Exome-wide age-of-onset analysis reveals exonic variants in ERN1 and SPPL2C associated with Alzheimer's disease

Mitochondrial unfolded protein response (UPRmt) as novel therapeutic targets for neurological disorders

Neurological disorders, including brain cancer, neurodegenerative diseases and ischemic/reperfusion injury, pose a significant threat to global human health. Due to the high metabolic demands of nerve cells, mitochondrial dysfunction is a critical feature of these disorders. The mitochondrial unfolded protein response (UPRmt) is an evolutionarily conserved mitochondrial response, which is critical for maintaining mitochondrial and energetic homeostasis under stress. Previous studies have found that UPRmt participates in diverse physiological processes especially metabolism and immunity. Currently, increasing evidence suggest that targeted regulation of UPRmt can also effectively delay the progression of neurological diseases and improve patients' prognosis. This review provides a comprehensive overview of UPRmt in the context of neurological diseases, with a particular emphasis on its regulatory functions. Additionally, we summarize the mechanistic insights into UPRmt in neurological disorders as investigated in preclinical studies, as well as its potential as a therapeutic target in the clinical management of neurological tumors. By highlighting the importance of UPRmt in the complex processes underlying neurological disorders, this review aims to bridge current knowledge gaps and inspire novel therapeutic strategies for these conditions.

Epigenetic and genetic profiling of comorbidity patterns among substance dependence diagnoses

This study investigated the genetic and epigenetic mechanisms underlying the comorbidity of five substance dependence diagnoses (SDs; alcohol, AD; cannabis, CaD; cocaine, CoD; opioid, OD; tobacco, TD). A latent class analysis (LCA) was performed on 22,668 individuals from six cohorts to identify comorbid DSM-IV SD patterns. In subsets of this sample, we tested SD-latent classes with respect to polygenic overlap of psychiatric and psychosocial traits in 7659 individuals of European descent and epigenome-wide changes in 886 individuals of African, European, and Admixed-American descents. The LCA identified four latent classes related to SD comorbidities: AD + TD, CoD + TD, AD + CoD + OD + TD (i.e., polysubstance addiction, PSU), and TD. In the epigenome-wide association analysis, SPATA4 cg02833127 was associated with CoD + TD, AD + TD, and PSU latent classes. AD + TD latent class was also associated with CpG sites located on ARID1B, NOTCH1, SERTAD4, and SIN3B, while additional epigenome-wide significant associations with CoD + TD latent class were observed in ANO6 and MOV10 genes. PSU-latent class was also associated with a differentially methylated region in LDB1. We also observed shared polygenic score (PGS) associations for PSU, AD + TD, and CoD + TD latent classes (i.e., attention-deficit hyperactivity disorder, anxiety, educational attainment, and schizophrenia PGS). In contrast, TD-latent class was exclusively associated with posttraumatic stress disorder-PGS. Other specific associations were observed for PSU-latent class (subjective wellbeing-PGS and neuroticism-PGS) and AD + TD-latent class (bipolar disorder-PGS). In conclusion, we identified shared and unique genetic and epigenetic mechanisms underlying SD comorbidity patterns. These findings highlight the importance of modeling the co-occurrence of SD diagnoses when investigating the molecular basis of addiction-related traits.

Association of genetic risk score for Alzheimer's disease with late-life body mass index in all of us: Evaluating reverse causation

INTRODUCTION

Decreases in body mass index (BMI) may be early consequences of Alzheimer's disease (AD) pathophysiological changes. Previous research in the UK Biobank estimated that AD-related genes began affecting BMI around age 47. We assessed whether this result could be replicated using longitudinal data in an independent cohort.

METHODS

Using All of Us (AOU) (N = 197,619, aged 30+) data, we estimated linear mixed models for associations of Z-scored AD-Genetic Risk Score (AD-GRS) with BMI, stratified by decade of age. We calculated the earliest age at which AD-GRS was associated with differences in BMI using cross-validated models adjusted for demographics.

