Associations of sleep behaviors and genetic risk with risk of incident osteoporosis: A prospective cohort study of 293,164 participants.

BACKGROUND: Unhealthy sleep behaviors are associated with higher risks of osteoporosis (OP), while prospective evidence is limited. This study aimed to prospectively investigate this association, quantify the attributable burden of OP incidence reduction due to unhealthy sleep behaviors, and explore potential modifications by genetic risk factors. METHODS: This longitudinal cohort study was conducted utilizing data from the UK Biobank, comprising 293,164 participants initially free of OP and with requisite sleep behaviors data at baseline. We followed the participants after recruitment until November 30, 2022, to ascertain incident OP. We assessed the associations of five sleep behaviors including sleep duration, chronotype, insomnia, daytime napping, and morning wake-up difficulties, as well as sleep behavior patterns identified based on the above sleep behaviors, with the risk of OP, using Cox models adjusted for multiple confounders. The analyses were then performed separately among individuals with different OP susceptibility, indexed by standard polygenetic risk scores(PRS) for OP. Our secondary outcome was OP with pathologic fracture. Subgroup and sensitivity analyses were performed. Additionally, attributable risk percent in the exposed population (AR%) and population attributable fraction (PAF) of sleep behaviors were calculated. RESULTS: Over a median follow-up of 13.7 years, 8253 new-onset OP cases were documented. Unhealthy sleep behaviors, such as long or short sleep duration, insomnia, daytime napping, morning wake-up difficulties, and unhealthy sleep patterns, were associated with elevated risks of OP (HRs ranging from 1.14 to 1.46, all P-value <0.001) compared to healthy sleep behaviors. Similar associations were observed for OP with pathologic fractures. Insomnia exhibited the largest AR% of 39.98 % (95%CI: 36.46, 43.31) and PAF of 33.25 % (95%CI: 30.00, 36.34) among healthy sleep patterns and components. A statistically significant multiplicative interaction was noted between sleep behaviors and OP PRS on OP risk (all P-interaction <0.001). CONCLUSIONS: Four unhealthy sleep behaviors and sleep behavior patterns were associated to increased OP risk, with insomnia contributing the most to OP incidence, while genetic risk for OP modified this association. These findings underscore the crucial role of adhering to healthy sleep behaviors for effective OP prevention.

Infant age inversely correlates with gut carriage of resistance genes, reflecting modifications in microbial carbohydrate metabolism during early life.

The infant gut microbiome is increasingly recognized as a reservoir of antibiotic resistance genes, yet the assembly of gut resistome in infants and its influencing factors remain largely unknown. We characterized resistome in 4132 metagenomes from 963 infants in six countries and 4285 resistance genes were observed. The inherent resistome pattern of healthy infants (N = 272) could be distinguished by two stages: a multicompound resistance phase (Months 0-7) and a tetracycline-mupirocin-ß-lactam-dominant phase (Months 8-14). Microbial taxonomy explained 40.7% of the gut resistome of healthy infants, with Escherichia (25.5%) harboring the most resistance genes. In a further analysis with all available infants (N = 963), we found age was the strongest influencer on the resistome and was negatively correlated with the overall resistance during the first 3 years (p < 0.001). Using a random-forest approach, a set of 34 resistance genes could be used to predict age (R 2 = 68.0%). Leveraging microbial host inference analyses, we inferred the age-dependent assembly of infant resistome was a result of shifts in the gut microbiome, primarily driven by changes in taxa that disproportionately harbor resistance genes across taxa (e.g., Escherichia coli more frequently harbored resistance genes than other taxa). We performed metagenomic functional profiling and metagenomic assembled genome analyses whose results indicate that the development of gut resistome was driven by changes in microbial carbohydrate metabolism, with an increasing need for carbohydrate-active enzymes from Bacteroidota and a decreasing need for Pseudomonadota during infancy. Importantly, we observed increased acquired resistance genes over time, which was related to increased horizontal gene transfer in the developing infant gut microbiome. In summary, infant age was negatively correlated with antimicrobial resistance gene levels, reflecting a composition shift in the gut microbiome, likely driven by the changing need for microbial carbohydrate metabolism during early life.

