Sex-Specific Cross Tissue Meta-Analysis Identifies Immune Dysregulation in Women With Alzheimer's Disease

Relationship between sex biases in gene expression and sex biases in autism and Alzheimer's disease

BACKGROUND

Sex differences in the brain may play an important role in sex-differential prevalence of neuropsychiatric conditions.

METHODS

In order to understand the transcriptional basis of sex differences, we analyzed multiple, large-scale, human postmortem brain RNA-Seq datasets using both within-region and pan-regional frameworks.

RESULTS

We find evidence of sex-biased transcription in many autosomal genes, some of which provide evidence for pathways and cell population differences between chromosomally male and female individuals. These analyses also highlight regional differences in the extent of sex-differential gene expression. We observe an increase in specific neuronal transcripts in male brains and an increase in immune and glial function-related transcripts in female brains. Integration with single-nucleus data suggests this corresponds to sex differences in cellular states rather than cell abundance. Integration with case-control gene expression studies suggests a female molecular predisposition towards Alzheimer's disease, a female-biased disease. Autism, a male-biased diagnosis, does not exhibit a male predisposition pattern in our analysis.

CONCLUSION

Overall, these analyses highlight mechanisms by which sex differences may interact with sex-biased conditions in the brain. Furthermore, we provide region-specific analyses of sex differences in brain gene expression to enable additional studies at the interface of gene expression and diagnostic differences.

The characteristics of brain atrophy prior to the onset of Alzheimer's disease: a longitudinal study

Objective

We aimed to use the onset time of Alzheimer's disease (AD) as the reference time to longitudinally investigate the atrophic characteristics of brain structures prior to the onset of AD.

Materials and methods

A total of 328 participants from the ADNI database with clear onset of AD and structural imaging data were included in our study. The time before the onset of AD (abbreviated as BAD) was calculated. We investigated the longitudinal brain changes in 97 regions using multivariate linear mixed effects regression models.

Results

The average BAD was -28.15 months, with a range from -156 to 0 months. The 54 brain regions showed significant atrophy prior to the onset of AD, and these regions were mainly distributed in the frontal and temporal lobes. The parietal and occipital lobe exhibited relatively less atrophy than the other brain lobes. Sex, age, and magnetic field strength had greater direct impacts on structural indicators than APOE genotype and education. The analysis of interaction effects revealed that the APOE ε4 mutation carriers exhibited more severe structural changes in specific brain regions as the BAD increased. However, sex, age, and education had minimal regulatory influence on the structural changes associated with BAD.

Conclusion

Longitudinal analysis, with the onset time point of AD as the reference, can accurately describe the features of structural changes preceding the onset of AD and provide a comprehensive understanding of AD development.

Alzheimer's disease as a women's health challenge: a call for action on integrative precision medicine approaches

Alzheimer's Disease (AD) is marked by pronounced sex differences in pathophysiology and progression. However, the field has yet to fully recognize AD as a women's health issue, delaying the development of targeted preventative strategies and treatments. This perspective explores the elements impacting AD in women, identifying sex specificity in risk factors, highlighting new diagnostic approaches with electronic health records, and reviewing key molecular studies to underscore the need for integrative precision medicine approaches. Established AD risk factors such as advancing age, the apolipoprotein E4 allele, and poorer cardiovascular health affect women differently. We also shed light on sociocultural risk factors, focusing on the gender disparities that may play a role in AD development. From a biological perspective, sex differences in AD are apparent in biomarkers and transcriptomics, further emphasizing the need for targeted diagnostics and treatments. The convergence of novel multiomics data and cutting-edge computational tools provides a unique opportunity to study the molecular underpinnings behind sex dimorphism in AD. Thus, precision medicine emerges as a promising framework for understanding AD pathogenesis through the integration of genetics, sex, environment, and lifestyle. By characterizing AD as a women's health challenge, we can catalyze a transformative shift in AD research and care, marked by improved diagnostic accuracy, targeted interventions, and ultimately, enhanced clinical outcomes.

