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.

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.

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.

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.

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.

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.

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.

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.

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.

Longitudinal associations of cardiovascular health and vascular events with incident dementia.

INTRODUCTION: Evidence supporting cardiovascular diseases could increase the risk of dementia remains fragmented. A comprehensive study to illuminate the distinctive associations across different dementia types is still lacking. This study is sought to: (1) determine the clinical validity of Framingham General Cardiovascular Risk Score (FGCRS) for dementia assessment and (2) examine the associations between cardiovascular diseases and the risk of dementia. METHODS: A total of 432 079 dementia-free individuals at baseline from UK Biobank were included. Multivariable Cox proportional hazard models were used to investigate the prospective associations for FGCRS and a series of cardiovascular diseases with all-cause dementia (ACD) and its major components, Alzheimer's disease (AD) and vascular dementia (VaD). RESULTS: During a median follow-up of 110.1 months, 4711 individuals were diagnosed with dementia. FGCRS was associated with increased risks across the dementia spectrum. In stratification analysis, high-risk groups have demonstrated the greatest dementia burdens, particularly to VaD. Over 74 traits, 9 adverse associations, such as chronic ischaemic heart disease (ACD: HR=1.354; AD: HR=1.269; VaD: HR=1.768), atrioventricular block (ACD: HR=1.562; AD: HR=1.556; VaD: HR=2.069), heart failure (ACD: HR=1.639; AD: HR=1.543; VaD: HR=2.141) and hypotension (ACD: HR=2.912; AD: HR=2.361; VaD: HR=3.315) were observed. Several distinctions were also found, with atrial fibrillation, cerebral infarction, and haemorrhage only associated with greater risks of ACD and VaD. DISCUSSION: By identifying distinctive associations between cardiovascular diseases and dementia, this study has established a comprehensive 'mapping' that may untangle the long-standing discrepancy. FGCRS has demonstrated its predictivity beyond cardiovascular diseases burdens, suggesting potential opportunities for implantation.

Association of biological age with health outcomes and its modifiable factors.

Identifying the clinical implications and modifiable and unmodifiable factors of aging requires the measurement of biological age (BA) and age gap. Leveraging the biomedical traits involved with physical measures, biochemical assays, genomic data, and cognitive functions from the healthy participants in the UK Biobank, we establish an integrative BA model consisting of multi-dimensional indicators. Accelerated aging (age gap >3.2 years) at baseline is associated incident circulatory diseases, related chronic disorders, all-cause, and cause-specific mortality. We identify 35 modifiable factors for age gap (p < 4.81 × 10-4 ), where pulmonary functions, body mass, hand grip strength, basal metabolic rate, estimated glomerular filtration rate, and C-reactive protein show the most significant associations. Genetic analyses replicate the possible associations between age gap and health-related outcomes and further identify CST3 as an essential gene for biological aging, which is highly expressed in the brain and is associated with immune and metabolic traits. Our study profiles the landscape of biological aging and provides insights into the preventive strategies and therapeutic targets for aging.

Association between polygenic risk for Alzheimer's disease and brain structure in children and adults.

BACKGROUND: The correlations between genetic risk for Alzheimer's disease (AD) with comprehensive brain regions at a regional scale are still not well understood. We aim to explore whether these associations vary across different age stages. METHODS: This study used large existing genome-wide association datasets to calculate polygenic risk score (PRS) for AD in two populations from the UK Biobank (N ~ 23 000) and Adolescent Brain Cognitive Development Study (N ~ 4660) who had multimodal macrostructural and microstructural magnetic resonance imaging (MRI) metrics. We used linear mixed-effect models to assess the strength of the association between AD PRS and multiple MRI metrics of regional brain structures at different stages of life. RESULTS: Compared to those with lower PRSs, adolescents with higher PRSs had thinner cortex in the caudal anterior cingulate and supramarginal. In the middle-aged and elderly population, AD PRS had correlations with regional structure shrink primarily located in the cingulate, prefrontal cortex, hippocampus, thalamus, amygdala, and striatum, whereas the brain expansion was concentrated near the occipital lobe. Furthermore, both adults and adolescents with higher PRSs exhibited widespread white matter microstructural changes, indicated by decreased fractional anisotropy (FA) or increased mean diffusivity (MD). CONCLUSIONS: In conclusion, our results suggest genetic loading for AD may influence brain structures in a highly dynamic manner, with dramatically different patterns at different ages. This age-specific change is consistent with the classical pattern of brain impairment observed in AD patients.

The genetic architecture of the corpus callosum and its genetic overlap with common neuropsychiatric diseases.