RESULTS

Higher AD-GRS was statistically associated with lower BMI in participants aged 60-70 (b = -0.060 [-0.113, -0.007]). Best fitting models suggested the inverse association of AD-GRS and BMI emerged beginning at ages 47-54.

DISCUSSION

AD genes accelerate age-related weight loss starting in middle age.

HIGHLIGHTS

Understanding when physiological changes from amyloid pathology begin is key for AD prevention. Our findings indicate that AD-associated genes accelerate midlife weight loss, starting between 47 and 54 years. AD prevention research should consider that disease pathology likely begins by middle age.

Genetically supported targets and drug repurposing for brain aging: A systematic study in the UK Biobank

Brain age gap (BAG), the deviation between estimated brain age and chronological age, is a promising marker of brain health. However, the genetic architecture and reliable targets for brain aging remains poorly understood. In this study, we estimate magnetic resonance imaging (MRI)-based brain age using deep learning models trained on the UK Biobank and validated with three external datasets. A genome-wide association study for BAG identified two unreported loci and seven previously reported loci. By integrating Mendelian Randomization (MR) and colocalization analysis on eQTL and pQTL data, we prioritized seven genetically supported druggable genes, including MAPT, TNFSF12, GZMB, SIRPB1, GNLY, NMB, and C1RL, as promising targets for brain aging. We rediscovered 13 potential drugs with evidence from clinical trials of aging and prioritized several drugs with strong genetic support. Our study provides insights into the genetic basis of brain aging, potentially facilitating drug development for brain aging to extend the health span.

Genome-wide and phenome-wide studies provided insights into brain glymphatic system function and its clinical associations

We applied an MRI technique diffusion tensor imaging along the perivascular space (DTI-ALPS) for assessing glymphatic system (GS) in a genome-wide association study (GWAS) and phenome-wide association study (PheWAS) of 40,486 European individuals. Exploratory analysis revealed 17 genetic loci significantly associating with the regional DTI-ALPS index. We found 58 genes, including SPPL2C and EFCAB5, which prioritized in the DTI-ALPS index subtypes and associated with neurodegenerative diseases. PheWAS of 241 traits suggested that body mass index and blood pressure phenotypes closely related to GS function. Moreover, we detected disrupted GS function in 44 of 625 predefined disease conditions. Notably, Mendelian randomization and mediation analysis indicated that lower DTI-ALPS index was a risk factor for ischemic stroke (odds ratio = 1.56, P = 0.028) by partly mediating the risk factor of obesity. Results provide insights into the genetic architecture and mechanism for the DIT-ALPS index and highlight its great clinical value, especially in cerebral stroke.

Epigenetic and Genetic Profiling of Comorbidity Patterns among Substance Dependence Diagnoses

Objective

This study investigated the genetic and epigenetic mechanisms underlying the comorbidity patterns of five substance dependence diagnoses (SDs; alcohol, AD; cannabis, CaD; cocaine, CoD; opioid, OD; tobacco, TD).

Methods

A latent class analysis (LCA) was performed on 31,197 individuals (average age 42±11 years; 49% females) from six cohorts to identify comorbid DSM-IV SD patterns. In subsets of this sample, we tested SD-latent classes with respect to polygenic burden of psychiatric and behavioral traits and epigenome-wide changes in three population groups.

Results

An LCA identified four latent classes related to SD comorbidities: AD+TD, CoD+TD, AD+CoD+OD+TD (i.e., polysubstance use, PSU), and TD. In the epigenome-wide association analysis, SPATA4 cg02833127 was associated with CoD+TD, AD+TD, and PSU latent classes. AD+TD latent class was also associated with CpG sites located on ARID1B , NOTCH1 , SERTAD4, and SIN3B , while additional epigenome-wide significant associations with CoD+TD latent class were observed in ANO6 and MOV10 genes. PSU-latent class was also associated with a differentially methylated region in LDB1 . We also observed shared polygenic score (PGS) associations for PSU, AD+TD, and CoD+TD latent classes (i.e., attention-deficit hyperactivity disorder, anxiety, educational attainment, and schizophrenia PGS). In contrast, TD-latent class was exclusively associated with posttraumatic stress disorder-PGS. Other specific associations were observed for PSU-latent class (subjective wellbeing-PGS and neuroticism-PGS) and AD+TD-latent class (bipolar disorder-PGS).

