The association between patterns of exposure to adverse life events and the risk of chronic kidney disease: a prospective cohort study of 140,997 individuals.

Exposure to adverse life events is linked to somatic disorders. The study aims to evaluate the association between adverse events at varying life stages and the risk of chronic kidney disease (CKD), a condition affecting about 10% population worldwide. This prospective cohort study included 140,997 participants from the UK Biobank. Using survey items related to childhood maltreatment, adulthood adversity and catastrophic trauma, we performed latent class analysis to summarize five distinct patterns of exposure to adverse life events, namely "low-level exposure", "childhood exposure", "adulthood exposure", "sexual abuse" and "child-to-adulthood exposure". We used Cox proportional hazard regression to evaluate the association of patterns of exposure to adverse life events with CKD, regression-based mediation analysis to decompose the total effect, and gene-environment-wide interaction study (GEWIS) to identify interactions between genetic loci and adverse life events. During a median follow-up of 5.98 years, 2734 cases of incident CKD were identified. Compared with the "low-level exposure" pattern, "child-to-adulthood exposure" was associated with increased risk of CKD (hazard ratio 1.37, 95% CI 1.14 to 1.65). BMI, smoking and hypertension mediated 11.45%, 9.79%, and 4.50% of this total effect, respectively. Other patterns did not show significant results. GEWIS and subsequent analyses indicated that the magnitude of the association between adverse life events and CKD differed according to genetic polymorphisms, and identified potential underlying pathways (e.g., interleukin 1 receptor activity). These findings underscore the importance of incorporating an individual's psychological encounters and genetic profiles into the precision prevention of CKD.

Association Between Early-Life and Premorbid Measurements of Body Composition and Risk of Motor Neuron Disease: A Prospective Cohort Study in the UK Biobank.

OBJECTIVE: The objective of this study was to investigate the association between developmental and premorbid body composition measurements and the risk of motor neuron disease (MND). METHODS: We performed a cohort study in the UK Biobank to assess the association of developmental body metrics and premorbid body composition measures (using 28 measurements and 7 patterns of body composition) with the risk of MND. Among participants with longitudinal measures, we compared the changes in body composition over time between individuals who later developed MND and those who remained free of MND. RESULTS: Among the 412,691 individuals included in this study, 549 people received an MND diagnosis during the follow-up visit. Higher birth weight was associated with an increased risk of MND among individuals born over 4 kg (hazard ratio [HR] per kg increase = 2.21, 95% confidence interval [CI] = 1.38-3.55), and taller adult height was associated with an increased risk of MND (HR per 5 cm increase = 1.10, 95% CI = 1.03-1.17). We observed that measures of elevated fat mass were associated with a lower risk of MND more than 5 years before diagnosis. A higher "leg-dominant fat distribution" pattern was associated with an increased risk whereas higher "muscle strength" was associated with a reduced risk of MND 5 years before diagnosis. Longitudinal analyses indicated a faster decline in measures of fat mass and muscle strength, as well as a shift in fat distribution from arm to leg dominant, among individuals who later developed MND, compared with others. INTERPRETATION: Body composition at early and middle age may be indicative of the risk of MND development. ANN NEUROL 2024.

Predicting suicidal behavior in individuals with depression over 50 years of age: Evidence from the UK biobank.

Objective: To construct applicable models suitable for predicting the risk of suicidal behavior among individuals with depression, particularly on the progression from no history of suicidal behavior to suicide attempts, as well as from suicidal ideation to suicide attempts. Methods: Based on a prospective cohort from the UK Biobank, a total of 55,139 individuals aged 50 and above with depression were enrolled in the study, among whom 29,528 exhibited suicidal behavior. Specifically, they were divided into control (25,611), suicidal ideation (24,361), and suicide attempt (5167) groups. Least absolute shrinkage and selection operator (LASSO) regression was used to identify a subset of important features for distinguishing suicidal ideation and suicide attempts. We used the Gradient Boosting Decision Tree (GBDT) algorithm with stratified 10-fold cross-validation and grid-search to construct the prediction models for suicidal ideation or suicide attempts. To address the dataset imbalance in classifying suicide attempts, we used random under-sampling. The SHapley Additive exPlanations (SHAP) were used to estimate the important variables in the GBDT model. Results: Significant differences in sociodemographic, economic, lifestyle, and psychological factors were observed across the three groups. Each classifier optimally utilized 8-11 features. Overall, the algorithms predicting suicide attempts demonstrated slightly higher performance than those predicting suicidal ideation. The GBDT classifier achieved the highest accuracy, with AUROC scores of 0.914 for suicide attempts and 0.803 for suicidal ideation. Distinctive predictive factors were identified for each group: while depression's inherent characteristics crucially distinguished the suicidal ideation group from controls, some key predictors, including the age of depression onset and childhood trauma events, were identified for suicide attempts. Conclusions: We established applicable machine learning-based models for predicting suicidal behavior, particularly suicide attempts, in individuals with depression, and clarified the differences in predictors between suicidal ideation and suicide attempts.

