Genome-wide association study of rate of cognitive decline in Alzheimer's disease patients identifies novel genes and pathways

Genome-wide association studies identify novel loci in rapidly progressive Alzheimer's disease

INTRODUCTION

Recent data suggest that distinct prion-like amyloid beta and tau strains are associated with rapidly progressive Alzheimer's disease (rpAD). The role of genetic factors in rpAD is largely unknown.

METHODS

Previously known AD risk loci were examined in rpAD cases. Genome-wide association studies (GWAS) were performed to identify variants that influence rpAD.

RESULTS

We identified 115 pathology-confirmed rpAD cases and 193 clinical rpAD cases, 80% and 69% were of non-Hispanic European ancestry. Compared to the clinical cohort, pathology-confirmed rpAD had higher frequencies of apolipoprotein E (APOE) ε4 and rare missense variants in AD risk genes. A novel genome-wide significant locus (P < 5×10-8 ) was observed for clinical rpAD on chromosome 21 (rs2832546); 102 loci showed suggestive associations with pathology-confirmed rpAD (P < 1×10-5 ). DISCUSSION rpAD constitutes an extreme subtype of AD with distinct features. GWAS found previously known and novel loci associated with rpAD. Highlights Rapidly progressive Alzheimer's disease (rpAD) was defined with different criteria. Whole genome sequencing identified rare missense variants in rpAD. Novel variants were identified for clinical rpAD on chromosome 21.

Navigating the dementia landscape: Biomarkers and emerging therapies

The field of dementia research has witnessed significant developments in our understanding of neurodegenerative disorders, with a particular focus on Alzheimer's disease (AD) and Frontotemporal Dementia (FTD). Dementia, a collection of symptoms arising from the degeneration of brain cells, presents a significant healthcare challenge, especially as its prevalence escalates with age. This abstract delves into the complexities of these disorders, the role of biomarkers in their diagnosis and monitoring, as well as emerging neurophysiological insights. In the context of AD, anti-amyloid therapy has gained prominence, aiming to reduce the accumulation of amyloid-beta (Aβ) plaques in the brain, a hallmark of the disease. Notably, Leqembi recently received full FDA approval, marking a significant breakthrough in AD treatment. Additionally, ongoing phase 3 clinical trials are investigating novel therapies, including Masitinib and NE3107, focusing on cognitive and functional improvements in AD patients. In the realm of FTD, research has unveiled distinct neuropathological features, including the involvement of proteins like TDP-43 and progranulin, providing valuable insights into the diagnosis and management of this heterogeneous condition. Biomarkers, including neurofilaments and various tau fragments, have shown promise in enhancing diagnostic accuracy. Neurophysiological techniques, such as transcranial magnetic stimulation (TMS), have contributed to our understanding of AD and FTD. TMS has uncovered unique neurophysiological signatures, highlighting impaired plasticity, hyperexcitability, and altered connectivity in AD, while FTD displays differences in neurotransmitter systems, particularly GABAergic and glutamatergic circuits. Lastly, ongoing clinical trials in anti-amyloid therapy for AD, such as Simufilam, Solanezumab, Gantenerumab, and Remternetug, offer hope for individuals affected by this devastating disease, with the potential to alter the course of cognitive decline. These advancements collectively illuminate the evolving landscape of dementia research and the pursuit of effective treatments for these challenging conditions.

Identifying the joint signature of brain atrophy and gene variant scores in Alzheimer's Disease