Conclusions

We identified shared and unique genetic and epigenetic mechanisms underlying SD comorbidity patterns. These findings highlight the importance of modeling the co-occurrence of SD diagnoses when investigating the molecular basis of addiction-related traits.

The ROSMAP project: aging and neurodegenerative diseases through omic sciences

The Religious Order Study and Memory and Aging Project (ROSMAP) is an initiative that integrates two longitudinal cohort studies, which have been collecting clinicopathological and molecular data since the early 1990s. This extensive dataset includes a wide array of omic data, revealing the complex interactions between molecular levels in neurodegenerative diseases (ND) and aging. Neurodegenerative diseases (ND) are frequently associated with morbidity and cognitive decline in older adults. Omics research, in conjunction with clinical variables, is crucial for advancing our understanding of the diagnosis and treatment of neurodegenerative diseases. This summary reviews the extensive omics research-encompassing genomics, transcriptomics, proteomics, metabolomics, epigenomics, and multiomics-conducted through the ROSMAP study. It highlights the significant advancements in understanding the mechanisms underlying neurodegenerative diseases, with a particular focus on Alzheimer's disease.

Cross-continental environmental and genome-wide association study on children and adolescent anxiety and depression

Anxiety and depression in children and adolescents warrant special attention as a public health concern given their devastating and long-term effects on development and mental health. Multiple factors, ranging from genetic vulnerabilities to environmental stressors, influence the risk for the disorders. This study aimed to understand how environmental factors and genomics affect children and adolescents anxiety and depression across three cohorts: Adolescent Brain and Cognitive Development Study (US, age of 9-10; N=11,875), Consortium on Vulnerability to Externalizing Disorders and Addictions (INDIA, age of 6-17; N=4,326) and IMAGEN (EUROPE, age of 14; N=1888). We performed data harmonization and identified the environmental impact on anxiety/depression using a linear mixed-effect model, recursive feature elimination regression, and the LASSO regression model. Subsequently, genome-wide association analyses with consideration of significant environmental factors were performed for all three cohorts by mega-analysis and meta-analysis, followed by functional annotations. The results showed that multiple environmental factors contributed to the risk of anxiety and depression during development, where early life stress and school support index had the most significant and consistent impact across all three cohorts. In both meta, and mega-analysis, SNP rs79878474 in chr11p15 emerged as a particularly promising candidate associated with anxiety and depression, despite not reaching genomic significance. Gene set analysis on the common genes mapped from top promising SNPs of both meta and mega analyses found significant enrichment in regions of chr11p15 and chr3q26, in the function of potassium channels and insulin secretion, in particular Kv3, Kir-6.2, SUR potassium channels encoded by the KCNC1, KCNJ11, and ABCCC8 genes respectively, in chr11p15. Tissue enrichment analysis showed significant enrichment in the small intestine, and a trend of enrichment in the cerebellum. Our findings provide evidences of consistent environmental impact from early life stress and school support index on anxiety and depression during development and also highlight the genetic association between mutations in potassium channels, which support the stress-depression connection via hypothalamic-pituitary-adrenal axis, along with the potential modulating role of potassium channels.

The genetic architecture of the human hypothalamus and its involvement in neuropsychiatric behaviours and disorders

Despite its crucial role in the regulation of vital metabolic and neurological functions, the genetic architecture of the hypothalamus remains unknown. Here we conducted multivariate genome-wide association studies (GWAS) using hypothalamic imaging data from 32,956 individuals to uncover the genetic underpinnings of the hypothalamus and its involvement in neuropsychiatric traits. There were 23 significant loci associated with the whole hypothalamus and its subunits, with functional enrichment for genes involved in intracellular trafficking systems and metabolic processes of steroid-related compounds. The hypothalamus exhibited substantial genetic associations with limbic system structures and neuropsychiatric traits including chronotype, risky behaviour, cognition, satiety and sympathetic-parasympathetic activity. The strongest signal in the primary GWAS, the ADAMTS8 locus, was replicated in three independent datasets (N = 1,685-4,321) and was strengthened after meta-analysis. Exome-wide association analyses added evidence to the association for ADAMTS8, and Mendelian randomization showed lower ADAMTS8 expression with larger hypothalamic volumes. The current study advances our understanding of complex structure-function relationships of the hypothalamus and provides insights into the molecular mechanisms that underlie hypothalamic formation.

