Using blood transcriptome analysis for Alzheimer's disease diagnosis and patient stratification.

INTRODUCTION: Blood protein biomarkers demonstrate potential for Alzheimer's disease (AD) diagnosis. Limited studies examine the molecular changes in AD blood cells. METHODS: Bulk RNA-sequencing of blood cells was performed on AD patients of Chinese descent (n = 214 and 26 in the discovery and validation cohorts, respectively) with normal controls (n = 208 and 38 in the discovery and validation cohorts, respectively). Weighted gene co-expression network analysis (WGCNA) and deconvolution analysis identified AD-associated gene modules and blood cell types. Regression and unsupervised clustering analysis identified AD-associated genes, gene modules, cell types, and established AD classification models. RESULTS: WGCNA on differentially expressed genes revealed 15 gene modules, with 6 accurately classifying AD (areas under the receiver operating characteristics curve [auROCs] > 0.90). These modules stratified AD patients into subgroups with distinct disease states. Cell-type deconvolution analysis identified specific blood cell types potentially associated with AD pathogenesis. DISCUSSION: This study highlights the potential of blood transcriptome for AD diagnosis, patient stratification, and mechanistic studies. HIGHLIGHTS: We comprehensively analyze the blood transcriptomes of a well-characterized Alzheimer's disease cohort to identify genes, gene modules, pathways, and specific blood cells associated with the disease. Blood transcriptome analysis accurately classifies and stratifies patients with Alzheimer's disease, with some gene modules achieving classification accuracy comparable to that of the plasma ATN biomarkers. Immune-associated pathways and immune cells, such as neutrophils, have potential roles in the pathogenesis and progression of Alzheimer's disease.

A blood-based multi-pathway biomarker assay for early detection and staging of Alzheimer's disease across ethnic groups.

INTRODUCTION: Existing blood-based biomarkers for Alzheimer's disease (AD) mainly focus on its pathological features. However, studies on blood-based biomarkers associated with other biological processes for a comprehensive evaluation of AD status are limited. METHODS: We developed a blood-based, multiplex biomarker assay for AD that measures the levels of 21 proteins involved in multiple biological pathways. We evaluated the assay's performance for classifying AD and indicating AD-related endophenotypes in three independent cohorts from Chinese or European-descent populations. RESULTS: The 21-protein assay accurately classified AD (area under the receiver operating characteristic curve [AUC] = 0.9407 to 0.9867) and mild cognitive impairment (MCI; AUC = 0.8434 to 0.8945) while also indicating brain amyloid pathology. Moreover, the assay simultaneously evaluated the changes of five biological processes in individuals and revealed the ethnic-specific dysregulations of biological processes upon AD progression. DISCUSSION: This study demonstrated the utility of a blood-based, multi-pathway biomarker assay for early screening and staging of AD, providing insights for patient stratification and precision medicine. HIGHLIGHTS: The authors developed a blood-based biomarker assay for Alzheimer's disease. The 21-protein assay classifies AD/MCI and indicates brain amyloid pathology. The 21-protein assay can simultaneously assess activities of five biological processes. Ethnic-specific dysregulations of biological processes in AD were revealed.

Temporal associations of diabetes-related complications with health-related quality of life decrements in Chinese patients with type 2 diabetes: A prospective study among 19 322 adults-Joint Asia Diabetes Evaluation (JADE) register (2007-2018).