Do microbes play a role in Alzheimer's disease?

Alzheimer's disease is a complex and progressive condition that affects essential neurological functions such as memory and reasoning. In the brain, neuronal loss, synaptic dysfunction, proteinopathy, neurofibrillary tangles, and neuroinflammation are the hallmarks of Alzheimer's disease pathophysiology. In addition, recent evidence has highlighted that microbes, whether commensal or pathogenic, also have the ability to interact with their host and to regulate its immune system, therefore participating in the exchanges that lead to peripheral inflammation and neuropathology. Because of this intimate relationship, bacteria, viruses, fungi, and protozoa have been implicated in the development of Alzheimer's disease. Here, we bring together current and most recent evidence of the role of microbes in Alzheimer's disease, raising burning questions that need to be addressed to guide therapeutic approaches and potential prophylactic strategies.

CSF proteomic profiling with amyloid/tau positivity identifies distinctive sex-different alteration of multiple proteins involved in Alzheimer's disease

In Alzheimer's disease (AD), the most common cause of dementia, females have higher prevalence and faster progression, but sex-specific molecular findings in AD are limited. Here, we comprehensively examined and validated 7,006 aptamers targeting 6,162 proteins in cerebral spinal fluid (CSF) from 2,077 amyloid/tau positive cases and controls to identify sex-specific proteomic signatures of AD. In discovery (N=1,766), we identified 330 male-specific and 121 female-specific proteomic alternations in CSF (FDR <0.05). These sex-specific proteins strongly predicted amyloid/tau positivity (AUC=0.98 in males; 0.99 in females), significantly higher than those with age, sex, and APOE-ε4 (AUC=0.85). The identified sex-specific proteins were well validated (r≥0.5) in the Stanford study (N=108) and Emory study (N=148). Biological follow-up of these proteins led to sex differences in cell-type specificity, pathways, interaction networks, and drug targets. Male-specific proteins, enriched in astrocytes and oligodendrocytes, were involved in postsynaptic and axon-genesis. The male network exhibited direct connections among 152 proteins and highlighted PTEN, NOTCH1, FYN, and MAPK8 as hubs. Drug target suggested melatonin (used for sleep-wake cycle regulation), nabumetone (used for pain), daunorubicin, and verteporfin for treating AD males. In contrast, female-specific proteins, enriched in neurons, were involved in phosphoserine residue binding including cytokine activities. The female network exhibits strong connections among 51 proteins and highlighted JUN and 14-3-3 proteins (YWHAG and YWHAZ) as hubs. Drug target suggested biperiden (for muscle control of Parkinson's disease), nimodipine (for cerebral vasospasm), quinostatin and ethaverine for treating AD females. Together, our findings provide mechanistic understanding of sex differences for AD risk and insights into clinically translatable interventions.

Single cell transcriptome analysis of the THY-Tau22 mouse model of Alzheimer's disease reveals sex-dependent dysregulations

Alzheimer's disease (AD) progression and pathology show pronounced sex differences, but the factors driving these remain poorly understood. To gain insights into early AD-associated molecular changes and their sex dependency for tau pathology in the cortex, we performed single-cell RNA-seq in the THY-Tau22 AD mouse model. By examining cell type-specific and cell type-agnostic AD-related gene activity changes and their sex-dimorphism for individual genes, pathways and cellular sub-networks, we identified both statistically significant alterations and interpreted the upstream mechanisms controlling them. Our results confirm several significant sex-dependent alterations in gene activity in the THY-Tau22 model mice compared to controls, with more pronounced alterations in females. Both changes shared across multiple cell types and cell type-specific changes were observed. The differential genes showed significant over-representation of known AD-relevant processes, such as pathways associated with neuronal differentiation, programmed cell death and inflammatory responses. Regulatory network analysis of these genes revealed upstream regulators that modulate many of the downstream targets with sex-dependent changes. Most key regulators have been previously implicated in AD, such as Egr1, Klf4, Chchd2, complement system genes, and myelin-associated glycoproteins. Comparing with similar data from the Tg2576 AD mouse model and human AD patients, we identified multiple genes with consistent, cell type-specific and sex-dependent alterations across all three datasets. These shared changes were particularly evident in the expression of myelin-associated genes such as Mbp and Plp1 in oligodendrocytes. In summary, we observed significant cell type-specific transcriptomic changes in the THY-Tau22 mouse model, with a strong over-representation of known AD-associated genes and processes. These include both sex-neutral and sex-specific patterns, characterized by consistent shifts in upstream master regulators and downstream target genes. Collectively, these findings provide insights into mechanisms influencing sex-specific susceptibility to AD and reveal key regulatory proteins that could be targeted for developing treatments addressing sex-dependent AD pathology.