The joint modeling of genetic data and brain imaging information allows for determining the pathophysiological pathways of neurodegenerative diseases such as Alzheimer's disease (AD). This task has typically been approached using mass-univariate methods that rely on a complete set of Single Nucleotide Polymorphisms (SNPs) to assess their association with selected image-derived phenotypes (IDPs). However, such methods are prone to multiple comparisons bias and, most importantly, fail to account for potential cross-feature interactions, resulting in insufficient detection of significant associations. Ways to overcome these limitations while reducing the number of traits aim at conveying genetic information at the gene level and capturing the integrated genetic effects of a set of genetic variants, rather than looking at each SNP individually. Their associations with brain IDPs are still largely unexplored in the current literature, though they can uncover new potential genetic determinants for brain modulations in the AD continuum. In this work, we explored an explainable multivariate model to analyze the genetic basis of the grey matter modulations, relying on the AD Neuroimaging Initiative (ADNI) phase 3 dataset. Cortical thicknesses and subcortical volumes derived from T1-weighted Magnetic Resonance were considered to describe the imaging phenotypes. At the same time the genetic counterpart was represented by gene variant scores extracted by the Sequence Kernel Association Test (SKAT) filtering model. Moreover, transcriptomic analysis was carried on to assess the expression of the resulting genes in the main brain structures as a form of validation. Results highlighted meaningful genotype-phenotype interactionsas defined by three latent components showing a significant difference in the projection scores between patients and controls. Among the significant associations, the model highlighted EPHX1 and BCAS1 gene variant scores involved in neurodegenerative and myelination processes, hence relevant for AD. In particular, the first was associated with decreased subcortical volumes and the second with decreasedtemporal lobe thickness. Noteworthy, BCAS1 is particularly expressed in the dentate gyrus. Overall, the proposed approach allowed capturing genotype-phenotype interactions in a restricted study cohort that was confirmed by transcriptomic analysis, offering insights into the underlying mechanisms of neurodegeneration in AD in line with previous findings and suggesting new potential disease biomarkers.

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.

A genome-wide search for pleiotropy in more than 100,000 harmonized longitudinal cognitive domain scores

BACKGROUND

More than 75 common variant loci account for only a portion of the heritability for Alzheimer's disease (AD). A more complete understanding of the genetic basis of AD can be deduced by exploring associations with AD-related endophenotypes.

METHODS

We conducted genome-wide scans for cognitive domain performance using harmonized and co-calibrated scores derived by confirmatory factor analyses for executive function, language, and memory. We analyzed 103,796 longitudinal observations from 23,066 members of community-based (FHS, ACT, and ROSMAP) and clinic-based (ADRCs and ADNI) cohorts using generalized linear mixed models including terms for SNP, age, SNP × age interaction, sex, education, and five ancestry principal components. Significance was determined based on a joint test of the SNP's main effect and interaction with age. Results across datasets were combined using inverse-variance meta-analysis. Genome-wide tests of pleiotropy for each domain pair as the outcome were performed using PLACO software.

RESULTS

Individual domain and pleiotropy analyses revealed genome-wide significant (GWS) associations with five established loci for AD and AD-related disorders (BIN1, CR1, GRN, MS4A6A, and APOE) and eight novel loci. ULK2 was associated with executive function in the community-based cohorts (rs157405, P = 2.19 × 10-9). GWS associations for language were identified with CDK14 in the clinic-based cohorts (rs705353, P = 1.73 × 10-8) and LINC02712 in the total sample (rs145012974, P = 3.66 × 10-8). GRN (rs5848, P = 4.21 × 10-8) and PURG (rs117523305, P = 1.73 × 10-8) were associated with memory in the total and community-based cohorts, respectively. GWS pleiotropy was observed for language and memory with LOC107984373 (rs73005629, P = 3.12 × 10-8) in the clinic-based cohorts, and with NCALD (rs56162098, P = 1.23 × 10-9) and PTPRD (rs145989094, P = 8.34 × 10-9) in the community-based cohorts. GWS pleiotropy was also found for executive function and memory with OSGIN1 (rs12447050, P = 4.09 × 10-8) and PTPRD (rs145989094, P = 3.85 × 10-8) in the community-based cohorts. Functional studies have previously linked AD to ULK2, NCALD, and PTPRD.

CONCLUSION

Our results provide some insight into biological pathways underlying processes leading to domain-specific cognitive impairment and AD, as well as a conduit toward a syndrome-specific precision medicine approach to AD. Increasing the number of participants with harmonized cognitive domain scores will enhance the discovery of additional genetic factors of cognitive decline leading to AD and related dementias.