Molecular and genetic basis of plant architecture in soybean.

Plant architecture determines canopy coverage, photosynthetic efficiency, and ultimately productivity in soybean (Glycine max). Optimizing plant architecture is a major goal of breeders to develop high yield soybean varieties. Over the past few decades, the yield per unit area of soybean has not changed significantly; however, rice and wheat breeders have succeeded in achieving high yields by generating semi-dwarf varieties. Semi-dwarf crops have the potential to ensure yield stability in high-density planting environments because they can significantly improve responses to fertilizer input, lodging resistance, and enhance resistance to various abiotic and biotic stresses. Soybean has a unique plant architecture, with leaves, inflorescences, and pods growing at each node; internode number greatly affects the final yield. Therefore, producing high-yielding soybean plants with an ideal architecture requires the coordination of effective node formation, effective internode formation, and branching. Dozens of quantitative trait loci (QTLs) controlling plant architecture have been identified in soybean, but only a few genes that control this trait have been cloned and characterized. Here, we review recent progress in understanding the genetic basis of soybean plant architecture. We provide our views and perspectives on how to breed new high-yielding soybean varieties.

Association of psychosocial state with subsequent risk of dementia: a prospective cohort study based on the UK Biobank.

BACKGROUND: Multiple psychosocial factors have been associated with dementia, while the individual or joint effects of various psychosocial states on dementia remain unrevealed due to the complex interplay between those factors. Here, the authors examined the associations of psychosocial factors and patterns with subsequent risk of dementia, and if the associations could be modified by genetic susceptibility to dementia. METHODS: UK Biobank dementia-free participants were followed from one year after recruitment (median date: 24 January, 2010) until 31 October, 2022. Psychosocial states were measured by 22 items related to five dimensions, including psychiatric history, recent stressful life events, current psychiatric symptoms, social contact, and individual socioeconomic state. We identified clusters of individuals with distinct psychosocial patterns using latent class analysis. Cox proportional hazards models were used to evaluate the association between psychosocial items, as well as psychosocial patterns, and risk of dementia. We further performed stratification analyses by apolipoprotein E (APOE) genotype, polygenic risk score (PRS) of dementia, and family history of dementia. RESULTS: Of 497,787 included participants, 54.54% were female. During a median follow-up of 12.70 years, we identified 9,858 (1.98%) patients with newly diagnosed dementia. We identified seven clusters with distinct psychosocial patterns. Compared to individuals with a pattern of 'good state', individuals with other unfavorable patterns, featured by varying degrees of poor psychological state ('fair state' and 'mildly, moderately, and extremely poor psychological state'), low social contact or socioeconomic state ('living alone' and 'short education years'), were all at an increased risk of dementia (hazard ratios [HR] between 1.29 and 2.63). The observed associations showed no significant differences across individuals with varying APOE genotypes, levels of PRS, and family histories of dementia. CONCLUSION: Unfavorable psychosocial patterns are associated with an increased risk of dementia, independent of genetic susceptibility. The findings highlight the importance of surveillance and prevention of cognitive decline among individuals with suboptimal psychosocial state.

The association of psychological and trauma-related factors with biological and facial aging acceleration: evidence from the UK Biobank.

BACKGROUND: Psychological and trauma-related factors are associated with many diseases and mortality. However, a comprehensive assessment of the association between psycho-trauma exposures and aging acceleration is currently lacking. METHODS: Using data from 332,359 UK Biobank participants, we calculated biological aging acceleration, indexed by the presence of leukocyte telomere length (LTL) deviation (i.e., the difference between genetically determined and observed LTL > 0). The acceleration of facial aging (i.e., looking older than the chronological age) was assessed using a self-report question. Then, we estimated the associations of each psycho-trauma factor with biological and facial aging acceleration, using logistic regression models adjusted for multiple important covariates. Furthermore, restricted to 99,180 participants with complete psychological and trauma-related data, we identified clusters of individuals with distinct psycho-trauma patterns using the latent class analysis method and assessed their associations with aging acceleration using similar models. RESULTS: We observed most of the studied psycho-trauma factors were associated with biological and facial aging acceleration. Compared to the "Absence of trauma and psychopathology" cluster, the "adverse childhood experiences (ACEs) with psychopathology" cluster showed strong associations with those aging measurements (odds ratio [OR] = 1.13 [1.05 - 1.23] for biological and 1.52 [1.18 - 1.95] for facial aging acceleration), while no such association was observed for the "ACEs without psychopathology" cluster (1.04 [0.99 - 1.09] and 1.02 [0.84 - 1.24]. CONCLUSIONS: Our study demonstrated significant associations of psycho-trauma factors with both biological and facial aging acceleration. The differential aging consequences observed among ACEs exposed individuals with and without psychopathology prompt interventions aimed to improve individuals' psychological resilience to prevent aging acceleration.