Dual roles of UPRer and UPRmt in neurodegenerative diseases

The unfolded protein response (UPR) is a cellular stress response mechanism induced by the accumulation of unfolded or misfolded proteins. Within the endoplasmic reticulum and mitochondria, a dynamic balance exists between protein folding mechanisms and unfolded protein levels under normal conditions. Disruption of this balance or an accumulation of unfolded proteins in these organelles can result in stress responses and UPR. The UPR restores organelle homeostasis and promotes cell survival by increasing the expression of chaperone proteins, regulating protein quality control systems, and enhancing the protein degradation pathway. However, prolonged or abnormal UPR can also have negative effects, including cell death. Therefore, many diseases, especially neurodegenerative diseases, are associated with UPR dysfunction. Neurodegenerative diseases are characterized by misfolded proteins accumulating and aggregating, and neuronal cells are particularly sensitive to misfolded proteins and are prone to degeneration. Many studies have shown that the UPR plays an important role in the pathogenesis of neurodegenerative diseases. Here, we will discuss the possible contributions of the endoplasmic reticulum unfolded protein response (UPRer) and the mitochondrial unfolded protein response (UPRmt) in the development of several neurodegenerative diseases.

Single-Nucleus Transcriptome Profiling of Dorsolateral Prefrontal Cortex: Mechanistic Roles for Neuronal Gene Expression, Including the 17q21.31 Locus, in PTSD Stress Response

OBJECTIVE

Multidisciplinary studies of posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) implicate the dorsolateral prefrontal cortex (DLPFC) in disease risk and pathophysiology. Postmortem brain studies have relied on bulk-tissue RNA sequencing (RNA-seq), but single-cell RNA-seq is needed to dissect cell-type-specific mechanisms. The authors conducted the first single-nucleus RNA-seq postmortem brain study in PTSD to elucidate disease transcriptomic pathology with cell-type-specific resolution.

METHOD

Profiling of 32 DLPFC samples from 11 individuals with PTSD, 10 with MDD, and 11 control subjects was conducted (∼415K nuclei; >13K cells per sample). A replication sample included 15 DLPFC samples (∼160K nuclei; >11K cells per sample).

RESULTS

Differential gene expression analyses identified significant single-nucleus RNA-seq differentially expressed genes (snDEGs) in excitatory (EX) and inhibitory (IN) neurons and astrocytes, but not in other cell types or bulk tissue. MDD samples had more false discovery rate-corrected significant snDEGs, and PTSD samples had a greater replication rate. In EX and IN neurons, biological pathways that were differentially enriched in PTSD compared with MDD included glucocorticoid signaling. Furthermore, glucocorticoid signaling in induced pluripotent stem cell (iPSC)-derived cortical neurons demonstrated greater relevance in PTSD and opposite direction of regulation compared with MDD, especially in EX neurons. Many snDEGs were from the 17q21.31 locus and are particularly interesting given causal roles in disease pathogenesis and DLPFC-based neuroimaging (PTSD: ARL17B, LINC02210-CRHR1, and LRRC37A2; MDD: LRRC37A and LRP4), while others were regulated by glucocorticoids in iPSC-derived neurons (PTSD: SLC16A6, TAF1C; MDD: CDH3).

CONCLUSIONS

The study findings point to cell-type-specific mechanisms of brain stress response in PTSD and MDD, highlighting the importance of examining cell-type-specific gene expression and indicating promising novel biomarkers and therapeutic targets.