Healthy lifestyles are associated with alleviating the single-nucleotide polymorphism-based genetic risks of ischaemic stroke, intracerebral haemorrhage and myocardial infarction.

BACKGROUND: Both genetic and lifestyle factors contribute to myocardial infarction (MI) and stroke, including ischaemic stroke (IS) and intracerebral haemorrhage (ICH). We explored how and the extent to which a healthy lifestyle, by considering a comprehensive list, could counteract the genetic risk of those diseases, respectively. METHODS: 315 044 participants free of stroke and MI at baseline were identified from the UK Biobank. Genetic risk scores (GRS) for those diseases were constructed separately and categorised as low, intermediate and high by tertile. Lifestyle risk scores (LRS) were constructed separately using smoking, alcohol intake, physical activity, dietary patterns and sleep patterns. Similarly, participants were categorised into low, intermediate and high LRS. The data were analysed using Cox proportional hazard models. RESULTS: Over a median follow-up of 12.8 years, 4642, 1046 and 9485 participants developed IS, ICH and MI, respectively. Compared with participants with low levels of GRS and LRS, the HRs of those with high levels of GRS and LRS were 3.45 (95% CI 2.71 to 4.41), 2.32 (95% CI 1.40 to 3.85) and 4.89 (95% CI 4.16 to 5.75) for IS, ICH and MI, respectively. Moreover, among participants with high GRS, the standardised 14-year rates of IS events were 4.40% (95% CI 3.45% to 5.36%) among those with high LRS. In contrast, it is only 1.78% (95% CI 1.63% to 1.94%) among those with low LRS. Similarly for MI, the high LRS group had standardised rates of 8.60% (95% CI 7.38% to 9.81%), compared with 3.34% (95% CI 3.12% to 3.56%) in low LRS. Among the high genetic risk group of ICH, the rate is reduced by about half compared low LRS to high LRS, although the rate was low for both (0.36% (95% CI 0.31% to 0.42%) and 0.71% (95% CI 0.36% to 1.05%), respectively). CONCLUSION: Healthy lifestyles were substantially associated with a reduction in the risk of IS, ICH and MI and attenuated the genetic risk of IS, ICH and MI by at least half, respectively.

Sleep Pattern, Genetic Susceptibility, and Abdominal Aortic Aneurysm in UK Biobank Participants: Large-Scale Cohort Study.

Background: Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality. Objectives: The authors aimed to explore the associations between sleep patterns and genetic susceptibility to AAA. Methods: We included 344,855 UK Biobank study participants free of AAA at baseline. A sleep pattern was defined by chronotype, sleep duration, insomnia, snoring, and daytime sleepiness, and an overall sleep score was constructed with a range from 0 to 5, where a high score denotes a healthy sleep pattern. Polygenic risk score based on 22 single nucleotide polymorphisms was categorized into tertiles and used to evaluate the genetic risk for AAA. Cox proportional hazards regression models were used to assess the association between sleep, genetic factors, and the incidence of AAA. Results: During a median of 12.59 years of follow-up, 1,622 incident AAA cases were identified. The HR per 1-point increase in the sleep score was 0.91 (95% CI: 0.86-0.96) for AAA. Unhealthy sleep patterns, defined as a sleep score ranging from 0 to 3, were found to be associated with a higher risk of AAA for the intermediate (HR: 1.18, 95% CI: 1.06-1.31) and poor sleep patterns (HR: 1.40, 95% CI: 1.13-1.73), respectively, compared to the healthy pattern. Participants with poor sleep patterns and high genetic risks had a 2.5-fold higher risk of AAA than those with healthy sleep patterns and low genetic risk. Conclusions: In this large prospective study, healthy sleep patterns were associated with a lower risk of AAA among participants with low, intermediate, or high genetic risk.

Lipid metabolism mediates the association between body mass index change and bone mineral density: The Taizhou imaging study.

