Modeling multi-component separation in hydrophobic interaction chromatography with improved parameter-by-parameter estimation method.

Mechanistic models are powerful tools for chromatographic process development and optimization. However, hydrophobic interaction chromatography (HIC) mechanistic models lack an effective and logical parameter estimation method, especially for multi-component system. In this study, a parameter-by-parameter method for multi-component system (called as mPbP-HIC) was derived based on the retention mechanism to estimate the six parameters of the Mollerup isotherm for HIC. The linear parameters (ks,i and keq,i) and nonlinear parameters (ni and qmax,i) of the isotherm can be estimated by the linear regression (LR) and the linear approximation (LA) steps, respectively. The remaining two parameters (kp,i and kkin,i) are obtained by the inverse method (IM). The proposed method was verified with a two-component model system. The results showed that the model could accurately predict the protein elution at a loading of 10 g/L. However, the elution curve fitting was unsatisfactory for high loadings (12 g/L and 14 g/L), which is mainly attributed to the demanding experimental conditions of the LA step and the potential large estimation error of the parameter qmax. Therefore, the inverse method was introduced to further calibrate the parameter qmax, thereby reducing the estimation error and improving the curve fitting. Moreover, the simplified linear approximation (SLA) was proposed by reasonable assumption, which provides the initial guess of qmax without solving any complex matrix and avoids the problem of matrix unsolvable. In the improved mPbP-HIC method, qmax would be initialized by the SLA and finally determined by the inverse method, and this strategy was named as SLA+IM. The experimental validation showed that the improved mPbP-HIC method has a better curve fitting, and the use of SLA+IM reduces the error accumulation effect. In process optimization, the parameters estimated by the improved mPbP-HIC method provided the model with excellent predictive ability and reasonable extrapolation. In conclusion, the SLA+IM strategy makes the improved mPbP-HIC method more rational and can be easily applied to the practical separation of protein mixture, which would accelerate the process development for HIC in downstream of biopharmaceuticals.

Parameter-by-parameter estimation method for adsorption isotherm in hydrophobic interaction chromatography.

Hydrophobic interaction chromatography (HIC) is used as a critical polishing step in the downstream processing of biopharmaceuticals. Normally the process development of HIC is a cumbersome and time-consuming task, and the mechanical models can provide a powerful tool to characterize the process, assist process design and accelerate process development. However, the current estimation of model parameters relies on the inverse method, which lacks an efficient and logical parameter estimation strategy. In this study, a parameter-by-parameter (PbP) method based on the theoretical derivation and simplifying assumptions was proposed to estimate the Mollerup isotherm parameters for HIC. The method involves three key steps: (1) linear regression (LR) to estimate the salt-protein interaction parameter and the equilibrium constant; (2) linear approximation (LA) to estimate the stoichiometric parameter and the maximum binding capacity; and (3) inverse method to estimate the protein-protein interaction parameter and the kinetic coefficient. The results indicated that the LR step should be used for dilution condition (loading factor below 5%), while the LA step should be conducted when the isotherm is in the transition or nonlinear regions. Six numerical experiments were conducted to implement the PbP method. The results demonstrated that the PbP method developed allows for the systematic estimation of HIC parameters one-by-one, effectively reducing the number of parameters required for inverse method estimation from six to two. This helps prevent non-identifiability of structural parameters. The feasibility of the PbP-HIC method was further validated by real-world experiments. Moreover, the PbP method enhances the mechanistic understanding of adsorption behavior of HIC and shows a promising application to other stoichiometric displacement model-derived isotherms.

Associations of cardiovascular risk factors and lifestyle behaviors with neurodegenerative disease: a Mendelian randomization study.

