Mitochondrial Genetics Reinforces Multiple Layers of Interaction in Alzheimer’s Disease

Patterns of Unwanted Biological and Technical Expression Variation Among 49 Human Tissues

Tissue gene expression studies are impacted by biological and technical sources of variation, which can be broadly classified into wanted and unwanted variation. The latter, if not addressed, results in misleading biological conclusions. Methods have been proposed to reduce unwanted variation, such as normalization and batch correction. A more accurate understanding of all causes of variation could significantly improve the ability of these methods to remove unwanted variation while retaining variation corresponding to the biological question of interest. We used 17,282 samples from 49 human tissues in the Genotype-Tissue Expression data set (v8) to investigate patterns and causes of expression variation. Transcript expression was transformed to z-scores, and only the most variable 2% of transcripts were evaluated and clustered based on coexpression patterns. Clustered gene sets were assigned to different biological or technical causes based on histologic appearances and metadata elements. We identified 522 variable transcript clusters (median: 11 per tissue) among the samples. Of these, 63% were confidently explained, 16% were likely explained, 7% were low confidence explanations, and 14% had no clear cause. Histologic analysis annotated 46 clusters. Other common causes of variability included sex, sequencing contamination, immunoglobulin diversity, and compositional tissue differences. Less common biological causes included death interval (Hardy score), disease status, and age. Technical causes included blood draw timing and harvesting differences. Many of the causes of variation in bulk tissue expression were identifiable in the Tabula Sapiens data set of single-cell expression. This is among the largest explorations of the underlying sources of tissue expression variation. It uncovered expected and unexpected causes of variable gene expression and demonstrated the utility of matched histologic specimens. It further demonstrated the value of acquiring meaningful tissue harvesting metadata elements to use for improved normalization, batch correction, and analysis of both bulk and single-cell RNA-seq data.

Promising use of metformin in treating neurological disorders: biomarker-guided therapies

Neurological disorders are a diverse group of conditions that affect the nervous system and include neurodegenerative diseases (Alzheimer's disease, multiple sclerosis, Parkinson's disease, Huntington's disease), cerebrovascular conditions (stroke), and neurodevelopmental disorders (autism spectrum disorder). Although they affect millions of individuals around the world, only a limited number of effective treatment options are available today. Since most neurological disorders express mitochondria-related metabolic perturbations, metformin, a biguanide type II antidiabetic drug, has attracted a lot of attention to be repurposed to treat neurological disorders by correcting their perturbed energy metabolism. However, controversial research emerges regarding the beneficial/detrimental effects of metformin on these neurological disorders. Given that most neurological disorders have complex etiology in their pathophysiology and are influenced by various risk factors such as aging, lifestyle, genetics, and environment, it is important to identify perturbed molecular functions that can be targeted by metformin in these neurological disorders. These molecules can then be used as biomarkers to stratify subpopulations of patients who show distinct molecular/pathological properties and can respond to metformin treatment, ultimately developing targeted therapy. In this review, we will discuss mitochondria-related metabolic perturbations and impaired molecular pathways in these neurological disorders and how these can be used as biomarkers to guide metformin-responsive treatment for the targeted therapy to treat neurological disorders.

Identifying potential genetic epistasis implicated in Alzheimer's disease via detection of SNP-SNP interaction on quantitative trait CSF Aβ42

Although genome-wide association studies have identified multiple Alzheimer's disease (AD)-associated loci by selecting the main effects of individual single-nucleotide polymorphisms (SNPs), the interpretation of genetic variance in AD is limited. Based on the linear regression method, we performed genome-wide SNP-SNP interaction on cerebrospinal fluid Aβ42 to identify potential genetic epistasis implicated in AD, with age, gender, and diagnosis as covariates. A GPU-based method was used to address the computational challenges posed by the analysis of epistasis. We found 368 SNP pairs to be statistically significant, and highly significant SNP-SNP interactions were identified between the marginal main effects of SNP pairs, which explained a relatively high variance at the Aβ42 level. Our results replicated 100 previously reported AD-related genes and 5 gene-gene interaction pairs of the protein-protein interaction network. Our bioinformatics analyses provided preliminary evidence that the 5-overlapping gene-gene interaction pairs play critical roles in inducing synaptic loss and dysfunction, thereby leading to memory decline and cognitive impairment in AD-affected brains.