BACKGROUND: Patients with type 2 diabetes (T2D) are at high risk of developing multiple complications, affecting their health-related quality of life (HRQoL). Existing studies only considered impact of complication on HRQoL in the year of occurrence but not its residual impacts in subsequent years. We investigated temporal impacts of diabetes-related complications on HRQoL in a 12-year prospective cohort of ambulatory Chinese patients with T2D enrolled in the clinic-based Joint Asia Diabetes Evaluation (JADE) Register. METHODS: HRQoL utility measures were derived from EuroQol five-dimensional three-level questionnaire (EQ-5D-3L) questionnaires completed by 19 322 patients with T2D in Hong Kong (2007-2018). Temporal EQ-5D utility decrements associated with subtypes of cardiovascular-renal events were estimated using generalized linear regression model after stepwise selection of covariates with p < .01 as cutoff. RESULTS: In this cohort (mean ± SD age:61.2 ± 11.5 years, 55.3% men, median [interquartile range] duration of diabetes:10.1 [3.0-15.0] years, glycated hemoglobin [HbA1C ] 7.5 ± 1.5%), EQ-5D utility was 0.860 ± 0.163. The largest HRQoL decrements were observed in year of occurrence of hemorrhagic stroke (-0.230), followed by ischemic stroke (-0.165), peripheral vascular disease (-0.117), lower extremity amputation (-0.093), chronic kidney disease (CKD) G5 without renal replacement therapy (RRT) (-0.079), congestive heart failure (CHF) (-0.061), and CKD G3-G4 without RRT (-0.042). Residual impacts on HRQoL persisted for 2 years after occurrence of CHF or ischemic stroke and 1 year after hemorrhagic stroke or CKD G3-G4 without RRT. CONCLUSION: This is the first comprehensive report on temporal associations of HRQoL decrements with subtypes of diabetes-related complications in ambulatory Asian patients with T2D. These data will improve the accuracy of cost-effectiveness analysis of diabetes interventions at an individual level in an Asian setting.

Neuronal γ-secretase regulates synaptic functions via cholesterol homeostasis.

In this issue of Neuron, Essayan-Perez and Südhof1 demonstrate roles for γ-secretase in the regulation of synaptic functions in human neurons. Chronic attenuation of γ-secretase activity increases synapse formation but decreases neurotransmission (i.e., the probability of presynaptic release), likely due to impairment of cholesterol metabolism.

The VCAM1-ApoE pathway directs microglial chemotaxis and alleviates Alzheimer's disease pathology.

In Alzheimer's disease (AD), sensome receptor dysfunction impairs microglial danger-associated molecular pattern (DAMP) clearance and exacerbates disease pathology. Although extrinsic signals, including interleukin-33 (IL-33), can restore microglial DAMP clearance, it remains largely unclear how the sensome receptor is regulated and interacts with DAMP during phagocytic clearance. Here, we show that IL-33 induces VCAM1 in microglia, which promotes microglial chemotaxis toward amyloid-beta (Aß) plaque-associated ApoE, and leads to Aß clearance. We show that IL-33 stimulates a chemotactic state in microglia, characterized by Aß-directed migration. Functional screening identified that VCAM1 directs microglial Aß chemotaxis by sensing Aß plaque-associated ApoE. Moreover, we found that disrupting VCAM1-ApoE interaction abolishes microglial Aß chemotaxis, resulting in decreased microglial clearance of Aß. In patients with AD, higher cerebrospinal fluid levels of soluble VCAM1 were correlated with impaired microglial Aß chemotaxis. Together, our findings demonstrate that promoting VCAM1-ApoE-dependent microglial functions ameliorates AD pathology.

Receptor-ligand interaction controls microglial chemotaxis and amelioration of Alzheimer's disease pathology.

Microglia maintain brain homeostasis through their ability to survey and phagocytose danger-associated molecular patterns (DAMPs). In Alzheimer's disease (AD), microglial phagocytic clearance regulates the turnover of neurotoxic DAMPs including amyloid beta (Aß) and hyperphosphorylated tau. To mediate DAMP clearance, microglia express a repertoire of surface receptors to sense DAMPs; the activation of these receptors subsequently triggers a chemotaxis-to-phagocytosis functional transition in microglia. Therefore, the interaction between microglial receptors and DAMPs plays a critical role in controlling microglial DAMP clearance and AD pathogenesis. However, there is no comprehensive overview on how microglial sensome receptors interact with DAMPs and regulate various microglial functions, including chemotaxis and phagocytosis. In this review, we discuss the important axes of receptor-ligand interaction that control different microglial functions and their roles in AD pathogenesis. First, we summarize how the accumulation and structural changes of DAMPs trigger microglial functional impairment, including impaired DAMP clearance and aberrant synaptic pruning, in AD. Then, we discuss the important receptor-ligand axes that restore microglial DAMP clearance in AD and aging. These findings suggest that targeting microglial chemotaxis-the first critical step of the microglial chemotaxis-to-phagocytosis state transition-can promote microglial DAMP clearance in AD. Thus, our review highlights the importance of microglial chemotaxis in promoting microglial clearance activity in AD. Further detailed investigations are essential to identify the molecular machinery that controls microglial chemotaxis in AD.