Pleiotropy with sex-specific traits reveals genetic aspects of sex differences in Parkinson's disease

Parkinson's disease is an age-related neurodegenerative disorder with a higher incidence in males than females. The causes for this sex difference are unknown. Genome-wide association studies (GWAS) have identified 90 Parkinson's disease risk loci, but the genetic studies have not found sex-specific differences in allele frequency on autosomal chromosomes or sex chromosomes. Genetic variants, however, could exert sex-specific effects on gene function and regulation of gene expression. To identify genetic loci that might have sex-specific effects, we studied pleiotropy between Parkinson's disease and sex-specific traits. Summary statistics from GWASs were acquired from large-scale consortia for Parkinson's disease (n cases = 13 708; n controls = 95 282), age at menarche (n = 368 888 females) and age at menopause (n = 69 360 females). We applied the conditional/conjunctional false discovery rate (FDR) method to identify shared loci between Parkinson's disease and these sex-specific traits. Next, we investigated sex-specific gene expression differences in the superior frontal cortex of both neuropathologically healthy individuals and Parkinson's disease patients (n cases = 61; n controls = 23). To provide biological insights to the genetic pleiotropy, we performed sex-specific expression quantitative trait locus (eQTL) analysis and sex-specific age-related differential expression analysis for genes mapped to Parkinson's disease risk loci. Through conditional/conjunctional FDR analysis we found 11 loci shared between Parkinson's disease and the sex-specific traits age at menarche and age at menopause. Gene-set and pathway analysis of the genes mapped to these loci highlighted the importance of the immune response in determining an increased disease incidence in the male population. Moreover, we highlighted a total of nine genes whose expression or age-related expression in the human brain is influenced by genetic variants in a sex-specific manner. With these analyses we demonstrated that the lack of clear sex-specific differences in allele frequencies for Parkinson's disease loci does not exclude a genetic contribution to differences in disease incidence. Moreover, further studies are needed to elucidate the role that the candidate genes identified here could have in determining a higher incidence of Parkinson's disease in the male population.

A case for seeking sex-specific treatments in Alzheimer's disease

There is no satisfactory explanation for the sex-related differences in the incidence of many diseases and this is also true of Alzheimer's disease (AD), where females have a higher lifetime risk of developing the disease and make up about two thirds of the AD patient population. The importance of understanding the cause(s) that account for this disproportionate distribution cannot be overestimated, and is likely to be a significant factor in the search for therapeutic strategies that will combat the disease and, furthermore, potentially point to a sex-targeted approach to treatment. This review considers the literature in the context of what is known about the impact of sex on processes targeted by drugs that are in clinical trial for AD, and existing knowledge on differing responses of males and females to these drugs. Current knowledge strongly supports the view that trials should make assessing sex-related difference in responses a priority with a focus on exploring the sex-stratified treatments.