Association between inflammatory biomarkers before pregnancy and risk of perinatal depression: A prospective cohort study of 4483 women in Sweden.

AIM: Perinatal depression (PND) is a global health concern, affecting millions of childbearing women. Emerging data suggest that inflammation may play a role in the development of PND. Peripheral blood inflammatory biomarkers before pregnancy are widely tested in clinical practice at minimum cost, yet their potential role in PND risk remains unknown. METHODS: We conducted a prospective cohort study of 4483 birthing women during 2009-2021 within the LifeGene study with linkage to Swedish registers. Peripheral blood inflammatory biomarkers were profiled at baseline. Cases of PND were identified using validated tools or clinical diagnosis from subsequent pregnancies and postpartum periods. Logistic regression models were employed to assess the associations of each inflammatory biomarker (z scored) with PND. RESULTS: We identified 495 (11.0 %) PND cases with an average age of 29.2 years. Pre-pregnancy platelet-to-lymphocyte ratio (PLR) was positively associated [OR, 95 % CI:1.14(1.01,1.27)], while lymphocyte count was inversely associated [OR, 95 % CI: 0.89(0.80,0.98)] with PND. A dose-response relationship was indicated for both PLR and lymphocytes when analyzed in categories based on tertile distribution. These associations appeared more pronounced for postpartum depression than antepartum depression and were independent of psychiatric comorbidities. CONCLUSION: With implications for future mechanistic research, these findings suggest that blood levels of lymphocytes and PLR before pregnancy are associated with subsequent risk of PND in a dose-response manner.

History of childhood maltreatment associated with hospitalization or death due to COVID-19: a cohort study.

BACKGROUND: Childhood maltreatment (CM) has been indicated in adverse health outcomes across the lifespan, including severe infection-related outcomes. Yet, data are scarce on the potential role of CM in severe COVID-19-related outcomes as well as on mechanisms underlying this association. METHODS: We included 151,427 individuals in the UK Biobank who responded to questions on the history of CM in 2016 and 2017 and were alive on January 31, 2020. Binomial logistic regression models were performed to estimate the association between a history of CM and severe COVID-19 outcomes (i.e. hospitalization or death due to COVID-19), as well as COVID-19 diagnosis and vaccination as secondary outcomes. We then explored the potential mediating roles of socio-economic status, lifestyle and pre-pandemic comorbidities, and the effect modification by polygenic risk score for severe COVID-19 outcomes. RESULTS: The mean age of the study population at the start of the pandemic was 67.7 (SD = 7.72) years, and 56.5% were female. We found the number of CM types was associated with the risk of severe COVID-19 outcomes in a graded manner (pfor trend < 0.01). Compared to individuals with no history of CM, individuals exposed to any CM were more likely to be hospitalized or die due to COVID-19 (odds ratio [OR] = 1.54 [95%CI 1.31-1.81]), particularly after physical neglect (2.04 [1.57-2.62]). Largely comparable risk patterns were observed across groups of high vs. low genetic risks for severe COVID-19 outcomes (pfor difference > 0.05). Mediation analysis revealed that 50.9% of the association between CM and severe COVID-19 outcomes was explained by suboptimal socio-economic status, lifestyle, and pre-pandemic diagnosis of psychiatric disorders or other chronic medical conditions. In contrast, any CM exposure was only weakly associated with COVID-19 diagnosis (1.06 [1.01-1.12]) while significantly associated with not being vaccinated for COVID-19 (1.21 [1.13-1.29]). CONCLUSIONS: Our results add to the growing knowledge base indicating the role of childhood maltreatment in negative health outcomes across the lifespan, including severe COVID-19-related outcomes. The identified factors underlying this association represent potential intervention targets for mitigating the harmful effects of childhood maltreatment in COVID-19 and similar future pandemics.

