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.

The causal role of circulating amino acids on neurodegenerative disorders: A two-sample Mendelian randomization study.

Potential associations between the risk of neurodegenerative diseases and circulating levels of amino acids have been implied in both experimental research and observational studies. However, because of the confounding and reverse causality, the findings could be biased. We aimed to determine whether circulating amino acid levels have potential effects on the risk of neurodegenerative diseases through a more robust analysis. So, we performed a total of two MR analyses, a discovery two-sample MR analysis, and a replication test, using summary-level genome-wide association study (GWAS) data, both with circulating levels of amino acids as exposure and risk of neurodegenerative diseases as an outcome. The potential causalities between nine amino acids (Glutamine [Glu], Leucine [Leu], Isoleucine [Ile], Phenylalanine [Phe], Valine [Val], Alanine [Ala], Tyrosine [Tyr], Histidine [His], and Glycine [Gly]) and six neurodegenerative disorders (Alzheimer's disease [AD], Parkinson's disease [PD], Multiple sclerosis [MS], Frontotemporal dementia [FTD], Lewy body dementia [DLB], Amyotrophic lateral sclerosis [ALS]) were explored in this study. According to the discovery MR analysis, 1 SD. increase in circulating levels of Gln was genetically determined to result in a 13% lower risk of AD (IVW ORSD [95% CI] = 0.872 [0.822, 0.926]; FDR = 7.46 × 10-5 ) while PD risk was decreased to 63% per SD. increase of circulating Leu levels (IVW ORSD [95% CI] = 0.628 [0.467, 0.843]; FDR = 0.021). Results from the replication test provide further evidence of the potential association between circulating Gln levels and AD risk (IVW ORSD [95% CI] = 0.094 [0.028, 0.311]; FDR = 9.98 × 10-4 ). Meanwhile, sensitivity analysis demonstrated that the significant relationships revealed by our two-sample MR outcomes were reliable. Our analyses provided robust evidence of causal associations between circulating levels of Gln and AD risk as well as circulating Leu levels and risk of PD. However, the underlying mechanisms remain to be further investigated.

Identifying causal genes for depression via integration of the proteome and transcriptome from brain and blood.

Genome-wide association studies (GWASs) have identified numerous risk genes for depression. Nevertheless, genes crucial for understanding the molecular mechanisms of depression and effective antidepressant drug targets are largely unknown. Addressing this, we aimed to highlight potentially causal genes by systematically integrating the brain and blood protein and expression quantitative trait loci (QTL) data with a depression GWAS dataset via a statistical framework including Mendelian randomization (MR), Bayesian colocalization, and Steiger filtering analysis. In summary, we identified three candidate genes (TMEM106B, RAB27B, and GMPPB) based on brain data and two genes (TMEM106B and NEGR1) based on blood data with consistent robust evidence at both the protein and transcriptional levels. Furthermore, the protein-protein interaction (PPI) network provided new insights into the interaction between brain and blood in depression. Collectively, four genes (TMEM106B, RAB27B, GMPPB, and NEGR1) affect depression by influencing protein and gene expression level, which could guide future researches on candidate genes investigations in animal studies as well as prioritize antidepressant drug targets.

Association of life course adiposity with risk of incident dementia: a prospective cohort study of 322,336 participants.

Cohort studies report inconsistent associations between body mass index (BMI) and all-cause incident dementia. Furthermore, evidence on fat distribution and body composition measures are scarce and few studies estimated the association between early life adiposity and dementia risk. Here, we included 322,336 participants from UK biobank to investigate the longitudinal association between life course adiposity and risk of all-cause incident dementia and to explore the underlying mechanisms driven by metabolites, inflammatory cells and brain structures. Among the 322,336 individuals (mean (SD) age, 62.24 (5.41) years; 53.9% women) in the study, during a median 8.74 years of follow-up, 5083 all-cause incident dementia events occurred. The risk of dementia was 22% higher with plumper childhood body size (p < 0.001). A strong U-shaped association was observed between adult BMI and dementia. More fat and less fat-free mass distribution on arms were associated with a higher risk of dementia. Interestingly, similar U-shaped associations were found between BMI and four metabolites (i.e., 3-hydroxybutrate, acetone, citrate and polyunsaturated fatty acids), four inflammatory cells (i.e., neutrophil, lymphocyte, monocyte and leukocyte) and abnormalities in brain structure that were also related to dementia. The findings that adiposity is associated with metabolites, inflammatory cells and abnormalities in brain structure that were related to dementia risk might provide clues to underlying biological mechanisms. Interventions to prevent dementia should begin early in life and include not only BMI control but fat distribution and body composition.