Complement-mediated synapse loss in Alzheimer's disease: mechanisms and involvement of risk factors

The complement system is increasingly recognized as a key player in the synapse loss and cognitive impairments observed in Alzheimer's disease (AD). In particular, the process of complement-dependent synaptic pruning through phagocytosis is over-activated in AD brains, driving detrimental excessive synapse elimination and contributing to synapse loss, which is the strongest neurobiological correlate of cognitive impairments in AD. Herein we review recent advances in characterizing complement-mediated synapse loss in AD, summarize the underlying mechanisms, and discuss the possible involvement of AD risk factors such as aging and various risk genes. We conclude with an overview of key questions that remain to be addressed.

Large-scale gene expression changes in APP/PSEN1 and GFAP mutation models exhibit high congruence with Alzheimer's disease

Alzheimer's disease (AD) is a complex neurodegenerative disorder with both genetic and non-genetic causes. Animal research models are available for a multitude of diseases and conditions affecting the central nervous system (CNS), and large-scale CNS gene expression data exist for many of these. Although there are several models specifically for AD, each recapitulates different aspects of the human disease. In this study we evaluate over 500 animal models to identify those with CNS gene expression patterns matching human AD datasets. Approaches included a hypergeometric based scoring system that rewards congruent gene expression patterns but penalizes discordant gene expression patterns. The top two models identified were APP/PS1 transgenic mice expressing mutant APP and PSEN1, and mice carrying a GFAP mutation that is causative of Alexander disease, a primary disorder of astrocytes in the CNS. The APP/PS1 and GFAP models both matched over 500 genes moving in the same direction as in human AD, and both had elevated GFAP expression and were highly congruent with one another. Also scoring highly were the 5XFAD model (with five mutations in APP and PSEN1) and mice carrying CK-p25, APP, and MAPT mutations. Animals with the APOE3 and 4 mutations combined with traumatic brain injury ranked highly. Bulbectomized rats scored high, suggesting anosmia could be causative of AD-like gene expression. Other matching models included the SOD1G93A strain and knockouts for SNORD116 (Prader-Willi mutation), GRID2, INSM1, XBP1, and CSTB. Many top models demonstrated increased expression of GFAP, and results were similar across multiple human AD datasets. Heatmap and Uniform Manifold Approximation Plot results were consistent with hypergeometric ranking. Finally, some gene manipulation models, including for TYROBP and ATG7, were identified with reversed AD patterns, suggesting possible neuroprotective effects. This study provides insight for the pathobiology of AD and the potential utility of available animal models.

Transcriptomics Meta-Analysis Reveals Phagosome and Innate Immune System Dysfunction as Potential Mechanisms in the Cortex of Alzheimer's Disease Mouse Strains

Immune-related pathways can affect the immune system directly, such as the chemokine signaling pathway, or indirectly, such as the phagosome pathway. Alzheimer's disease (AD) is reportedly associated with several immune-related pathways. However, exploring its underlying mechanism is challenging in animal studies because AD mouse strains differentially express immune-related pathway characteristics. To overcome this problem, we performed a meta-analysis to identify significant and consistent immune-related AD pathways that are expressed in different AD mouse strains. Next-generation RNA sequencing (RNA-seq) and microarray datasets for the cortex of AD mice from different strains such as APP/PSEN1, APP/PS2, 3xTg, TREM, and 5xFAD were collected from the NCBI GEO database. Each dataset's quality control and normalization were already processed from each original study source using various methods depending on the high-throughput analysis platform (FastQC, median of ratios, RMA, between array normalization). Datasets were analyzed using DESeq2 for RNA-seq and GEO2R for microarray to identify differentially expressed (DE) genes. Significantly DE genes were meta-analyzed using Stouffer's method, with significant genes further analyzed for functional enrichment. Ten datasets representing 20 conditions were obtained from the NCBI GEO database, comprising 116 control and 120 AD samples. The DE analysis identified 284 significant DE genes. The meta-analysis identified three significantly enriched immune-related AD pathways: phagosome, the complement and coagulation cascade, and chemokine signaling. Phagosomes-related genes correlated with complement and immune system. Meanwhile, phagosomes and chemokine signaling genes overlapped with B cells receptors pathway genes indicating potential correlation between phagosome, chemokines, and adaptive immune system as well. The transcriptomic meta-analysis showed that AD is associated with immune-related pathways in the brain's cortex through the phagosome, complement and coagulation cascade, and chemokine signaling pathways. Interestingly, phagosome and chemokine signaling pathways had potential correlation with B cells receptors pathway.