Deep learning-based polygenic risk analysis for Alzheimer's disease prediction.

BACKGROUND: The polygenic nature of Alzheimer's disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual's genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Because of the complexity of genomic data, current statistical analyses cannot comprehensively capture the polygenic risk of AD, resulting in unsatisfactory disease risk prediction. However, deep learning methods, which capture nonlinearity within high-dimensional genomic data, may enable more accurate disease risk prediction and improve our understanding of AD etiology. Accordingly, we developed deep learning neural network models for modeling AD polygenic risk. METHODS: We constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk derived from deep learning methods and AD endophenotypes (i.e., plasma biomarkers and individual cognitive performance). We stratified individuals by applying unsupervised clustering to the outputs from the hidden layers of the neural network model. RESULTS: The deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms. CONCLUSION: Our results suggest that deep learning methods are effective for modeling the genetic risks of AD and other diseases, classifying disease risks, and uncovering disease mechanisms.

Polygenic diseases, such as Alzheimer's disease (AD), are those caused by the interplay between multiple genetic risk factors. Statistical models can be used to predict disease risk based on a person's genetic profile. However, there are limitations to existing methods, while emerging methods such as deep learning may improve risk prediction. Deep learning involves computer-based software learning from patterns in data to perform a certain task, e.g. predict disease risk. Here, we test whether deep learning models can help to predict AD risk. Our models not only outperformed existing methods in modeling AD risk, they also allow us to estimate an individual's risk of AD and determine the biological processes that may be involved in AD. With further testing and optimization, deep learning may be a useful tool to help accurately predict risk of AD and other diseases.

Gender-associated cardiometabolic risk profiles and health behaviors in patients with type 2 diabetes: a cross-sectional analysis of the Joint Asia Diabetes Evaluation (JADE) program.

Background: In Asia, diabetes-associated death due to cardiorenal diseases were 2-3 times higher in women than men which might be due to gender disparity in quality of care and health habits. Methods: Adults with type 2 diabetes (T2D) from 11 Asian countries/areas were assessed using the same protocol (2007-2015). We compared treatment target attainment (HbA1c < 7%, blood pressure [BP] < 130/80 mmHg, risk-based LDL-cholesterol, lack of central obesity [waist circumference <90 cm in men or <80 cm in women), use of cardiorenal-protective drugs (renin-angiotensin system [RAS] inhibitors, statins), and self-reported health habits including self-monitoring blood glucose (SMBG) by gender. Analyses were stratified by countries/areas, age of natural menopause (<50 vs. ≥50 years), and comorbidities (atherosclerotic cardiovascular disease [ASCVD], heart failure, kidney impairment [eGFR < 60 mL/min/1.73 m2]). Findings: Among 106,376 patients (53.2% men; median (interquartile range) diabetes duration: 6.0 (2.0-12.0) years; mean ± SD HbA1c 8.0 ± 1.9%; 27% insulin-treated), women were older and less likely to receive college education than men (28.9% vs. 48.8%). Women were less likely to smoke/drink alcohol and were physically less active than men. Women had lower BP (<130/80 mmHg: 29.4% vs. 25.7%), less general obesity (54.8% vs. 57.8%) but more central obesity than men (77.5% vs. 57.3%). Women were less likely to have ASCVD (12.8% vs. 17.0%) or heart failure (1.3% vs. 2.3%), but more likely to have kidney impairment (22.3% vs. 17.6%) and any-site cancer than men (2.5% vs. 1.6%). In most countries/areas, more men attained HbA1c <7% and risk-based LDL-cholesterol level than women. After adjusting for potential confounders including countries and centres, men had 1.63 odds ratio (95% CI 1.51, 1.74) of attaining ≥3 treatment targets than women. Interpretation: Asian women with T2D had worse quality of care than men especially in middle-income countries/areas, calling for targeted implementation programs to close these care gaps. Sponsor: Asia Diabetes Foundation. Funding: Nil.

