Genetic overlap between Alzheimer's disease and immune-mediated diseases: an atlas of shared genetic determinants and biological convergence.

The occurrence of immune disease comorbidities in Alzheimer's disease (AD) has been observed in both epidemiological and molecular studies, suggesting a neuroinflammatory basis in AD. However, their shared genetic components have not been systematically studied. Here, we composed an atlas of the shared genetic associations between 11 immune-mediated diseases and AD by analyzing genome-wide association studies (GWAS) summary statistics. Our results unveiled a significant genetic overlap between AD and 11 individual immune-mediated diseases despite negligible genetic correlations, suggesting a complex shared genetic architecture distributed across the genome. The shared loci between AD and immune-mediated diseases implicated several genes, including GRAMD1B, FUT2, ADAMTS4, HBEGF, WNT3, TSPAN14, DHODH, ABCB9, and TNIP1, all of which are protein-coding genes and thus potential drug targets. Top biological pathways enriched with these identified shared genes were related to the immune system and cell adhesion. In addition, in silico single-cell analyses showed enrichment of immune and brain cells, including neurons and microglia. In summary, our results suggest a genetic relationship between AD and the 11 immune-mediated diseases, pinpointing the existence of a shared however non-causal genetic basis. These identified protein-coding genes have the potential to serve as a novel path to therapeutic interventions for both AD and immune-mediated diseases and their comorbidities.

Identifying candidate genes and drug targets for Alzheimer's disease by an integrative network approach using genetic and brain region-specific proteomic data.

Genome-wide association studies (GWAS) have identified more than 75 genetic variants associated with Alzheimer's disease (ad). However, how these variants function and impact protein expression in brain regions remain elusive. Large-scale proteomic datasets of ad postmortem brain tissues have become available recently. In this study, we used these datasets to investigate brain region-specific molecular pathways underlying ad pathogenesis and explore their potential drug targets. We applied our new network-based tool, Edge-Weighted Dense Module Search of GWAS (EW_dmGWAS), to integrate ad GWAS statistics of 472 868 individuals with proteomic profiles from two brain regions from two large-scale ad cohorts [parahippocampal gyrus (PHG), sample size n = 190; dorsolateral prefrontal cortex (DLPFC), n = 192]. The resulting network modules were evaluated using a scale-free network index, followed by a cross-region consistency evaluation. Our EW_dmGWAS analyses prioritized 52 top module genes (TMGs) specific in PHG and 58 TMGs in DLPFC, of which four genes (CLU, PICALM, PRRC2A and NDUFS3) overlapped. Those four genes were significantly associated with ad (GWAS gene-level false discovery rate < 0.05). To explore the impact of these genetic components on TMGs, we further examined their differentially co-expressed genes at the proteomic level and compared them with investigational drug targets. We pinpointed three potential drug target genes, APP, SNCA and VCAM1, specifically in PHG. Gene set enrichment analyses of TMGs in PHG and DLPFC revealed region-specific biological processes, tissue-cell type signatures and enriched drug signatures, suggesting potential region-specific drug repurposing targets for ad.

Dissecting the shared genetic architecture between Alzheimer's disease and frailty: a cross-trait meta-analyses of genome-wide association studies.

Introduction: Frailty is the most common medical condition affecting the aging population, and its prevalence increases in the population aged 65 or more. Frailty is commonly diagnosed using the frailty index (FI) or frailty phenotype (FP) assessments. Observational studies have indicated the association of frailty with Alzheimer's disease (AD). However, the shared genetic and biological mechanism of these comorbidity has not been studied. Methods: To assess the genetic relationship between AD and frailty, we examined it at single nucleotide polymorphism (SNP), gene, and pathway levels. Results: Overall, 16 genome-wide significant loci (15 unique loci) (p meta-analysis < 5 × 10-8) and 22 genes (21 unique genes) were identified between AD and frailty using cross-trait meta-analysis. The 8 shared loci implicated 11 genes: CLRN1-AS1, CRHR1, FERMT2, GRK4, LINC01929, LRFN2, MADD, RP11-368P15.1, RP11-166N6.2, RNA5SP459, and ZNF652 between AD and FI, and 8 shared loci between AD and FFS implicated 11 genes: AFF3, C1QTNF4, CLEC16A, FAM180B, FBXL19, GRK4, LINC01104, MAD1L1, RGS12, ZDHHC5, and ZNF521. The loci 4p16.3 (GRK4) was identified in both meta-analyses. The colocalization analysis supported the results of our meta-analysis in these loci. The gene-based analysis revealed 80 genes between AD and frailty, and 4 genes were initially identified in our meta-analyses: C1QTNF4, CRHR1, MAD1L1, and RGS12. The pathway analysis showed enrichment for lipoprotein particle plasma, amyloid fibril formation, protein kinase regulator, and tau protein binding. Conclusion: Overall, our results provide new insights into the genetics of AD and frailty, suggesting the existence of non-causal shared genetic mechanisms between these conditions.

Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach.

Background: The progressive cognitive decline, an integral component of Alzheimer's disease (AD), unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and AD between different chronological points. Objective: To disentangle the normal aging effect from the AD-related accelerated cognitive decline and unravel its genetic components using a neuroimaging-based deep learning approach. Methods: We developed a deep-learning framework based on a dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline. Results: We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G > T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neurons and plays a role in controlling cell growth and differentiation. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways. Conclusions: Our deep learning model effectively extracted relevant neuroimaging features and predicted individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease.

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis-regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease.

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis- regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

The kynurenine pathway in Alzheimer's disease: a meta-analysis of central and peripheral levels.

OBJECTIVE: Changes in the kynurenine pathway are recognized in psychiatric disorders, but their role in Alzheimer's disease (AD) is less clear. We aimed to conduct a systematic review and meta-analysis to determine whether tryptophan and kynurenine pathway metabolites are altered in AD. METHODS: We performed a systematic review and random-effects meta-analyses. Inclusion criteria were studies that compared AD and cognitively normal (CN) groups and assessed tryptophan or kynurenine pathway metabolites in cerebrospinal fluid or peripheral blood. RESULTS: Twenty-two studies with a total of 1,356 participants (664 with AD and 692 CN individuals) were included. Tryptophan was decreased only in peripheral blood. The kynurenine-to-tryptophan ratio was only increased in peripheral blood of the AD group. 3-Hydroxykynurenine was decreased only in cerebrospinal fluid and showed higher variability in the CN group than the AD group. Kynurenic acid was increased in cerebrospinal fluid and decreased in peripheral blood. Finally, there were no changes in kynurenine and quinolinic acid between the groups. CONCLUSIONS: Our results suggested a shift toward the kynurenine pathway in both the brain and in the periphery, as well as a shift towards increased kynurenic acid production in the brain but decreased production in peripheral blood. In addition, our analysis indicated dissociation between the central and peripheral levels, as well as between plasma and serum for some of these metabolites. Finally, changes in the kynurenine pathway are suggested to be a core component of AD. More studies are warranted to verify and consolidate our results.

Genetic overlap between Alzheimer's disease and immune-mediated diseases: An atlas of shared genetic determinants and biological convergence.

The occurrence of immune disease comorbidities in Alzheimer's disease (AD) has been observed in both epidemiological and molecular studies, suggesting a neuroinflammatory basis in AD. However, their shared genetic components have not been systematically studied. Here, we composed an atlas of the shared genetic associations between 11 immune-mediated diseases and AD by analyzing genome-wide association studies (GWAS) summary statistics. Our results unveiled a significant genetic overlap between AD and 11 individual immune-mediated diseases despite negligible genetic correlations, suggesting a complex shared genetic architecture distributed across the genome. The shared loci between AD and immune-mediated diseases implicated several genes, including GRAMD1B, FUT2, ADAMTS4, HBEGF, WNT3, TSPAN14, DHODH, ABCB9 and TNIP1, all of which are protein-coding genes and thus potential drug targets. Top biological pathways enriched with these identified shared genes were related to the immune system and cell adhesion. In addition, in silico single-cell analyses showed enrichment of immune and brain cells, including neurons and microglia. In summary, our results suggest a genetic relationship between AD and the 11 immune-mediated diseases, pinpointing the existence of a shared however non-causal genetic basis. These identified protein-coding genes have the potential to serve as a novel path to therapeutic interventions for both AD and immune-mediated diseases and their comorbidities.

Disentangling accelerated cognitive decline from the normal aging process and unraveling its genetic components: A neuroimaging-based deep learning approach.

Background: The progressive cognitive decline that is an integral component of AD unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and Alzheimer's disease between different chronological points. Methods: We developed a deep-learning framework based on dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline. Results: We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G>T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neuron and plays a role in controlling cell growth and differentiation. In addition, MUC7 and PROL1/OPRPNon chromosome 4 were significant at the gene level. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways. Furthermore, we found that the cognitive decline slope GWAS was positively correlated with previous AD GWAS. Conclusion: Our deep learning model was demonstrated effective on extracting relevant neuroimaging features and predicting individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene. Our approach has the potential to disentangle accelerated cognitive decline from the normal aging process and to determine its related genetic factors, leveraging opportunities for early intervention.