BACKGROUND: Limited research explores the impact of body mass index (BMI) change on osteoporosis, regarding the role of lipid metabolism. We aimed to cross-sectionally investigate these relationships in 820 Chinese participants aged 55-65 from the Taizhou Imaging Study. METHODS: We used the baseline data collected between 2013 and 2018. T-score was calculated by standardizing bone mineral density and was used for osteoporosis and osteopenia diagnosis. Multinomial logistic regression was used to examine the effect of BMI change on bone health status. Multivariable linear regression was employed to identify the metabolites corrected with BMI change and T-score. Exploratory factor analysis (EFA) and mediation analysis were conducted to ascertain the involvement of the metabolites. RESULTS: BMI increase served as a protective factor against osteoporosis (OR = 0.79[0.71-0.88], P-value<0.001) and osteopenia (OR = 0.88[0.82-0.95], P-value<0.001). Eighteen serum metabolites were associated with both BMI change and T-score. Specifically, high-density lipoprotein (HDL) substructures demonstrated negative correlations (ß = -0.08 to -0.06 and - 0.12 to -0.08, respectively), while very low-density lipoprotein (VLDL) substructions showed positive correlations (ß = 0.09 to 0.10 and 0.10 to 0.11, respectively). The two lipid factors (HDL and VLDL) extracted by EFA acted as mediators between BMI change and T-score (Prop. Mediated = 8.16% and 10.51%, all P-value<0.01). CONCLUSION: BMI gain among Chinese aged 55-65 is beneficial for reducing the risk of osteoporosis. The metabolism of HDL and VLDL partially mediates the effect of BMI change on bone loss. Our research offers novel insights into the prevention of osteoporosis, approached from the perspective of weight management and lipid metabolomics.

Mobility-related brain regions linking carotid intima-media thickness to specific gait performances in old age.

BACKGROUND: Gait disturbance is common in older adults with vascular diseases. However, how carotid atherosclerosis affects gait remains poorly understood. The objectives were to investigate the associations between carotid intima-media thickness and specific gait performances and explore the potential role of brain structure in mediating these associations. METHODS: A cross-sectional analysis of data from the Taizhou Imaging Study was conducted, including 707 individuals who underwent both gait and carotid ultrasound examinations. Gait assessments include the Timed-Up-and-Go test, the Tinetti test, and quantitative gait assessment using a wearable device. Quantitative parameters were summarized into independent gait domains with factor analysis. Magnetic resonance images were obtained on a 3.0-Tesla scanner, and the volumes of fifteen brain regions related to motor function (primary motor, sensorimotor), visuospatial attention (inferior posterior parietal lobules, superior posterior parietal lobules), executive control function (dorsolateral prefrontal cortex, anterior cingulate), memory (hippocampus, entorhinal cortex), motor imagery (precuneus, parahippocampus, posterior cingulated cortex), and balance (basal ganglia: pallidum, putamen, caudate, thalamus) were computed using FreeSurfer and the Desikan-Killiany atlas. Mediation analysis was conducted with carotid intima-media thickness as the predictor and mobility-related brain regions as mediators. RESULTS: Carotid intima-media thickness was found to be associated with the Timed-Up-and-Go performance (ß = 0.129, p = 0.010) as well as gait performances related to pace (ß=-0.213, p < 0.001) and symmetry (ß = 0.096, p = 0.045). Besides, gait performances were correlated with mobility-related brain regions responsible for motor, visuospatial attention, executive control, memory, and balance (all FDR < 0.05). Notably, significant regions differed depending on the gait outcomes measured. The primary motor (41.9%), sensorimotor (29.3%), visuospatial attention (inferior posterior parietal lobules, superior posterior parietal lobules) (13.8%), entorhinal cortex (36.4%), and motor imagery (precuneus, parahippocampus, posterior cingulated cortex) (27.3%) mediated the association between increased carotid intima-media thickness and poorer Timed-Up-and-Go performance. For the pace domain, the primary motor (37.5%), sensorimotor (25.8%), visuospatial attention (12.3%), entorhinal cortex (20.7%), motor imagery (24.9%), and balance (basal ganglia: pallidum, putamen, caudate, thalamus) (11.6%) acted as mediators. CONCLUSIONS: Carotid intima-media thickness is associated with gait performances, and mobility-related brain volume mediates these associations. Moreover, the distribution of brain regions regulating mobility varies in the different gait domains. Our study adds value in exploring the underlying mechanisms of gait disturbance in the aging population.