Disentangling the genetic overlap and causal relationships between primary open-angle glaucoma, brain morphology and four major neurodegenerative disorders

BACKGROUND

Primary open-angle glaucoma (POAG) is an optic neuropathy characterized by progressive degeneration of the optic nerve that leads to irreversible visual impairment. Multiple epidemiological studies suggest an association between POAG and major neurodegenerative disorders (Alzheimer's disease, amyotrophic lateral sclerosis, frontotemporal dementia, and Parkinson's disease). However, the nature of the overlap between neurodegenerative disorders, brain morphology and glaucoma remains inconclusive.

METHOD

In this study, we performed a comprehensive assessment of the genetic and causal relationship between POAG and neurodegenerative disorders, leveraging genome-wide association data from studies of magnetic resonance imaging of the brain, POAG, and four major neurodegenerative disorders.

FINDINGS

This study found a genetic overlap and causal relationship between POAG and its related phenotypes (i.e., intraocular pressure and optic nerve morphology traits) and brain morphology in 19 regions. We also identified 11 loci with a significant local genetic correlation and a high probability of sharing the same causal variant between neurodegenerative disorders and POAG or its related phenotypes. Of interest, a region on chromosome 17 corresponding to MAPT, a well-known risk locus for Alzheimer's and Parkinson's disease, was shared between POAG, optic nerve degeneration traits, and Alzheimer's and Parkinson's diseases. Despite these local genetic overlaps, we did not identify strong evidence of a causal association between these neurodegenerative disorders and glaucoma.

INTERPRETATION

Our findings indicate a distinctive and likely independent neurodegenerative process for POAG involving several brain regions although several POAG or optic nerve degeneration risk loci are shared with neurodegenerative disorders, consistent with a pleiotropic effect rather than a causal relationship between these traits.

FUNDING

PG was supported by an NHMRC Investigator Grant (#1173390), SM by an NHMRC Senior Research Fellowship and an NHMRC Program Grant (APP1150144), DM by an NHMRC Fellowship, LP is funded by the NEIEY015473 and EY032559 grants, SS is supported by an NIH-Oxford Cambridge Fellowship and NIH T32 grant (GM136577), APK is supported by a UK Research and Innovation Future Leaders Fellowship, an Alcon Research Institute Young Investigator Award and a Lister Institute for Preventive Medicine Award.

Investigating a Genetic Link Between Alzheimer's Disease and CADASIL-Related Cerebral Small Vessel Disease

Monogenic forms of Alzheimer's disease (AD) have been identified through mutations in genes such as APP, PSEN1, and PSEN2, whilst other genetic markers such as the APOE ε carrier allele status have been shown to increase the likelihood of having the disease. Mutations in these genes are not limited to AD, as APP mutations can also cause an amyloid form of cerebral small vessel disease (CSVD) known as cerebral amyloid angiopathy, whilst PSEN1 and PSEN2 are involved in NOTCH3 signalling, a process known to be dysregulated in the monogenic CSVD, cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). The overlap between AD genes and causes of CSVD led to the hypothesis that mutations in other genes within the PANTHER AD-presenilin pathway may be novel causes of CSVD in a cohort of clinically suspicious CADASIL patients without a pathogenic NOTCH3 mutation. To investigate this, whole exome sequencing was performed on 50 suspected CADASIL patients with no NOTCH3 mutations, and a targeted gene analysis was completed on the PANTHER. ERN1 was identified as a novel candidate CSVD gene following predicted pathogenic gene mutation analysis. Rare variant burden testing failed to identify an association with any gene; however, it did show a nominally significant link with ERN1 and TRPC3. This study provides evidence to support a genetic overlap between CSVD and Alzheimer's disease.