Deep multimodality-disentangled association analysis network for imaging genetics in neurodegenerative diseases

Imaging genetics is a crucial tool that is applied to explore potentially disease-related biomarkers, particularly for neurodegenerative diseases (NDs). With the development of imaging technology, the association analysis between multimodal imaging data and genetic data is gradually being concerned by a wide range of imaging genetics studies. However, multimodal data are fused first and then correlated with genetic data in traditional methods, which leads to an incomplete exploration of their common and complementary information. In addition, the inaccurate formulation in the complex relationships between imaging and genetic data and information loss caused by missing multimodal data are still open problems in imaging genetics studies. Therefore, in this study, a deep multimodality-disentangled association analysis network (DMAAN) is proposed to solve the aforementioned issues and detect the disease-related biomarkers of NDs simultaneously. First, the imaging data are nonlinearly projected into a latent space and imaging representations can be achieved. The imaging representations are further disentangled into common and specific parts by using a multimodal-disentangled module. Second, the genetic data are encoded to achieve genetic representations, and then, the achieved genetic representations are nonlinearly mapped to the common and specific imaging representations to build nonlinear associations between imaging and genetic data through an association analysis module. Moreover, modality mask vectors are synchronously synthesized to integrate the genetic and imaging data, which helps the following disease diagnosis. Finally, the proposed method achieves reasonable diagnosis performance via a disease diagnosis module and utilizes the label information to detect the disease-related modality-shared and modality-specific biomarkers. Furthermore, the genetic representation can be used to impute the missing multimodal data with our learning strategy. Two publicly available datasets with different NDs are used to demonstrate the effectiveness of the proposed DMAAN. The experimental results show that the proposed DMAAN can identify the disease-related biomarkers, which suggests the proposed DMAAN may provide new insights into the pathological mechanism and early diagnosis of NDs. The codes are publicly available at https://github.com/Meiyan88/DMAAN.

Predictive network analysis identifies JMJD6 and other potential key drivers in Alzheimer's disease

Despite decades of genetic studies on late-onset Alzheimer's disease, the underlying molecular mechanisms remain unclear. To better comprehend its complex etiology, we use an integrative approach to build robust predictive (causal) network models using two large human multi-omics datasets. We delineate bulk-tissue gene expression into single cell-type gene expression and integrate clinical and pathologic traits, single nucleotide variation, and deconvoluted gene expression for the construction of cell type-specific predictive network models. Here, we focus on neuron-specific network models and prioritize 19 predicted key drivers modulating Alzheimer's pathology, which we then validate by knockdown in human induced pluripotent stem cell-derived neurons. We find that neuronal knockdown of 10 of the 19 targets significantly modulates levels of amyloid-beta and/or phosphorylated tau peptides, most notably JMJD6. We also confirm our network structure by RNA sequencing in the neurons following knockdown of each of the 10 targets, which additionally predicts that they are upstream regulators of REST and VGF. Our work thus identifies robust neuronal key drivers of the Alzheimer's-associated network state which may represent therapeutic targets with relevance to both amyloid and tau pathology in Alzheimer's disease.

The Association of the Polymorphisms in the FUT8-Related Locus with the Plasma Glycosylation in Post-Traumatic Stress Disorder

The molecular underpinnings of post-traumatic stress disorder (PTSD) are still unclear due to the complex interactions of genetic, psychological, and environmental factors. Glycosylation is a common post-translational modification of proteins, and different pathophysiological states, such as inflammation, autoimmune diseases, and mental disorders including PTSD, show altered N-glycome. Fucosyltransferase 8 (FUT8) is the enzyme that catalyzes the addition of core fucose on glycoproteins, and mutations in the FUT8 gene are associated with defects in glycosylation and functional abnormalities. This is the first study that investigated the associations of plasma N-glycan levels with FUT8-related rs6573604, rs11621121, rs10483776, and rs4073416 polymorphisms and their haplotypes in 541 PTSD patients and control participants. The results demonstrated that the rs6573604 T allele was more frequent in the PTSD than in the control participants. Significant associations of plasma N-glycan levels with PTSD and FUT8-related polymorphisms were observed. We also detected associations of rs11621121 and rs10483776 polymorphisms and their haplotypes with plasma levels of specific N-glycan species in both the control and PTSD groups. In carriers of different rs6573604 and rs4073416 genotypes and alleles, differences in plasma N-glycan levels were only found in the control group. These molecular findings suggest a possible regulatory role of FUT8-related polymorphisms in glycosylation, the alternations of which could partially explain the development and clinical manifestation of PTSD.