Sleep, physical activity, sedentary behavior, and risk of incident dementia: a prospective cohort study of 431,924 UK Biobank participants.

Although sleep, physical activity and sedentary behavior have been found to be associated with dementia risk, findings are inconsistent and their joint relationship remains unclear. This study aimed to investigate independent and joint associations of these three modifiable behaviors with dementia risks. A total of 431,924 participants (median follow-up 9.0 years) without dementia from UK Biobank were included. Multiple Cox regressions were used to estimate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). Models fitted with restricted cubic spline were conducted to test for linear and nonlinear shapes of each association. Sleep duration, leisure-time physical activity (LTPA), and screen-based sedentary behavior individually associated with dementia risks in different non-linear patterns. Sleep duration associated with dementia in a U-shape with a nadir at 7 h/day. LTPA revealed a curvilinear relationship with dementia in diminishing tendency, while sedentary behavior revealed a J-shaped relationship. The dementia risk was 17% lower in the high LTPA group (HR[95%CI]: 0.83[0.76-0.91]) and 22% higher in the high sedentary behavior group (1.22[1.10-1.35]) compared to the corresponding low-level group, respectively. A combination of seven-hour/day sleep, moderate-to-high LTPA, and low-to-moderate sedentary behavior showed the lowest dementia risk (0.59[0.50-0.69]) compared to the referent group (longer or shorter sleep/low LTPA/high sedentary behavior). Notably, each behavior was non-linearly associated with brain structures in a pattern similar to its association with dementia, suggesting they may affect dementia risk by affecting brain structures. Our findings highlight the potential to change these three daily behaviors individually and simultaneously to reduce the risk of dementia.

Residential greenness and risk of incident dementia: A prospective study of 375,342 participants.

INTRODUCTION: Incorporation of greenspace may be a novel environmental policy that might result in positive health effects; hence, this study aimed to investigate the association between residential greenness and dementia incidence. The effects of particulate air pollution on mediating dementia were also determined. METHODS: A prospective cohort study involving 375,342 UK biobank participants was conducted, in which Cox regression models were used to determine the association of greenspace exposure with the risks of all-cause dementia (ACD), Alzheimer's disease (AD) and vascular dementia (VD). Sociodemographic variables, lifestyle or dietary characteristics and apolipoprotein E4 status were controlled using two levels of adjusted models. Mediation analyses were performed to determine the mediation effects of PMs. RESULTS: The results indicated that there were 4929 ACD, 2132 AD, and 1184 VD incidents throughout the 8-year study. In the multi-adjusted model, each interquartile increment in greenspace (buffer 300m) conferred the lower risks of ACD (HR = 0.968, 95% confidence intervals [CI]: 0.938-1.000]) and VD (HR = 0.926, 95% CI: 0.867-0.989). The fourth greenspace quartile conferred also reduced risks of ACD (HR = 0.891, 95% CI: 0.804-0.989) and VD (HR = 0.778, 95% CI: 0.630-0.960) in reference to the first quartile. With regard to 1000m catchment, each interquartile increment conferred a 5.0% (95% CI: 1.8-8.1) lower risk of ACD, and the fourth greenspace quartile conferred a 10.9% (95% CI: 0.9-19.8) lower risk of ACD compared to the first quartile. The protective effect of greenness might be mediated based on the reduction of PM2.5 and PM10 (Pindirect effect<0.05). CONCLUSIONS: Increasing greenness reduces the risk of dementia. This study suggests that greenspace is an environmental strategy that helps prevent dementia.

Associations of blood cell indices and anemia with risk of incident dementia: A prospective cohort study of 313,448 participants.

INTRODUCTION: Low hemoglobin and anemia are associated with cognitive impairment and Alzheimer's disease (AD). However, the associations of other blood cell indices with incident dementia risk and the underlined mechanisms are unknown. METHODS: Three hundred thirteen thousand four hundred forty-eight participants from the UK Biobank were included. Cox and restricted cubic spline models were used to investigate linear and non-linear longitudinal associations. Mendelian randomization analysis was used to identify causal associations. Linear regression models were used to explore potential mechanisms driven by brain structures. RESULTS: During a mean follow-up of 9.03 years, 6833 participants developed dementia. Eighteen indices were associated with dementia risk regarding erythrocytes, immature erythrocytes, and leukocytes. Anemia was associated with a 56% higher risk of developing dementia. Hemoglobin and red blood cell distribution width were causally associated with AD. Extensive associations exist between most blood cell indices and brain structures. DISCUSSION: These findings consolidated associations between blood cells and dementia. HIGHLIGHT: Anemia was associated with 56% higher risk for all-cause dementia. Hematocrit percentage, mean corpuscular volume, platelet crit, and mean platelet volume had U-shaped associations with incident dementia risk. Hemoglobin (HGB) and red blood cell distribution width had causal effects on Alzheimer's risk. HGB and anemia were associated with brain structure alterations.

