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.

Contribution of copy number variations to education, socioeconomic status and cognition from a genome-wide study of 305,401 subjects.

Educational attainment (EA), socioeconomic status (SES) and cognition are phenotypically and genetically linked to health outcomes. However, the role of copy number variations (CNVs) in influencing EA/SES/cognition remains unclear. Using a large-scale (n = 305,401) genome-wide CNV-level association analysis, we discovered 33 CNV loci significantly associated with EA/SES/cognition, 20 of which were novel (deletions at 2p22.2, 2p16.2, 2p12, 3p25.3, 4p15.2, 5p15.33, 5q21.1, 8p21.3, 9p21.1, 11p14.3, 13q12.13, 17q21.31, and 20q13.33, as well as duplications at 3q12.2, 3q23, 7p22.3, 8p23.1, 8p23.2, 17q12 (105 kb), and 19q13.32). The genes identified in gene-level tests were enriched in biological pathways such as neurodegeneration, telomere maintenance and axon guidance. Phenome-wide association studies further identified novel associations of EA/SES/cognition-associated CNVs with mental and physical diseases, such as 6q27 duplication with upper respiratory disease and 17q12 (105 kb) duplication with mood disorders. Our findings provide a genome-wide CNV profile for EA/SES/cognition and bridge their connections to health. The expanded candidate CNVs database and the residing genes would be a valuable resource for future studies aimed at uncovering the biological mechanisms underlying cognitive function and related clinical phenotypes.

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.

Whole exome sequencing analyses identified novel genes for Alzheimer's disease and related dementia.

INTRODUCTION: The heritability of Alzheimer's disease (AD) is estimated to be 58%-79%. However, known genes can only partially explain the heritability. METHODS: Here, we conducted gene-based exome-wide association study (ExWAS) of rare variants and single-variant ExWAS of common variants, utilizing data of 54,569 clinically diagnosed/proxy AD and related dementia (ADRD) and 295,421 controls from the UK Biobank. RESULTS: Gene-based ExWAS identified 11 genes predicting a higher ADRD risk, including five novel ones, namely FRMD8, DDX1, DNMT3L, MORC1, and TGM2, along with six previously reported ones, SORL1, GRN, PSEN1, ABCA7, GBA, and ADAM10. Single-variant ExWAS identified two ADRD-associated novel genes, SLCO1C1 and NDNF. The identified genes were predominantly enriched in amyloid-ß process pathways, microglia, and brain regions like hippocampus. The druggability evidence suggests that DDX1, DNMT3L, TGM2, SLCO1C1, and NDNF could be effective drug targets. DISCUSSION: Our study contributes to the current body of evidence on the genetic etiology of ADRD. HIGHLIGHTS: Gene-based analyses of rare variants identified five novel genes for Alzheimer's disease and related dementia (ADRD), including FRMD8, DDX1, DNMT3L, MORC1, and TGM2. Single-variant analyses of common variants identified two novel genes for ADRD, including SLCO1C1 and NDNF. The identified genes were predominantly enriched in amyloid-ß process pathways, microglia, and brain regions like hippocampus. DDX1, DNMT3L, TGM2, SLCO1C1, and NDNF could be effective drug targets.

Genome-wide meta-analysis identifies ancestry-specific loci for Alzheimer's disease.

INTRODUCTION: Alzheimer's disease (AD) is a devastating neurological disease with complex genetic etiology. Yet most known loci have only identified from the late-onset type AD in populations of European ancestry. METHODS: We performed a two-stage genome-wide association study (GWAS) of AD totaling 6878 Chinese and 63,926 European individuals. RESULTS: In addition to the apolipoprotein E (APOE) locus, our GWAS of two independent Chinese samples uncovered three novel AD susceptibility loci (KIAA2013, SLC52A3, and TCN2) and a novel ancestry-specific variant within EGFR (rs1815157). More replicated variants were observed in the Chinese (31%) than in the European samples (15%). In combining genome-wide associations and functional annotations, EGFR and TCN2 were prioritized as two of the most biologically significant genes. Phenome-wide Mendelian randomization suggests that high mean corpuscular hemoglobin concentration might protect against AD. DISCUSSION: The current study reveals novel AD susceptibility loci, emphasizes the importance of diverse populations in AD genetic research, and advances our understanding of disease etiology. HIGHLIGHTS: Loci KIAA2013, SLC52A3, and TCN2 were associated with Alzheimer's disease (AD) in Chinese populations. rs1815157 within the EGFR locus was associated with AD in Chinese populations. The genetic architecture of AD varied between Chinese and European populations. EGFR and TCN2 were prioritized as two of the most biologically significant genes. High mean corpuscular hemoglobin concentrations might have protective effects against AD.

Genome-wide association study of cerebellar white matter microstructure and genetic overlap with common brain disorders.

BACKGROUND: The cerebellum is recognized as being involved in neurocognitive and motor functions with communication with extra-cerebellar regions relying on the white matter integrity of the cerebellar peduncles. However, the genetic determinants of cerebellar white matter integrity remain largely unknown. METHODS: We conducted a genome-wide association analysis of cerebellar white matter microstructure using diffusion tensor imaging data from 25,415 individuals from UK Biobank. The integrity of cerebellar white matter microstructure was measured as fractional anisotropy (FA) and mean diffusivity (MD). Identification of independent genomic loci, functional annotation, and tissue and cell-type analysis were conducted with FUMA. The linkage disequilibrium score regression (LDSC) was used to calculate genetic correlations between cerebellar white matter microstructure and regional brain volumes and brain-related traits. Furthermore, the conditional/conjunctional false discovery rate (condFDR/conjFDR) framework was employed to identify the shared genetic basis between cerebellar white matter microstructure and common brain disorders. RESULTS: We identified 11 genetic loci (P < 8.3 × 10-9) and 86 genes associated with cerebellar white matter microstructure. Further functional enrichment analysis implicated the involvement of GABAergic neurons and cholinergic pathways. Significant polygenetic overlap between cerebellar white matter tracts and their anatomically connected or adjacent brain regions was detected. In addition, we report the overall genetic correlation and specific loci shared between cerebellar white matter microstructural integrity and brain-related traits, including movement, cognitive, psychiatric, and cerebrovascular categories. CONCLUSIONS: Collectively, this study represents a step forward in understanding the genetics of cerebellar white matter microstructure and its shared genetic etiology with common brain disorders.

