Exome sequencing identifies novel genetic variants associated with varicose veins.

BACKGROUND: Varicose veins (VV) are one of the common human diseases, but the role of genetics in its development is not fully understood. METHODS: We conducted an exome-wide association study of VV using whole-exome sequencing data from the UK Biobank, and focused on common and rare variants using single-variant association analysis and gene-level collapsing analysis. FINDINGS: A total of 13,823,269 autosomal genetic variants were obtained after quality control. We identified 36 VV-related independent common variants mapping to 34 genes by single-variant analysis and three rare variant genes (PIEZO1, ECE1, FBLN7) by collapsing analysis, and most associations between genes and VV were replicated in FinnGen. PIEZO1 was the closest gene associated with VV (P = 5.05 × 10-31), and it was found to reach exome-wide significance in both single-variant and collapsing analyses. Two novel rare variant genes (ECE1 and METTL21A) associated with VV were identified, of which METTL21A was associated only with females. The pleiotropic effects of VV-related genes suggested that body size, inflammation, and pulmonary function are strongly associated with the development of VV. CONCLUSIONS: Our findings highlight the importance of causal genes for VV and provide new directions for treatment.

Shift work effects on incident neuropsychiatric disorders and shift work tolerance.

BACKGROUND: Shift work is associated with susceptibility to several neuropsychiatric disorders. This study aims to investigate the effect of shift work on the incidence of neuropsychiatric disorders, and highlighting how individual variability may influence the association. METHODS: UK Biobank participants with employment information were included. Cox survival was conducted in main and subgroup analyses. Correlation analyses explored the impact of shift work on brain structures, and mediation analyses were performed to elucidate the shared underlying mechanisms. Shift work tolerance was evaluated through survival analyses contrasting the risks associated with five neuropsychiatric disorders in shift versus non-shift workers across different demographic or occupational strata. RESULTS: The analysis encompassed 254,646 participants. Shift work was associated with higher risk of dementia (HR 1.29, 95 % CI 1.10-1.52), anxiety (1.08, 1.01-1.15), depression (1.29, 1.22-1.36), and sleep disorders (1.18, 1.09-1.28), but not stroke (p = 0.20). Shift work was correlated with decreasing volume of various brain regions, particularly in thalamus, lateral orbitofrontal, and middle temporal. Mediation analysis revealed that increased immune response and glucose levels are common pathways linking shift work to these disorders. We observed diversity in shift work tolerance across different individual characteristics, among which socioeconomic status and length of working hours were the most essential. LIMITATIONS: Self-reported employment information may cause misclassification and recall bias. And since we focused on the middle-aged population, the conclusions may not be representative of younger or older populations. CONCLUSIONS: Our findings indicated the need to monitor shift worker health and provide personalized management to help adapt to shift work.

Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease.

Recent expansion of proteomic coverage opens unparalleled avenues to unveil new biomarkers of Alzheimer's disease (AD). Among 6,361 cerebrospinal fluid (CSF) proteins analysed from the ADNI database, YWHAG performed best in diagnosing both biologically (AUC = 0.969) and clinically (AUC = 0.857) defined AD. Four- (YWHAG, SMOC1, PIGR and TMOD2) and five- (ACHE, YWHAG, PCSK1, MMP10 and IRF1) protein panels greatly improved the accuracy to 0.987 and 0.975, respectively. Their superior performance was validated in an independent external cohort and in discriminating autopsy-confirmed AD versus non-AD, rivalling even canonical CSF ATN biomarkers. Moreover, they effectively predicted the clinical progression to AD dementia and were strongly associated with AD core biomarkers and cognitive decline. Synaptic, neurogenic and infectious pathways were enriched in distinct AD stages. Mendelian randomization did not support the significant genetic link between CSF proteins and AD. Our findings revealed promising high-performance biomarkers for AD diagnosis and prediction, with implications for clinical trials targeting different pathomechanisms.

Whole exome sequencing analyses reveal novel genes in telomere length and their biomedical implications.