Phase separation of PML/RARα and BRD4 coassembled microspeckles governs transcriptional dysregulation in acute promyelocytic leukemia.

In acute promyelocytic leukemia (APL), the promyelocytic leukemia-retinoic acid receptor alpha (PML/RARα) fusion protein destroys PML nuclear bodies (NBs), leading to the formation of microspeckles. However, our understanding, largely learned from morphological observations, lacks insight into the mechanisms behind PML/RARα-mediated microspeckle formation and its role in APL leukemogenesis. This study presents evidence uncovering liquid-liquid phase separation (LLPS) as a key mechanism in the formation of PML/RARα-mediated microspeckles. This process is facilitated by the intrinsically disordered region containing a large portion of PML and a smaller segment of RARα. We demonstrate the coassembly of bromodomain-containing protein 4 (BRD4) within PML/RARα-mediated condensates, differing from wild-type PML-formed NBs. In the absence of PML/RARα, PML NBs and BRD4 puncta exist as two independent phases, but the presence of PML/RARα disrupts PML NBs and redistributes PML and BRD4 into a distinct phase, forming PML/RARα-assembled microspeckles. Genome-wide profiling reveals a PML/RARα-induced BRD4 redistribution across the genome, with preferential binding to super-enhancers and broad-promoters (SEBPs). Mechanistically, BRD4 is recruited by PML/RARα into nuclear condensates, facilitating BRD4 chromatin binding to exert transcriptional activation essential for APL survival. Perturbing LLPS through chemical inhibition (1, 6-hexanediol) significantly reduces chromatin co-occupancy of PML/RARα and BRD4, attenuating their target gene activation. Finally, a series of experimental validations in primary APL patient samples confirm that PML/RARα forms microspeckles through condensates, recruits BRD4 to coassemble condensates, and co-occupies SEBP regions. Our findings elucidate the biophysical, pathological, and transcriptional dynamics of PML/RARα-assembled microspeckles, underscoring the importance of BRD4 in mediating transcriptional activation that enables PML/RARα to initiate APL.

Inflammatory Biomarkers and Risk of Psychiatric Disorders.

Importance: Individuals with psychiatric disorders have been reported to have elevated levels of inflammatory biomarkers, and prospective evidence is limited regarding the association between inflammatory biomarkers and subsequent psychiatric disorders risk. Objective: To assess the associations between inflammation biomarkers and subsequent psychiatric disorders risk. Design, Setting, and Participants: This was a prospective cohort study including individuals from the Swedish Apolipoprotein Mortality Risk (AMORIS) cohort, with no prior psychiatric diagnoses and having a measurement of at least 1 inflammatory biomarker. Data from the UK Biobank were used for validation. Longitudinal trajectories of studied biomarkers were visualized before diagnosis of psychiatric disorders in the AMORIS cohort via a nested case-control study. In addition, genetic correlation and mendelian randomization (MR) analyses were conducted to determine the genetic overlap and causality of the studied associations using publicly available GWAS summary statistics. Exposures: Inflammatory biomarkers, eg, leukocytes, haptoglobin, immunoglobulin G (IgG), C-reactive protein (CRP), platelets, or albumin. Main Outcomes and Measures: Any psychiatric disorder or specific psychiatric disorder (ie, depression, anxiety, and stress-related disorders) was identified through the International Statistical Classification of Diseases, Eighth, Ninth, and Tenth Revision codes. Results: Among the 585 279 individuals (mean [SD] age, 45.5 [14.9] years; 306 784 male [52.4%]) in the AMORIS cohort, individuals with a higher than median level of leukocytes (hazard ratio [HR], 1.11; 95% CI, 1.09-1.14), haptoglobin (HR, 1.13; 95% CI, 1.12-1.14), or CRP (HR, 1.02; 95% CI, 1.00-1.04) had an elevated associated risk of any psychiatric disorders. In contrast, we found an inverse association for IgG level (HR, 0.92; 95% CI, 0.89-0.94). The estimates were comparable for depression, anxiety, and stress-related disorders, specifically, and these results were largely validated in the UK Biobank (n = 485 620). Analyses of trajectories revealed that individuals with psychiatric disorders had higher levels of leukocytes and haptoglobin and a lower level of IgG than their controls up to 30 years before the diagnosis. The MR analysis suggested a possible causal relationship between leukocytes and depression. Conclusions and Relevance: In this cohort study, inflammatory biomarkers including leukocytes, haptoglobin, CRP, and IgG were associated with a subsequent risk of psychiatric disorders, and thus might be used for high-risk population identification. The possible causal link between leukocytes and depression supports the crucial role of inflammation in the development of psychiatric disorders.