Circulating metabolites and risk of incident dementia: A prospective cohort study.

Identifying circulating metabolites associated with dementia, cognition, and brain volume may improve the understanding of dementia pathogenesis and provide novel insights for preventive and therapeutic interventions. This cohort study included a total of 87 885 participants (median follow-up of 9.1 years, 54% female) without dementia at baseline from the UK Biobank. A total of 249 plasma metabolites were measured using nuclear magnetic resonance spectroscopy at baseline. Cox proportional regression was used to examine the associations of each metabolite with incident dementia (cases = 1134), Alzheimer's disease (AD; cases = 488), and vascular dementia (VD; cases = 257) during follow-up. Dementia-associated metabolites were further analyzed for association with cognitive deficits (N = 87 885) and brain volume (N = 7756) using logistic regression and linear regression. We identified 26 metabolites associated with incident dementia, of which 6 were associated with incident AD and 5 were associated with incident VD. These 26 dementia-related metabolites were subfractions of intermediate-density lipoprotein, large low-density lipoprotein (L-LDL), small high-density lipoprotein (S-HDL), very-low-density lipoprotein, fatty acids, ketone bodies, citrate, glucose, and valine. Among them, the cholesterol percentage in L-LDL (L-LDL-C%) was associated with lower risk of AD (HR [95% CI] = 0.92 [0.87-0.97], p = 0.002), higher brain cortical (ß = 0.047, p = 3.91 × 10-6 ), and hippocampal (ß = 0.043, p = 1.93 × 10-4 ) volume. Cholesteryl ester-to-total lipid ratio in L-LDL (L-LDL-CE%) was associated with lower risk of AD (HR [95% CI] = 0.93 [0.90-0.96], p = 1.48 × 10-4 ), cognitive deficits (odds ratio = 0.98, p = 0.009), and higher hippocampal volume (ß = 0.027, p = 0.009). Cholesteryl esters in S-HDL (S-HDL-CE) were associated with lower risk of VD (HR [95% CI] = 0.81 [0.71-0.93], p = 0.002), but not AD. Taken together, circulating levels of L-LDL-CE% and L-LDL-C% were robustly associated with risk of AD and AD phenotypes, but not with VD. S-HDL-CE was associated with lower risk of VD, but not with AD or AD phenotypes. These metabolites may play a role in the advancement of future intervention trials. Additional research is necessary to gain a complete comprehension of the molecular mechanisms behind these associations.

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.

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.

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.

Clinical laboratory tests and dementia incidence: A prospective cohort study.

BACKGROUND: Dementia is a major public health issue and a heavy economic burden. It is urgently necessary to understand the underlying biological processes and to identify biomarkers predicting risk of dementia in the preclinical stage for prevention and treatment. METHODS: By using the data of the 367,093 white British individuals from UK Biobank, we investigated the relationship between 56 laboratory measures and 5-year dementia incidence using logistic regression. Adjusted odds ratios for dementia incidence with values below or above the 95 % confidence interval (<2.5th or > 97.5th percentile) on each of clinical laboratory tests were computed. RESULTS: We observed that markers of endocrine dysregulation: elevated hemoglobin A1C (AOR = 2.01 [1.35, 2.88]) was associated with increased dementia incidence. Indicators of liver dysfunction: elevated gamma glutamyltransferase (AOR = 2.28 [1.49, 3.32]), and albumin (AOR = 2.01 [1.15, 3.25]), indicators of renal impairment: high urea (AOR = 1.69 [1.15, 2.40]), and cystatin C (AOR = 1.89 [1.30, 2.67]), and some immune markers, like elevated neutrophill count, low lymphocyte count, and indicators of anemia were also observed to be associated with increased dementia incidence. Both low and high concentrations of insulin-like growth factor 1 were found to be risk factors for dementia. LIMITATIONS: This is an observational study. CONCLUSION: Several systemic biomarkers were associated with dementia incidence. These results implicate a contributory role of diverse biological processes to dementia onset, and enrich our understanding of potential dementia prevention strategy.

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.

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.

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.

Whole-exome sequencing identifies protein-coding variants associated with brain iron in 29,828 individuals.

Iron plays a fundamental role in multiple brain disorders. However, the genetic underpinnings of brain iron and its implications for these disorders are still lacking. Here, we conduct an exome-wide association analysis of brain iron, measured by quantitative susceptibility mapping technique, across 26 brain regions among 26,789 UK Biobank participants. We find 36 genes linked to brain iron, with 29 not being previously reported, and 16 of them can be replicated in an independent dataset with 3,039 subjects. Many of these genes are involved in iron transport and homeostasis, such as FTH1 and MLX. Several genes, while not previously connected to brain iron, are associated with iron-related brain disorders like Parkinson's (STAB1, KCNA10), Alzheimer's (SHANK1), and depression (GFAP). Mendelian randomization analysis reveals six causal relationships from regional brain iron to brain disorders, such as from the hippocampus to depression and from the substantia nigra to Parkinson's. These insights advance our understanding of the genetic architecture of brain iron and offer potential therapeutic targets for brain disorders.

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.

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.