Cross-Sectional and Prospective Association of Serum 25-Hydroxyvitamin D with Gut Mycobiota during Pregnancy among Women with Gestational Diabetes

SCOPE

Little is known about the effect of blood vitamin D status on the gut mycobiota (i.e., fungi), a crucial component of the gut microbial ecosystem. The study aims to explore the association between 25-hydroxyvitamin D [25(OH)D] and gut mycobiota and to investigate the link between the identified mycobial features and blood glycemic traits.

METHODS AND RESULTS

The study examines the association between serum 25(OH)D levels and the gut mycobiota in the Westlake Precision Birth Cohort, which includes pregnant women with gestational diabetes mellitus (GDM). The study develops a genetic risk score (GRS) for 25(OH)D to validate the observational results. In both the prospective and cross-sectional analyses, the vitamin D is associated with gut mycobiota diversity. Specifically, the abundance of Saccharomyces is significantly lower in the vitamin D-sufficient group than in the vitamin D-deficient group. The GRS of 25(OH)D is inversely associated with the abundance of Saccharomyces. Moreover, the Saccharomyces is positively associated with blood glucose levels.

CONCLUSION

Blood vitamin D status is associated with the diversity and composition of gut mycobiota in women with GDM, which may provide new insights into the mechanistic understanding of the relationship between vitamin D levels and metabolic health.

Mapping multi-omics characteristics related to short-term PM2.5 trajectory and their impact on type 2 diabetes in middle-aged and elderly adults in Southern China

The relationship between PM2.5 and metabolic diseases, including type 2 diabetes (T2D), has become increasingly prominent, but the molecular mechanism needs to be further clarified. To help understand the mechanistic association between PM2.5 exposure and human health, we investigated short-term PM2.5 exposure trajectory-related multi-omics characteristics from stool metagenome and metabolome and serum proteome and metabolome in a cohort of 3267 participants (age: 64.4 ± 5.8 years) living in Southern China. And then integrate these features to examine their relationship with T2D. We observed significant differences in overall structure in each omics and 193 individual biomarkers between the high- and low-PM2.5 groups. PM2.5-related features included the disturbance of microbes (carbohydrate metabolism-associated Bacteroides thetaiotaomicron), gut metabolites of amino acids and carbohydrates, serum biomarkers related to lipid metabolism and reducing n-3 fatty acids. The patterns of overall network relationships among the biomarkers differed between T2D and normal participants. The subnetwork membership centered on the hub nodes (fecal rhamnose and glycylproline, serum hippuric acid, and protein TB182) related to high-PM2.5, which well predicted higher T2D prevalence and incidence and a higher level of fasting blood glucose, HbA1C, insulin, and HOMA-IR. Our findings underline crucial PM2.5-related multi-omics biomarkers linking PM2.5 exposure and T2D in humans.

Soliton Based Dynamic Nuclear Polarization: An Overhauser Effect in Cyclic Polyacetylene at High Field and Room Temperature

Polyacetylene, a versatile material with an electrical conductivity that can span 7 orders of magnitude, is the prototypical conductive polymer. In this letter, we report the observation of a significant Overhauser effect at the high magnetic field of 14.1 T that operates at 100 K and room temperature in both linear and cyclic polyacetylene. Significant NMR signal enhancements ranging from 24 to 45 are obtained. The increased sensitivity enabled the characterization of the polymer chain defects at natural abundance. The absence of end methyl group carbon-13 signals provides proof of the closed-loop molecular structure of cyclic polyacetylene. The remarkable efficiency of the soliton based Overhauser effect DNP mechanism at high temperature and high field holds promise for applications and extension to other conductive polymer systems.

Proteome-wide profiling reveals dysregulated molecular features and accelerated aging in osteoporosis: A 9.8-year prospective study

The role of circulatory proteomics in osteoporosis is unclear. Proteome-wide profiling holds the potential to offer mechanistic insights into osteoporosis. Serum proteome with 413 proteins was profiled by liquid chromatography-tandem mass spectrometry (LC-MS/MS) at baseline, and the 2nd, and 3rd follow-ups (7704 person-tests) in the prospective Chinese cohorts with 9.8 follow-up years: discovery cohort (n = 1785) and internal validation cohort (n = 1630). Bone mineral density (BMD) was measured using dual-energy X-ray absorptiometry (DXA) at follow-ups 1 through 3 at lumbar spine (LS) and femoral neck (FN). We used the Light Gradient Boosting Machine (LightGBM) to identify the osteoporosis (OP)-related proteomic features. The relationships between serum proteins and BMD in the two cohorts were estimated by linear mixed-effects model (LMM). Meta-analysis was then performed to explore the combined associations. We identified 53 proteins associated with osteoporosis using LightGBM, and a meta-analysis showed that 22 of these proteins illuminated a significant correlation with BMD (p < 0.05). The most common proteins among them were PHLD, SAMP, PEDF, HPTR, APOA1, SHBG, CO6, A2MG, CBPN, RAIN APOD, and THBG. The identified proteins were used to generate the biological age (BA) of bone. Each 1 SD-year increase in KDM-Proage was associated with higher risk of LS-OP (hazard ratio [HR], 1.25; 95% CI, 1.14-1.36, p = 4.96 × 10-06 ), and FN-OP (HR, 1.13; 95% CI, 1.02-1.23, p = 9.71 × 10-03 ). The findings uncovered that the apolipoproteins, zymoproteins, complements, and binding proteins presented new mechanistic insights into osteoporosis. Serum proteomics could be a crucial indicator for evaluating bone aging.

Nutri-microbiome epidemiology, an emerging field to disentangle the interplay between nutrition and microbiome for human health

Diet and nutrition have a substantial impact on the human microbiome, and interact with the microbiome, especially gut microbiome, to modulate various diseases and health status. Microbiome research has also guided the nutrition field to a more integrative direction, becoming an essential component of the rising area of precision nutrition. In this review, we provide a broad insight into the interplay among diet, nutrition, microbiome, and microbial metabolites for their roles in the human health. Among the microbiome epidemiological studies regarding the associations of diet and nutrition with microbiome and its derived metabolites, we summarize those most reliable findings and highlight evidence for the relationships between diet and disease-associated microbiome and its functional readout. Then, the latest advances of the microbiome-based precision nutrition research and multidisciplinary integration are described. Finally, we discuss several outstanding challenges and opportunities in the field of nutri-microbiome epidemiology.

Early-life exposure to the Great Chinese Famine and gut microbiome disruption across adulthood for type 2 diabetes: three population-based cohort studies

BACKGROUND

The early life stage is critical for the gut microbiota establishment and development. We aimed to investigate the lifelong impact of famine exposure during early life on the adult gut microbial ecosystem and examine the association of famine-induced disturbance in gut microbiota with type 2 diabetes.