Previous observational studies reported that midlife clustering of cardiovascular risk factors and lifestyle behaviors were associated with neurodegenerative disease; however, these findings might be biased by confounding and reverse causality. This study aimed to investigate the causal associations of cardiovascular risk factors and lifestyle behaviors with neurodegenerative disease, using the two-sample Mendelian randomization design. Genetic variants for the modifiable risk factors and neurodegenerative disease were extracted from large-scale genome-wide association studies. The inverse-variance weighted method was used as the main analysis method, and MR-Egger regression and leave-one-out analyses were performed to identify potential violations. Genetically predicted diastolic blood pressure (DBP: OR per 1 mmHg, 0.990 [0.979-1.000]), body mass index (BMI: OR per 1 SD, 0.880 [0.825-0.939]), and educational level (OR per 1 SD, 0.698 [0.602-0.810]) were associated with lower risk of late-onset Alzheimer's disease (LOAD), while genetically predicted low-density lipoprotein (LDL: OR per 1 SD, 1.302 [1.066-1.590]) might increase LOAD risk. Genetically predicted exposures (including LDL and BMI) applied to familial AD showed the same effect. The association of LDL was also found with Amyotrophic lateral sclerosis (ALS) (LDL: OR per 1 SD, 1.180 [1.080-1.289]). This MR analysis showed that LDL, BMI, BP, and educational level were causally related to AD; a significant association between LDL and ALS risk, as well as the potential effect of sleep duration on PD risk, were also revealed. Targeting these modifiable factors was a promising strategy of neurodegenerative disease prevention.

Genome-wide association study of brain tau deposition as measured by 18F-flortaucipir positron emission tomography imaging.

The related genetic variants of tau deposition, a seminal pathological hallmark of Alzheimer's disease, remain poorly understood. We sought to perform a genome-wide association study of brain tau load as measured by AV1451 positron emission tomography (PET). Among 543 non-demented European individuals, novel associations with higher tau were identified for rs56298435 (p = 8.35 × 10-10, ß=0.31) within ZBTB20, and for rs150532 (p = 1.90 × 10-8, ß=0.26) in the protein phosphorylation regulatory gene EYA4. The APOE association additionally reached genome-wide significant when APOE ε4 was not adjusted. Minor allele carriers of rs56298435 or rs150532 showed higher levels of tau PET load. As expected, phosphorylated-tau analyses in both plasma and cerebrospinal fluid also revealed the same direction of effect. Functionally, the effects of novel loci on cognitive decline could be mediated by tau pathology. In addition, we observed that the expression of VNN2 as regulated by rs150532, together with EYA4, displayed significant correlations with the tau-related gene MAPT in numerous brain regions. Our novel finding lends additional credence to heritable underpinnings of tau deposition.

Genetic determinants of circulating metabolites and the risk of stroke and its subtypes.

BACKGROUND AND PURPOSE: Circulating metabolites have been implicated in stroke pathogenesis, but their genetic determinants are understudied. Using a Mendelian randomization approach, our aim was to provide evidence for the relationship of circulating metabolites and the risk of stroke and its subtypes. METHODS: Genetic instruments of 102 circulating metabolites were obtained from a genome-wide association study, including 24,925 European individuals. Stroke was extracted from the MEGASTROKE dataset (67,162 cases; 454,450 controls) and a lacunar stroke dataset (7338 cases; 254,798 controls). The magnetic resonance imaging markers of cerebral small vessel disease and microstructural injury were evaluated by a genome-wide association study of white matter hyperintensities (N = 18,381), fractional anisotropy (N = 17,663), mean diffusivity (N = 17,467) and brain microbleeds (N = 25,862). The inverse-variance weighted method Mendelian randomization was used as the primary analytical method, and directional pleiotropy and heterogeneity were examined in sensitivity analyses. RESULTS: A genetic predisposition to a higher level of cholesterol in small and low-density lipoprotein (LDL) was associated with risk of stroke (odds ratio [OR] 1.14, 95% confidence interval [CI] 1.08-1.21, p = 5.98 × 10-7 ), especially for large-artery atherosclerotic stroke (OR 1.34, 95% CI 1.19-1.52, p = 1.90 × 10-6 ). Total lipids in LDL particles were also associated with risk of stroke. A genetically determined higher cholesterol level in high-density lipoprotein (HDL-C) was associated with risk of intracerebral haemorrhage (OR 1.74, 95% CI 1.23-2.45, p = 1.66 × 10-3 ). No statistically significant association was found between genetic predisposition to circulating metabolites and magnetic resonance imaging markers of cerebral small vessel disease and microstructural injury. CONCLUSIONS: Genetically determined levels of lipids in small LDL were associated with the risk of stroke, suggesting that a therapeutic strategy targeting small LDL levels may be crucial for stroke prevention. HDL-C was positively associated with the risk of intracerebral haemorrhage.