Relationship between sex biases in gene expression and sex biases in autism and Alzheimer's disease

Sex differences in the brain may play an important role in sex-differential prevalence of neuropsychiatric conditions. In order to understand the transcriptional basis of sex differences, we analyzed multiple, large-scale, human postmortem brain RNA-seq datasets using both within-region and pan-regional frameworks. We find evidence of sex-biased transcription in many autosomal genes, some of which provide evidence for pathways and cell population differences between chromosomally male and female individuals. These analyses also highlight regional differences in the extent of sex-differential gene expression. We observe an increase in specific neuronal transcripts in male brains and an increase in immune and glial function-related transcripts in female brains. Integration with single-cell data suggests this corresponds to sex differences in cellular states rather than cell abundance. Integration with case-control gene expression studies suggests a female molecular predisposition towards Alzheimer's disease, a female-biased disease. Autism, a male-biased diagnosis, does not exhibit a male predisposition pattern in our analysis. Finally, we provide region specific analyses of sex differences in brain gene expression to enable additional studies at the interface of gene expression and diagnostic differences.

Single-cell sequencing of entorhinal cortex reveals widespread disruption of neuropeptide networks in Alzheimer's disease

INTRODUCTION

Abnormalities of neuropeptides (NPs) that play important roles in modulating neuronal activities are commonly observed in Alzheimer's disease (AD). We hypothesize that NP network disruption is widespread in AD brains.

METHODS

Single-cell transcriptomic data from the entorhinal cortex (EC) were used to investigate the NP network disruption in AD. Bulk RNA-sequencing data generated from the temporal cortex by independent groups and machine learning were employed to identify key NPs involved in AD. The relationship between aging and AD-associated NP (ADNP) expression was studied using GTEx data.

RESULTS

The proportion of cells expressing NPs but not their receptors decreased significantly in AD. Neurons expressing higher level and greater diversity of NPs were disproportionately absent in AD. Increased age coincides with decreased ADNP expression in the hippocampus.

DISCUSSION

NP network disruption is widespread in AD EC. Neurons expressing more NPs may be selectively vulnerable to AD. Decreased expression of NPs participates in early AD pathogenesis. We predict that the NP network can be harnessed for treatment and/or early diagnosis of AD.

Sex difference in biological change and mechanism of Alzheimer’s disease: from macro- to micro-landscape

Alzheimer's disease (AD) is the most common form of dementia and numerous studies reported a higher prevalence and incidence of AD among women. Although women have longer lifetime, longevity does not wholly explain the higher frequency and lifetime risk in women. It is important to understand sex differences in AD pathophysiology and pathogenesis, which could provide foundation for future clinical AD research. Here, we reviewed the most recent and relevant literature on sex differences in biological change of AD from macroscopical neuroimaging to microscopical pathologic change (neuronal degeneration, synaptic dysfunction, amyloid-beta and tau accumulation). We also discussed sex differences in cellular mechanisms related to AD (neuroinflammation, mitochondria dysfunction, oxygen stress, apoptosis, autophagy, blood-brain-barrier dysfunction, gut microbiome alteration, bulk and single cell/nucleus omics) and possible causes underlying these differences including sex-chromosome, sex hormone and hypothalamic-pituitary- adrenal (HPA) axis effects.