Telomere length is a putative biomarker of aging and is associated with multiple age-related diseases. There are limited data on the landscape of rare genetic variations in telomere length. Here, we systematically characterize the rare variant associations with leukocyte telomere length (LTL) through exome-wide association study (ExWAS) among 390,231 individuals in the UK Biobank. We identified 18 robust rare-variant genes for LTL, most of which estimated effects on LTL were significant (> 0.2 standard deviation per allele). The biological functions of the rare-variant genes were associated with telomere maintenance and capping and several genes were specifically expressed in the testis. Three novel genes (ASXL1, CFAP58, and TET2) associated with LTL were identified. Phenotypic association analyses indicated significant associations of ASXL1 and TET2 with cancers, age-related diseases, blood assays, and cardiovascular traits. Survival analyses suggested that carriers of ASXL1 or TET2 variants were at increased risk for cancers; diseases of the circulatory, respiratory, and genitourinary systems; and all-cause and cause-specific deaths. The CFAP58 carriers were at elevated risk of deaths due to cancers. Collectively, the present whole exome sequencing study provides novel insights into the genetic landscape of LTL, identifying novel genes associated with LTL and their implications on human health and facilitating a better understanding of aging, thus pinpointing the genetic relevance of LTL with clonal hematopoiesis, biomedical traits, and health-related outcomes.

Identifying modifiable factors and their joint effect on brain health: an exposome-wide association study.

Considerable uncertainty remains regarding the associations of multiple factors with brain health. We aimed to conduct an exposome-wide association study on neurodegenerative disease and neuropsychiatry disorders using data of participants from the UK Biobank. Multivariable Cox regression models with the least absolute shrinkage and selection operator technique as well as principal component analyses were used to evaluate the exposures in relation to common disorders of central nervous system (CNS). Restricted cubic splines were conducted to explore potential nonlinear correlations. Then, weighted standardized scores were generated based on the coefficients to calculate the joint effects of risk factors. We also estimated the potential impact of eliminating the unfavorable profiles of risk domains on CNS disorders using population attributable fraction (PAF). Finally, sensitivity analyses were performed to reduce the risk of reverse causality. The current study discovered the significantly associated exposures fell into six primary exposome categories. The joint effects of identified risk factors demonstrated higher risks for common disorders of CNS (HR = 1.278 ~ 3.743, p < 2e-16). The PAF varied by exposome categories, with lifestyle and medical history contributing to majority of disease cases. In total, we estimated that up to 3.7 ~ 64.1% of disease cases could be prevented.This study yielded modifiable variables of different categories and assessed their joint effects on common disorders of CNS. Targeting the identified exposures might help formulate effective strategies for maintaining brain health.

Physical frailty, genetic predisposition, and incident dementia: a large prospective cohort study.

Physical frailty and genetic factors are both risk factors for increased dementia; nevertheless, the joint effect remains unclear. This study aimed to investigated the long-term relationship between physical frailty, genetic risk, and dementia incidence. A total of 274,194 participants from the UK Biobank were included. We applied Cox proportional hazards regression models to estimate the association between physical frailty and genetic and dementia risks. Among the participants (146,574 females [53.45%]; mean age, 57.24 years), 3,353 (1.22%) new-onset dementia events were recorded. Compared to non-frailty, the hazard ratio (HR) for dementia incidence in prefrailty and frailty was 1.396 (95% confidence interval [CI], 1.294-1.506, P < 0.001) and 2.304 (95% CI, 2.030-2.616, P < 0.001), respectively. Compared to non-frailty and low polygenic risk score (PRS), the HR for dementia risk was 3.908 (95% CI, 3.051-5.006, P < 0.001) for frailty and high PRS. Furthermore, among the participants, slow walking speed (HR, 1.817; 95% CI, 1.640-2.014, P < 0.001), low physical activity (HR, 1.719; 95% CI, 1.545-1.912, P < 0.001), exhaustion (HR, 1.670; 95% CI, 1.502-1.856, P < 0.001), low grip strength (HR, 1.606; 95% CI, 1.479-1.744, P < 0.001), and weight loss (HR, 1.464; 95% CI, 1.328-1.615, P < 0.001) were independently associated with dementia risk compared to non-frailty. Particularly, precise modulation for different dementia genetic risk populations can also be identified due to differences in dementia risk resulting from the constitutive pattern of frailty in different genetic risk populations. In conclusion, both physical frailty and high genetic risk are significantly associated with higher dementia risk. Early intervention to modify frailty is beneficial for achieving primary and precise prevention of dementia, especially in those at high genetic risk.

Large-scale whole-exome sequencing of neuropsychiatric diseases and traits in 350,770 adults.