Analysis of gait pattern related to high cerebral small vessel disease burden using quantitative gait data from wearable sensors.

BACKGROUND AND OBJECTIVES: Sensor-based wearable devices help to obtain a wide range of quantitative gait parameters, which provides sufficient data to investigate disease-specific gait patterns. Although cerebral small vessel disease (CSVD) plays a significant role in gait impairment, the specific gait pattern associated with a high burden of CSVD remains to be explored. METHODS: We analyzed the gait pattern related to high CSVD burden from 720 participants (aged 55-65 years, 42.5 % male) free of neurological disease in the Taizhou Imaging Study. All participants underwent detailed quantitative gait assessments (obtained from an insole-like wearable gait tracking device) and brain magnetic resonance imaging examinations. Thirty-three gait parameters were summarized into five gait domains. Sparse sliced inverse regression was developed to extract the gait pattern related to high CSVD burden. RESULTS: The specific gait pattern derived from several gait domains (i.e., angles, phases, variability, and spatio-temporal) was significantly associated with the CSVD burden (OR=1.250, 95 % CI: 1.011-1.546). The gait pattern indicates that people with a high CSVD burden were prone to have smaller gait angles, more stance time, more double support time, larger gait variability, and slower gait velocity. Furthermore, people with this gait pattern had a 25 % higher risk of a high CSVD burden. CONCLUSIONS: We established a more stable and disease-specific quantitative gait pattern related to high CSVD burden, which is prone to facilitate the identification of individuals with high CSVD burden among the community residents or the general population.

Bidirectional mediation of bone mineral density and brain atrophy on their associations with gait variability.

This mediation analysis aimed to investigate the associations among areal bone mineral density, mobility-related brain atrophy, and specific gait patterns. A total of 595 participants from the Taizhou Imaging Study, who underwent both gait and bone mineral density measurements, were included in this cross-sectional analysis. We used a wearable gait tracking device to collect quantitative gait parameters and then summarized them into independent gait domains with factor analysis. Bone mineral density was measured in the lumbar spine, femoral neck, and total hip using dual-energy X-ray absorptiometry. Magnetic resonance images were obtained on a 3.0-Tesla scanner, and the volumes of brain regions related to mobility were computed using FreeSurfer. Lower bone mineral density was found to be associated with higher gait variability, especially at the site of the lumbar spine (ß = 0.174, FDR = 0.001). Besides, higher gait variability was correlated with mobility-related brain atrophy, like the primary motor cortex (ß = 0.147, FDR = 0.006), sensorimotor cortex (ß = 0.153, FDR = 0.006), and entorhinal cortex (ß = 0.106, FDR = 0.043). Bidirectional mediation analysis revealed that regional brain atrophy contributed to higher gait variability through the low lumbar spine bone mineral density (for the primary motor cortex, P = 0.018; for the sensorimotor cortex, P = 0.010) and the low lumbar spine bone mineral density contributed to higher gait variability through the primary motor and sensorimotor cortices (P = 0.026 and 0.010, respectively).

Circulating Lipoproteins Mediate the Association Between Cardiovascular Risk Factors and Cognitive Decline: A Community-Based Cohort Study.