Expanding the scope of health disparities research in Alzheimer's disease and related dementias: Recommendations from the "Leveraging Existing Data and Analytic Methods for Health Disparities Research Related to Aging and Alzheimer's Disease and Related Dementias" Workshop Series

Topics discussed at the "Leveraging Existing Data and Analytic Methods for Health Disparities Research Related to Aging and Alzheimer's Disease and Related Dementias" workshop, held by Duke University and the Alzheimer's Association with support from the National Institute on Aging, are summarized.  Ways in which existing data resources paired with innovative applications of both novel and well-known methodologies can be used to identify the effects of multi-level societal, community, and individual determinants of race/ethnicity, sex, and geography-related health disparities in Alzheimer's disease and related dementia are proposed.  Current literature on the population analyses of these health disparities is summarized with a focus on identifying existing gaps in knowledge, and ways to mitigate these gaps using data/method combinations are discussed at the workshop.  Substantive and methodological directions of future research capable of advancing health disparities research related to aging are formulated.

Sex-specific biomarkers in Alzheimer's disease progression: Framingham Heart Study

Background

Sex differences in Alzheimer's disease (AD) are not well understood.

Methods

We performed sex-specific analyses of AD and annualized cognitive decline with clinical and blood biomarker data in participants 60+ years old in the community-based longitudinal Framingham Heart Study Offspring Cohort (n = 1398, mean age 68 years, 55% women).

Results

During 11 years of follow-up, women were 96% more likely than men to be diagnosed with clinical AD dementia after adjusting for age and education in the younger age group 60 to 70 years (n = 946; 95% confidence interval [CI], 1.08 to 3.56) although not in the older age group (70+) (n = 452; hazard ratio = 0.98; 95% CI, 0.68 to 1.53). Sex-differences in incident AD rates decreased with increasing levels of education. The total contribution of the biomarkers to AD risk variance was 7.6% in women and 11.7% in men. One unit (pg/ml) lower plasma Aβ42 was associated with 0.0095 unit faster memory decline in women (p = 0.0002) but not in men (p = 0.55) after adjusting for age and education.

Discussion

Our study suggests that both early life and later-life pathological factors may contribute to potential sex differences in incident AD.

Alzheimer's disease large-scale gene expression portrait identifies exercise as the top theoretical treatment

Alzheimer's disease (AD) is a complex neurodegenerative disorder that affects multiple brain regions and is difficult to treat. In this study we used 22 AD large-scale gene expression datasets to identify a consistent underlying portrait of AD gene expression across multiple brain regions. Then we used the portrait as a platform for identifying treatments that could reverse AD dysregulated expression patterns. Enrichment of dysregulated AD genes included multiple processes, ranging from cell adhesion to CNS development. The three most dysregulated genes in the AD portrait were the inositol trisphosphate kinase, ITPKB (upregulated), the astrocyte specific intermediate filament protein, GFAP (upregulated), and the rho GTPase, RHOQ (upregulated). 41 of the top AD dysregulated genes were also identified in a recent human AD GWAS study, including PNOC, C4B, and BCL11A. 42 transcription factors were identified that were both dysregulated in AD and that in turn affect expression of other AD dysregulated genes. Male and female AD portraits were highly congruent. Out of over 250 treatments, three datasets for exercise or activity were identified as the top three theoretical treatments for AD via reversal of large-scale gene expression patterns. Exercise reversed expression patterns of hundreds of AD genes across multiple categories, including cytoskeleton, blood vessel development, mitochondrion, and interferon-stimulated related genes. Exercise also ranked as the best treatment across a majority of individual region-specific AD datasets and meta-analysis AD datasets. Fluoxetine also scored well and a theoretical combination of fluoxetine and exercise reversed 549 AD genes. Other positive treatments included curcumin. Comparisons of the AD portrait to a recent depression portrait revealed a high congruence of downregulated genes in both. Together, the AD portrait provides a new platform for understanding AD and identifying potential treatments for AD.

Distinct sex-specific DNA methylation differences in Alzheimer's disease

BACKGROUND

Sex is increasingly recognized as a significant factor contributing to the biological and clinical heterogeneity in AD. There is also growing evidence for the prominent role of DNA methylation (DNAm) in Alzheimer's disease (AD).