A global view of aging and Alzheimer's pathogenesis-associated cell population dynamics and molecular signatures in human and mouse brains

Conventional methods fall short in unraveling the dynamics of rare cell types related to aging and diseases. Here we introduce EasySci, an advanced single-cell combinatorial indexing strategy for exploring age-dependent cellular dynamics in the mammalian brain. Profiling approximately 1.5 million single-cell transcriptomes and 400,000 chromatin accessibility profiles across diverse mouse brains, we identified over 300 cell subtypes, uncovering their molecular characteristics and spatial locations. This comprehensive view elucidates rare cell types expanded or depleted upon aging. We also investigated cell-type-specific responses to genetic alterations linked to Alzheimer's disease, identifying associated rare cell types. Additionally, by profiling 118,240 human brain single-cell transcriptomes, we discerned cell- and region-specific transcriptomic changes tied to Alzheimer's pathogenesis. In conclusion, this research offers a valuable resource for probing cell-type-specific dynamics in both normal and pathological aging.

The fusiform gyrus exhibits differential gene-gene co-expression in Alzheimer's disease

Alzheimer's Disease (AD) is an irreversible neurodegenerative disease clinically characterized by the presence of β-amyloid plaques and tau deposits in various regions of the brain. However, the underlying factors that contribute to the development of AD remain unclear. Recently, the fusiform gyrus has been identified as a critical brain region associated with mild cognitive impairment, which may increase the risk of AD development. In our study, we performed gene co-expression and differential co-expression network analyses, as well as gene-expression-based prediction, using RNA-seq transcriptome data from post-mortem fusiform gyrus tissue samples collected from both cognitively healthy individuals and those with AD. We accessed differential co-expression networks in large cohorts such as ROSMAP, MSBB, and Mayo, and conducted over-representation analyses of gene pathways and gene ontology. Our results comprise four exclusive gene hubs in co-expression modules of Alzheimer's Disease, including FNDC3A, MED23, NRIP1, and PKN2. Further, we identified three genes with differential co-expressed links, namely FAM153B, CYP2C8, and CKMT1B. The differential co-expressed network showed moderate predictive performance for AD, with an area under the curve ranging from 0.71 to 0.76 (+/- 0.07). The over-representation analysis identified enrichment for Toll-Like Receptors Cascades and signaling pathways, such as G protein events, PIP2 hydrolysis and EPH-Epherin mechanism, in the fusiform gyrus. In conclusion, our findings shed new light on the molecular pathophysiology of AD by identifying new genes and biological pathways involved, emphasizing the crucial role of gene regulatory networks in the fusiform gyrus.

Mitochondrial Ca2+ Signaling and Bioenergetics in Alzheimer's Disease

Alzheimer's disease (AD) is a hereditary and sporadic neurodegenerative illness defined by the gradual and cumulative loss of neurons in specific brain areas. The processes that cause AD are still under investigation and there are no available therapies to halt it. Current progress puts at the forefront the "calcium (Ca2+) hypothesis" as a key AD pathogenic pathway, impacting neuronal, astrocyte and microglial function. In this review, we focused on mitochondrial Ca2+ alterations in AD, their causes and bioenergetic consequences in neuronal and glial cells, summarizing the possible mechanisms linking detrimental mitochondrial Ca2+ signals to neuronal death in different experimental AD models.

Targeted Mitochondrial Epigenetics: A New Direction in Alzheimer’s Disease Treatment

Mitochondrial epigenetic alterations are closely related to Alzheimer’s disease (AD), which is described in this review. Reports of the alteration of mitochondrial DNA (mtDNA) methylation in AD demonstrate that the disruption of the dynamic balance of mtDNA methylation and demethylation leads to damage to the mitochondrial electron transport chain and the obstruction of mitochondrial biogenesis, which is the most studied mitochondrial epigenetic change. Mitochondrial noncoding RNA modifications and the post-translational modification of mitochondrial nucleoproteins have been observed in neurodegenerative diseases and related diseases that increase the risk of AD. Although there are still relatively few mitochondrial noncoding RNA modifications and mitochondrial nuclear protein post-translational modifications reported in AD, we have reason to believe that these mitochondrial epigenetic modifications also play an important role in the AD process. This review provides a new research direction for the AD mechanism, starting from mitochondrial epigenetics. Further, this review summarizes therapeutic approaches to targeted mitochondrial epigenetics, which is the first systematic summary of therapeutic approaches in the field, including folic acid supplementation, mitochondrial-targeting antioxidants, and targeted ubiquitin-specific proteases, providing a reference for therapeutic targets for AD.