Experimental Demonstration of Quantum Pseudotelepathy.

Quantum pseudotelepathy is a strong form of nonlocality. Different from the conventional nonlocal games where quantum strategies win statistically, e.g., the Clauser-Horne-Shimony-Holt game, quantum pseudotelepathy in principle allows quantum players to with probability 1. In this Letter, we report a faithful experimental demonstration of quantum pseudotelepathy via playing the nonlocal version of Mermin-Peres magic square game, where Alice and Bob cooperatively fill in a 3×3 magic square. We adopt the hyperentanglement scheme and prepare photon pairs entangled in both the polarization and the orbital angular momentum degrees of freedom, such that the experiment is carried out in a resource-efficient manner. Under the locality and fair-sampling assumption, our results show that quantum players can simultaneously win all the queries over any classical strategy.

Identification of novel drug targets for the risk and prognosis of COVID-19.

Background: Since the epidemic continues, there is a pressing need to improve our understanding of coronavirus disease 2019 (COVID-19). Mendelian randomization (MR) studies provide us with a method to explore the causality between circulating proteins and COVID-19 susceptibility and severity. We aim to find new perspectives on the pathological mechanism of the disease and possible drug targets for treatment based on this study. Methods: We conducted a phenome-wide MR study to prioritize circulating proteins causally associated with COVID-19 susceptibility, which was defined as "patients tested positive for COVID-19 vs. population controls", and severity, which was defined as "patients hospitalized with COVID-19 vs. population controls". And we repeated the analysis for different definition of COVID-19 susceptibility, severity and control groups. Results: Association of three circulating proteins with COVID-19 susceptibility and severity were demonstrated via our study. C-C motif chemokine 4 (OR =1.887, 95% CI: 1.608-2.165, P=8.04×10-6) and 2'-5'-oligoadenylate synthase 1 (OR =0.511, 95% CI: 0.266-0.757, P=8.51×10-8) were found respectively positively and negatively correlated with increased COVID-19 severity. Tissue factor, contrary to previous studies, was found associated with decreased COVID-19 susceptibility (OR =0.667, 95% CI: 0.484-0.850, P=1.47×10-5) and decreased COVID-19 severity (OR =0.459, 95% CI: 0.132-0.786, P=3.01×10-6). Conclusions: Genetic evidence supports C-C motif chemokine 4 as a risk factor for COVID-19 severity, and 2'-5'-oligoadenylate synthase 1 as a protective factor for COVID-19 severity. The causal association between tissue factor and COVID-19 is contrary to the previous studies, needing further analyses. Further research is warranted to assess the viability of C-C motif chemokine 4 and 2'-5'-oligoadenylate synthase 1 as well as their downstream pathways as drug targets for anti-inflammatory and anti-virus treatment in severe cases.

Causal Relations between Exposome and Stroke: A Mendelian Randomization Study.