METHODS

We profiled the gut microbial composition among 11,513 adults (18-97 years) from three independent cohorts and examined the association of famine exposure during early life with alterations of adult gut microbial diversity and composition. We performed co-abundance network analyses to identify keystone taxa in the three cohorts and constructed an index with the shared keystone taxa across the three cohorts. Among each cohort, we used linear regression to examine the association of famine exposure during early life with the keystone taxa index and assessed the correlation between the keystone taxa index and type 2 diabetes using logistic regression adjusted for potential confounders. We combined the effect estimates from the three cohorts using random-effects meta-analysis.

RESULTS

Compared with the no-exposed control group (born during 1962-1964), participants who were exposed to the famine during the first 1000 days of life (born in 1959) had consistently lower gut microbial alpha diversity and alterations in the gut microbial community during adulthood across the three cohorts. Compared with the no-exposed control group, participants who were exposed to famine during the first 1000 days of life were associated with consistently lower levels of keystone taxa index in the three cohorts (pooled beta - 0.29, 95% CI - 0.43, - 0.15). Per 1-standard deviation increment in the keystone taxa index was associated with a 13% lower risk of type 2 diabetes (pooled odds ratio 0.87, 95% CI 0.80, 0.93), with consistent results across three individual cohorts.

CONCLUSIONS

These findings reveal a potential role of the gut microbiota in the developmental origins of health and disease (DOHaD) hypothesis, deepening our understanding about the etiology of type 2 diabetes.

Continuous glucose monitoring-derived glycemic metrics and adverse pregnancy outcomes among women with gestational diabetes: a prospective cohort study

Background

Continuous glucose monitoring (CGM) has shown potential in improving maternal and neonatal outcomes in individuals with type 1/2 diabetes, but data in gestational diabetes mellitus (GDM) is limited. We aimed to explore the relationship between CGM-derived metrics during pregnancy and pregnancy outcomes among women with GDM.

Methods

We recruited 1302 pregnant women with GDM at a mean gestational age of 26.0 weeks and followed them until delivery. Participants underwent a 14-day CGM measurement upon recruitment. The primary outcome was any adverse pregnancy outcome, defined as having at least one of the outcomes: preterm birth, large-for-gestational-age (LGA) birth, fetal distress, premature rupture of membranes, and neonatal intensive care unit (NICU) admission. The individual outcomes included in the primary outcome were considered as secondary outcomes. We conducted multivariable logistic regression to evaluate the association of CGM-derived metrics with these outcomes.

Findings

Per 1-SD difference in time above range (TAR), glucose area under the curve (AUC), nighttime mean blood glucose (MBG), daytime MBG, and daily MBG was associated with higher risk of any adverse pregnancy outcome, with odds ratio: 1.22 (95% CI 1.08-1.36), 1.22 (95% CI 1.09-1.37), 1.18 (95% CI 1.05-1.32), 1.21 (95% CI 1.07-1.35), and 1.22 (95% CI 1.09-1.37), respectively. Time in range, TAR, AUC, nighttime MBG, daytime MBG, daily MBG, and mean amplitude of glucose excursions were positively associated, while time blow range was inversely associated with the risk of LGA. Additionally, higher value for TAR was associated with higher risk of NICU admission. We further summarized the potential thresholds of TAR (2.5%) and daily MBG (4.8 mmol/L) to distinguish individuals with and without any adverse pregnancy outcome.

Interpretation

The CGM-derived metrics may help identify individuals at higher risk of adverse pregnancy outcomes. These CGM biomarkers could serve as potential new intervention targets to maintain a healthy pregnancy status among women with GDM.

Funding

National Key R&D Program of China, National Natural Science Foundation of China, and Westlake Laboratory of Life Sciences and Biomedicine.

Population serum proteomics uncovers a prognostic protein classifier for metabolic syndrome

Metabolic syndrome (MetS) is a complex metabolic disorder with a global prevalence of 20%-25%. Early identification and intervention would help minimize the global burden on healthcare systems. Here, we measured over 400 proteins from ∼20,000 proteomes using data-independent acquisition mass spectrometry for 7,890 serum samples from a longitudinal cohort of 3,840 participants with two follow-up time points over 10 years. We then built a machine-learning model for predicting the risk of developing MetS within 10 years. Our model, composed of 11 proteins and the age of the individuals, achieved an area under the curve of 0.774 in the validation cohort (n = 242). Using linear mixed models, we found that apolipoproteins, immune-related proteins, and coagulation-related proteins best correlated with MetS development. This population-scale proteomics study broadens our understanding of MetS and may guide the development of prevention and targeted therapies for MetS.

Allisartan Isoproxil Promotes Uric Acid Excretion by Interacting with Intestinal Urate Transporters in Hyperuricemic Zebrafish (Danio rerio)

To evaluate the urate-lowering effect and potential drug targets of antihypertensive agent allisartan isoproxil (ALI) and its bioactive metabolite EXP3174, we developed an acute hyperuricemic zebrafish model using potassium oxonate and xanthine sodium salt. Losartan potassium served as the positive control (reference drug). In this model, ALI and losartan potassium exerted a greater urate-lowering effect than EXP3174 indicating that the latter is not the critical substance for elimination of uric acid. The quantitative real-time PCR showed that ALI upregulates the expression of intestinal urate transporters genes ABCG2, PDZK1, and SLC2A9 (p<0.01). Thus, we can suggest that this substance promotes uric acid excretion mainly by interacting with intestinal urate transporters.

Furan fatty acid metabolite CMPF is associated with lower risk of type 2 diabetes, but not chronic kidney disease: a longitudinal population-based cohort study

BACKGROUND

Furan fatty acid metabolite 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid (CMPF) is a strong biomarker of fish and n-3 polyunsaturated fatty acid (PUFA) intake. The relationship of CMPF with human health has been controversial, especially for type 2 diabetes and chronic kidney disease.

OBJECTIVE

We performed a prospective cohort study to examine the association of serum CMPF with incident type 2 diabetes and chronic kidney disease.

METHODS

In the Guangzhou Nutrition and Health Study, during a median follow-up of 8.8 y, we used a multivariable-adjusted Poisson regression model to investigate the association of baseline serum CMPF with the incidence of type 2 diabetes (1470 participants and 170 incident cases) and chronic kidney disease (1436 participants and 112 incident cases). We also examined the association of serial measures of serum CMPF with glycemic and renal function biomarkers. Mediation analysis was also performed to examine the contribution of CMPF in the association between marine n-3 PUFAs and risk of type 2 diabetes or chronic kidney disease.

RESULTS

Each standard deviation increase in baseline serum CMPF was associated with an 18% lower risk of type 2 diabetes (relative risk: 0.82, 95% confidence interval [CI]: 0.68, 0.99) but was not associated with chronic kidney disease (relative risk: 0.95; 95% CI: 0.77-1.16). Correlation analyses of CMPF with glycemic and renal function biomarkers showed similar results. Mediation analysis suggested that serum CMPF contributed to the inverse association between erythrocyte marine n-3 PUFAs and incident type 2 diabetes (proportion mediated 37%, P-mediation = 0.022).