Cardiovascular health metrics are now widely recognized as modifiable risk factors for cognitive decline and dementia. Metabolic perturbations might play roles in the linkage of cardiovascular diseases and dementia. Circulating metabolites profiling by metabolomics may improve understanding of the potential mechanism by which cardiovascular risk factors contribute to cognitive decline. In a prospective community-based cohort in China (n = 725), 312 serum metabolic phenotypes were quantified, and cardiovascular health score was calculated including smoking, exercise, sleep, diet, body mass index, blood pressure, and blood glucose. Cognitive function assessments were conducted in baseline and follow-up visits to identify longitudinal cognitive decline. A better cardiovascular health was significantly associated with lower risk of concentration decline and orientation decline (hazard ratio (HR): 0.84-0.90; p < 0.05). Apolipoprotein-A1, high-density lipoprotein (HDL) cholesterol, cholesterol ester, and phospholipid concentrations were significantly associated with a lower risk of longitudinal memory and orientation decline (p < 0.05 and adjusted-p < 0.20). Mediation analysis suggested that the negative association between health status and the risk of orientation decline was partly mediated by cholesterol ester and total lipids in HDL-2 and -3 (proportion of mediation: 7.68-8.21%, both p < 0.05). Cardiovascular risk factors were associated with greater risks of cognitive decline, which were found to be mediated by circulating lipoproteins, particularly the medium-size HDL components. These findings underscore the potential of utilizing lipoproteins as targets for early stage dementia screening and intervention. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-023-00120-2.

Unraveling the role of serum metabolites in the relationship between plant-based diets and bone health in community-dwelling older adults.

The potential adverse effects of the plant-based dietary pattern on bone health have received widespread attention. However, the biological mechanisms underlying the adverse effects of plant-based diets on bone health remain incompletely understood. The objective of this study was to identify potential biomarkers between plant-based diets and bone loss utilizing metabolomic techniques in the Taizhou Imaging Study (TIS) (N = 788). Plant-based diet indexes (overall plant-based diet index (PDI), healthy plant-based diet index (hPDI), and unhealthy plant-based diet index (uPDI)) were calculated using the food frequency questionnaire, and bone mineral density (BMD) was measured using dual-energy X-ray absorptiometry. A multinomial logistic regression was used to explore the associations of plant-based diet indexes with bone loss. Furthermore, mediation analysis and exploratory factor analysis (EFA) were performed to explore the mediated effects of metabolites on the association of plant-based diets with BMD T-score. Our results showed that higher hPDI and uPDI were positively associated with bone loss. Moreover, nineteen metabolites were significantly associated with BMD T-score, among them, seven metabolites were associated with uPDI. Except for cholesterol esters in VLDL-1, the remaining six metabolites significantly mediated the negative association between uPDI and BMD T-score. Interestingly, we observed that the same six metabolites mediated the positive association between fresh fruit and BMD T-score. Collectively, our results support the deleterious effects of plant-based diets on bone health and discover the potential mediation effect of metabolites on the association of plant-based diets with bone loss. The findings offer valuable insights that could optimize dietary recommendations and interventions, contributing to alleviate the potential adverse effects associated with plant-based diets.

Single extracellular vesicle surface protein-based blood assay identifies potential biomarkers for detection and screening of five cancers.

Extracellular vesicles (EVs) and EV proteins are promising biomarkers for cancer liquid biopsy. Herein, we designed a case-control study involving 100 controls and 100 patients with esophageal, stomach, colorectal, liver, or lung cancer to identify common and type-specific biomarkers of plasma-derived EV surface proteins for the five cancers. EV surface proteins were profiled using a sequencing-based proximity barcoding assay. In this study, five differentially expressed proteins (DEPs) and eight differentially expressed protein combinations (DEPCs) showed promising performance (area under curve, AUC > 0.900) in pan-cancer identification [e.g., TENM2 (AUC = 0.982), CD36 (AUC = 0.974), and CD36-ITGA1 (AUC = 0.971)]. Our classification model could properly discriminate between cancer patients and controls using DEPs (AUC = 0.981) or DEPCs (AUC = 0.965). When distinguishing one cancer from the other four, the accuracy of the classification model using DEPCs (85-92%) was higher than that using DEPs (78-84%). We validated the performance in an additional 14 cancer patients and 14 controls, and achieved an AUC value of 0.786 for DEPs and 0.622 for DEPCs, highlighting the necessity to recruit a larger cohort for further validation. When clustering EVs into subpopulations, we detected cluster-specific proteins highly expressed in immune-related tissues. In the context of colorectal cancer, we identified heterogeneous EV clusters enriched in cancer patients, correlating with tumor initiation and progression. These findings provide epidemiological and molecular evidence for the clinical application of EV proteins in cancer prediction, while also illuminating their functional roles in cancer physiopathology.