Ultrasound-guided dry needling versus traditional dry needling for patients with knee osteoarthritis: A double-blind randomized controlled trial.

OBJECTIVE: To compare the effect of ultrasound (US)-guided dry needling (DN) with traditional DN in the treatment of pain and dysfunction for patients with knee osteoarthritis (KOA). DESIGN: A double-blind, randomized controlled trial. METHODS: Patients (25 male and 65 female), age 50-80 years diagnosed with KOA were recruited and randomly assigned to one of three groups in a 1:1:1 ratio for intervention: real US-guided DN with exercise therapy (G1), placebo US-guided DN with exercise therapy (G2), and exercise therapy solely (G3). G1 and G2 were blinded to the application of real or placebo US guidance by turning the monitor of US imaging out-of-view from participants' vantage points. The effectiveness of blinding was evaluated by asking the participants whether they had received real-US guided DN. The responses were assessed by Chi-square test. Visual Analogue Scale (VAS), Knee injury, and Osteoarthritis Outcome Score (KOOS) subscales (KOOS-pain, KOOS-symptoms, KOOS-quality-of-life (QoL)) were collected at baseline, 4 weeks, and 8 weeks by a blinded assessor. Data were analyzed by mixed model analysis of variance (ANOVA) with Bonferroni correction. RESULTS: Eighty-four participants (61.26±5.57 years) completed the study. G1 achieved significant improvement in VAS at 8 weeks compared to G2 and G3 (G1 vs. G2: MD = -15.61, 95% CI [-25.49, -5.51], p = 0.001; G1 vs. G3: MD = -19.90, 95% CI [-29.71, -10.08], p< 0.001). G1 achieved significant improvement in KOOS-pain at 8 weeks compared to G2 and G3 (G1 vs. G2: MD = 9.76, 95% CI [2.38, 17.14], p = 0.006; G1 vs. G3: MD = 9.48, 95% CI [2.31, 16.66], p = 0.010). KOOS-symptoms and KOOS-QoL were not statistically significant between groups. G2 had no significant difference of the perceptions as G1 with p = 0.128. G2 were successfully blinded to placebo US-guided DN. CONCLUSION: US-guided DN with exercise therapy may be more effective than traditional DN with exercise therapy or exercise therapy alone in reduce pain of KOA.

Attenuated Risk Association of End-Stage Kidney Disease with Metformin in Type 2 Diabetes with eGFR Categories 1-4.

Type 2 diabetes (T2D)-associated end-stage kidney disease (ESKD) is a global burden, while the renoprotective effects of metformin remain controversial. In a population-based cohort (2002-2018) including 96,643 patients with T2D observed for 0.7 million person-years, we estimated the risk association of metformin and its dose-relationship with ESKD in a propensity-score overlap-weighting (PS-OW) cohort by eGFR categories. Amongst 96,643, 83,881 (86.8%) had eGFR-G1/G2 (≥60 mL/min/1.73 m2), 8762 (9.1%) had eGFR-G3a (≥45-60 mL/min/1.73 m2), 3051 (3.2%) had eGFR-G3b (≥30-45 mL/min/1.73 m2), and 949 (1.0%) had eGFR-G4 (≥15-30 mL/min/1.73 m2). The respective proportions of metformin users in these eGFR categories were 95.1%, 81.9%, 53.8%, and 20.8%. In the PS-OW cohort with 88,771 new-metformin and 7872 other oral glucose-lowering-drugs (OGLDs) users, the respective incidence rates of ESKD were 2.8 versus 22.4/1000 person-years. Metformin use associated with reduced risk of ESKD (hazard ratio (HR) = 0.43 [95% CI: 0.35-0.52] in eGFR-G1/G2, 0.64 [0.52-0.79] in eGFR-G3a, 0.67 [0.56-0.80] in eGFR-G3b, and 0.63 [0.48-0.83] in eGFR-G4). Metformin use was associated with reduced or neutral risk of major adverse cardiovascular events (MACE) (7.2 versus 16.0/1000 person-years) and all-cause mortality (14.6 versus 65.1/1000 person-years). Time-weighted mean daily metformin dose was 1000 mg in eGFR-G1/G2, 850 mg in eGFR-G3a, 650 mg in eGFR-G3b, and 500 mg in eGFR-G4. In a subcohort of 14,766 patients observed for 0.1 million person-years, the respective incidence rates of lactic acidosis and HR in metformin users and non-users were 42.5 versus 226.4 events/100,000 person-years (p = 0.03) for eGFR-G1/G2 (HR = 0.57, 0.25-1.30) and 54.5 versus 300.6 events/100,000 person-years (p = 0.01) for eGFR-G3/G4 (HR = 0.49, 0.19-1.30). These real-world data underscore the major benefits and low risk of lactic acidosis with metformin use down to an eGFR of 30 mL/min/1.73 m2 and possibly even 15 mL/min/1.73 m2, while reinforcing the importance of dose adjustment and frequent monitoring of eGFR.