BACKGROUND: The corpus callosum (CC) is the main structure transferring information between the cerebral hemispheres. Although previous large-scale genome-wide association study (GWAS) has illustrated the genetic architecture of white matter integrity of CC, CC volume is less stressed. METHODS: Using MRI data from 33,861 individuals in UK Biobank, we conducted univariate and multivariate GWAS for CC fractional anisotropy (FA) and volume with PLINK 2.0 and MOSTest. All discovered SNPs in the multivariate framework were functionally annotated in FUMA v1.3.8. In the meanwhile, a series of gene property analyses was conducted simultaneously. In addition, we estimated genetic relationship between CC metrics and other neuropsychiatric traits and diseases. RESULTS: We identified a total of 36 and 82 significant genomic loci for CC FA and volume (P < 5 × 10-8). And 53 and 27 genes were respectively mapped by four mapping strategies. For CC volume, gene-set analysis revealed pathways mainly relating to cell migration; cell-type analysis found the top enrichment in neuroglia while for CC FA in GABAergic neurons. Furthermore, we found a lot of genetic overlap and shared loci between CC FA and volume and common neuropsychiatric diseases. DISCUSSION: Collectively, this study helps to better understand the genetic architecture of whole CC and CC subregions. However, the way to divide CC FA and volume in our study restricts the interpretations of our results. Future work will be needed to pay attention to the genetic structure of white matter volume, and an appropriate division of CC may help to better understand CC structure.

The genetic architecture of fornix white matter microstructure and their involvement in neuropsychiatric disorders.

The fornix is a white matter bundle located in the center of the hippocampaldiencephalic limbic circuit that controls memory and executive functions, yet its genetic architectures and involvement in brain disorders remain largely unknown. We carried out a genome-wide association analysis of 30,832 UK Biobank individuals of the six fornix diffusion magnetic resonance imaging (dMRI) traits. The post-GWAS analysis allowed us to identify causal genetic variants in phenotypes at the single nucleotide polymorphisms (SNP), locus, and gene levels, as well as genetic overlap with brain health-related traits. We further generalized our GWAS in adolescent brain cognitive development (ABCD) cohort. The GWAS identified 63 independent significant variants within 20 genomic loci associated (P < 8.33 × 10-9) with the six fornix dMRI traits. Geminin coiled-coil domain containing (GMNC) and NUAK family SNF1-like kinase 1 (NUAK1) gene were highlighted, which were found in UKB and replicated in ABCD. The heritability of the six traits ranged from 10% to 27%. Gene mapping strategies identified 213 genes, where 11 were supported by all of four methods. Gene-based analyses revealed pathways relating to cell development and differentiation, with astrocytes found to be significantly enriched. Pleiotropy analyses with eight neurological and psychiatric disorders revealed shared variants, especially with schizophrenia under the conjFDR threshold of 0.05. These findings advance our understanding of the complex genetic architectures of fornix and their relevance in neurological and psychiatric disorders.

Identifying modifiable factors and their joint effect on dementia risk in the UK Biobank.

Previous hypothesis-driven research has identified many risk factors linked to dementia. However, the multiplicity and co-occurrence of risk factors have been underestimated. Here we analysed data of 344,324 participants from the UK Biobank with 15 yr of follow-up data for 210 modifiable risk factors. We first conducted an exposure-wide association study and then combined factors associated with dementia to generate composite scores for different domains. We then evaluated their joint associations with dementia in a multivariate Cox model. We estimated the potential impact of eliminating the unfavourable profiles of risk domains on dementia using population attributable fraction. The associations varied by domain, with lifestyle (16.6%), medical history (14.0%) and socioeconomic status (13.5%) contributing to the majority of dementia cases. Overall, we estimated that up to 47.0%-72.6% of dementia cases could be prevented.

Genome-wide Survival Study Identifies PARL as a Novel Locus for Clinical Progression and Neurodegeneration in Alzheimer's Disease.

BACKGROUND: Variability exists in the trajectories of Alzheimer's disease (AD). We aimed to identify genetic modulators of clinical progression in AD. METHODS: We conducted the first genome-wide survival study on AD using a two-stage approach. The discovery and replication stage separately included 1158 and 211,817 individuals without dementia from the Alzheimer's Disease Neuroimaging Initiative and the UK Biobank, respectively (325 and 1103 progressed in average follow-up of 4.33 and 8.63 years, respectively). Cox proportional hazards models were applied with time to AD dementia as the phenotype of clinical progression. A series of bioinformatic analyses and functional experiments was performed to validate the novel findings. RESULTS: We found that APOE and PARL, a novel locus tagged by rs6795172 (hazard ratio = 1.66, p = 1.45 × 10-9), were significantly associated with AD clinical progression and were successfully replicated. The novel locus was linked to accelerated cognitive changes, higher tau levels, and faster atrophy of AD-specific brain structures, which were also verified in UK Biobank neuroimaging follow-up. Gene analysis and summary data-based Mendelian randomization indicated PARL as the most functionally relevant gene in the locus. Expression quantitative trait locus analyses and dual-luciferase reporter assays confirmed that PARL expression could be regulated by rs6795172. Three different AD mouse models consistently showed decreased PARL expression accompanied by elevated tau levels, and in vitro experiments revealed that knockdown/overexpression of PARL inversely changed tau levels. CONCLUSIONS: Collectively, genetic, bioinformatic, and functional evidence suggests that PARL modulates clinical progression and neurodegeneration in AD. Targeting PARL may potentially modify AD progression and have implications for disease-modifying therapies.