Clonal hematopoiesis of indeterminate potential and risk of neurodegenerative diseases.

BACKGROUND: Little is known regarding the association between clonal hematopoiesis of indeterminate potential (CHIP) and risk of neurodegenerative diseases. OBJECTIVE: To estimate the risk of neurodegenerative diseases among individuals with CHIP. METHODS: We conducted a community-based cohort study based on UK Biobank and used Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the risk of any neurodegenerative disease, subtypes of neurodegenerative diseases (including primary neurodegenerative diseases, vascular neurodegenerative diseases, and other neurodegenerative diseases), and specific diagnoses of neurodegenerative diseases (i.e., amyotrophic lateral sclerosis [ALS], Alzheimer's disease [AD], and Parkinson's disease [PD]) associated with CHIP. RESULTS: We identified 14,440 individuals with CHIP and 450,907 individuals without CHIP. Individuals with CHIP had an increased risk of any neurodegenerative disease (HR 1.10, 95% CI: 1.01-1.19). We also observed a statistically significantly increased risk for vascular neurodegenerative diseases (HR 1.31, 95% CI 1.05-1.63) and ALS (HR 1.50, 95% CI 1.05-2.15). An increased risk was also noted for other neurodegenerative diseases (HR 1.13, 95% CI 0.97-1.32), although not statistically significant. Null association was noted for primary neurodegenerative diseases (HR 1.06, 95% CI 0.96-1.17), AD (HR 1.04, 95% CI 0.88-1.23), and PD (HR 1.02, 95% CI 0.86-1.21). The risk increase in any neurodegenerative disease was mainly observed for DNMT3A-mutant CHIP, ASXL1-mutant CHIP, or SRSF2-mutant CHIP. CONCLUSION: Individuals with CHIP were at an increased risk of neurodegenerative diseases, primarily vascular neurodegenerative diseases and ALS, but potentially also other neurodegenerative diseases. These findings suggest potential shared mechanisms between CHIP and neurodegenerative diseases.

[Effects of Questionnaire-Based Psychological Survey Methods on the Evaluation Results in a Patient Cohort].

Objective To assess the influences of self-and interviewer-administered methods on the scores of anxiety and depression questionnaires among the patients with sports injuries.Methods A total of 532 participants with sports injuries treated in the Sports Medicine Center of West China Hospital,Sichuan University from November 2022 to May 2023 were included.They were randomly assigned to either the interviewer-administered group (n=270) or the self-administered group (n=262) to complete the generalized anxiety disorder (GAD-7) and the patient health questionnaire (PHQ-9) scales.The total scores and prevalence rates of anxiety and depression were compared between the two groups.Results There was no statistically significant difference in gender,occupation,or surgical site between the two groups (all P>0.05).The self-administered group had higher scores of GAD-7 and PHQ-9 scales than the interviewer-administered group (P<0.001,P<0.001).A greater proportion of participants in the self-administered group than in the interview-administered group met the criteria for mild to moderate anxiety and depression (P<0.001,P=0.002).The prevalence rates of moderate to severe anxiety (GAD-7≥10) and depression (PHQ-9≥10) showed no statistically significant difference between the two groups (P=0.761,P=0.086).Conclusion This study demonstrates that the participants in the self-administered group are more likely to report mild to moderate symptoms of anxiety and depression than those in the interviewer-administered group.

Hospital-Treated Infections and Risk of Disability Worsening in Multiple Sclerosis.

OBJECTIVE: To investigate the association between infections and disability worsening in people with multiple sclerosis (MS) treated with either B-cell depleting therapy (rituximab) or interferon-beta/glatiramer acetate (IFN/GA). METHODS: This cohort study spanned from 2000 to 2021, using data from the Swedish MS Registry linked to national health care registries, comprising 8,759 rituximab and 7,561 IFN/GA treatment episodes. The risk of hospital-treated infection was estimated using multivariable Cox models. The association between infections and increase in Expanded Disability Status Scale (EDSS) scores was assessed using a doubly robust generalized estimating equations model. Additionally, a piece-wise exponential model analyzed events of increased disability beyond defined cut-off values, controlling for relapses, and MRI activity. RESULTS: Compared with IFN/GA, rituximab displayed increased risk of both inpatient- and outpatient-treated infections (hazard ratio [HR], 2.08; 95% confidence interval [CI], 1.50-2.90 and HR, 1.37; 95% CI, 1.13-1.67, respectively). An inpatient-treated infection was associated with a 0.19-unit increase in EDSS (95% CI, 0.12-0.26). Degree of worsening was greatest for progressive MS, and under IFN/GA treatment, which unlike rituximab, was more commonly associated with MRI activity. After controlling for relapses and MRI activity, inpatient-treated infections were associated with disability worsening in people with relapsing-remitting MS treated with IFN/GA (HR, 2.01; 95% CI, 1.59-2.53), but not in those treated with rituximab. INTERPRETATION: Compared to IFN/GA, rituximab doubled the infection risk, but reduced the risk of subsequent disability worsening. Further, the risk of worsening after hospital-treated infection was greater with progressive MS than with relapsing-remitting MS. Infection risk should be considered to improve long term outcomes. ANN NEUROL 2024.