Combined associations of family history and self-management with age at diagnosis and cardiometabolic risk in 86,931 patients with type 2 diabetes: Joint Asia Diabetes Evaluation (JADE) Register from 11 countries.

BACKGROUND: Family history (FamH) of type 2 diabetes might indicate shared genotypes, environments, and/or behaviors. We hypothesize that FamH interacts with unhealthy behaviors to increase the risk of early onset of diabetes and poor cardiometabolic control. METHODS: In a cross-sectional analysis of the prospective Joint Asia Diabetes Evaluation Register including patients from 427 clinics in 11 Asian countries/regions in 2007-2021, we defined positive FamH as affected parents/siblings and self-management as (1) healthy lifestyles (balanced diet, non-use of alcohol and tobacco, regular physical activity) and (2) regular self-monitoring of blood glucose (SMBG). RESULTS: Among 86,931 patients with type 2 diabetes (mean±SD age: 56.6±11.6 years; age at diagnosis of diabetes: 49.8±10.5 years), the prevalence of FamH ranged from 39.1% to 85.3% in different areas with FamH affecting mother being most common (32.5%). The FamH group (n=51,705; 59.5%) was diagnosed 4.6 years earlier than the non-FamH group [mean (95% CI): 47.9 (47.8-48.0) vs. 52.5 (52.4-52.6), logrank p<0.001]. In the FamH group, patients with both parents affected had the earliest age at diagnosis [44.6 (44.5-44.8)], followed by affected single parent [47.7 (47.6-47.8)] and affected siblings only [51.5 (51.3-51.7), logrank p<0.001]. The FamH plus ≥2 healthy lifestyle group had similar age at diagnosis [48.2 (48.1-48.3)] as the non-FamH plus <2 healthy lifestyle group [50.1 (49.8-50.5)]. The FamH group with affected parents had higher odds of hyperglycemia, hypertension, and dyslipidemia than the FamH group with affected siblings, with the lowest odds in the non-FamH group. Self-management (healthy lifestyles plus SMBG) was associated with higher odds of attaining HbA1c<7%, blood pressure<130/80mmHg, and LDL-C<2.6 mmol/L especially in the FamH group (FamH×self-management, pinteraction=0.050-0.001). CONCLUSIONS: In Asia, FamH was common and associated with young age of diagnosis which might be delayed by healthy lifestyle while self management  was associated with better control of  cardiometabolic risk factors especially in those with FamH.

Multi-Omics-Based Autophagy-Related Untypical Subtypes in Patients with Cerebral Amyloid Pathology.

