in mediating this relationship. These findings have significant implications for understanding the intricate connections between lifestyle, metabolism and brain health.

Long-Term Exposure to Low Concentrations of Ambient Benzene and Mortality in a National English Cohort.

Background: Benzene affects human health through environmental exposure in addition to occupational contact. However, few studies have examined the associations between long-term exposure to low concentrations of ambient benzene and mortality risks in nonoccupational settings.Methods: This prospective cohort study consists of 393,042 participants without stroke, myocardial infarction, or cancer at baseline from the UK Biobank. Annual average concentrations of benzene for each year during follow-up were measured using air dispersion models. The main outcomes were all-cause mortality and mortality from specific causes. Cox proportional-hazards models with time-varying exposure measurements were used to estimate the hazard ratios and 95% confidence intervals (CIs) for mortality risks. Restricted cubic spline models were used to estimate exposure-response relationships.Measurements and Main Results: With each interquartile range increase in the average annual concentration of benzene, the adjusted hazard ratios of mortality risk from all causes, cardiovascular disease, cancer, and respiratory disease were 1.26 (95% CI, 1.24-1.27), 1.24 (95% CI, 1.21-1.28), 1.27 (95% CI, 1.25-1.29), and 1.25 (95% CI, 1.20-1.30), respectively. The monotonically increasing exposure-response curves showed no threshold and plateau within the observed concentration range. Furthermore, the effect of benzene exposure on mortality persisted across different subgroups and was somewhat stronger in younger and White people (P for interaction < 0.05).Conclusions: Long-term exposure to low concentrations of ambient benzene significantly increases mortality risk in the general population. Ambient benzene represents a potential threat to public health, and further investigations are needed to support timely pollution regulation and health protection.

Aging, generational shifts, and energy consumption in urban China.

China is recognized as the largest energy consumer and is also the country with the largest and fastest-aging population. Ongoing demographic changes may reshape China's household-based energy consumption patterns because of the large gap in consumption behavior between the elderly and the young as well as varying attitudes toward the environment among generations. However, when the impact of China's aging population on energy consumption is projected, the heterogeneous cognitive norms of generations in the process of demographic transition are not well understood. In this study, we assessed the future impact of China's demographic transition on energy consumption using a proposed theoretical framework to distinguish between age and generational effects. Specifically, we used age-period-cohort (APC) detrended analysis to estimate age and generational effects based on China's urban household survey data from 1992 to 2015. The results indicated large differences in energy use propensity across ages and generations. The elderly and younger generations tended to be energy-intensive consumers, resulting in higher energy consumption in this aging society. Our results consequently show that future changes in China's elderly population will result in a substantial increase in energy consumption. By 2050, the changing consumption share of the elderly population will account for ∼17 to 26% of total energy consumption in the residential sector, which is close to 115 million tons of standard coal (Mtce). These findings highlight the need to interlace environmental education policies and demographic transitions to promote energy conservation behavior in children and youth for low-carbon, sustainable development.

Risk of heart failure in inflammatory bowel disease: a Swedish population-based study.

BACKGROUND AND AIMS: Dysregulation of inflammatory and immune responses has been implicated in the pathogenesis of heart failure (HF). But even if inflammation is a prerequisite for inflammatory bowel disease (IBD), little is known about HF risk in IBD. METHODS: In this Swedish nationwide cohort, patients with biopsy-confirmed IBD were identified between 1969 and 2017 [n = 81 749, Crohn's disease (CD, n = 24 303), ulcerative colitis (UC, n = 45 709), and IBD-unclassified (IBD-U, n = 11 737)]. Each patient was matched with up to five general population reference individuals (n = 382 190) and IBD-free full siblings (n = 95 239) and followed until 31 December 2019. Flexible parametric survival models estimated the adjusted hazard ratio (aHR) and standardized cumulative incidence for HF, with 95% confidence intervals (CI). RESULTS: There were 5582 incident HF identified in IBD patients (incidence rate [IR]: 50.3/10 000 person-years) and 20 343 in reference individuals (IR: 37.9) during a median follow-up of 12.4 years. IBD patients had a higher risk of HF than reference individuals (aHR 1.19, 95% CI 1.15-1.23). This increased risk remained significant ≥20 years after IBD diagnosis, leading to one extra HF case per 130 IBD patients until then. The increased risk was also observed across IBD subtypes: CD (IR: 46.9 vs. 34.4; aHR 1.28 [1.20-1.36]), UC (IR: 50.1 vs. 39.7; aHR 1.14 [1.09-1.19]), and IBD-U (IR: 60.9 vs. 39.0; aHR 1.28 [1.16-1.42]). Sibling-controlled analyses showed slightly attenuated association (IBD: aHR 1.10 [1.03-1.19]). CONCLUSIONS: Patients with IBD had a moderately higher risk of developing HF for ≥20 years after IBD diagnosis than the general population.