Disease trajectory of high neuroticism and the relevance to psychiatric disorders: A retro-prospective cohort study.

BACKGROUND: Neuroticism is a psychological personality trait that has a significant impact on public health and is also a potential predisposing factor for adverse disease outcomes; however, comprehensive studies of the subsequently developed conditions are lacking. The starting point of disease trajectory in terms of genetic variation remains unclear. METHOD: Our study included 344,609 adult participants from the UK Biobank cohort who were virtually followed up from January 1, 1997. Neuroticism levels were assessed using 12 items from the Eysenck Personality Questionnaire. We performed a phenome-wide association analysis of neuroticism and subsequent diseases. Binomial tests and logistic regression models were used to test the temporal directionality and association between disease pairs to construct disease trajectories. We also investigated the association between polygenic risk scores (PRSs) for five psychiatric traits and high neuroticism. RESULTS: The risk for 59 diseases was significantly associated with high neuroticism. Depression, anxiety, irritable bowel syndrome, migraine, spondylosis, and sleep disorders were the most likely to develop, with hazard ratios of 6.13, 3.66, 2.28, 1.74, 1.74, and 1.71, respectively. The disease trajectory network revealed two major disease clusters: cardiometabolic and chronic inflammatory diseases. Medium/high genetic risk groups stratified by the PRSs of four psychiatric traits were associated with an elevated risk of high neuroticism. We further identified eight complete phenotypic trajectory clusters of medium or high genetic risk for psychotic, anxiety-, depression-, and stress-related disorders. CONCLUSION: Neuroticism plays an important role in the development of somatic and mental disorders. The full picture of disease trajectories from the genetic risk of psychiatric traits and neuroticism in early life to a series of diseases later provides evidence for future research to explore the etiological mechanisms and precision management.

Intake of dietary flavonoids in relation to bone loss among U.S. adults: a promising strategy for improving bone health.

Dietary flavonoids have been recommended for improving bone health due to their antioxidant, anti-inflammatory and osteogenic properties. However, the effectiveness of each flavonoid subclass in the prevention and treatment of osteoporosis remains controversial. The objective of the current study was to examine the association between the intake of flavonoid subclasses and bone loss in 10 480 U.S. adults in the National Health and Nutrition Examination Survey. We employed a multinomial logistic regression model to calculate the odds ratios (OR) and 95% confidence intervals (95% CI). The intake of flavones, isoflavones, and flavanones was beneficially associated with osteoporosis (ORQ5 vs. Q1 = 0.44; 95% CI: 0.30-0.64 for flavones; ORQ5 vs. Q1 = 0.53; 95% CI: 0.37-0.77 for isoflavones; ORQ5 vs. Q1 = 0.66; 95% CI: 0.45-0.97 for flavanones). A higher intake of flavones and flavanones was significantly associated with a lower risk of bone loss at the femoral neck rather than the lumbar spine. Notably, stratified analysis showed that genistein had a harmful association with osteopenia in the population with lower serum calcium levels, whereas it had a beneficial association with osteoporosis in the population with higher serum calcium levels. Multiple sensitivity analyses were performed to test the robustness of the results, including subgroup analysis, exclusion of individuals' use of anti-osteoporosis, corticosteroid, and estrogenic medications, adjusting more potential confounders and calculation of the E-value. Overall, incorporating this modifiable diet into an individual's lifestyle could provide potential possibilities to prevent and ameliorate osteoporosis.

Association between oral health and cognitive function among Chinese older adults: the Taizhou imaging study.