Life changes and symptoms of depression and anxiety among Chinese children and adolescents before, during, and after the COVID-19 pandemic lockdown: a combination of cross-sectional, longitudinal, and clustering studies.

The measures to prevent COVID-19 pandemic had caused significant life changes, which may have caused stress on the mental health of children and adolescents. We aimed to evaluate the short- and long-term effects of life changes on children's mental health in a large Chinese cohort. Survey-based life changes during COVID-19 lockdown were measured among 7,829 Chinese students at Grade 1-9, including social contacts, lifestyles and family financial status. Clustering analysis was applied to identify potential patterns of these changes. Depressive and anxiety symptoms were measured using the Center for Epidemiologic Studies Depression Scale and Screen for Child Anxiety Related Emotional Disorders. Logistic regression models were used to investigate the associations between these changes, their patterns and the presence of depression/anxiety symptoms using both cross-sectional and longitudinal designs. We found that the prevalence of depression and anxiety symptoms decreased during pandemic (34.6-32.6%). However, during and shortly after lockdown, students who reported negative impacts on their study, social and outside activities, and diet had increased risks of depressive/anxiety symptoms. Decreased electronic time and sugar-sweetened consumption, as well as family income decline and unemployment, were also associated with higher risks of these symptoms. Additionally, students with changed sleep time had increased depressive symptoms. These associations attenuated or disappeared one year later. Similar patterns were observed in clustering analysis, while only the group with severe impact on family financial status showed a sustained increase in depression symptoms. In summary, restrictive measures that changed children and adolescents' daily life during COVID-19 lockdown showed negative effects on their mental health, with some commonalities and distinctions patterns in the manifestation of depression and anxiety symptoms.

Data Set and Benchmark (MedGPTEval) to Evaluate Responses From Large Language Models in Medicine: Evaluation Development and Validation.

Background: Large language models (LLMs) have achieved great progress in natural language processing tasks and demonstrated the potential for use in clinical applications. Despite their capabilities, LLMs in the medical domain are prone to generating hallucinations (not fully reliable responses). Hallucinations in LLMs' responses create substantial risks, potentially threatening patients' physical safety. Thus, to perceive and prevent this safety risk, it is essential to evaluate LLMs in the medical domain and build a systematic evaluation. Objective: We developed a comprehensive evaluation system, MedGPTEval, composed of criteria, medical data sets in Chinese, and publicly available benchmarks. Methods: First, a set of evaluation criteria was designed based on a comprehensive literature review. Second, existing candidate criteria were optimized by using a Delphi method with 5 experts in medicine and engineering. Third, 3 clinical experts designed medical data sets to interact with LLMs. Finally, benchmarking experiments were conducted on the data sets. The responses generated by chatbots based on LLMs were recorded for blind evaluations by 5 licensed medical experts. The evaluation criteria that were obtained covered medical professional capabilities, social comprehensive capabilities, contextual capabilities, and computational robustness, with 16 detailed indicators. The medical data sets include 27 medical dialogues and 7 case reports in Chinese. Three chatbots were evaluated: ChatGPT by OpenAI; ERNIE Bot by Baidu, Inc; and Doctor PuJiang (Dr PJ) by Shanghai Artificial Intelligence Laboratory. Results: Dr PJ outperformed ChatGPT and ERNIE Bot in the multiple-turn medical dialogues and case report scenarios. Dr PJ also outperformed ChatGPT in the semantic consistency rate and complete error rate category, indicating better robustness. However, Dr PJ had slightly lower scores in medical professional capabilities compared with ChatGPT in the multiple-turn dialogue scenario. Conclusions: MedGPTEval provides comprehensive criteria to evaluate chatbots by LLMs in the medical domain, open-source data sets, and benchmarks assessing 3 LLMs. Experimental results demonstrate that Dr PJ outperforms ChatGPT and ERNIE Bot in social and professional contexts. Therefore, such an assessment system can be easily adopted by researchers in this community to augment an open-source data set.