Genome-wide association study of brain biochemical phenotypes reveals distinct genetic architecture of Alzheimer's disease related proteins

BACKGROUND

Alzheimer's disease (AD) is neuropathologically characterized by amyloid-beta (Aβ) plaques and neurofibrillary tangles. The main protein components of these hallmarks include Aβ40, Aβ42, tau, phosphor-tau, and APOE. We hypothesize that genetic variants influence the levels and solubility of these AD-related proteins in the brain; identifying these may provide key insights into disease pathogenesis.

METHODS

Genome-wide genotypes were collected from 441 AD cases, imputed to the haplotype reference consortium (HRC) panel, and filtered for quality and frequency. Temporal cortex levels of five AD-related proteins from three fractions, buffer-soluble (TBS), detergent-soluble (Triton-X = TX), and insoluble (Formic acid = FA), were available for these same individuals. Variants were tested for association with each quantitative biochemical measure using linear regression, and GSA-SNP2 was used to identify enriched Gene Ontology (GO) terms. Implicated variants and genes were further assessed for association with other relevant variables.

RESULTS

We identified genome-wide significant associations at seven novel loci and the APOE locus. Genes and variants at these loci also associate with multiple AD-related measures, regulate gene expression, have cell-type specific enrichment, and roles in brain health and other neuropsychiatric diseases. Pathway analysis identified significant enrichment of shared and distinct biological pathways.

CONCLUSIONS

Although all biochemical measures tested reflect proteins core to AD pathology, our results strongly suggest that each have unique genetic architecture and biological pathways that influence their specific biochemical states in the brain. Our novel approach of deep brain biochemical endophenotype GWAS has implications for pathophysiology of proteostasis in AD that can guide therapeutic discovery efforts focused on these proteins.

Re-Addressing Dementia by Network Medicine and Mechanism-Based Molecular Endotypes

Alzheimer's disease (AD) and other forms of dementia are together a leading cause of disability and death in the aging global population, imposing a high personal, societal, and economic burden. They are also among the most prominent examples of failed drug developments. Indeed, after more than 40 AD trials of anti-amyloid interventions, reduction of amyloid-β (Aβ) has never translated into clinically relevant benefits, and in several cases yielded harm. The fundamental problem is the century-old, brain-centric phenotype-based definitions of diseases that ignore causal mechanisms and comorbidities. In this hypothesis article, we discuss how such current outdated nosology of dementia is a key roadblock to precision medicine and articulate how Network Medicine enables the substitution of clinicopathologic phenotypes with molecular endotypes and propose a new framework to achieve precision and curative medicine for patients with neurodegenerative disorders.

1-L Transcription in Alzheimer's Disease

Alzheimer’s disease is a very complex disease and better explanations and models are needed to understand how neurons are affected and microglia are activated. A new model of Alzheimer’s disease is presented here, the β-amyloid peptide is considered an important RNA recognition/binding peptide. 1-L transcription revealed compatible sequences with AAUAAA (PAS signal) and UUUC (class III ARE rich in U) in the Aβ peptide, supporting the peptide–RNA regulatory model. When a hypothetical model of fibril selection with the prionic character of amyloid assemblies is added to the peptide-RNA regulatory model, the downregulation of the PI3K-Akt pathway and the upregulation of the PLC-IP3 pathway are well explained. The model explains why neurons are less protected from inflammation and why microglia are activated; why mitochondria are destabilized; why the autophagic flux is destabilized; and why the post-transcriptional attenuation of the axonal signal “noise” is interrupted. For example, the model suggests that Aβ peptide may post-transcriptionally control ELAVL2 (ELAV-like RNA binding protein 2) and DCP2 (decapping mRNA protein 2), which are known to regulate RNA processing, transport, and stability.