BACKGROUND AND PURPOSE: To explore the causal relationships of elements of the exposome with ischemic stroke and its subtypes at the omics level and to provide evidence for stroke prevention. METHODS: We conducted a Mendelian randomization study between exposure and any ischemic stroke (AIS) and its subtypes (large-artery atherosclerotic disease [LAD], cardioembolic stroke [CE], and small vessel disease [SVD]). The exposure dataset was the UK Biobank involving 361,194 subjects, and the outcome dataset was the MEGASTROKE consortium including 52,000 participants. RESULTS: We found that higher blood pressure (BP) (systolic BP: odds ratio [OR], 1.02; 95% confidence interval [CI], 1.01 to 1.04; diastolic BP: OR, 1.03; 95% CI, 1.01 to 1.05; pulse pressure: OR, 1.03; 95% CI, 1.00 to 1.06), atrial fibrillation (OR, 1.18; 95% CI, 1.13 to 1.25), and diabetes (OR, 1.13; 95% CI, 1.07 to 1.18) were significantly associated with ischemic stroke. Importantly, higher education (OR, 0.69; 95% CI, 0.60 to 0.79) decreased the risk of ischemic stroke. Higher systolic BP (OR, 1.06; 95% CI, 1.02 to 1.10), pulse pressure (OR, 1.08; 95% CI, 1.02 to 1.14), diabetes (OR, 1.28; 95% CI, 1.13 to 1.45), and coronary artery disease (OR, 1.58; 95% CI, 1.25 to 2.00) could cause LAD. Atrial fibrillation could cause CE (OR, 1.90; 95% CI, 1.71 to 2.11). For SVD, higher systolic BP (OR, 1.04; 95% CI, 1.00 to 1.07), diastolic BP (OR, 1.06; 95% CI, 1.01 to 1.12), and diabetes (OR, 1.22; 95% CI, 1.10 to 1.36) were causal factors. CONCLUSIONS: The study revealed elements of the exposome causally linked to ischemic stroke and its subtypes, including conventional causal risk factors and novel protective factors such as higher education.

Genome-wide association study identifies APOE locus influencing plasma p-tau181 levels.

As a promising diagnostic and prognostic biomarker for Alzheimer's Disease (AD), plasma p-tau181 is robustly differentiated AD dementia from non-AD neurodegenerative diseases. We aimed to discover single nucleotide polymorphisms (SNPs) associated with plasma phosphorylated tau at threonine 181 (p-tau181) levels that affect the risk of developing AD. We carried out a genome-wide association study for plasma p-tau181 levels using participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The thresholds of P < 5 × 10-6 was used for suggestive associations, and thresholds of P < 5 × 10-8 was used for significant associations. Subsequently, we tested whether the associations remained significant in subgroup analysis and examined the impact of SNPs on the longitudinal changes in plasma p-tau181 levels. A total of 714 eligible non-Hispanic white participants with plasma p-tau181 data were included. The most significant SNP (rs769449, P = 6.26 × 10-8) in APOE gene was suggestively associated with plasma p-tau181, which is close to the genome-wide significance threshold. The minor allele (A) of rs769449 in the APOE was associated with higher plasma p-tau181 levels in a dose-dependent fashion. Besides, rs769449- A carriers were more likely to exhibit a greater longitudinal cognitive decline (P = 0.03). Our results suggest that the AD risk variant in the APOE gene participates in the regulation of plasma p-tau181. The plasma p-tau181 concentration could be a useful endophenotype for identifying risk for AD in elderly individuals.

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.

Investigating Causal Relations Between Circulating Metabolites and Alzheimer's Disease: A Mendelian Randomization Study.

BACKGROUND: Metabolomics is a promising approach that can be used to understand pathophysiological pathways of Alzheimer's disease (AD). However, the causal relationships between metabolism and AD are poorly understood. OBJECTIVE: We aimed to investigate the causal association between circulating metabolites and risk of AD through two-sample Mendelian randomization (MR) approach. METHODS: Genetic associations with 123 circulating metabolic traits were utilized as exposures. Summary statistics data from International Genomics of Alzheimer's Project was used in primary analysis, including 21,982 AD cases and 41,944 controls. Validation was performed using family history of AD data from UK Biobank (27,696 cases of maternal AD, 14,338 cases of paternal AD, and 272,244 controls). We utilized inverse-variance weighted method as primary method. RESULTS: We found significantly increased risks of developing AD per standard deviation increase in the levels of circulating ApoB (odd ratio[OR] = 3.18; 95% confidence interval[CI]: 1.52-6.66, p = 0.0022), glycoprotein acetyls (OR = 1.21; 95% CI: 1.05-1.39, p = 0.0093), total cholesterol (OR = 2.73; 95% CI: 1.41-5.30, p = 0.0030), and low-density lipoprotein (LDL) cholesterol (OR = 2.34; 95% CI: 1.53-3.57, p = 0.0001). Whereas glutamine (OR = 0.81; 95% CI: 0.71-0.92, p = 0.0011) were significantly associated with lower risk of AD. We also detected causal effects of several different composition of LDL fractions on increased AD risk, which has been verified in validation. However, we found no association between circulating high-density lipoprotein cholesterol and AD. CONCLUSION: Our findings suggest causal effects of circulating glycoprotein acetyls, ApoB, LDL cholesterol, and serum total cholesterol on higher risk of AD, whereas glutamine showed the protective effect.