Associations of grip strength, walking pace, and the risk of incident dementia: A prospective cohort study of 340212 participants.

INTRODUCTION: Grip strength and walking pace have been linked to cognitive dysfunction. Their relationships, however, demand further clarification as the evidence is derived primarily from less-comprehensive investigations. METHODS: A total of 340212 UK Biobank participants without dementia and cardiovascular diseases at baseline were analyzed. Cox proportional hazard models assessed the longitudinal associations. RESULTS: Over a mean follow-up of 8.51 ± 2.68 years, 2424 incident dementia cases were documented. A 5 kg increment of absolute grip strength was associated with lower risks of all-cause dementia (hazard ratio [HR] 0.857), Alzheimer's disease (HR 0.874), and vascular dementia (HR 0.788). The patterns of associations remained similar when grip strength was expressed in relative terms and quintiles. A slow walking pace demonstrated consistent associations with increased risks of all dementia types. DISCUSSION: Our findings provide amplified evidence and suggest that muscle fitness, reflected by objective grip strength measures and self-reported walking pace, may be imperative for estimating the risks of dementia.

Circulating metabolites associated with incident myocardial infarction and stroke: A prospective cohort study of 90 438 participants.

The relevance between circulating metabolites and vascular events remains controversial and comprehensive studies are lacking. We sought to investigate the prospective associations of plasma metabolomics with risks of incident stroke, ischemic stroke (IS), hemorrhagic stroke (HS), and myocardial infarction (MI). Within the UK Biobank cohort, 249 circulating metabolites were measured in 90 438 participants without baseline vascular diseases. Cox proportional hazards regressions were applied to estimate adjusted hazard ratios (HRs) for per 1 standard deviation increment in metabolites. The least absolute shrinkage and selection operator algorithm was used for selecting metabolite subsets. During a median of 9.0 years of follow-up, we documented 833 incident stroke and 1256 MI cases. Lipid constituents, comprising cholesterol, cholesteryl esters, free cholesterol, phospholipids, and total lipids, in very low- (VLDL), intermediate- (IDL), and low-density lipoprotein (LDL) particles were positively associated with MI risk (HR = 1.12 to 1.36; 95% CI = 1.06 to 1.44), while in high-density lipoprotein (HDL) particles showed inverse associations (HR = 0.68 to 0.81; 95% CI = 0.63 to 0.87). Similar association pattern with MI was also observed for VLDL, IDL, LDL, and HDL particles themselves. In contrast, triglycerides within all lipoproteins, including most HDL particles, were positively associated with MI risk (HR = 1.14 to 1.28; 95% CI = 1.08 to 1.35) and, to a slightly lesser extent, with stroke and IS. Unsaturation of fatty acids and albumin were inversely associated with risks of stroke, IS, and MI. In contrast, the linear association for HS is absent. When combining multiple metabolites, the metabolite risk score captured a drastically elevated risk of all vascular events, about twice that of any single metabolite. Taken together, circulating metabolites showed remarkably widespread associations with incident MI, but substantially weakened associations with risks of stroke and its subtypes. Exhaustive metabolomics profiling may shed light on vascular risk prediction and, in turn, guide pertinent strategies of intervention and treatment.

Identifying causal genes for stroke via integrating the proteome and transcriptome from brain and blood.

BACKGROUND: Genome-wide association studies (GWAS) have revealed numerous loci associated with stroke. However, the underlying mechanisms at these loci in the pathogenesis of stroke and effective stroke drug targets are elusive. Therefore, we aimed to identify causal genes in the pathogenesis of stroke and its subtypes. METHODS: Utilizing multidimensional high-throughput data generated, we integrated proteome-wide association study (PWAS), transcriptome-wide association study (TWAS), Mendelian randomization (MR), and Bayesian colocalization analysis to prioritize genes that contribute to stroke and its subtypes risk via affecting their expression and protein abundance in brain and blood. RESULTS: Our integrative analysis revealed that ICA1L was associated with small-vessel stroke (SVS), according to robust evidence at both protein and transcriptional levels based on brain-derived data. We also identified NBEAL1 that was causally related to SVS via its cis-regulated brain expression level. In blood, we identified 5 genes (MMP12, SCARF1, ABO, F11, and CKAP2) that had causal relationships with stroke and stroke subtypes. CONCLUSIONS: Together, via using an integrative analysis to deal with multidimensional data, we prioritized causal genes in the pathogenesis of SVS, which offered hints for future biological and therapeutic studies.