While numerous genomic loci have been identified for neuropsychiatric conditions, the contribution of protein-coding variants has yet to be determined. Here we conducted a large-scale whole-exome-sequencing study to interrogate the impact of protein-coding variants on 46 neuropsychiatric diseases and 23 traits in 350,770 adults from the UK Biobank. Twenty new genes were associated with neuropsychiatric diseases through coding variants, among which 16 genes had impacts on the longitudinal risks of diseases. Thirty new genes were associated with neuropsychiatric traits, with SYNGAP1 showing pleiotropic effects across cognitive function domains. Pairwise estimation of genetic correlations at the coding-variant level highlighted shared genetic associations among pairs of neurodegenerative diseases and mental disorders. Lastly, a comprehensive multi-omics analysis suggested that alterations in brain structures, blood proteins and inflammation potentially contribute to the gene-phenotype linkages. Overall, our findings characterized a compendium of protein-coding variants for future research on the biology and therapeutics of neuropsychiatric phenotypes.

Clinical trajectories preceding incident dementia up to 15 years before diagnosis: a large prospective cohort study.

BACKGROUND: Dementia has a long prodromal stage with various pathophysiological manifestations; however, the progression of pre-diagnostic changes remains unclear. We aimed to determine the evolutional trajectories of multiple-domain clinical assessments and health conditions up to 15 years before the diagnosis of dementia. METHODS: Data was extracted from the UK-Biobank, a longitudinal cohort that recruited over 500,000 participants from March 2006 to October 2010. Each demented subject was matched with 10 healthy controls. We performed logistic regressions on 400 predictors covering a comprehensive range of clinical assessments or health conditions. Their evolutional trajectories were quantified using adjusted odds ratios (ORs) and FDR-corrected p-values under consecutive timeframes preceding the diagnosis of dementia. FINDINGS: During a median follow-up of 13.7 [Interquartile range, IQR 12.9-14.2] years until July 2022, 7620 subjects were diagnosed with dementia. In general, upon approaching the diagnosis, demented subjects witnessed worse functional assessments and a higher prevalence of health conditions. Associations up to 15 years preceding the diagnosis comprised declined physical strength (hand grip strength, OR 0.65 [0.63-0.67]), lung dysfunction (peak expiratory flow, OR 0.78 [0.76-0.81]) and kidney dysfunction (cystatin C, OR 1.13 [1.11-1.16]), comorbidities of coronary heart disease (OR 1.78 [1.67-1.91]), stroke (OR 2.34 [2.1-1.37]), diabetes (OR 2.03 [1.89-2.18]) and a series of mental disorders. Cognitive functions in multiple tests also demonstrate decline over a decade before the diagnosis. Inadequate activity (3-5 year, overall time of activity, OR 0.82 [0.73-0.92]), drowsiness (3-5 year, sleep duration, OR 1.13 [1.04-1.24]) and weight loss (0-5 year, weight, OR 0.9 [0.83-0.98]) only exhibited associations within five years before the diagnosis. In addition, serum biomarkers of enriched endocrine, dysregulations of ketones, deficiency of brand-chain amino acids and polyunsaturated fatty acids were found in a similar prodromal time window and can be witnessed as the last pre-symptomatic conditions before the diagnosis. INTERPRETATION: Our findings present a comprehensive temporal-diagnostic landscape preceding incident dementia, which could improve selection for preventive and early disease-modifying treatment trials.

Glymphatic system dysfunction predicts amyloid deposition, neurodegeneration, and clinical progression in Alzheimer's disease.

INTRODUCTION: Although glymphatic function is involved in Alzheimer's disease (AD), its potential for predicting the pathological and clinical progression of AD and its sequential association with core AD biomarkers is poorly understood. METHODS: Whole-brain glymphatic activity was measured by diffusion tensor image analysis along the perivascular space (DTI-ALPS) in participants with AD dementia (n = 47), mild cognitive impairment (MCI; n = 137), and normal controls (n = 235) from the Alzheimer's Disease Neuroimaging Initiative. RESULTS: ALPS index was significantly lower in AD dementia than in MCI or controls. Lower ALPS index was significantly associated with faster changes in amyloid positron emission tomography (PET) burden and AD signature region of interest volume, higher risk of amyloid-positive transition and clinical progression, and faster rates of amyloid- and neurodegeneration-related cognitive decline. Furthermore, the associations of the ALPS index with cognitive decline were fully mediated by amyloid PET and brain atrophy. DISCUSSION: Glymphatic failure may precede amyloid pathology, and predicts amyloid deposition, neurodegeneration, and clinical progression in AD. HIGHLIGHTS: The analysis along the perivascular space (ALPS) index is reduced in patients with Alzheimer's disease (AD) dementia, prodromal AD, and preclinical AD. Lower ALPS index predicted accelerated amyloid beta (Aß) positron emission tomography (PET) burden and Aß-positive transition. The decrease in the ALPS index occurs before cerebrospinal fluid Aß42 reaches the positive threshold. ALPS index predicted brain atrophy, clinical progression, and cognitive decline. Aß PET and brain atrophy mediated the link of ALPS index with cognitive decline.