Inter- and intra-chromosomal modulators of the APOE ɛ2 and ɛ4 effects on the Alzheimer's disease risk

The mechanisms of incomplete penetrance of risk-modifying impacts of apolipoprotein E (APOE) ε2 and ε4 alleles on Alzheimer's disease (AD) have not been fully understood. We performed genome-wide analysis of differences in linkage disequilibrium (LD) patterns between 6,136 AD-affected and 10,555 AD-unaffected subjects from five independent studies to explore whether the association of the APOE ε2 allele (encoded by rs7412 polymorphism) and ε4 allele (encoded by rs429358 polymorphism) with AD was modulated by autosomal polymorphisms. The LD analysis identified 24 (mostly inter-chromosomal) and 57 (primarily intra-chromosomal) autosomal polymorphisms with significant differences in LD with either rs7412 or rs429358, respectively, between AD-affected and AD-unaffected subjects, indicating their potential modulatory roles. Our Cox regression analysis showed that minor alleles of four inter-chromosomal and ten intra-chromosomal polymorphisms exerted significant modulating effects on the ε2- and ε4-associated AD risks, respectively, and identified ε2-independent (rs2884183 polymorphism, 11q22.3) and ε4-independent (rs483082 polymorphism, 19q13.32) associations with AD. Our functional analysis highlighted ε2- and/or ε4-linked processes affecting the lipid and lipoprotein metabolism and cell junction organization which may contribute to AD pathogenesis. These findings provide insights into the ε2- and ε4-associated mechanisms of AD pathogenesis, underlying their incomplete penetrance.

The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach

The common features of all neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease, are the accumulation of aggregated and misfolded proteins and the progressive loss of neurons, leading to cognitive decline and locomotive dysfunction. Still, they differ in their ultimate manifestation, the affected brain region, and the kind of proteinopathy. In the last decades, a vast number of processes have been described as associated with neurodegenerative diseases, making it increasingly harder to keep an overview of the big picture forming from all those data. In this meta-study, we analyzed genomic, transcriptomic, proteomic, and epigenomic data of the aforementioned diseases using the data of 234 studies in a network-based approach to study significant general coherences but also specific processes in individual diseases or omics levels. In the analysis part, we focus on only some of the emerging findings, but trust that the meta-study provided here will be a valuable resource for various other researchers focusing on specific processes or genes contributing to the development of neurodegeneration.

Integrated analysis of direct and proxy genome wide association studies highlights polygenicity of Alzheimer's disease outside of the APOE region

Recent meta-analyses combining direct genome-wide association studies (GWAS) with those of family history (GWAX) have indicated very low SNP heritability of Alzheimer's disease (AD). These low estimates may call into question the prospects of continued progress in genetic discovery for AD within the spectrum of common variants. We highlight dramatic downward biases in previous methods, and we validate a novel method for the estimation of SNP heritability via integration of GWAS and GWAX summary data. We apply our method to investigate the genetic architecture of AD using GWAX from UK Biobank and direct case-control GWAS from the International Genomics of Alzheimer's Project (IGAP). We estimate the liability scale common variant SNP heritability of Clinical AD outside of APOE region at ~7-11%, and we project the corresponding estimate for AD pathology to be up to approximately 23%. We estimate that nearly 90% of common variant SNP heritability of Clinical AD exists outside the APOE region. Rare variants not tagged in standard GWAS may account for additional variance. Our results indicate that, while GWAX for AD in UK Biobank may result in greater attenuation of genetic effects beyond that conventionally assumed, it does not introduce appreciable contamination of signal by genetically distinct traits relative to direct case-control GWAS in IGAP. Genetic risk for AD represents a strong effect of APOE superimposed upon a highly polygenic background.

MSR1 and NEP Are Correlated with Alzheimer's Disease Amyloid Pathology and Apolipoprotein Alterations

BACKGROUND

In mouse models of amyloidosis, macrophage receptor 1 (MSR1) and neprilysin (NEP) have been shown to interact to reduce amyloid burden in the brain.