CONCLUSIONS

Our findings suggest that serum CMPF was associated with a lower risk of type 2 diabetes but not chronic kidney disease. This study also suggests that CMPF may be a functional metabolite underlying the protective relationship between marine n-3 PUFA intake and type 2 diabetes.

Gut microbiome, cognitive function and brain structure: a multi-omics integration analysis

BACKGROUND

Microbiome-gut-brain axis may be involved in the progression of age-related cognitive impairment and relevant brain structure changes, but evidence from large human cohorts is lacking. This study was aimed to investigate the associations of gut microbiome with cognitive impairment and brain structure based on multi-omics from three independent populations.

METHODS

We included 1430 participants from the Guangzhou Nutrition and Health Study (GNHS) with both gut microbiome and cognitive assessment data available as a discovery cohort, of whom 272 individuals provided fecal samples twice before cognitive assessment. We selected 208 individuals with baseline microbiome data for brain magnetic resonance imaging during the follow-up visit. Fecal 16S rRNA and shotgun metagenomic sequencing, targeted serum metabolomics, and cytokine measurements were performed in the GNHS. The validation analyses were conducted in an Alzheimer's disease case-control study (replication study 1, n = 90) and another community-based cohort (replication study 2, n = 1300) with cross-sectional dataset.

RESULTS

We found protective associations of specific gut microbial genera (Odoribacter, Butyricimonas, and Bacteroides) with cognitive impairment in both the discovery cohort and the replication study 1. Result of Bacteroides was further validated in the replication study 2. Odoribacter was positively associated with hippocampal volume (β, 0.16; 95% CI 0.06-0.26, P = 0.002), which might be mediated by acetic acids. Increased intra-individual alterations in gut microbial composition were found in participants with cognitive impairment. We also identified several serum metabolites and inflammation-associated metagenomic species and pathways linked to impaired cognition.

CONCLUSIONS

Our findings reveal that specific gut microbial features are closely associated with cognitive impairment and decreased hippocampal volume, which may play an important role in dementia development.

Associations of dietary diversity with the gut microbiome, fecal metabolites, and host metabolism: results from 2 prospective Chinese cohorts

BACKGROUND

Dietary diversity is essential for human health. The gut ecosystem provides a potential link between dietary diversity, host metabolism, and health, yet this mechanism is poorly understood.

OBJECTIVES

Here, we aimed to investigate the relation between dietary diversity and the gut environment as well as host metabolism from a multiomics perspective.

METHODS

Two independent longitudinal Chinese cohorts (a discovery and a validation cohort) were included in the present study. Dietary diversity was evaluated with FFQs. In the discovery cohort (n = 1916), we performed shotgun metagenomic and 16S ribosomal ribonucleic acid (rRNA) sequencing to profile the gut microbiome. We used targeted metabolomics to quantify fecal and serum metabolites. The associations between dietary diversity and the microbial composition were replicated in the validation cohort (n = 1320).

RESULTS

Dietary diversity was positively associated with α diversity of the gut microbiota. We identified dietary diversity-related gut environment features, including the microbial structure (β diversity), 68 microbial genera, 18 microbial species, 8 functional pathways, and 13 fecal metabolites. We further found 332 associations of dietary diversity and related gut environment features with circulating metabolites. Both the dietary diversity and diversity-related features were inversely correlated with 4 circulating secondary bile acids. Moreover, 16 mediation associations were observed among dietary diversity, diversity-related features, and the 4 secondary bile acids.

CONCLUSIONS

These results suggest that high dietary diversity is associated with the gut microbial environment. The identified key microbes and metabolites may serve as hypotheses to test for preventing metabolic diseases.

Mapping the human gut mycobiome in middle-aged and elderly adults: multiomics insights and implications for host metabolic health

OBJECTIVE

The human gut fungal community, known as the mycobiome, plays a fundamental role in the gut ecosystem and health. Here we aimed to investigate the determinants and long-term stability of gut mycobiome among middle-aged and elderly adults. We further explored the interplay between gut fungi and bacteria on metabolic health.

DESIGN

The present study included 1244 participants from the Guangzhou Nutrition and Health Study. We characterised the long-term stability and determinants of the human gut mycobiome, especially long-term habitual dietary consumption. The comprehensive multiomics analyses were performed to investigate the ecological links between gut bacteria, fungi and faecal metabolome. Finally, we examined whether the interaction between gut bacteria and fungi could modulate the metabolic risk.

RESULTS

The gut fungal composition was temporally stable and mainly determined by age, long-term habitual diet and host physiological states. Specifically, compared with middle-aged individuals, Blastobotrys and Agaricomycetes spp were depleted, while Malassezia was enriched in the elderly. Dairy consumption was positively associated with Saccharomyces but inversely associated with Candida. Notably, Saccharomycetales spp interacted with gut bacterial diversity to influence insulin resistance. Bidirectional mediation analyses indicated that bacterial function or faecal histidine might causally mediate an impact of Pichia on blood cholesterol.

CONCLUSION

We depict the sociodemographic and dietary determinants of human gut mycobiome in middle-aged and elderly individuals, and further reveal that the gut mycobiome may be closely associated with the host metabolic health through regulating gut bacterial functions and metabolites.

Association of gut microbiota with glycaemic traits and incident type 2 diabetes, and modulation by habitual diet: a population-based longitudinal cohort study in Chinese adults

AIMS/HYPOTHESIS

The gut microbiome is mainly shaped by diet, and varies across geographical regions. Little is known about the longitudinal association of gut microbiota with glycaemic control. We aimed to identify gut microbiota prospectively associated with glycaemic traits and type 2 diabetes in a geographically diverse population, and examined the cross-sectional association of dietary or lifestyle factors with the identified gut microbiota.

METHODS

The China Health and Nutrition Survey is a population-based longitudinal cohort covering 15 provinces/megacities across China. Of the participants in that study, 2772 diabetes-free participants with a gut microbiota profile based on 16S rRNA analysis were included in the present study (age 50.8 ± 12.7 years, mean ± SD). Using a multivariable-adjusted linear mixed-effects model, we examined the prospective association of gut microbiota with glycaemic traits (fasting glucose, fasting insulin, HbA_1c and HOMA-IR). We constructed a healthy microbiome index (HMI), and used Poisson regression to examine the relationship between the HMI and incident type 2 diabetes. We evaluated the association of dietary or lifestyle factors with the glycaemic trait-related gut microbiota using a multivariable-adjusted linear regression model.

RESULTS

After follow-up for 3 years, 123 incident type 2 diabetes cases were identified. We identified 25 gut microbial genera positively or inversely associated with glycaemic traits. The newly created HMI (per SD unit) was inversely associated with incident type 2 diabetes (risk ratio 0.69, 95% CI 0.58, 0.84). Furthermore, we found that several microbial genera that were favourable for the glycaemic trait were consistently associated with healthy dietary habits (higher consumption of vegetable, fruit, fish and nuts).