The Time-Varying Impact of COVID-19 on the Acute Kidney Disorders: A Historical Matched Cohort Study and Mendelian Randomization Analysis.

Background: This study aimed to explore the time-varying impact of COVID-19 on acute kidney disorders, including acute kidney injury and other acute kidney diseases. Methods: From the UK Biobank, 10,121 participants with COVID-19 were matched with up to 3 historically unexposed controls by age, sex, Townsend deprivation index, and the status of hospitalization or receiving critical care. We investigated the association between COVID-19 and incidence of acute kidney disorders, within the first 4 weeks after infection, using conditional and time-varying Cox proportional hazard regression. In addition, one-sample Mendelian randomization, utilizing the polygenic risk score for COVID-19 as an instrumental variable, was conducted to explore the potential causality of the association. Results: In the matched cohort study, we observed a significant association between COVID-19 and acute kidney disorders predominantly within the first 3 weeks. The impact of COVID-19 was time dependent, peaking in the second week (hazard ratio, 12.77; 95% confidence interval, 5.93 to 27.70) and decreasing by the fourth week (hazard ratio, 2.28; 95% confidence interval, 0.75 to 6.93). In subgroup analyses, only moderate to severe COVID-19 cases were associated with acute worsening of renal function in a time-dependent pattern. One-sample Mendelian randomization analyses further showed that COVID-19 might exert a "short-term" causal effect on the risk of acute kidney disorders, primarily confined to the first week after infection. Conclusions: The risk of acute kidney disorders following COVID-19 demonstrates a time-varying pattern. Hazard effects were observed only in patients with moderate or severe but not mild COVID-19.

Association Between Body Composition Patterns, Cardiovascular Disease, and Risk of Neurodegenerative Disease in the UK Biobank.

BACKGROUND AND OBJECTIVES: Accumulating evidence connects diverse components of body composition (e.g., fat, muscle, and bone) to neurodegenerative disease risk, yet their interplay remains underexplored. This study examines the associations between patterns of body composition and the risk of neurodegenerative diseases, exploring the mediating role of cardiovascular diseases (CVDs). METHODS: This retrospective analysis used data from the UK Biobank, a prospective community-based cohort study. We included participants free of neurodegenerative diseases and with requisite body composition measurements at recruitment, who were followed from 5 years after recruitment until April 1, 2023, to identify incident neurodegenerative diseases. We assessed the associations between different components and major patterns of body composition (identified by principal component analysis) with the risk of neurodegenerative diseases, using multivariable Cox models. Analyses were stratified by disease susceptibility, indexed by polygenetic risk scores for Alzheimer and Parkinson diseases, APOE genotype, and family history of neurodegenerative diseases. Furthermore, we performed mediation analysis to estimate the contribution of CVDs to these associations. In addition, in a subcohort of 40,790 participants, we examined the relationship between body composition patterns and brain aging biomarkers (i.e., brain atrophy and cerebral small vessel disease). RESULTS: Among 412,691 participants (mean age 56.0 years, 55.1% female), 8,224 new cases of neurodegenerative diseases were identified over an average follow-up of 9.1 years. Patterns identified as "fat-to-lean mass," "muscle strength," "bone density," and "leg-dominant fat distribution" were associated with a lower rate of neurodegenerative diseases (hazard ratio [HR] = 0.74-0.94) while "central obesity" and "arm-dominant fat distribution" patterns were associated with a higher rate (HR = 1.13-1.18). Stratification analysis yielded comparable risk estimates across different susceptibility groups. Notably, 10.7%-35.3% of the observed associations were mediated by CVDs, particularly cerebrovascular diseases. The subcohort analysis of brain aging biomarkers corroborated the findings for "central obesity," "muscle strength," and "arm-dominant fat distribution" patterns. DISCUSSION: Our analyses demonstrated robust associations of body composition patterns featured by "central obesity," "muscle strength," and "arm-dominant fat distribution" with both neurodegenerative diseases and brain aging, which were partially mediated by CVDs. These findings underscore the potential of improving body composition and early CVD management in mitigating risk of neurodegenerative diseases.

Cardiovascular Disease, Genetic Susceptibility, and Risk of Psychiatric Disorders and Suicide Attempt: A Community-Based Matched Cohort Study Based on the UK Biobank.