Recent multi-omics analyses paved the way for a comprehensive understanding of pathological processes. However, only few studies have explored Alzheimer's disease (AD) despite the possibility of biological subtypes within these patients. For this study, unsupervised classification of four datasets (genetics, miRNA transcriptomics, proteomics, and blood-based biomarkers) using Multi-Omics Factor Analysis+ (MOFA+), along with systems-biological approaches following various downstream analyses are performed. New subgroups within 170 patients with cerebral amyloid pathology (Aß+) are revealed and the features of them are identified based on the top-rated targets constructing multi-omics factors of both whole (M-TPAD) and immune-focused models (M-IPAD). The authors explored the characteristics of subtypes and possible key-drivers for AD pathogenesis. Further in-depth studies showed that these subtypes are associated with longitudinal brain changes and autophagy pathways are main contributors. The significance of autophagy or clustering tendency is validated in peripheral blood mononuclear cells (PBMCs; n = 120 including 30 Aß- and 90 Aß+), induced pluripotent stem cell-derived human brain organoids/microglia (n = 12 including 5 Aß-, 5 Aß+, and CRISPR-Cas9 apolipoprotein isogenic lines), and human brain transcriptome (n = 78). Collectively, this study provides a strategy for precision medicine therapy and drug development for AD using integrative multi-omics analysis and network modelling.

Demographics and Medication Use of Patients with Late-Onset Alzheimer's Disease in Hong Kong.

BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia in the elderly population. However, epidemiological studies on the demographics of AD in Hong Kong population are lacking. OBJECTIVE: We investigated the demographics, comorbidities, mortality rates, and medication use of patients with AD in Hong Kong to understand how the disease has been managed locally. METHODS: This was a collaborative study of The Hong Kong University of Science and Technology and the Hospital Authority Data Collaboration Lab. We analyzed the demographic data, clinical records, diagnoses, and medication records of patients with AD under the care of the Hospital Authority between January 1, 2007 and December 31, 2017. RESULTS: We identified 23,467 patients diagnosed with AD. The median age at diagnosis was 84 years old, and 71% of patients were female. The most common comorbidity was hypertension (52.6%). 39.9% of patients received medications for dementia; of those, 68.4% had taken those medications for > 1 year. Compared to nonusers, long-term AD medication users had a significantly younger age of AD onset and were taking more lipid-regulating medication, diabetes medication, or antidepressants. Surprisingly, the use of antipsychotics in patients with AD was quite common; 50.7% of patients had received any type of antipsychotic during disease progression. CONCLUSION: This study provides detailed information on the demographics and medication use of patients with AD in Hong Kong. The data from this AD cohort will aid our future research aiming to identify potential AD risk factors and associations between AD and other diseases.

Association of SPI1 Haplotypes with Altered SPI1 Gene Expression and Alzheimer's Disease Risk.

BACKGROUND: Genetic studies reveal that single-nucleotide polymorphisms (SNPs) of SPI1 are associated with Alzheimer's disease (AD), while their effects in the Chinese population remain unclear. OBJECTIVE: We aimed to examine the AD-association of SPI1 SNPs in the Chinese population and investigate the underlying mechanisms of these SNPs in modulating AD risk. METHODS: We conducted a genetic analysis of three SPI1 SNPs (i.e., rs1057233, rs3740688, and rs78245530) in a Chinese cohort (n = 333 patients with AD, n = 721 normal controls). We also probed public European-descent AD cohorts and gene expression datasets to investigate the putative functions of those SNPs. RESULTS: We showed that SPI1 SNP rs3740688 is significantly associated with AD in the Chinese population (odds ratio [OR] = 0.72 [0.58-0.89]) and identified AD-protective SPI1 haplotypes ß (tagged by rs1057233 and rs3740688) and γ (tagged by rs3740688 and rs78245530). Specifically, haplotypes ß and γ are associated with decreased SPI1 gene expression level in the blood and brain tissues, respectively. The regulatory roles of these haplotypes are potentially mediated by changes in miRNA binding and the epigenetic landscape. Our results suggest that the AD-protective SPI1 haplotypes regulate pathways involved in immune and neuronal functions. CONCLUSION: This study is the first to report a significant association of SPI1 with AD in the Chinese population. It also identifies SPI1 haplotypes that are associated with SPI1 gene expression and decreased AD risk.

Effect of a Web-Based Management Guide on Risk Factors in Patients With Type 2 Diabetes and Diabetic Kidney Disease: A JADE Randomized Clinical Trial.