The genetic architecture of human amygdala volumes and their overlap with common brain disorders.

The amygdala is a crucial interconnecting structure in the brain that performs several regulatory functions, yet its genetic architectures and involvement in brain disorders remain largely unknown. We carried out the first multivariate genome-wide association study (GWAS) of amygdala subfield volumes in 27,866 UK Biobank individuals. The whole amygdala was segmented into nine nuclei groups using Bayesian amygdala segmentation. The post-GWAS analysis allowed us to identify causal genetic variants in phenotypes at the SNP, locus, and gene levels, as well as genetic overlap with brain health-related traits. We further generalized our GWAS in Adolescent Brain Cognitive Development (ABCD) cohort. The multivariate GWAS identified 98 independent significant variants within 32 genomic loci associated (P < 5 × 10-8) with amygdala volume and its nine nuclei. The univariate GWAS identified significant hits for eight of the ten volumes, tagging 14 independent genomic loci. Overall, 13 of the 14 loci identified in the univariate GWAS were replicated in the multivariate GWAS. The generalization in ABCD cohort supported the GWAS results with the 12q23.2 (RNA gene RP11-210L7.1) being discovered. All of these imaging phenotypes are heritable, with heritability ranging from 15% to 27%. Gene-based analyses revealed pathways relating to cell differentiation/development and ion transporter/homeostasis, with the astrocytes found to be significantly enriched. Pleiotropy analyses revealed shared variants with neurological and psychiatric disorders under the conjFDR threshold of 0.05. These findings advance our understanding of the complex genetic architectures of amygdala and their relevance in neurological and psychiatric disorders.

Prioritization of Drug Targets for Neurodegenerative Diseases by Integrating Genetic and Proteomic Data From Brain and Blood.

BACKGROUND: Neurodegenerative diseases are among the most prevalent and devastating neurological disorders, with few effective prevention and treatment strategies. We aimed to integrate genetic and proteomic data to prioritize drug targets for neurodegenerative diseases. METHODS: We screened human proteomes through Mendelian randomization to identify causal mediators of Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, multiple sclerosis, frontotemporal dementia, and Lewy body dementia. For instruments, we used brain and blood protein quantitative trait loci identified from one genome-wide association study with 376 participants and another with 3301 participants, respectively. Causal associations were subsequently validated by sensitivity analyses and colocalization. The safety and druggability of identified targets were also evaluated. RESULTS: Our analyses showed targeting BIN1, GRN, and RET levels in blood as well as ACE, ICA1L, MAP1S, SLC20A2, and TOM1L2 levels in brain might reduce Alzheimer's disease risk, while ICA1L, SLC20A2, and TOM1L2 were not recommended as prioritized drugs due to the identified potential side effects. Brain CD38, DGKQ, GPNMB, and SEC23IP were candidate targets for Parkinson's disease. Among them, GPNMB was the most promising target for Parkinson's disease with their causal relationship evidenced by studies on both brain and blood tissues. Interventions targeting FCRL3, LMAN2, and MAPK3 in blood and DHRS11, FAM120B, SHMT1, and TSFM in brain might affect multiple sclerosis risk. The risk of amyotrophic lateral sclerosis might be reduced by medications targeting DHRS11, PSMB3, SARM1, and SCFD1 in brain. CONCLUSIONS: Our study prioritized 22 proteins as targets for neurodegenerative diseases and provided preliminary evidence for drug development. Further studies are warranted to validate these targets.

A Phenome-wide Association and Mendelian Randomization Study for Alzheimer's Disease: A Prospective Cohort Study of 502,493 Participants From the UK Biobank.

BACKGROUND: Considerable uncertainty remains regarding associations of multiple risk factors with Alzheimer's disease (AD). We aimed to systematically screen and validate a wide range of potential risk factors for AD. METHODS: Among 502,493 participants from the UK Biobank, baseline data were extracted for 4171 factors spanning 10 different categories. Phenome-wide association analyses and time-to-event analyses were conducted to identify factors associated with both polygenic risk scores for AD and AD diagnosis at follow-up. We performed two-sample Mendelian randomization analysis to further assess their potential causal relationships with AD and imaging association analysis to discover underlying mechanisms. RESULTS: We identified 39 factors significantly associated with both AD polygenic risk scores and risk of incident AD, where higher levels of education, body size, basal metabolic rate, fat-free mass, computer use, and cognitive functions were associated with a decreased risk of developing AD, and selective food intake and more outdoor exposures were associated with an increased risk of developing AD. The identified factors were also associated with AD-related brain structures, including the hippocampus, entorhinal cortex, and inferior/middle temporal cortex, and 21 of these factors were further supported by Mendelian randomization evidence. CONCLUSIONS: To our knowledge, this is the first study to comprehensively and rigorously assess the effects of wide-ranging risk factors on AD. Strong evidence was found for fat-free body mass, basal metabolic rate, computer use, selective food intake, and outdoor exposures as new risk factors for AD. Integration of genetic, clinical, and neuroimaging information may help prioritize risk factors and prevention targets for 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.