BACKGROUND: We aimed to investigate the association between oral health and cognitive function in a sample of older adults from a Chinese rural community. METHODS: The cross-sectional cognitive function of 677 individuals were assessed by Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). A comprehensive profile of the oral health status was evaluated by questionnaire and clinical examination. RESULTS: Multiple covariates-adjusted regression models demonstrated decayed teeth (DT) and decayed/missing/filled teeth (DMFT) were negatively associated with MoCA score (all p < 0.05). Calculus index (CI) and clinical attachment loss (CAL) were significantly associated with the lower MoCA, short-term memory and executive function score, respectively (all p < 0.05). Additionally, participants with missing teeth unrestored tend to get lower MMSE and MoCA scores (p < 0.05). The results also showed that increased DT and CI were modestly associated with higher odds of cognitive impairment (p < 0.05). CONCLUSIONS: There is an association between oral health and global cognition. Poor periodontal status was strongly associated with worse global cognition performance, especially in the short-term memory and executive domain for the aging population.

Retraction: Down-regulation of MRPS23 inhibits LPS-induced proliferation and invasion via regulation of the NF-κB signaling pathway in osteosarcoma cells.

[This retracts the article DOI: 10.1039/C8RA08973F.].

BMI trajectory of rapid and excessive weight gain during adulthood is associated with bone loss: a cross-sectional study from NHANES 2005-2018.

BACKGROUND: Studies have examined the effect of weight change on osteoporosis, but the results were controversial. Among them, few had looked at weight change over the life span. This study aimed to fill this gap and investigate the association between lifetime body mass index (BMI) trajectories and bone loss. METHODS: In this cross-sectional study, participants at age 50 and above were selected from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. Dual-energy X-ray Absorptiometry was used to measure the bone mineral density at the femoral neck and lumbar spine. Standard BMI criteria were used, with < 25 kg/m2 for normal, 25-29.9 kg/m2 for overweight, and ≥ 30 kg/m2 for obesity. The latent class trajectory model (LCTM) was used to identify BMI trajectories. Multinomial logistic regression models were fitted to evaluate the association between different BMI trajectories and osteoporosis or osteopenia. RESULTS: For the 9,706 eligible participants, we identified four BMI trajectories, including stable (n = 7,681, 70.14%), slight increase (n = 1253, 12.91%), increase to decrease (n = 195, 2.01%), and rapid increase (n = 577, 5.94%). Compared with individuals in the stable trajectory, individuals in the rapid increase trajectory had higher odds of osteoporosis (OR = 2.25, 95% CI 1.19-4.23) and osteopenia (OR = 1.49, 95% CI 1.02-2.17). This association was only found in the lumbar spine (OR = 2.11, 95% CI 1.06-4.2) but not in the femoral neck. In early-stage (age 25-10 years ago) weight change, staying an obesity and stable weight seemed to have protective effects on osteoporosis (OR = 0.26, 95% CI 0.08-0.77) and osteopenia (OR = 0.46, 95% CI 0.25-0.84). Meanwhile, keeping an early-stage stable and overweight was related to lower odds of osteopenia (OR = 0.53, 95% CI 0.34-0.83). No statistically significant association between recent (10 years ago to baseline) weight change and osteoporosis was found. CONCLUSIONS: Rapid and excess weight gain during adulthood is associated with a higher risk of osteoporosis. But this association varies by skeletal sites. Maintaining stable overweight and obesity at an early stage may have potentially beneficial effects on bone health.