CONCLUSIONS/INTERPRETATION

Our results revealed multiple gut microbiota prospectively associated with glycaemic traits and type 2 diabetes in a geographically diverse population, and highlighted the potential of gut microbiota-based diagnosis or therapy for type 2 diabetes.

DATA AVAILABILITY

The code for data analysis associated with the current study is available at https://github.com/wenutrition/Microbiota-T2D-CHNS.

Gut microbiota signatures of long-term and short-term plant-based dietary pattern and cardiometabolic health: a prospective cohort study

BACKGROUND

The interplay among the plant-based dietary pattern, gut microbiota, and cardiometabolic health is still unclear, and evidence from large prospective cohorts is rare. We aimed to examine the association of long-term and short-term plant-based dietary patterns with gut microbiota and to assess the prospective association of the identified microbial features with cardiometabolic biomarkers.

METHODS

Using a population-based prospective cohort study: the China Health and Nutrition Survey, we included 3096 participants from 15 provinces/megacities across China. We created an overall plant-based diet index (PDI), a healthful plant-based diet index (hPDI), and an unhealthful plant-based diet index (uPDI). The average PDIs were calculated using repeat food frequency questionnaires collected in 2011 and 2015 to represent a long-term dietary pattern. Short-term dietary pattern was estimated using 3-day 24-h dietary recalls collected in 2015. Fecal samples were collected in 2015 and measured using 16S rRNA sequencing. We investigated the association of long-term and short-term plant-based dietary patterns with gut microbial diversity, taxonomies, and functional pathways using linear mixed models. Furthermore, we assessed the prospective associations between the identified gut microbiome signatures and cardiometabolic biomarkers (measured in 2018) using linear regression.

RESULTS

We found a significant association of short-term hPDI with microbial alpha-diversity. Both long-term and short-term plant-based diet indices were correlated with microbial overall structure, whereas long-term estimates explained more variance. Long-term and short-term PDIs were differently associated with microbial taxonomic composition, yet only microbes related to long-term estimates showed association with future cardiometabolic biomarkers. Higher long-term PDI was associated with the lower relative abundance of Peptostreptococcus, while this microbe was positively correlated with the high-sensitivity C-reactive protein and inversely associated with high-density lipoprotein cholesterol.

CONCLUSIONS

We found shared and distinct gut microbial signatures of long-term and short-term plant-based dietary patterns. The identified microbial genera may provide insights into the protective role of long-term plant-based dietary pattern for cardiometabolic health, and replication in large independent cohorts is needed.

The gut microbiota-bile acid axis links the positive association between chronic insomnia and cardiometabolic diseases

Evidence from human cohorts indicates that chronic insomnia is associated with higher risk of cardiometabolic diseases (CMD), yet whether gut microbiota plays a role is unclear. Here, in a longitudinal cohort (n = 1809), we find that the gut microbiota-bile acid axis may link the positive association between chronic insomnia and CMD. Ruminococcaceae UCG-002 and Ruminococcaceae UCG-003 are the main genera mediating the positive association between chronic insomnia and CMD. These results are also observed in an independent cross-sectional cohort (n = 6122). The inverse associations between those gut microbial biomarkers and CMD are mediated by certain bile acids (isolithocholic acid, muro cholic acid and nor cholic acid). Habitual tea consumption is prospectively associated with the identified gut microbiota and bile acids in an opposite direction compared with chronic insomnia. Our work suggests that microbiota-bile acid axis may be a potential intervention target for reducing the impact of chronic insomnia on cardiometabolic health.

Chronic insomnia is associated with cardiometabolic diseases. Here, in two clinical cohorts (n = 7,931), authors show that gut microbiota-bile acid axis may be an intervention target to attenuate the impact of chronic insomnia on cardiometabolic health.

Circulating Proteome and Progression of Type 2 Diabetes

CONTEXT

Circulating proteomes may provide intervention targets for type 2 diabetes (T2D).

OBJECTIVE

We aimed to identify proteomic biomarkers associated with incident T2D and assess its joint effect with dietary or lifestyle factors on the T2D risk.

METHODS

We established 2 nested case-control studies for incident T2D: discovery cohort (median 6.5 years of follow-up, 285 case-control pairs) and validation cohort (median 2.8 years of follow-up, 38 case-control pairs). We integrated untargeted mass spectrometry-based proteomics and interpretable machine learning to identify T2D-related proteomic biomarkers. We constructed a protein risk score (PRS) with the identified proteomic biomarkers and used a generalized estimating equation to evaluate PRS-T2D relationship with repeated profiled proteome. We evaluated association of PRS with trajectory of glycemic traits in another non-T2D cohort (n = 376). Multiplicative interactions of dietary or lifestyle factors with PRS were evaluated using logistic regression.

RESULTS

Seven proteins (SHBG, CAND1, APOF, SELL, MIA3, CFH, IGHV1-2) were retained as the proteomic biomarkers for incident T2D. PRS (per SD change) was positively associated with incident T2D across 2 cohorts, with an odds ratio 1.29 (95% CI, 1.08-1.54) and 1.84 (1.19-2.84), respectively. Participants with a higher PRS had a higher probability showing unfavored glycemic trait trajectory in the non-T2D cohort. Red meat intake and PRS showed a multiplicative interaction on T2D risk in the discovery (P = 0.003) and validation cohort (P = 0.017).

CONCLUSION

This study identified proteomic biomarkers for incident T2D among the Chinese populations. The higher intake of red meat may synergistically interact with the proteomic biomarkers to exaggerate the T2D risk.

Human Gut Antibiotic Resistome and Progression of Diabetes

The antibiotic resistance crisis underlies globally increasing failures in treating deadly bacterial infections, largely due to the selection of antibiotic resistance genes (ARG) collection, known as the resistome, in human gut microbiota. So far, little is known about the relationship between gut antibiotic resistome and host metabolic disorders such as type 2 diabetes (T2D). Here, metagenomic landscape of gut antibiotic resistome is profiled in a large multiomics human cohort (n = 1210). There is a significant overall shift in gut antibiotic resistome structure among healthy, prediabetes, and T2D groups. It is found that larger ARG diversity is associated with a higher risk of T2D. The novel diabetes ARG score is positively associated with glycemic traits. Longitudinal validation analysis confirms that the ARG score is associated with T2D progression, characterized by the change of insulin resistance. Collectively, the data describe the profiles of gut antibiotic resistome and support its close relationship with T2D progression.

Dynamics of the Gut Bacteria and Fungi Accompanying Low-Carbohydrate Diet-Induced Weight Loss in Overweight and Obese Adults

Background

Low-carbohydrate (e.g., Atkins) dietary pattern is one of the most effective diets for weight loss, but little is known about the characteristics of the gut microbiota accompanying low-carbohydrate diets-induced weight loss. This study aims to profile dynamics of gut bacteria and fungi accompanying modified Atkins diets-induced weight loss among overweight and obese adults.