Plasma proteomic profiles predict future dementia in healthy adults.

The advent of proteomics offers an unprecedented opportunity to predict dementia onset. We examined this in data from 52,645 adults without dementia in the UK Biobank, with 1,417 incident cases and a follow-up time of 14.1 years. Of 1,463 plasma proteins, GFAP, NEFL, GDF15 and LTBP2 consistently associated most with incident all-cause dementia (ACD), Alzheimer's disease (AD) and vascular dementia (VaD), and ranked high in protein importance ordering. Combining GFAP (or GDF15) with demographics produced desirable predictions for ACD (area under the curve (AUC) = 0.891) and AD (AUC = 0.872) (or VaD (AUC = 0.912)). This was also true when predicting over 10-year ACD, AD and VaD. Individuals with higher GFAP levels were 2.32 times more likely to develop dementia. Notably, GFAP and LTBP2 were highly specific for dementia prediction. GFAP and NEFL began to change at least 10 years before dementia diagnosis. Our findings strongly highlight GFAP as an optimal biomarker for dementia prediction, even more than 10 years before the diagnosis, with implications for screening people at high risk for dementia and for early intervention.

Association of grip strength and walking pace with the risk of incident Parkinson's disease: a prospective cohort study of 422,531 participants.

BACKGROUND: Muscle weakness is a prominent feature of Parkinson's disease, but whether the occurrence of this deficit in healthy adults is associated with subsequent PD diagnosis remains unclear. OBJECTIVE: This study sought to examine the relationship between muscle strength, represented by grip strength and walking pace, and the risk of incident PD. METHODS: A total of 422,531 participants from the UK biobank were included in this study. Longitudinal associations of grip strength and walking pace with the risk of incident PD were investigated by Cox proportional hazard models adjusting for several well-established risk factors. Subgroup and sensitivity analyses were also conducted for further validation. RESULTS: After a median follow-up of 9.23 years, 2,118 (0.5%) individuals developed incident PD. For per 5 kg increment of absolute grip strength, there was a significant 10.2% reduction in the risk of incident PD (HR = 0.898, 95% CI [0.872-0.924], P < 0.001). Similarly, per 0.05 kg/kg increment of relative grip strength was related to a 9.2% reduced risk of incident PD (HR = 0.908, 95% CI [0.887-0.929], P < 0.001). Notably, the associations remained consistent when grip strength was calculated as quintiles. Moreover, participants with a slower walking pace demonstrated an elevated risk of incident PD (HR = 1.231, 95%CI [1.075-1.409], P = 0.003). Subgroup and sensitivity analyses further validated the robustness of the observed associations. CONCLUSION: Our findings showed a negative association of grip strength and walking pace with the risk of incident PD independent of important confounding factors. These results hold potential implications for the early screening of people at high-risk of PD.

The genetic architecture of the human hypothalamus and its involvement in neuropsychiatric behaviours and disorders.

Despite its crucial role in the regulation of vital metabolic and neurological functions, the genetic architecture of the hypothalamus remains unknown. Here we conducted multivariate genome-wide association studies (GWAS) using hypothalamic imaging data from 32,956 individuals to uncover the genetic underpinnings of the hypothalamus and its involvement in neuropsychiatric traits. There were 23 significant loci associated with the whole hypothalamus and its subunits, with functional enrichment for genes involved in intracellular trafficking systems and metabolic processes of steroid-related compounds. The hypothalamus exhibited substantial genetic associations with limbic system structures and neuropsychiatric traits including chronotype, risky behaviour, cognition, satiety and sympathetic-parasympathetic activity. The strongest signal in the primary GWAS, the ADAMTS8 locus, was replicated in three independent datasets (N = 1,685-4,321) and was strengthened after meta-analysis. Exome-wide association analyses added evidence to the association for ADAMTS8, and Mendelian randomization showed lower ADAMTS8 expression with larger hypothalamic volumes. The current study advances our understanding of complex structure-function relationships of the hypothalamus and provides insights into the molecular mechanisms that underlie hypothalamic formation.