BACKGROUND: The associations between cardiovascular disease (CVD) and multiple psychiatric disorders and suicide attempt, and whether different genetic susceptibilities affect such links, have not been investigated clearly. METHODS AND RESULTS: Based on the UK Biobank, we conducted a matched cohort study involving 63 923 patients who were first hospitalized with a CVD diagnosis between 1997 and 2020, and their 127 845 matched unexposed individuals. Cox models were used to examine the subsequent risk of psychiatric disorders and suicide attempt (ie, anxiety, depression, stress-related disorder, substance misuse, psychotic disorder, and suicide behaviors) following CVD. We further performed stratified analyses by polygenic risk score for each studied psychiatric condition to detect the possible effects of genetic susceptibility on the observed associations. We found an increased risk of any psychiatric disorders and suicide attempt among CVD patients, compared with matched unexposed individuals, particularly within 1 year following the CVD (fully adjusted hazard ratio [HR] within 1 year, 1.83 [95% CI, 1.58-2.12]; HR after 1 year, 1.24 [95% CI, 1.16-1.32]). By subtype, the risk elevations existed for any psychiatric disorders and suicide attempt following most categories of CVDs. Analyses stratified by polygenic risk score revealed little impact of genetic predisposition to studied psychiatric conditions on these observed links. CONCLUSIONS: Patients hospitalized for CVD were at increased subsequent risk of multiple types of psychiatric disorders and suicide attempt, especially in the first year after hospitalization, irrespective of their genetic susceptibilities to studied psychiatric conditions, and these findings underscore the necessity of developing timely psychological interventions for this vulnerable population.

Isoliquiritigenin alleviates experimental autoimmune encephalomyelitis by modulating inflammatory and neuroprotective reactive astrocytes.

Multiple sclerosis (MS) is an autoimmune-mediated chronic inflammatory demyelinating disease of the central nervous system (CNS) that poses significant treatment challenges. Currently, it is believed that inflammatory and neuroprotective reactive astrocytes, along with other resident CNS cells and immune cells, contribute to the pathophysiology of MS. In our study, we found that isoliquiritigenin (ILG), a bioactive chalcone compound, significantly reduces the clinical scores of experimental autoimmune encephalomyelitis (EAE) by 44 % (P < 0.05). Additionally, ILG significantly decreases the pathological scores of spinal cord inflammation and demyelination by 61 % and 65 %, respectively (both P < 0.0001). Furthermore, ILG affects the populations of CD4, Th1, Th17, and Treg cells in vivo. More importantly, ILG significantly promotes the activation of astrocytes in EAE (P < 0.0001). Additionally, ILG treatment indirectly inhibits inflammatory reactive astrocytes and promotes neuroprotective reactive astrocytes. It reduces spleen levels of TNFα, IL1α, C1qa, IL1ß, and IL17A by 95 % (P < 0.001), 98 % (P < 0.01), 46 % (P < 0.05), 97 % (P < 0.001), and 60 % (P < 0.001), respectively. It also decreases CNS levels of TNFα, IL1α, C1qa, IL1ß, and IL17A by 53 % (P < 0.05), 88 % (P < 0.05), 64 % (P < 0.01), 57 % (P < 0.05), and 60 % (P < 0.001), respectively. These results indicate that ILG exerts an immunoregulatory effect by inhibiting the secretion of pro-inflammatory cytokines. Consequently, ILG inhibits inflammatory reactive astrocytes, promotes neuroprotective reactive astrocytes, alleviates inflammation and improves EAE. These findings provide a theoretical basis and support for the application of ILG in the prevention and treatment of MS.

Lactylated Apolipoprotein C-II Induces Immunotherapy Resistance by Promoting Extracellular Lipolysis.

Mortality rates due to lung cancer are high worldwide. Although PD-1 and PD-L1 immune checkpoint inhibitors boost the survival of patients with non-small-cell lung cancer (NSCLC), resistance often arises. The Warburg Effect, which causes lactate build-up and potential lysine-lactylation (Kla), links immune dysfunction to tumor metabolism. The role of non-histone Kla in tumor immune microenvironment and immunotherapy remains to be clarified. Here, global lactylome profiling and metabolomic analyses of samples from patients with NSCLC is conducted. By combining multi-omics analysis with in vitro and in vivo validation, that intracellular lactate promotes extracellular lipolysis through lactyl-APOC2 is revealed. Mechanistically, lactate enhances APOC2 lactylation at K70, stabilizing it and resulting in FFA release, regulatory T cell accumulation, immunotherapy resistance, and metastasis. Moreover, the anti-APOC2K70-lac antibody that sensitized anti-PD-1 therapy in vivo is developed. This findings highlight the potential of anti lactyl-APOC2-K70 approach as a new combination therapy for sensitizing immunotherapeutic responses.