OBJECTIVE

The purpose of this study is to analyze these two gene products in combination with apolipoproteins and Aβ1-42 in the cerebrospinal fluid (CSF) and plasma of individuals at different stages of Alzheimer's disease (AD), as well as in autopsied brain samples from ROSMAP (Religious Orders Study and Memory and Aging Project).

METHODS

CSF/plasma levels of MSR1 and NEP were measured using the sensitive primer extension assay technology. CSF Aβ1-42 was assessed with ELISA, while CSF ApoE and ApoJ were measured with the Luminex's multiplex technology. Brain MSR1, APOE, and CLU (APOJ) mRNA levels were measured with RNA-Seq and contrasted to amyloid plaques pathology using CERAD staging.

RESULTS

While plasma and CSF MSR1 levels are significantly correlated, this correlation was not observed for NEP. In addition to be highly correlated to one another, CSF levels of both MSR1 and NEP are strongly correlated with AD status and CSF Aβ1-42, ApoE, and ApoJ levels. In the cortical tissues of subjects from ROSMAP, MSR1 mRNA levels are correlated with CLU mRNA levels and the CERAD scores but not with APOE mRNA levels.

CONCLUSION

The discrepancies observed between CSF/plasma levels of MSR1 and NEP with CSF Aβ1-42 and ApoE concentrations can be explained by many factors, such as the disease stage or the involvement of the blood-brain barrier breakdown that leads to the infiltration of peripheral monocytes or macrophages.

Macrophage mitochondrial bioenergetics and tissue invasion are boosted by an Atossa-Porthos axis in Drosophila

Cellular metabolism must adapt to changing demands to enable homeostasis. During immune responses or cancer metastasis, cells leading migration into challenging environments require an energy boost, but what controls this capacity is unclear. Here, we study a previously uncharacterized nuclear protein, Atossa (encoded by CG9005), which supports macrophage invasion into the germband of Drosophila by controlling cellular metabolism. First, nuclear Atossa increases mRNA levels of Porthos, a DEAD‐box protein, and of two metabolic enzymes, lysine‐α‐ketoglutarate reductase (LKR/SDH) and NADPH glyoxylate reductase (GR/HPR), thus enhancing mitochondrial bioenergetics. Then Porthos supports ribosome assembly and thereby raises the translational efficiency of a subset of mRNAs, including those affecting mitochondrial functions, the electron transport chain, and metabolism. Mitochondrial respiration measurements, metabolomics, and live imaging indicate that Atossa and Porthos power up OxPhos and energy production to promote the forging of a path into tissues by leading macrophages. Since many crucial physiological responses require increases in mitochondrial energy output, this previously undescribed genetic program may modulate a wide range of cellular behaviors.

Hypoglycemic activity of Codonopsis pilosula (Franch.) Nannf. in vitro and in vivo and its chemical composition identification by UPLC-Triple-TOF-MS/MS

Codonopsis pilosula (Franch.) Nannf. (CPN), mainly planted in the northwest region, is a traditional Chinese medicine/good health food for nourishing qi and promoting blood circulation. This study firstly evaluated the inhibitory effects of the CPN extraction (CPNE) on α-glucosidase in vitro and in vivo, and tentatively confirmed its chemical ingredients by employing UHPLC-Triple-TOF-MS/MS. The CPNE had strong inhibitory activities against mammalian α-glucosidase (sucrase and maltase) and yeast α-glycosidase with semi-inhibitory concentrations (IC₅₀) of 0.241 mg mL^-1, 0.326 mg mL^-1 and 1.167 mg mL^-1, respectively. In addition, the CPNE could significantly decrease the postprandial blood glucose (PBG) levels in the sucrose/maltose/starch tolerance assays of diabetic mice. Furthermore, a total of 29 compounds, including 3 alkaloids, 13 phenolic acids, 8 alcohol glycosides and 5 alkynosides, were assigned based on comparison with the standards and references, as well as the analysis of main fragments. These results demonstrated that CPN could be used as an adjuvant therapy or dietary supplements to effectively control the occurrence and development of diabetes.