Methods

Overweight and obese adults were screened to follow a modified Atkins diet plan (30% of energy from protein, 40% from carbohydrate and 30% from fat). We longitudinally profiled dynamics of gut bacteria and fungi based on 16S rRNA and ITS rRNA gene sequencing data, respectively.

Results

A total of 65 participants followed the modified Atkins diets for 20–231 days, with 61 and 27 participants achieving a weight loss of at least 5 and 10%, respectively. Most of the participants who achieved 10% weight loss also experienced improvements on metabolic health. The diversity of gut bacteria and fungi increased after a weight loss of 5% and kept stable thereafter. Bacteria genera including Lachnoclostridium and Ruminococcus 2 from Firmicutes phylum were depleted, while Parabacteroides and Bacteroides from Bacteroidetes phylum were enriched after weight loss. The inter-kingdom analysis found an intensive covariation between gut fungi and bacteria, involving more than half of the weight loss-associated bacteria.

Conclusions

This study confirmed the modulation of bacterial and fungal composition during weight loss with the low-carbohydrate diets and showed previously unknown links between intestinal bacteria and fungi accompanying the weight loss.

Symptomatic and Asymptomatic Chronic Carotid Artery Occlusion on High-Resolution MR Vessel Wall Imaging

BACKGROUND AND PURPOSE

Chronic carotid artery occlusion remains a poorly understood risk factor for subsequent stroke, and potential revascularization is dependent on understanding the anatomy and nature of the occlusion. Luminal imaging cannot assess the nature of an occlusion, so the internal structure of the occlusion must be inferred. The present study examines the signal characteristics of symptomatic and asymptomatic carotid occlusion that may point to management differentiation.

MATERIALS AND METHODS

We prospectively recruited patients who were diagnosed with chronic carotid artery occlusion defined as longer than 4 weeks and confirmed by DSA. All patients underwent high-resolution MR vessel wall imaging examinations after enrollment. Baseline characteristics, vessel wall imaging features, and DSA features were collected and evaluated. The vessel wall imaging features included segment involvement, signal intensity, contrast enhancement, and vessel wall thickness. The symptomatic and asymptomatic chronic carotid artery occlusions were compared.

RESULTS

A total of 44 patients with 48 lesions were included in this study from February 2020 to December 2020. Of the 48 lesions, 35 (72.9%) were symptomatic and 13 (27.1%) were asymptomatic. There was no difference in baseline and DSA features. On vessel wall imaging, C1 and C2 were the most commonly involved segments (91.7% and 68.8%, respectively). Compared with symptomatic lesions, asymptomatic lesions were more often isointense (69.2%) in the distal segment (P = .03). Both groups had diffuse wall thickening (80% and 100%).

CONCLUSIONS

Signal characteristics between those with symptomatic and asymptomatic carotid artery occlusions differ in a statistically significant fashion, indicating a different structure of the occlusion.

Individual Postprandial Glycemic Responses to Diet in n-of-1 Trials: Westlake N-of-1 Trials for Macronutrient Intake (WE-MACNUTR)

BACKGROUND

The role of different types and quantities of macronutrients on human health has been controversial, and the individual response to dietary macronutrient intake needs more investigation.

OBJECTIVES

We aimed to use an 'n-of-1' study design to investigate the individual variability in postprandial glycemic response when eating diets with different macronutrient distributions among apparently healthy adults.

METHODS

Thirty apparently healthy young Chinese adults (women, 68%) aged between 22 and 34 y, with BMI between 17.2 and 31.9 kg/m2, were provided with high-fat, low-carbohydrate (HF-LC, 60-70% fat, 15-25% carbohydrate, 15% protein, of total energy) and low-fat, high-carbohydrate (LF-HC, 10-20% fat, 65-75% carbohydrate, 15% protein) diets, for 6 d wearing continuous glucose monitoring systems, respectively, in a randomized sequence, interspersed by a 6-d wash-out period. Three cycles were conducted. The primary outcomes were the differences of maximum postprandial glucose (MPG), mean amplitude of glycemic excursions (MAGE), and AUC24 between intervention periods of LF-HC and HF-LC diets. A Bayesian model was used to predict responders with the posterior probability of any 1 of the 3 outcomes reaching a clinically meaningful difference.

RESULTS

Twenty-eight participants were included in the analysis. Posterior probability of reaching a clinically meaningful difference of MPG (0.167 mmol/L), MAGE (0.072 mmol/L), and AUC24 (13.889 mmol/L·h) between LF-HC and HF-LC diets varied among participants, and those with posterior probability >80% were identified as high-carbohydrate responders (n = 9) or high-fat responders (n = 6). Analyses of the Bayesian-aggregated n-of-1 trials among all participants showed a relatively low posterior probability of reaching a clinically meaningful difference of the 3 outcomes between LF-HC and HF-LC diets.

CONCLUSIONS

N-of-1 trials are feasible to characterize personal response to dietary intervention in young Chinese adults.

The Association of Gut Microbiota With Osteoporosis Is Mediated by Amino Acid Metabolism: Multiomics in a Large Cohort

CONTEXT

Several small studies have suggested that the gut microbiome might influence osteoporosis, but there is little evidence from human metabolomics studies to explain this association.

OBJECTIVE

This study examined the association of gut microbiome dysbiosis with osteoporosis and explored the potential pathways through which this association occurs using fecal and serum metabolomics.

METHODS

We analyzed the composition of the gut microbiota by 16S rRNA profiling and bone mineral density using dual-energy X-ray absorptiometry in 1776 community-based adults. Targeted metabolomics in feces (15 categories) and serum (12 categories) were further analyzed in 971 participants using ultra-high-performance liquid chromatography coupled to tandem mass spectrometry.

RESULTS

This study showed that osteoporosis was related to the beta diversity, taxonomy, and functional composition of the gut microbiota. The relative abundance of Actinobacillus, Blautia, Oscillospira, Bacteroides, and Phascolarctobacterium was positively associated with osteoporosis. However, Veillonellaceae other, Collinsella, and Ruminococcaceae other were inversely associated with the presence of osteoporosis. The association between microbiota biomarkers and osteoporosis was related to levels of peptidases and transcription machinery in microbial function. Fecal and serum metabolomics analyses suggested that tyrosine and tryptophan metabolism and valine, leucine, and isoleucine degradation were significantly linked to the identified microbiota biomarkers and to osteoporosis, respectively.

CONCLUSION

This large population-based study provided robust evidence connecting gut dysbiosis, fecal metabolomics, and serum metabolomics with osteoporosis. Our results suggest that gut dysbiosis and amino acid metabolism could be targets for intervention in osteoporosis.

Targeting STING attenuates ROS induced intervertebral disc degeneration

OBJECTIVE

DNA damage induced by ROS is considered one of the main causes of nucleus pulposus (NP) cells degeneration during the progression of intervertebral disc degeneration (IVDD). cGAS-STING pathway acts as DNA-sensing mechanism for monitoring DNA damage. Recent studies have proved that cGAS-STING contributes to the development of various diseases by inducing inflammation, senescence, and apoptosis. This work explored the role of STING, the main effector of cGAS-STING signaling pathway, in NP degeneration.