Experimental self-testing for photonic graph states.

Graph states-one of the most representative families of multipartite entangled states-are important resources for multiparty quantum communication, quantum error correction, and quantum computation. Device-independent certification of highly entangled graph states plays a prominent role in quantum information processing tasks. Here we have experimentally demonstrated device-independent certification for multipartite graph states by adopting the robust self-testing scheme based on scalable Bell inequalities. Specifically, the prepared multi-qubit Greenberger-Horne-Zeilinger (GHZ) states and linear cluster states achieve a high degree of Bell violation, which are beyond the nontrivial bounds of the robust self-testing scheme. Furthermore, our work paves the way to the device-independent certification of complex multipartite quantum states.

Validation of external and internal exposome of the findings associated to cerebral small vessel disease: A Mendelian randomization study.

The exposome characterizes all environmental exposures and their impact on a disease. To determine the causally-associated components of the exposome for cerebral small vessel disease (CSVD), we performed mendelian randomization analysis of 5365 exposures on six clinical and subclinical CSVD measures. We found statistically significant evidence (FDR-corrected P < 0.05) that hypertension, high cholesterol, longer television-watching time, lower educational qualifications, younger age of first sexual intercourse, smoking, reduced pulmonary function, higher subjective overall health rating, and frequent tiredness were associated with increased risk of intracerebral hemorrhage or small vessel stroke. Adiposity, diabetes, frequent alcoholic drinks, higher white blood cell count and neutrophil count were significantly associated with higher risk of non-lobar hemorrhage or small vessel stroke, but not lobar hemorrhage. Hypertension, higher arm or leg fat-free mass and higher sitting height were significantly associated with higher white matter hyperintensities. The results were robust to sensitivity analyses and showed no evidence of horizontal pleiotropy. We also identified 41 exposures suggestively associated (uncorrected P < 0.05) with multiple CSVD measures as the "the CSVD exposome". This exposome-wide association study provides insight into CSVD development and prevention.

Hong-Ou-Mandel Interference between Two Hyperentangled Photons Enables Observation of Symmetric and Antisymmetric Particle Exchange Phases.

Two-photon Hong-Ou-Mandel (HOM) interference is a fundamental quantum effect with no classical counterpart. The existing research on two-photon interference was mainly limited in one degree of freedom (DOF); hence, it is still a challenge to realize quantum interference in multiple DOFs. Here, we demonstrate HOM interference between two hyperentangled photons in two DOFs of polarization and orbital angular momentum (OAM) for all 16 hyperentangled Bell states. We observe hyperentangled two-photon interference with a bunching effect for ten symmetric states (nine boson-boson states and one fermion-fermion state) and an antibunching effect for six antisymmetric states (three boson-fermion states and three fermion-boson states). More interestingly, expanding the Hilbert space by introducing an extra DOF for two photons enables one to transfer the unmeasurable external phase in the initial DOF to a measurable internal phase in the expanded two DOFs. We directly measured the symmetric exchange phases being 0.012±0.002, 0.025±0.002, and 0.027±0.002 in radian for the three boson states in OAM and the antisymmetric exchange phase being 0.991π±0.002 in radian for the other fermion state, as theoretical predictions. Our Letter may not only pave the way for more wide applications of quantum interference, but also develop new technologies by expanding Hilbert space in more DOFs.

Genetically determined low income modifies Alzheimer's disease risk.