Exome sequencing identifies genes associated with sleep-related traits.

Sleep is vital for human health and has a moderate heritability. Previous genome-wide association studies have limitations in capturing the role of rare genetic variants in sleep-related traits. Here we conducted a large-scale exome-wide association study of eight sleep-related traits (sleep duration, insomnia symptoms, chronotype, daytime sleepiness, daytime napping, ease of getting up in the morning, snoring and sleep apnoea) among 450,000 participants from UK Biobank. We identified 22 new genes associated with chronotype (ADGRL4, COL6A3, CLK4 and KRTAP3-3), daytime sleepiness (ST3GAL1 and ANKRD12), daytime napping (PLEKHM1, ANKRD12 and ZBTB21), snoring (WDR59) and sleep apnoea (13 genes). Notably, 20 of these genes were confirmed to be significantly associated with sleep disorders in the FinnGen cohort. Enrichment analysis revealed that these discovered genes were enriched in circadian rhythm and central nervous system neurons. Phenotypic association analysis showed that ANKRD12 was associated with cognition and inflammatory traits. Our results demonstrate the value of large-scale whole-exome analysis in understanding the genetic architecture of sleep-related traits and potential biological mechanisms.

Genetic susceptibility modifies the association of long-term air pollution exposure on Parkinson's disease.

Inconsistent findings exist regarding the potential association between polluted air and Parkinson's disease (PD), with unclear insights into the role of inherited sensitivity. This study sought to explore the potential link between various air pollutants and PD risk, investigating whether genetic susceptibility modulates these associations. The population-based study involved 312,009 initially PD-free participants with complete genotyping data. Annual mean concentrations of PM2.5, PM10, NO2, and NOx were estimated, and a polygenic risk score (PRS) was computed to assess individual genetic risks for PD. Cox proportional risk models were employed to calculate hazard ratios (HR) and 95% confidence intervals (CI) for the associations between ambient air pollutants, genetic risk, and incident PD. Over a median 12.07-year follow-up, 2356 PD cases (0.76%) were observed. Compared to the lowest quartile of air pollution, the highest quartiles of NO2 and PM10 pollution showed HRs and 95% CIs of 1.247 (1.089-1.427) and 1.201 (1.052-1.373) for PD incidence, respectively. Each 10 µg/m3 increase in NO2 and PM10 yielded elevated HRs and 95% CIs for PD of 1.089 (1.026-1.155) and 1.363 (1.043-1.782), respectively. Individuals with significant genetic and PM10 exposure risks had the highest PD development risk (HR: 2.748, 95% CI: 2.145-3.520). Similarly, those with substantial genetic and NO2 exposure risks were over twice as likely to develop PD compared to minimal-risk counterparts (HR: 2.414, 95% CI: 1.912-3.048). Findings suggest that exposure to air contaminants heightens PD risk, particularly in individuals genetically predisposed to high susceptibility.

Associations between adiposity and white matter hyperintensities: Cross-sectional and longitudinal analyses of 34,653 participants.

OBJECTIVES: White matter hyperintensities (WMH) increase the risk of stroke and cognitive impairment. This study aims to determine the cross-sectional and longitudinal associations between adiposity and WMH. METHODS: Participants were enrolled from the UK Biobank cohort. Associations of concurrent, past, and changes in overall and central adiposity with WMH were investigated by linear and nonlinear regression models. The association of longitudinal adiposity and WMH volume changes was determined by a linear mixed model. Mediation analysis investigated the potential mediating effect of blood pressure. RESULTS: In 34,653 participants with available adiposity measures and imaging data, the concurrent obese group had a 25.3% (ß [95% CI] = 0.253 [0.222-0.284]) higher WMH volume than the ideal weight group. Increment in all adiposity measures was associated with a higher WMH volume. Among them, waist circumference demonstrated the strongest effect (ß [95% CI] = 0.113 [0.101-0.125]). Past adiposity also demonstrated similar effects. Among the subset of 2664 participants with available WMH follow-up data, adiposity measures were predictive of WMH change. Regarding changes of adiposity, compared with ideal weight stable group, those who turned from ideal weight to overweight/obese had a 8.1% higher WMH volume (ß [95% CI] = 0.081 [0.039-0.123]), while participants who turned from overweight/obese to ideal weight demonstrated no significant WMH volume change. Blood pressure partly meditates the associations between adiposity and WMH. CONCLUSIONS: Both concurrent and past adiposity were associated with a higher WMH volume. The detrimental effects of adiposity on WMH occurred throughout midlife and in the elderly and may still exist after changes in obesity status.