METHOD

Immunohistochemistry was conducted to measure STING protein levels in the nucleus pulposus tissues from human and puncture-induced IVDD rat models. TBHP induces degeneration of nucleus pulposus cells in vitro. For in vivo experiments, lv-NC or lv-STING were injected into the central intervertebral disc space. The degeneration level of IVDD was assessed by MRI, X-ray, HE, and Safranin O staining.

RESULTS

We found that the expression of STING was upregulated in human and rat degenerated NP tissue as well as in TBHP-treated NP cells. Overexpression of STING promoted the degradation of extracellular matrix; it also promoted apoptosis and senescence of TBHP-treated and untreated NP cells. Knock-down of STING significantly reversed these effects. Mechanistically, STING activated IRF3, whereas blockage of IRF3 attenuated STING-induced apoptosis, senescence and ECM degradation. In vivo experiments revealed that STING knock-down alleviated puncture-induced IVDD development.

CONCLUSION

STING promotes IVDD progress via IRF3, while suppression of STING may be a promising treatment for IVDD.

Circulating vitamin C concentration and risk of cancers: a Mendelian randomization study

BACKGROUND

Circulating vitamin C concentrations have been associated with several cancers in observational studies, but little is known about the causal direction of the associations. This study aims to explore the potential causal relationship between circulating vitamin C and risk of five most common cancers in Europe.

METHODS

We used summary-level data for genetic variants associated with plasma vitamin C in a large vitamin C genome-wide association study (GWAS) meta-analysis on 52,018 Europeans, and the corresponding associations with lung, breast, prostate, colon, and rectal cancer from GWAS consortia including up to 870,984 participants of European ancestry. We performed two-sample, bi-directional Mendelian randomization (MR) analyses using inverse-variance-weighted method as the primary approach, while using 6 additional methods (e.g., MR-Egger, weighted median-based, and mode-based methods) as sensitivity analysis to detect and adjust for pleiotropy. We also conducted a meta-analysis of prospective cohort studies and randomized controlled trials to examine the association of vitamin C intakes with cancer outcomes.

RESULTS

The MR analysis showed no evidence of a causal association of circulating vitamin C concentration with any examined cancer. Although the odds ratio (OR) per one standard deviation increase in genetically predicted circulating vitamin C concentration was 1.34 (95% confidence interval 1.14 to 1.57) for breast cancer in the UK Biobank, this association could not be replicated in the Breast Cancer Association Consortium with an OR of 1.05 (0.94 to 1.17). Smoking initiation, as a positive control for our reverse MR analysis, showed a negative association with circulating vitamin C concentration. However, there was no strong evidence of a causal association of any examined cancer with circulating vitamin C. Sensitivity analysis using 6 different analytical approaches yielded similar results. Moreover, our MR results were consistent with the null findings from the meta-analysis exploring prospective associations of dietary or supplemental vitamin C intakes with cancer risk, except that higher dietary vitamin C intake, but not vitamin C supplement, was associated with a lower risk of lung cancer (risk ratio: 0.84, 95% confidence interval 0.71 to 0.99).

CONCLUSIONS

These findings provide no evidence to support that physiological-level circulating vitamin C has a large effect on risk of the five most common cancers in European populations, but we cannot rule out very small effect sizes.

Gut microbiota, inflammation, and molecular signatures of host response to infection

Gut microbial dysbiosis has been linked to many noncommunicable diseases. However, little is known about specific gut microbiota composition and its correlated metabolites associated with molecular signatures underlying host response to infection. Here, we describe the construction of a proteomic risk score based on 20 blood proteomic biomarkers, which have recently been identified as molecular signatures predicting the progression of the COVID-19. We demonstrate that in our cohort of 990 healthy individuals without infection, this proteomic risk score is positively associated with proinflammatory cytokines mainly among older, but not younger, individuals. We further discover that a core set of gut microbiota can accurately predict the above proteomic biomarkers among 301 individuals using a machine learning model and that these gut microbiota features are highly correlated with proinflammatory cytokines in another independent set of 366 individuals. Fecal metabolomics analysis suggests potential amino acid-related pathways linking gut microbiota to host metabolism and inflammation. Overall, our multi-omics analyses suggest that gut microbiota composition and function are closely related to inflammation and molecular signatures of host response to infection among healthy individuals. These results may provide novel insights into the cross-talk between gut microbiota and host immune system.

Multi-omics analyses reveal relationships among dairy consumption, gut microbiota and cardiometabolic health

BACKGROUND

Little is known about the interplay among dairy intake, gut microbiota and cardiometabolic health in human prospective cohort studies.

METHODS

The present study included 1780 participants from the Guangzhou Nutrition and Health Study. We examined the prospective association between habitual dairy consumption (total dairy, milk, yogurt) and gut microbial composition using linear regression after adjusting for socio-demographic, lifestyle and dietary factors. The cross-sectional association of dairy-associated microbial features with cardiometabolic risk factors was examined with a linear regression model, adjusting for potential confounders. Serum metabolomic profiles were analyzed by partial correlation analysis.

FINDINGS

There was a significant overall difference in gut microbial community structure (β-diversity) comparing the highest with the lowest category for each of total dairy, milk and yogurt (P < 0.05). We observed that dairy-associated microbes and α-diversity indices were inversely associated with blood triglycerides, while positively associated with high-density lipoprotein cholesterol. A follow-up metabolomics analysis revealed the association of targeted serum metabolites with dairy-microbial features and cardiometabolic traits. Specifically, 2-hydroxy-3-methylbutyric acid, 2-hydroxybutyric acid and L-alanine were inversely associated with dairy-microbial score, while positively associated with triglycerides (FDR-corrected P < 0.1).

INTERPRETATION

Dairy consumption is associated with the gut microbial composition and a higher α-diversity, which provides new insights into the understanding of dairy-gut microbiota interactions and their relationship with cardiometabolic health.

FUNDING

This work was supported by the National Natural Science Foundation of China, Zhejiang Ten-thousand Talents Program, Westlake University and the 5010 Program for Clinical Researches of the Sun Yat-sen University.

Interpretable Machine Learning Framework Reveals Robust Gut Microbiome Features Associated With Type 2 Diabetes

OBJECTIVE

To identify the core gut microbial features associated with type 2 diabetes risk and potential demographic, adiposity, and dietary factors associated with these features.

RESEARCH DESIGN AND METHODS

We used an interpretable machine learning framework to identify the type 2 diabetes-related gut microbiome features in the cross-sectional analyses of three Chinese cohorts: one discovery cohort (n = 1,832, 270 cases of type 2 diabetes) and two validation cohorts (cohort 1: n = 203, 48 cases; cohort 2: n = 7,009, 608 cases). We constructed a microbiome risk score (MRS) with the identified features. We examined the prospective association of the MRS with glucose increment in 249 participants without type 2 diabetes and assessed the correlation between the MRS and host blood metabolites (n = 1,016). We transferred human fecal samples with different MRS levels to germ-free mice to confirm the MRS-type 2 diabetes relationship. We then examined the prospective association of demographic, adiposity, and dietary factors with the MRS (n = 1,832).