BACKGROUND: Socioeconomic status (SES) is considered to be associated with the prevalence of Alzheimer's disease (AD). However, the causal association remain unclear. Here, we determining whether income has a causal protective effect on the risk of developing AD using Mendelian randomization (MR). METHODS: Single-nucleotide polymorphisms (SNPs) that are strongly associated with household income levels (P<5×10-8) from the UK Biobank (UKB) (n=286,301) were selected as instrumental variables for this study. Confounding instruments were removed through data set browsing. Selected SNPs were then harmonized with results from an AD genome-wide meta-analysis (71,880 cases, 383,378 controls) including both case-control and proxy cases. The analysis was conducted using MR methods, and multiple sensitivity analyses were applied for testing of potential bias. RESULTS: After confounding instrument removal and clumping, 9 SNPs associated with household income level identified by the UKB were left for the MR analysis. Our results demonstrated that higher household income level was causally related with a lower risk of AD (odds ratio 0.78, 95% confidence interval: 0.69-0.89; P<0.001). Multiple sensitivity analyses suggested no obvious evidence for heterogeneity or pleiotropy of the results. CONCLUSIONS: Under MR assumptions, our results suggest robust evidence of a causal association between household income and AD risk, which may provide potential prevention strategies for this devastating disease.

Herpesvirus infections and Alzheimer's disease: a Mendelian randomization study.

BACKGROUND: Observational studies have suggested that herpesvirus infection increased the risk of Alzheimer's disease (AD), but it is unclear whether the association is causal. The aim of the present study is to evaluate the causal relationship between four herpesvirus infections and AD. METHODS: We performed a two-sample Mendelian randomization analysis to investigate association of four active herpesvirus infections with AD using summary statistics from genome-wide association studies. The four herpesvirus infections (i.e., chickenpox, shingles, cold sores, mononucleosis) are caused by varicella-zoster virus, herpes simplex virus type 1, and Epstein-Barr virus (EBV), respectively. A large summary statistics data from International Genomics of Alzheimer's Project was used in primary analysis, including 21,982 AD cases and 41,944 controls. Validation was further performed using family history of AD data from UK Biobank (27,696 cases of maternal AD, 14,338 cases of paternal AD and 272,244 controls). RESULTS: We found evidence of a significant association between mononucleosis (caused by EBV) and risk of AD after false discovery rates (FDR) correction (odds ratio [OR] = 1.634, 95% confidence interval [CI] = 1.092-2.446, P = 0.017, FDR-corrected P = 0.034). It has been verified in validation analysis that mononucleosis is also associated with family history of AD (OR [95% CI] = 1.392 [1.061, 1.826], P = 0.017). Genetically predicted shingles were associated with AD risk (OR [95% CI] = 0.867 [0.784, 0.958], P = 0.005, FDR-corrected P = 0.020), while genetically predicted chickenpox was suggestively associated with increased family history of AD (OR [95% CI] = 1.147 [1.007, 1.307], P = 0.039). CONCLUSIONS: Our findings provided evidence supporting a positive relationship between mononucleosis and AD, indicating a causal link between EBV infection and AD. Further elucidations of this association and underlying mechanisms are likely to identify feasible interventions to promote AD prevention.

Staging tau pathology with tau PET in Alzheimer's disease: a longitudinal study.

A biological research framework to define Alzheimer' disease with dichotomized biomarker measurement was proposed by National Institute on Aging-Alzheimer's Association (NIA-AA). However, it cannot characterize the hierarchy spreading pattern of tau pathology. To reflect in vivo tau progression using biomarker, we constructed a refined topographic 18F-AV-1451 tau PET staging scheme with longitudinal clinical validation. Seven hundred and thirty-four participants with baseline 18F-AV-1451 tau PET (baseline age 73.9 ± 7.7 years, 375 female) were stratified into five stages by a topographic PET staging scheme. Cognitive trajectories and clinical progression were compared across stages with or without further dichotomy of amyloid status, using linear mixed-effect models and Cox proportional hazard models. Significant cognitive decline was first observed in stage 1 when tau levels only increased in transentorhinal regions. Rates of cognitive decline and clinical progression accelerated from stage 2 to stage 3 and stage 4. Higher stages were also associated with greater CSF phosphorylated tau and total tau concentrations from stage 1. Abnormal tau accumulation did not appear with normal ß-amyloid in neocortical regions but prompt cognitive decline by interacting with ß-amyloid in temporal regions. Highly accumulated tau in temporal regions independently led to cognitive deterioration. Topographic PET staging scheme have potentials in early diagnosis, predicting disease progression, and studying disease mechanism. Characteristic tau spreading pattern in Alzheimer's disease could be illustrated with biomarker measurement under NIA-AA framework. Clinical-neuroimaging-neuropathological studies in other cohorts are needed to validate these findings.