Identification of novel drug targets for Alzheimer's disease by integrating genetics and proteomes from brain and blood.

Genome-wide association studies (GWASs) have discovered numerous risk genes for Alzheimer's disease (AD), but how these genes confer AD risk is challenging to decipher. To efficiently transform genetic associations into drug targets for AD, we employed an integrative analytical pipeline using proteomes in the brain and blood by systematically applying proteome-wide association study (PWAS), Mendelian randomization (MR) and Bayesian colocalization. Collectively, we identified the brain protein abundance of 7 genes (ACE, ICA1L, TOM1L2, SNX32, EPHX2, CTSH, and RTFDC1) are causal in AD (P < 0.05/proteins identified for PWAS and MR; PPH4 >80% for Bayesian colocalization). The proteins encoded by these genes were mainly expressed on the surface of glutamatergic neurons and astrocytes. Of them, ACE with its protein abundance was also identified in significant association with AD on the blood-based studies and showed significance at the transcriptomic level. SNX32 was also found to be associated with AD at the blood transcriptomic level. Collectively, our current study results on genetic, proteomic, and transcriptomic approaches has identified compelling genes, which may provide important leads to design future functional studies and potential drug targets for AD.

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.

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.

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.

Whole exome sequencing analysis identifies genes for alcohol consumption.

Alcohol consumption is a heritable behavior seriously endangers human health. However, genetic studies on alcohol consumption primarily focuses on common variants, while insights from rare coding variants are lacking. Here we leverage whole exome sequencing data across 304,119 white British individuals from UK Biobank to identify protein-coding variants associated with alcohol consumption. Twenty-five variants are associated with alcohol consumption through single variant analysis and thirteen genes through gene-based analysis, ten of which have not been reported previously. Notably, the two unreported alcohol consumption-related genes GIGYF1 and ANKRD12 show enrichment in brain function-related pathways including glial cell differentiation and are strongly expressed in the cerebellum. Phenome-wide association analyses reveal that alcohol consumption-related genes are associated with brain white matter integrity and risk of digestive and neuropsychiatric diseases. In summary, this study enhances the comprehension of the genetic architecture of alcohol consumption and implies biological mechanisms underlying alcohol-related adverse outcomes.

Genetic associations of protein-coding variants in venous thromboembolism.

Previous genetic studies of venous thromboembolism (VTE) have been largely limited to common variants, leaving the genetic determinants relatively incomplete. We performed an exome-wide association study of VTE among 14,723 cases and 334,315 controls. Fourteen known and four novel genes (SRSF6, PHPT1, CGN, and MAP3K2) were identified through protein-coding variants, with broad replication in the FinnGen cohort. Most genes we discovered exhibited the potential to predict future VTE events in longitudinal analysis. Notably, we provide evidence for the additive contribution of rare coding variants to known genome-wide polygenic risk in shaping VTE risk. The identified genes were enriched in pathways affecting coagulation and platelet activation, along with liver-specific expression. The pleiotropic effects of these genes indicated the potential involvement of coagulation factors, blood cell traits, liver function, and immunometabolic processes in VTE pathogenesis. In conclusion, our study unveils the valuable contribution of protein-coding variants in VTE etiology and sheds new light on its risk stratification.

Large-scale whole-exome sequencing analyses identified protein-coding variants associated with immune-mediated diseases in 350,770 adults.

The genetic contribution of protein-coding variants to immune-mediated diseases (IMDs) remains underexplored. Through whole exome sequencing of 40 IMDs in 350,770 UK Biobank participants, we identified 162 unique genes in 35 IMDs, among which 124 were novel genes. Several genes, including FLG which is associated with atopic dermatitis and asthma, showed converging evidence from both rare and common variants. 91 genes exerted significant effects on longitudinal outcomes (interquartile range of Hazard Ratio: 1.12-5.89). Mendelian randomization identified five causal genes, of which four were approved drug targets (CDSN, DDR1, LTA, and IL18BP). Proteomic analysis indicated that mutations associated with specific IMDs might also affect protein expression in other IMDs. For example, DXO (celiac disease-related gene) and PSMB9 (alopecia areata-related gene) could modulate CDSN (autoimmune hypothyroidism-, psoriasis-, asthma-, and Graves' disease-related gene) expression. Identified genes predominantly impact immune and biochemical processes, and can be clustered into pathways of immune-related, urate metabolism, and antigen processing. Our findings identified protein-coding variants which are the key to IMDs pathogenesis and provided new insights into tailored innovative therapies.

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.

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.