Importance: Diabetic kidney disease (DKD) and its comorbidities can be prevented by treating multiple targets. Technology-assisted team-based care with regular feedback and patient empowerment can improve the attainment of multiple targets and clinical outcomes in patients with type 2 diabetes, but the effects of this intervention on patients with DKD are unclear. Objective: To evaluate the effect of the Joint Asia Diabetes Evaluation (JADE) web portal, nurse reminders, and team-based care on multiple risk factors in patients with DKD. Design, Setting, and Participants: This 12-month multinational, open-label randomized clinical trial was conducted between June 27, 2014, and February 19, 2019, at 13 hospital-based diabetes centers in 8 countries or regions in Asia. All patients who participated had DKD. The intention-to-treat data analysis was performed from April 7 to June 30, 2020. Interventions: Patients were randomized in a 1:1:1 ratio at each site to usual care, empowered care, or team-based empowered care. All patients underwent a JADE web portal-guided structured assessment at baseline and month 12. Patients in the usual care and empowered care groups received a medical follow-up. Patients in the empowered care group also received a personalized JADE report and nurse telephone calls every 3 months. Patients in the team-based empowered care group received additional face-to-face reviews every 3 months from a physician-nurse team. Main Outcomes and Measures: The primary outcome was the proportion of patients who attained multiple treatment targets (defined as ≥3 of 5 targets: HbA1c level <7.0% [53 mmol/mol], blood pressure <130/80 mm Hg, low-density lipoprotein cholesterol level <1.8 mmol/L, triglyceride level <1.7 mmol/L, and/or persistent use of renin-angiotensin-aldosterone system inhibitors). Results: A total of 2393 patients (mean [SD] age, 67.7 [9.8] years; 1267 men [52.9%]) were randomized to the usual care group (n = 795), empowered care group (n = 802), and team-based empowered care group (n = 796). At baseline, 34.7% patients (n = 830) were on 3 treatment targets. On intention-to-treat analysis, the team-based empowered care group had the highest proportion of patients who had further increase in attainment of multiple treatment targets (within-group differences: usual care group, 3.9% [95% CI, 0.0%-7.8%]; empowered care group, 1.3% [95% CI, -2.8% to 5.4%]; team-based empowered care group, 9.1% [95% CI, 4.7%-13.5%]). The team-based empowered care group was more likely to attain multiple treatment targets than the usual care group (risk ratio [RR], 1.17; 95% CI, 1.00-1.37) and the empowered care group (RR, 1.25; 95% CI, 1.06-1.48) after adjustment for site. Compared with the group that did not attain multiple treatment targets, the group that attained multiple treatment targets reported a lower incidence of cardiovascular, kidney, and cancer events (8.4% [n = 51] vs 14.5% [n = 134]; P = .004). Analysis of the per-protocol population yielded similar results. Conclusions and Relevance: This trial found that technology-assisted team-based care for 12 months improved the attainment of multiple treatment targets as well as empowerment in patients with DKD. Trial Registration: ClinicalTrials.gov Identifier: NCT02176278.

Brain-wide Cas9-mediated cleavage of a gene causing familial Alzheimer's disease alleviates amyloid-related pathologies in mice.

The pathology of familial Alzheimer's disease, which is caused by dominant mutations in the gene that encodes amyloid-beta precursor protein (APP) and in those that encode presenilin 1 and presenilin 2, is characterized by extracellular amyloid plaques and intracellular neurofibrillary tangles in multiple brain regions. Here we show that the brain-wide selective disruption of a mutated APP allele in transgenic mouse models carrying the human APP Swedish mutation alleviates amyloid-beta-associated pathologies for at least six months after a single intrahippocampal administration of an adeno-associated virus that encodes both Cas9 and a single-guide RNA that targets the mutation. We also show that the deposition of amyloid-beta, as well as microgliosis, neurite dystrophy and the impairment of cognitive performance, can all be ameliorated when the CRISPR-Cas9 construct is delivered intravenously via a modified adeno-associated virus that can cross the blood-brain barrier. Brain-wide disease-modifying genome editing could represent a viable strategy for the treatment of familial Alzheimer's disease and other monogenic diseases that affect multiple brain regions.