Associations between antipsychotics exposure and dementia risk: A prospective cohort study of 415,100 participants.

BACKGROUND: Antipsychotics (APs) are among the most widely prescribed medications, and have been shown to cause cognitive decline. But previous studies on their effects on dementia risk are controversial and scarce. We aimed to examine the relationships of APs exposure with the risk of dementia. METHODS: Data were obtained from a prospective cohort of 415,100 UK Biobank (UKB) participants. We investigated the effects of APs exposure and their various classes on dementia risk by using multivariable Cox proportional hazard models and further the dose-response effects of oral APs. RESULTS: After a mean follow-up of 8.64 years, 5235 (1.3 %) participants developed all-cause dementia (ACD), among whom 2313 (0.6 %) developed Alzheimer's disease (AD), and 1213 (0.3 %) developed vascular dementia (VaD). Exposure to any APs conferred increased risks of ACD (HR: 1.33, 95 % CI = 1.17-1.51, P < 0.001) and VaD (HR: 1.90, 95 % CI = 1.51-2.40, P < 0.001), but not AD (HR: 1.22, 95 % CI = 1.00-1.48, P = 0.051). Cumulative dose-response relationships of oral APs with the risks of ACD and VaD were observed (P for trend, P < 0.05). LIMITATIONS: Our study is observational and does not show evidence of causality. Since there are relatively few cases of dementia in the UKB, APs exposure may be higher than estimated in our study. CONCLUSIONS: APs exposure increased the risk of developing dementia. Dose-response relationships were found between oral APs and dementia risk. Efforts to raise awareness of doctors and patients about this potential drug-related risk are critical to reducing APs use.

Plasma metabolic profiles predict future dementia and dementia subtypes: a prospective analysis of 274,160 participants.

BACKGROUND: Blood-based biomarkers for dementia are gaining attention due to their non-invasive nature and feasibility in regular healthcare settings. Here, we explored the associations between 249 metabolites with all-cause dementia (ACD), Alzheimer's disease (AD), and vascular dementia (VaD) and assessed their predictive potential. METHODS: This study included 274,160 participants from the UK Biobank. Cox proportional hazard models were employed to investigate longitudinal associations between metabolites and dementia. The importance of these metabolites was quantified using machine learning algorithms, and a metabolic risk score (MetRS) was subsequently developed for each dementia type. We further investigated how MetRS stratified the risk of dementia onset and assessed its predictive performance, both alone and in combination with demographic and cognitive predictors. RESULTS: During a median follow-up of 14.01 years, 5274 participants developed dementia. Of the 249 metabolites examined, 143 were significantly associated with incident ACD, 130 with AD, and 140 with VaD. Among metabolites significantly associated with dementia, lipoprotein lipid concentrations, linoleic acid, sphingomyelin, glucose, and branched-chain amino acids ranked top in importance. Individuals within the top tertile of MetRS faced a significantly greater risk of developing dementia than those in the lowest tertile. When MetRS was combined with demographic and cognitive predictors, the model yielded the area under the receiver operating characteristic curve (AUC) values of 0.857 for ACD, 0.861 for AD, and 0.873 for VaD. CONCLUSIONS: We conducted the largest metabolome investigation of dementia to date, for the first time revealed the metabolite importance ranking, and highlighted the contribution of plasma metabolites for dementia prediction.

Associations of liver dysfunction with incident dementia, cognition, and brain structure: A prospective cohort study of 431 699 adults.