RESULTS

The MRS (including 14 microbial features) consistently associated with type 2 diabetes, with risk ratio for per 1-unit change in MRS 1.28 (95% CI 1.23-1.33), 1.23 (1.13-1.34), and 1.12 (1.06-1.18) across three cohorts. The MRS was positively associated with future glucose increment (P < 0.05) and was correlated with a variety of gut microbiota-derived blood metabolites. Animal study further confirmed the MRS-type 2 diabetes relationship. Body fat distribution was found to be a key factor modulating the gut microbiome-type 2 diabetes relationship.

CONCLUSIONS

Our results reveal a core set of gut microbiome features associated with type 2 diabetes risk and future glucose increment.

[The relationship between HPV integration and prognosis of cervical cancer]

Objective: To investigate the relationship between human papillomavirus (HPV) integration and prognosis of cervical cancer patients. Methods: The data of 82 patients with cervical cancer treated in the Radiotherapy Department of Peking Union Medical College Hospital from October 2004 to June 2012 were retrospectively analyzed.The patients were divided into poor prognosis group (recurrence or metastasis after surgery and adjuvant radiotherapy) and good prognosis group based on a propensity score matching strategy.The HPV integration of the two groups were detected by whole exome sequencing to determine whether the integration sites were located in the common fragile sites (CFSs). HPV integration and integration into CFSs were compared between the two groups. Results: Among the enrolled 82 patients, 37 were divided in poor survival group and 45 in good survival group. A total of 90 integration breakpoints were identified, 30 of them occurred in poor prognosis group and 60 occurred in good prognosis group. In the poor prognosis group, HPV integration occurred in 20 patients, 13 of them were inserted in CFSs of 11 patients, and the numbers in good prognosis group were 26, 17, 11, respectively. There were no significantly statistical differences in the number of HPV integration events (P=0.289), HPV integration patients (P=0.735), CFSs integration events (P=0.427), and CFSs integration patients (P=0.591) between the two groups. In poor prognosis group, more CFSs integration events occurred in patients with metastasis than those in patients with only local recurrence (9 vs 2, P=0.003). Conclusions: No significant differences are observed in HPV integration and HPV integration into CFSs between cervical cancer patients with different prognoses. HPV integration into CFSs may be associated with distant metastasis.

The interplay between host genetics and the gut microbiome reveals common and distinct microbiome features for complex human diseases

BACKGROUND

Interest in the interplay between host genetics and the gut microbiome in complex human diseases is increasing, with prior evidence mainly being derived from animal models. In addition, the shared and distinct microbiome features among complex human diseases remain largely unclear.

RESULTS

This analysis was based on a Chinese population with 1475 participants. We estimated the SNP-based heritability, which suggested that Desulfovibrionaceae and Odoribacter had significant heritability estimates (0.456 and 0.476, respectively). We performed a microbiome genome-wide association study to identify host genetic variants associated with the gut microbiome. We then conducted bidirectional Mendelian randomization analyses to examine the potential causal associations between the gut microbiome and complex human diseases. We found that Saccharibacteria could potentially decrease the concentration of serum creatinine and increase the estimated glomerular filtration rate. On the other hand, atrial fibrillation, chronic kidney disease and prostate cancer, as predicted by host genetics, had potential causal effects on the abundance of some specific gut microbiota. For example, atrial fibrillation increased the abundance of Burkholderiales and Alcaligenaceae and decreased the abundance of Lachnobacterium, Bacteroides coprophilus, Barnesiellaceae, an undefined genus in the family Veillonellaceae and Mitsuokella. Further disease-microbiome feature analysis suggested that systemic lupus erythematosus and chronic myeloid leukaemia shared common gut microbiome features.

CONCLUSIONS

These results suggest that different complex human diseases share common and distinct gut microbiome features, which may help reshape our understanding of disease aetiology in humans. Video Abstract.

Erythrocyte n-6 Polyunsaturated Fatty Acids, Gut Microbiota, and Incident Type 2 Diabetes: A Prospective Cohort Study

OBJECTIVE

To examine the association of erythrocyte n-6 polyunsaturated fatty acid (PUFA) biomarkers with incident type 2 diabetes and explore the potential role of gut microbiota in the association.

RESEARCH DESIGN AND METHODS

We evaluated 2,731 participants without type 2 diabetes recruited between 2008 and 2013 in the Guangzhou Nutrition and Health Study (Guangzhou, China). Case subjects with type 2 diabetes were identified with clinical and biochemical information collected at follow-up visits. Using stool samples collected during the follow-up in the subset (n = 1,591), 16S rRNA profiling was conducted. Using multivariable-adjusted Poisson or linear regression, we examined associations of erythrocyte n-6 PUFA biomarkers with incident type 2 diabetes and diversity and composition of gut microbiota.

RESULTS

Over 6.2 years of follow-up, 276 case subjects with type 2 diabetes were identified (risk 0.10). Higher levels of erythrocyte γ-linolenic acid (GLA), but not linoleic or arachidonic acid, were associated with higher type 2 diabetes incidence. Comparing the top to the bottom quartile groups of GLA levels, relative risk was 1.72 (95% CI 1.21, 2.44) adjusted for potential confounders. Baseline GLA was inversely associated with gut microbial richness and diversity (α-diversity, both P < 0.05) during follow-up and significantly associated with microbiota β-diversity (P = 0.002). α-Diversity acted as a potential mediator in the association between GLA and type 2 diabetes (P < 0.05). Seven genera (Butyrivibrio, Blautia, Oscillospira, Odoribacter, S24-7 other, Rikenellaceae other, and Clostridiales other) were enriched in quartile 1 of GLA and in participants without type 2 diabetes.

CONCLUSIONS

Relative concentrations of erythrocyte GLA were positively associated with incident type 2 diabetes in a Chinese population and also with gut microbial profiles. These results highlight that gut microbiota may play an important role linking n-6 PUFA metabolism and type 2 diabetes etiology.