METHODS

We studied sex-specific DNA methylation differences in the blood samples of AD subjects compared to cognitively normal subjects, by performing sex-specific meta-analyses of two large blood-based epigenome-wide association studies (ADNI and AIBL), which included DNA methylation data for a total of 1284 whole blood samples (632 females and 652 males). Within each dataset, we used two complementary analytical strategies, a sex-stratified analysis that examined methylation to AD associations in male and female samples separately, and a methylation-by-sex interaction analysis that compared the magnitude of these associations between different sexes. After adjusting for age, estimated immune cell type proportions, batch effects, and correcting for inflation, the inverse-variance fixed-effects meta-analysis model was used to identify the most consistent DNAm differences across datasets. In addition, we also evaluated the performance of the sex-specific methylation-based risk prediction models for AD diagnosis using an independent external dataset.

RESULTS

In the sex-stratified analysis, we identified 2 CpGs, mapped to the PRRC2A and RPS8 genes, significantly associated with AD in females at a 5% false discovery rate, and an additional 25 significant CpGs (21 in females, 4 in males) at P-value < 1×10^-5. In methylation-by-sex interaction analysis, we identified 5 significant CpGs at P-value < 10^-5. Out-of-sample validations using the AddNeuroMed dataset showed in females, the best logistic prediction model included age, estimated immune cell-type proportions, and methylation risk scores (MRS) computed from 9 of the 23 CpGs identified in AD vs. CN analysis that are also available in AddNeuroMed dataset (AUC = 0.74, 95% CI: 0.65-0.83). In males, the best logistic prediction model included only age and MRS computed from 2 of the 5 CpGs identified in methylation-by-sex interaction analysis that are also available in the AddNeuroMed dataset (AUC = 0.70, 95% CI: 0.56-0.82).

CONCLUSIONS

Overall, our results show that the DNA methylation differences in AD are largely distinct between males and females. Our best-performing sex-specific methylation-based prediction model in females performed better than that for males and additionally included estimated cell-type proportions. The significant discriminatory classification of AD samples with our methylation-based prediction models demonstrates that sex-specific DNA methylation could be a predictive biomarker for AD. As sex is a strong factor underlying phenotypic variability in AD, the results of our study are particularly relevant for a better understanding of the epigenetic architecture that underlie AD and for promoting precision medicine in AD.

Biological underpinnings of sex differences in neurological disorders

The importance of sex differences in neurological disorders has been increasingly acknowledged in recent clinical and basic research studies, but the complex biology and genetics underlying sex-linked biological heterogeneity and its brain-to-body impact remained incompletely understood. Men and women differ substantially in their susceptibility to certain neurological diseases, in the severity of symptoms, prognosis as well as the nature and efficacy of their response to treatments. The detailed mechanisms underlying these differences, especially at the molecular level, are being addressed in many studies but leave a lot to be further revealed. Here, we provide an overview of recent advances in our understanding of how sex differences in the brain and brain-body signaling contribute to neurological disorders and further present some future prospects entailed in terms of diagnostics and therapeutics.

Identification and immunological characterization of cuproptosis-related molecular clusters in Alzheimer's disease

Introduction

Alzheimer's disease is the most common dementia with clinical and pathological heterogeneity. Cuproptosis is a recently reported form of cell death, which appears to result in the progression of various diseases. Therefore, our study aimed to explore cuproptosis-related molecular clusters in Alzheimer's disease and construct a prediction model.

Methods

Based on the GSE33000 dataset, we analyzed the expression profiles of cuproptosis regulators and immune characteristics in Alzheimer's disease. Using 310 Alzheimer's disease samples, we explored the molecular clusters based on cuproptosis-related genes, along with the related immune cell infiltration. Cluster-specific differentially expressed genes were identified using the WGCNA algorithm. Subsequently, the optimal machine model was chosen by comparing the performance of the random forest model, support vector machine model, generalized linear model, and eXtreme Gradient Boosting. Nomogram, calibration curve, decision curve analysis, and three external datasets were applied for validating the predictive efficiency.