Mapping the serum proteome to neurological diseases using whole genome sequencing

Despite the increasing global burden of neurological disorders, there is a lack of effective diagnostic and therapeutic biomarkers. Proteins are often dysregulated in disease and have a strong genetic component. Here, we carry out a protein quantitative trait locus analysis of 184 neurologically-relevant proteins, using whole genome sequencing data from two isolated population-based cohorts (N = 2893). In doing so, we elucidate the genetic landscape of the circulating proteome and its connection to neurological disorders. We detect 214 independently-associated variants for 107 proteins, the majority of which (76%) are cis-acting, including 114 variants that have not been previously identified. Using two-sample Mendelian randomisation, we identify causal associations between serum CD33 and Alzheimer's disease, GPNMB and Parkinson's disease, and MSR1 and schizophrenia, describing their clinical potential and highlighting drug repurposing opportunities.

Admixture mapping reveals the association between Native American ancestry at 3q13.11 and reduced risk of Alzheimer's disease in Caribbean Hispanics

BACKGROUND

Genetic studies have primarily been conducted in European ancestry populations, identifying dozens of loci associated with late-onset Alzheimer's disease (AD). However, much of AD's heritability remains unexplained; as the prevalence of AD varies across populations, the genetic architecture of the disease may also vary by population with the presence of novel variants or loci.

METHODS

We conducted genome-wide analyses of AD in a sample of 2565 Caribbean Hispanics to better understand the genetic contribution to AD in this population. Statistical analysis included both admixture mapping and association testing. Evidence for differential gene expression within regions of interest was collected from independent transcriptomic studies comparing AD cases and controls in samples with primarily European ancestry.

RESULTS

Our genome-wide association study of AD identified no loci reaching genome-wide significance. However, a genome-wide admixture mapping analysis that tests for association between a haplotype's ancestral origin and AD status detected a genome-wide significant association with chromosome 3q13.11 (103.7-107.7Mb, P = 8.76E-07), driven by a protective effect conferred by the Native American ancestry (OR = 0.58, 95%CI = 0.47-0.73). Within this region, two variants were significantly associated with AD after accounting for the number of independent tests (rs12494162, P = 2.33E-06; rs1731642, P = 6.36E-05). The significant admixture mapping signal is composed of 15 haplotype blocks spanning 5 protein-coding genes (ALCAM, BBX, CBLB, CCDC54, CD47) and four brain-derived topologically associated domains, and includes markers significantly associated with the expression of ALCAM, BBX, CBLB, and CD47 in the brain. ALCAM and BBX were also significantly differentially expressed in the brain between AD cases and controls with European ancestry.

CONCLUSION

These results provide multiethnic evidence for a relationship between AD and multiple genes at 3q13.11 and illustrate the utility of leveraging genetic ancestry diversity via admixture mapping for new insights into AD.

Extraction, purification, structural characteristics and biological properties of the polysaccharides from Codonopsis pilosula: A review

Codonopsis pilosula (Franch.) Nannf., as a well-known homology plant of medicine and food, has the function of replenishing the Qi, strengthening the spleen and tonifying the lung, nourishing the blood and engendering the liquid in traditional Chinese medicine. Accumulating evidence has demonstrated that the C. pilosula polysaccharides (CPPs) are one of the major and representative pharmacologically active macromolecules and present multiple biological activities both in vitro and in vivo methods, such as immunomodulatory, antitumor, antioxidant, neuroprotective, antiviral, anti-inflammatory, anti-fatigue, hypoglycemic, anti-hypoxia, renoprotective, gastroprotective, hepatoprotective, and prebiotic. The purpose of the present review is to provide comprehensively and systematically reorganized information in the extraction and purification, structure characterization, biological activities and the underlying mechanisms of action as well as toxicities of CPPs to support their therapeutic potentials and sanitarian functions. New valuable insights for the future researches regarding CPPs were also proposed in the fields of therapeutic agents and functional foods.