Insulin resistance in depression: A large meta-analysis of metabolic parameters and variation.

Increased insulin resistance is recognized in psychiatric disorders, such as schizophrenia and bipolar disorder, but its occurrence in depression is less clear. Our aims were to verify if insulin resistance is altered in depression, to test the metabolic subgroup hypothesis of depression and if there are changes with antidepressants. Inclusion criteria were studies including adult subjects with depression and either a control group or follow-up after treatment with antidepressants, and assessing fasting insulin or glucose levels or the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) index. Seventy studies with 240,704 participants were included. Both insulin levels and the HOMA-IR index were increased in acute depression. Neither insulin nor the HOMA-IR index were altered during remission. Insulin was increased in atypical, but not typical depression. There was higher variation in insulin in individuals with depression than in controls. Insulin resistance did not change with antidepressant treatment. Insulin resistance is increased in depression during acute episodes. Heterogeneity was high in most of the analyses. Laboratory assessment of insulin resistance might have clinical utility in people with depression for diagnosis of the metabolic subtype and treatment selection, following precision psychiatry standards.

Polygenic Risk, Midlife Life's Simple 7, and Lifetime Risk of Stroke.

Background Recent genetic discoveries in stroke have unleashed the potential of using genetic information for risk prediction and health interventions aimed at disease prevention. We sought to estimate the lifetime risk of stroke (LTRS) by levels of genetic risk and to investigate whether optimal cardiovascular health can offset the negative impact of high genetic risk on lifetime risk of stroke. Methods and Results Study participants were 11 568 middle-aged adults (56% women, 23% Black adults), who were free of stroke at baseline and were followed up for a median of 28 years. The remaining LTRS was estimated according to levels of genetic risk based on a validated stroke polygenic risk score, and to levels of cardiovascular health based on the American Heart Association Life's Simple 7 recommendations. At age 45, individuals with high, intermediate, and low polygenic risk score had a remaining LTRS of 23.2% (95% CI, 20.8%-25.5%), 13.8% (95% CI, 11.7%-15.8%), and 9.6% (95% CI, 7.3%-11.8%), respectively. Those with both a high genetic risk and an inadequate Life's Simple 7 experienced the highest LTRS: 24.8% (95% CI, 22.0%-27.6%). Across all polygenic risk score categories, those with an optimal Life's Simple 7 had a ≈30% to 43% lower LTRS than those with an inadequate Life's Simple 7. This corresponded to almost 6 additional years lived free of stroke. Conclusions The LTRS varies by levels of polygenic risk and cardiovascular health. Maintaining an optimal cardiovascular health can partially offset a high genetic risk, emphasizing the importance of modifiable risk factors and illustrating the potential of personalizing genetic risk information to motivate lifestyle changes for stroke prevention.

The kynurenine pathway in Alzheimer's disease: a meta-analysis of central and peripheral levels

Objective: Changes in the kynurenine pathway are recognized in psychiatric disorders, but their role in Alzheimer's disease (AD) is less clear. We aimed to conduct a systematic review and meta-analysis to determine whether tryptophan and kynurenine pathway metabolites are altered in AD. Methods: We performed a systematic review and random-effects meta-analyses. Inclusion criteria were studies that compared AD and cognitively normal (CN) groups and assessed tryptophan or kynurenine pathway metabolites in cerebrospinal fluid or peripheral blood. Results: Twenty-two studies with a total of 1,356 participants (664 with AD and 692 CN individuals) were included. Tryptophan was decreased only in peripheral blood. The kynurenine-to-tryptophan ratio was only increased in peripheral blood of the AD group. 3-Hydroxykynurenine was decreased only in cerebrospinal fluid and showed higher variability in the CN group than the AD group. Kynurenic acid was increased in cerebrospinal fluid and decreased in peripheral blood. Finally, there were no changes in kynurenine and quinolinic acid between the groups. Conclusions: Our results suggested a shift toward the kynurenine pathway in both the brain and in the periphery, as well as a shift towards increased kynurenic acid production in the brain but decreased production in peripheral blood. In addition, our analysis indicated dissociation between the central and peripheral levels, as well as between plasma and serum for some of these metabolites. Finally, changes in the kynurenine pathway are suggested to be a core component of AD. More studies are warranted to verify and consolidate our results.