The relationship between liver dysfunction and dementia has been researched extensively but remains poorly understood. In this study, we investigate the longitudinal and cross-sectional associations between liver function and liver diseases and risk of incident dementia, impaired cognition, and brain structure abnormalities using Cox proportion hazard model and linear regression model. 431 699 participants with a mean of 8.65 (standard deviation [SD] 2.61) years of follow-up were included from the UK Biobank; 5542 all-cause dementia (ACD), 2427 Alzheimer's disease (AD), and 1282 vascular dementia (VaD) cases were documented. We observed that per SD decreases in alanine transaminase (ALT; hazard ratio [HR], 0.917; PFDR <0.001) and per SD increases in aspartate aminotransferase (AST; HR, 1.048; PFDR = 0.010), AST to ALT ratio (HR, 1.195; PFDR <0.001), gamma-glutamyl transpeptidase (GGT; HR, 1.066; PFDR <0.001), alcoholic liver disease (ALD; HR, 2.872; PFDR <0.001), and fibrosis and cirrhosis of liver (HR, 2.285; PFDR = 0.002), being significantly associated with a higher risk of incident ACD. Restricted cubic spline models identified a strong U-shaped association between Alb and AST and incident ACD (Pnonlinear <0.05). Worse cognition was positively correlated with AST, AST to ALT ratio, direct bilirubin (DBil), and GGT; negatively correlated with ALT, Alb, and total bilirubin (TBil); and ALD and fibrosis and cirrhosis of liver (PFDR <0.05). Moreover, changes in ALT, GGT, AST to ALT ratio, and ALD were significantly associated with altered cortical and subcortical regions, including hippocampus, amygdala, thalamus, pallidum, and fusiform (PFDR <0.05). In sensitivity analysis, metabolic dysfunction-associated steatotic liver disease (MASLD) was associated with the risk of ACD and brain subcortical changes. Our findings provide substantial evidence that liver dysfunction may be an important factor for incident dementia. Early intervention in the unhealthy liver may help prevent cognitive impairment and dementia incidence.

Socioeconomic status, lifestyle and risk of incident dementia: a prospective cohort study of 276730 participants.

Healthy lifestyle might alleviate the socioeconomic inequities in health, but the extent of the joint and interactive effects of these two factors on dementia are unclear. This study aimed to detect the joint and interactive associations of socioeconomic status (SES) and lifestyle factors with incident dementia risk, and the underlying brain imaging alterations. Cox proportional hazards analysis was performed to test the joint and interactive associations. Partial correlation analysis was performed to reflect the brain imaging alterations. A total of 276,730 participants with a mean age of 55.9 (±8.0) years old from UK biobank were included. Over 8.5 (±2.6) years of follow-up, 3013 participants were diagnosed with dementia. Participants with high SES and most healthy lifestyle had a significantly lower risk of incident dementia (HR=0.19, 95% CI=0.14 to 0.26, P<2×10-16), Alzheimer's disease (AD, HR=0.19, 95% CI=0.13 to 0.29, P=8.94×10-15), and vascular dementia (HR=0.24, 95% CI=0.12 to 0.48, P=7.57×10-05) compared with participants with low SES and an unhealthy lifestyle. Significant interactions were found between SES and lifestyle on dementia (P=0.002) and AD (P=0.001) risks; the association between lifestyle and dementia was stronger among those of high SES. The combination of high SES and healthy lifestyle was positively associated with higher volumes in brain regions vulnerable to dementia-related atrophy. These findings suggest that SES and lifestyle significantly interact and influence dementia with its related brain structure phenotypes.

Genetic architectures of cerebral ventricles and their overlap with neuropsychiatric traits.

The cerebral ventricles are recognized as windows into brain development and disease, yet their genetic architectures, underlying neural mechanisms and utility in maintaining brain health remain elusive. Here we aggregated genetic and neuroimaging data from 61,974 participants (age range, 9 to 98 years) in five cohorts to elucidate the genetic basis of ventricular morphology and examined their overlap with neuropsychiatric traits. Genome-wide association analysis in a discovery sample of 31,880 individuals identified 62 unique loci and 785 candidate genes associated with ventricular morphology. We replicated over 80% of loci in a well-matched cohort of lateral ventricular volume. Gene set analysis revealed enrichment of ventricular-trait-associated genes in biological processes and disease pathogenesis during both early brain development and degeneration. We explored the age-dependent genetic associations in cohorts of different age groups to investigate the possible roles of ventricular-trait-associated loci in neurodevelopmental and neurodegenerative processes. We describe the genetic overlap between ventricular and neuropsychiatric traits through comprehensive integrative approaches under correlative and causal assumptions. We propose the volume of the inferior lateral ventricles as a heritable endophenotype to predict the risk of Alzheimer's disease, which might be a consequence of prodromal Alzheimer's disease. Our study provides an advance in understanding the genetics of the cerebral ventricles and demonstrates the potential utility of ventricular measurements in tracking brain disorders and maintaining brain health across the lifespan.