Contributions of Lactobacillus plantarum PC170 administration on the recovery of gut microbiota after short-term ceftriaxone exposure in mice

This study aimed to determine the impact of Lactobacillus plantarum PC170 concurrent with antibiotic treatment and/or during the recovery phase after antibiotic treatment on the body weight, faecal bacterial composition, short-chain fatty acids (SCFAs) concentration, and splenic cytokine mRNA expression of mice. Orally administrated ceftriaxone quantitatively and significantly decreased body weight, faecal total bacteria, Akkermansia muciniphila, and Lactobacillus plantarum, and faecal SCFAs concentration. Ceftriaxone treatment also dramatically altered the faecal microbiota with an increased Chao1 index, decreased species diversities and Bacteroidetes, and more Firmicutes and Proteobacteria. After ceftriaxone intervention, these changes all gradually started to recover. However, faecal microbiota diversities were still totally different from control by significantly increased α- and β-diversities. Bacteroidetes all flourished and became dominant during the recovery process. However, mice treated with PC170 both in parallel with and after ceftriaxone treatment encouraged more Bacteroidetes, Verrucomicrobia, and Actinobacteria, and the diversity by which to make faecal microbiota was very much closer to control. Furthermore, the expression of splenic pro-inflammatory cytokine tumour necrosis factor-α mRNA in mice supplemented with PC170 during the recovery phase was significantly lower than natural recovery. These results indicated that antibiotics, such as ceftriaxone, even with short-term intervention, could dramatically damage the structure of gut microbiota and their abilities to produce SCFAs with loss of body weight. Although such damages could be partly recovered with the cessation of antibiotics, the implication of antibiotics to gut microbiota might remain even after antibiotic treatment. The selected strain PC170 might be a potential probiotic because of its contributions in helping the host animal to remodel or stabilise its gut microbiome and enhancing the anti-inflammatory response as protection from the side effects of antibiotic therapy when it was administered in parallel with and after antibiotic treatment.

Incidence and Risk Factors of In-Stent Restenosis for Symptomatic Intracranial Atherosclerotic Stenosis: A Systematic Review and Meta-Analysis

BACKGROUND

In-stent restenosis affects long-term outcome in patients with intracranial atherosclerotic stenosis.

PURPOSE

The aim of this meta-analysis was to evaluate the incidence and risk factors of in-stent restenosis.

DATA SOURCES

All literature that reported in-stent restenosis was searched on PubMed, Ovid EMBASE and Ovid MEDLINE data bases.

STUDY SELECTION

Original articles about stents for symptomatic intracranial atherosclerotic stenosis were selected.

DATA ANALYSIS

Meta-analysis was conducted to derive the pooled in-stent restenosis using a random-effects model. Meta-regression was performed to explore the risk factors predisposing to in-stent restenosis.

DATA SYNTHESIS

In total, 51 studies with 5043 patients were included. The pooled incidence rate of in-stent restenosis was 14.8% (95% CI, 11.9%-17.9%). Among the lesions with in-stent restenosis, 28.8% of them led to (95% CI, 22.0%-36.0%) related neurologic symptoms. The series in the United States had a higher in-stent restenosis rate (27.0%; 95% CI, 20.6%-33.9%) compared with those from Asia (13.6%; 95% CI, 10.3%-17.2%) and other regions as a whole (7.6%; 95% CI, 1.1%-18.1%) (P < .01). Multiregression analysis revealed that younger patient age was related to high in-stent restenosis rates (P = .019), and vertebrobasilar junction location (P = .010) and low residual stenosis (P = .018) were 2 independent risk factors for symptomatic in-stent restenosis rate.

LIMITATIONS

The heterogeneity of most outcomes was high.

CONCLUSIONS

Our study showed promising results of in-stent restenosis for symptomatic atherosclerotic stenosis. Studies are needed to further expatiate on the mechanisms by which younger patient age, vertebrobasilar junction location, and low residual stenosis could increase in-stent restenosis and symptomatic in-stent restenosis, respectively.

Landscape-level validation of allometric relationships for carbon stock estimation reveals bias driven by soil type

Mitigation of climate change depends on accurate estimation and mapping of terrestrial carbon stocks, particularly in carbon dense tropical forests. Allometric equations can be used to robustly estimate biomass of tropical trees, but often require tree height, which is frequently unknown. Researchers and practitioners must, therefore, decide whether to directly measure a subset of tree heights to develop diameter : height (D:H) equations or rely on previously published generic equations. To date, studies comparing the two approaches have been spatially restricted and/or not randomly allocated across the landscape of interest, making the implications of deciding whether or not to measure tree heights difficult to determine. To address this issue, we use inventory data from a systematic-random forest inventory across Gabon (102 forest sites; 42,627 trees, including 7,036 height-measured trees). Using plot-specific models of D:H as a benchmark, we compare the performance of a suite of locally fitted and commonly used generic models (parameterized national, georegional, and pantropical equations) across a variety of scales, and assess which abiotic, anthropogenic, and topographical covariates contribute the most to bias in height estimation. We reveal marked spatial structure in the magnitude and direction of bias in tree height estimation using all generic models, due at least in part to soil type, which compounded to substantial error in site-level AGB estimates (of up to 38% or 150 Mg/ha). However, two generic pantropical models (Chave 2014; Feldpausch 2012) converged to within 2.5% of mean AGB at the landscape scale. Our results suggest that some (not all) pantropical equations can extrapolate AGB across large spatial scales with minimal bias in estimated mean AGB. However, extreme caution must be taken when interpreting the AGB estimates from generic models at the site-level as they fail to capture substantial spatial variation in D:H relationships, which could lead to dramatic under- or over-estimation of site-level carbon stocks. Validated allometric models derived at site- or soil-type-levels may be the best way to reduce such biases arising from landscape-level heterogeneity in D:H model fit in the Afrotropics.

Effect of dual versus mono antiplatelet therapy on recurrent stroke modulated by activated partial thromboplastin time

BACKGROUND AND PURPOSE

The efficacy of dual antiplatelet treatment may be modified by many factors. The aim was to assess whether the effect of clopidogrel plus aspirin versus aspirin alone on recurrent stroke would be affected by admission activated partial thromboplastin time (aPTT).

METHODS

Data were derived from the Clopidogrel in High-Risk Patients with Acute Nondisabling Cerebrovascular Events (CHANCE) trial. A total of 5074 patients were categorized into three groups based on the aPTT distribution according to the 15th and 85th percentile. The primary outcome was any stroke within 90 days. The interaction of aPTT with antiplatelet therapy on stroke risk was assessed with a Cox proportional hazards model with adjustment for covariates.

RESULTS

In the high aPTT group (defined as ≥35.9 s), stroke occurred in 6.7% of patients in the clopidogrel-aspirin arm and 11.9% in the aspirin arm [adjusted hazard ratio (HR) 0.50; 95% confidence interval (CI) 0.29-0.85]. In the medium aPTT group (24.6-35.8 s), stroke occurred in 7.7% of patients in the clopidogrel-aspirin arm and 11.8% in the aspirin arm (adjusted HR 0.62; 95% CI 0.50-0.75). Furthermore, in the low aPTT group (≤24.5 s), stroke occurred in 11.2% of patients in the clopidogrel-aspirin arm and 9.9% in the aspirin arm (adjusted HR 1.07; 95% CI 0.65-1.62). The interaction P value of antiplatelet therapy with aPTT level at the cut-point of approximately 25 s or below was significant (P < 0.05).

CONCLUSIONS

Dual antiplatelet therapy was superior to single antiplatelet therapy in the high or medium aPTT group but not in the low aPTT group.