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.

Investigating causal relationships between exposome and human longevity: a Mendelian randomization analysis.

BACKGROUND: Environmental factors are associated with human longevity, but their specificity and causality remain mostly unclear. By integrating the innovative "exposome" concept developed in the field of environmental epidemiology, this study aims to determine the components of exposome causally linked to longevity using Mendelian randomization (MR) approach. METHODS: A total of 4587 environmental exposures extracting from 361,194 individuals from the UK biobank, in exogenous and endogenous domains of exposome were assessed. We examined the relationship between each environmental factor and two longevity outcomes (i.e., surviving to the 90th or 99th percentile age) from various cohorts of European ancestry. Significant results after false discovery rates correction underwent validation using an independent exposure dataset. RESULTS: Out of all the environmental exposures, eight age-related diseases and pathological conditions were causally associated with lower odds of longevity, including coronary atherosclerosis (odds ratio = 0.77, 95% confidence interval [0.70, 0.84], P = 4.2 × 10-8), ischemic heart disease (0.66, [0.51, 0.87], P = 0.0029), angina (0.73, [0.65, 0.83], P = 5.4 × 10-7), Alzheimer's disease (0.80, [0.72, 0.89], P = 3.0 × 10-5), hypertension (0.70, [0.64, 0.77], P = 4.5 × 10-14), type 2 diabetes (0.88 [0.80, 0.96], P = 0.004), high cholesterol (0.81, [0.72, 0.91], P = 0.0003), and venous thromboembolism (0.92, [0.87, 0.97], P = 0.0028). After adjusting for genetic correlation between different types of blood lipids, higher levels of low-density lipoprotein cholesterol (0.72 [0.64, 0.80], P = 2.3 × 10-9) was associated with lower odds of longevity, while high-density lipoprotein cholesterol (1.36 [1.13, 1.62], P = 0.001) showed the opposite. Genetically predicted sitting/standing height was unrelated to longevity, while higher comparative height size at 10 was negatively associated with longevity. Greater body fat, especially the trunk fat mass, and never eat sugar or foods/drinks containing sugar were adversely associated with longevity, while education attainment showed the opposite. CONCLUSIONS: The present study supports that some age-related diseases as well as education are causally related to longevity and highlights several new targets for achieving longevity, including management of venous thromboembolism, appropriate intake of sugar, and control of body fat. Our results warrant further studies to elucidate the underlying mechanisms of these reported causal associations.

Subtle cognitive impairment as a marker of Alzheimer's pathologies and clinical progression in cognitively normal individuals.

INTRODUCTION: Subtle cognitive impairment (SCI) may appear before pathological changes surpass thresholds for abnormality. We aimed to investigate whether SCI could predict Alzheimer's pathologies and advancement. METHODS: A total of 816 cognitively normal individuals were enrolled to assess the longitudinal neuropathological and clinical correlates of baseline SCI, via linear mixed-effects and Cox proportional-hazard models. Cross-lagged panel models were used in specific time waves. RESULTS: SCI individuals had a faster increase in brain amyloid burden and a higher risk of conversion. They also showed greater rates of cerebrospinal fluid (CSF) phosphorylated tau (p-tau)181 increase and glucose metabolism decrease. In addition, baseline SCI predicted worse clinical progression, whereas multi-domain SCI advanced faster compared to the single domain group. DISCUSSION: Baseline SCI could be an imperative prediction indicator of clinical and pathological progression. It enables cognitive measures to be informative at a very early stage and provided objective criteria for high-risk population screening.