Host Genetic Factors, Comorbidities and the Risk of Severe COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was varied in disease symptoms. We aim to explore the effect of host genetic factors and comorbidities on severe COVID-19 risk. METHODS: A total of 20,320 COVID-19 patients in the UK Biobank cohort were included. Genome-wide association analysis (GWAS) was used to identify host genetic factors in the progression of COVID-19 and a polygenic risk score (PRS) consisted of 86 SNPs was constructed to summarize genetic susceptibility. Colocalization analysis and Logistic regression model were used to assess the association of host genetic factors and comorbidities with COVID-19 severity. All cases were randomly split into training and validation set (1:1). Four algorithms were used to develop predictive models and predict COVID-19 severity. Demographic characteristics, comorbidities and PRS were included in the model to predict the risk of severe COVID-19. The area under the receiver operating characteristic curve (AUROC) was applied to assess the models' performance. RESULTS: We detected an association with rs73064425 at locus 3p21.31 reached the genome-wide level in GWAS (odds ratio: 1.55, 95% confidence interval: 1.36-1.78). Colocalization analysis found that two genes (SLC6A20 and LZTFL1) may affect the progression of COVID-19. In the predictive model, logistic regression models were selected due to simplicity and high performance. Predictive model consisting of demographic characteristics, comorbidities and genetic factors could precisely predict the patient's progression (AUROC = 82.1%, 95% CI 80.6-83.7%). Nearly 20% of severe COVID-19 events could be attributed to genetic risk. CONCLUSION: In this study, we identified two 3p21.31 genes as genetic susceptibility loci in patients with severe COVID-19. The predictive model includes demographic characteristics, comorbidities and genetic factors is useful to identify individuals who are predisposed to develop subsequent critical conditions among COVID-19 patients.

The Hidden Dangers of Plant-Based Diets Affecting Bone Health: A Cross-Sectional Study with U.S. National Health and Nutrition Examination Survey (NHANES) Data from 2005-2018.

The plant-based dietary pattern has been recommended for its potential health and environmental benefits, but its association with bone loss needs to be further explored. This study aimed to investigate the association between three plant-based diet indexes and bone loss in 16,085 adults, using data from the National Health and Nutrition Examination Survey. Three plant-based diet indexes (PDI, hPDI, and uPDI) were calculated from two NHANES 24-h dietary recall interviews, to characterize a plant-based diet. A multinomial logistic regression model was used to estimate the odds ratios (OR) and 95% confidence intervals (95% CI). Higher hPDI and PDI were associated with increased risk of bone loss (ORQ5 vs. Q1 = 1.50; 95% CI: 1.24-1.81 for hPDI; ORQ5 vs. Q1 = 1.22; 95% CI: 1.03-1.45 for PDI), while higher uPDI was associated with increased risk of osteoporosis (ORQ5 vs. Q1 = 1.48; 95% CI: 1.04-2.11). A harmful association between plant-based diet indexes (hPDI and PDI) and osteopenia was observed at the lumbar spine rather than the femoral neck. We conducted several sensitivity analyses to ensure the robustness of results, including subgroup analysis, exclusion of people taking anti-osteoporotic and estrogenic drugs, further adjustment for menopausal status, corticosteroid usage, and dietary supplements, and calculation of E-value. Our study demonstrates the deleterious effects of a plant-based diet on bone health and emphasizes the importance of a balanced diet.

Metagenomic association analysis of cognitive impairment in community-dwelling older adults.

The gut microbiota is reportedly involved in neurodegenerative disorders, and exploration of differences in the gut microbiota in different cognitive status could provide clues for early detection and intervention in cognitive impairment. Here, we used data from the Taizhou Imaging Study (N = 516), a community-based cohort, to compare the overall structure of the gut microbiota at the species level through metagenomic sequencing, and to explore associations with cognition. Interestingly, bacteria capable of producing short-chain fatty acids (SCFAs), such as Bacteroides massiliensis, Bifidobacterium pseudocatenulatum, Fusicatenibacter saccharivorans and Eggerthella lenta, that can biotransform polyphenols, were positively associated with better cognitive performance (p < 0.05). Although Diallister invisus and Streptococcus gordonii were not obviously related to cognition, the former was dominant in individuals with mild cognitive impairment (MCI), while the later was more abundant in cognitively normal (CN) than MCI groups, and positively associated with cognitive performance (p < 0.05). Functional analysis further supported a potential role of SCFAs and lactic acid in the association between the gut microbiota and cognition. The significant associations persisted after accounting for dietary patterns. Collectively, our results demonstrate an association between the gut microbiota and cognition in the general population, indicating a potential role in cognitive impairment. The findings provide clues for microbiome biomarkers of dementia, and insight for the prevention and treatment of dementia.