Large-scale plasma proteomic profiling identifies a high-performance biomarker panel for Alzheimer's disease screening and staging.

INTRODUCTION: Blood proteins are emerging as candidate biomarkers for Alzheimer's disease (AD). We systematically profiled the plasma proteome to identify novel AD blood biomarkers and develop a high-performance, blood-based test for AD. METHODS: We quantified 1160 plasma proteins in a Hong Kong Chinese cohort by high-throughput proximity extension assay and validated the results in an independent cohort. In subgroup analyses, plasma biomarkers for amyloid, tau, phosphorylated tau, and neurodegeneration were used as endophenotypes of AD. RESULTS: We identified 429 proteins that were dysregulated in AD plasma. We selected 19 "hub proteins" representative of the AD plasma protein profile, which formed the basis of a scoring system that accurately classified clinical AD (area under the curve  = 0.9690-0.9816) and associated endophenotypes. Moreover, specific hub proteins exhibit disease stage-dependent dysregulation, which can delineate AD stages. DISCUSSION: This study comprehensively profiled the AD plasma proteome and serves as a foundation for a high-performance, blood-based test for clinical AD screening and staging.

Instructive roles of astrocytes in hippocampal synaptic plasticity: neuronal activity-dependent regulatory mechanisms.

In the adult hippocampus, synaptic plasticity is important for information processing, learning, and memory encoding. Astrocytes, the most common glial cells, play a pivotal role in the regulation of hippocampal synaptic plasticity. While astrocytes were initially described as a homogenous cell population, emerging evidence indicates that in the adult hippocampus, astrocytes are highly heterogeneous and can differentially respond to changes in neuronal activity in a subregion-dependent manner to actively modulate synaptic plasticity. In this review, we summarize how local neuronal activity changes regulate the interactions between astrocytes and synapses, either by modulating the secretion of gliotransmitters and synaptogenic proteins or via contact-mediated signaling pathways. In turn, these specific responses induced in astrocytes mediate the interactions between astrocytes and neurons, thus shaping synaptic communication in the adult hippocampus. Importantly, the activation of astrocytic signaling is required for memory performance including memory acquisition and recall. Meanwhile, the dysregulation of this signaling can cause hippocampal circuit dysfunction in pathological conditions, resulting in cognitive impairment and neurodegeneration. Indeed, reactive astrocytes, which have dysregulated signaling associated with memory, are induced in the brains of patients with Alzheimer's disease (AD) and transgenic mouse model of AD. Emerging technologies that can precisely manipulate and monitor astrocytic signaling in vivo enable the examination of the specific actions of astrocytes in response to neuronal activity changes as well as how they modulate synaptic connections and circuit activity. Such findings will clarify the roles of astrocytes in hippocampal synaptic plasticity and memory in health and disease.

An IL1RL1 genetic variant lowers soluble ST2 levels and the risk effects of APOE-ε4 in female patients with Alzheimer's disease.

Changes in the levels of circulating proteins are associated with Alzheimer's disease (AD), whereas their pathogenic roles in AD are unclear. Here, we identified soluble ST2 (sST2), a decoy receptor of interleukin-33-ST2 signaling, as a new disease-causing factor in AD. Increased circulating sST2 level is associated with more severe pathological changes in female individuals with AD. Genome-wide association analysis and CRISPR-Cas9 genome editing identified rs1921622 , a genetic variant in an enhancer element of IL1RL1, which downregulates gene and protein levels of sST2. Mendelian randomization analysis using genetic variants, including rs1921622 , demonstrated that decreased sST2 levels lower AD risk and related endophenotypes in females carrying the Apolipoprotein E (APOE)-ε4 genotype; the association is stronger in Chinese than in European-descent populations. Human and mouse transcriptome and immunohistochemical studies showed that rs1921622 /sST2 regulates amyloid-beta (Aß) pathology through the modulation of microglial activation and Aß clearance. These findings demonstrate how sST2 level is modulated by a genetic variation and plays a disease-causing role in females with AD.