Results

The dysregulated cuproptosis-related genes and activated immune responses were determined between Alzheimer's disease and non-Alzheimer's disease controls. Two cuproptosis-related molecular clusters were defined in Alzheimer's disease. Analysis of immune infiltration suggested the significant heterogeneity of immunity between distinct clusters. Cluster2 was characterized by elevated immune scores and relatively higher levels of immune infiltration. Functional analysis showed that cluster-specific differentially expressed genes in Cluster2 were closely related to various immune responses. The Random forest machine model presented the best discriminative performance with relatively lower residual and root mean square error, and a higher area under the curve (AUC = 0.9829). A final 5-gene-based random forest model was constructed, exhibiting satisfactory performance in two external validation datasets (AUC = 0.8529 and 0.8333). The nomogram, calibration curve, and decision curve analysis also demonstrated the accuracy to predict Alzheimer's disease subtypes. Further analysis revealed that these five model-related genes were significantly associated with the Aβ-42 levels and β-secretase activity.

Conclusion

Our study systematically illustrated the complicated relationship between cuproptosis and Alzheimer's disease, and developed a promising prediction model to evaluate the risk of cuproptosis subtypes and the pathological outcome of Alzheimer's disease patients.

Deep phenotyping of Alzheimer's disease leveraging electronic medical records identifies sex-specific clinical associations

Alzheimer's Disease (AD) is a neurodegenerative disorder that is still not fully understood. Sex modifies AD vulnerability, but the reasons for this are largely unknown. We utilize two independent electronic medical record (EMR) systems across 44,288 patients to perform deep clinical phenotyping and network analysis to gain insight into clinical characteristics and sex-specific clinical associations in AD. Embeddings and network representation of patient diagnoses demonstrate greater comorbidity interactions in AD in comparison to matched controls. Enrichment analysis identifies multiple known and new diagnostic, medication, and lab result associations across the whole cohort and in a sex-stratified analysis. With this data-driven method of phenotyping, we can represent AD complexity and generate hypotheses of clinical factors that can be followed-up for further diagnostic and predictive analyses, mechanistic understanding, or drug repurposing and therapeutic approaches.

Sex Differences in Alzheimer's Disease: Insights From the Multiomics Landscape

Alzheimer's disease (AD) has complex etiologies, and the impact of sex on AD varies over the course of disease development. The literature provides some evidence of sex-specific contributions to AD. However, molecular mechanisms of sex-biased differences in AD remain elusive. Multiomics data in tandem with systems biology approaches offer a new avenue to dissect sex-stratified molecular mechanisms of AD and to develop sex-specific diagnostic and therapeutic strategies for AD. Single-cell transcriptomic datasets and cell deconvolution of bulk tissue transcriptomic data provide additional insights into brain cell type-specific impact on sex-biased differences in AD. In this review, we summarize the impact of sex chromosomes and sex hormones on AD, the impact of sex-biased differences during AD development, and the interplay between sex and a major AD genetic risk factor, the APOE ε4 genotype, through the multiomics landscape. Several sex-biased molecular pathways such as neuroinflammation and bioenergetic metabolism have been identified. The importance of sex chromosome and sex hormones, as well as the associated pathways in AD pathogenesis, is further strengthened by findings from omics studies. Future research efforts should integrate the multiomics data from different brain regions and different cell types using systems biology approaches, and leverage the knowledge into a holistic examination of sex differences in AD. Advances in systems biology technologies and increasingly available large-scale multiomics datasets will facilitate future studies dissecting such complex signaling mechanisms to better understand AD pathogenesis in both sexes, with the ultimate goals of developing efficacious sex- and APOE-stratified preventive and therapeutic interventions for AD.