Unfolded protein response IRE1/XBP1 signaling is required for healthy mammalian brain aging

Aging is a major risk factor to develop neurodegenerative diseases and is associated with decreased buffering capacity of the proteostasis network. We investigated the significance of the unfolded protein response (UPR), a major signaling pathway activated to cope with endoplasmic reticulum (ER) stress, in the functional deterioration of the mammalian brain during aging. We report that genetic disruption of the ER stress sensor IRE1 accelerated age-related cognitive decline. In mouse models, overexpressing an active form of the UPR transcription factor XBP1 restored synaptic and cognitive function, in addition to reducing cell senescence. Proteomic profiling of hippocampal tissue showed that XBP1 expression significantly restore changes associated with aging, including factors involved in synaptic function and pathways linked to neurodegenerative diseases. The genes modified by XBP1 in the aged hippocampus where also altered. Collectively, our results demonstrate that strategies to manipulate the UPR in mammals may help sustain healthy brain aging.

A Fast and Robust Strategy to Remove Variant-Level Artifacts in Alzheimer Disease Sequencing Project Data

Background and Objectives

Exome sequencing (ES) and genome sequencing (GS) are expected to be critical to further elucidate the missing genetic heritability of Alzheimer disease (AD) risk by identifying rare coding and/or noncoding variants that contribute to AD pathogenesis. In the United States, the Alzheimer Disease Sequencing Project (ADSP) has taken a leading role in sequencing AD-related samples at scale, with the resultant data being made publicly available to researchers to generate new insights into the genetic etiology of AD. To achieve sufficient power, the ADSP has adapted a study design where subsets of larger AD cohorts are collected and sequenced across multiple centers, using a variety of sequencing platforms. This approach may lead to variable variant quality across sequencing centers and/or platforms. In this study, we sought to implement and evaluate filters that can be applied fast to robustly remove variant-level artifacts in the ADSP data.

Methods

We implemented a robust quality control procedure to handle ADSP data. We evaluated this procedure while performing exome-wide and genome-wide association analyses on AD risk using the latest ADSP whole ES (WES) and whole GS (WGS) data releases (NG00067.v5).

Results

We observed that many variants displayed large variation in allele frequencies across sequencing centers/platforms and contributed to spurious association signals with AD risk. We also observed that sequencing platform/center adjustment in association models could not fully account for these spurious signals. To address this issue, we designed and implemented variant filters that could capture and remove these center-specific/platform-specific artifactual variants.

Discussion

We derived a fast and robust approach to filter variants that represent sequencing center-related or platform-related artifacts underlying spurious associations with AD risk in ADSP WES and WGS data. This approach will be important to support future robust genetic association studies on ADSP data, as well as other studies with similar designs.

Deep neural networks with controlled variable selection for the identification of putative causal genetic variants

Deep neural networks (DNNs) have been successfully utilized in many scientific problems for their high prediction accuracy, but their application to genetic studies remains challenging due to their poor interpretability. Here we consider the problem of scalable, robust variable selection in DNNs for the identification of putative causal genetic variants in genome sequencing studies. We identified a pronounced randomness in feature selection in DNNs due to its stochastic nature, which may hinder interpretability and give rise to misleading results. We propose an interpretable neural network model, stabilized using ensembling, with controlled variable selection for genetic studies. The merit of the proposed method includes: flexible modelling of the nonlinear effect of genetic variants to improve statistical power; multiple knockoffs in the input layer to rigorously control the false discovery rate; hierarchical layers to substantially reduce the number of weight parameters and activations, and improve computational efficiency; and stabilized feature selection to reduce the randomness in identified signals. We evaluate the proposed method in extensive simulation studies and apply it to the analysis of Alzheimer's disease genetics. We show that the proposed method, when compared with conventional linear and nonlinear methods, can lead to substantially more discoveries.

Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein–protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. The top hub genes such as MYC, EGFR, LNX1, YBX1, HSP90AA1, ESR1, FN1, TK1, ANLN and SMAD9 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Receiver operating characteristic curve (ROC) analysis confirmed that these genes were significantly associated with T1DM. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the advancement and progression of T1DM, and certain genes might be used as candidate target molecules to diagnose, monitor and treat T1DM.

Challenge accepted: uncovering the role of rare genetic variants in Alzheimer's disease

The search for rare variants in Alzheimer's disease (AD) is usually deemed a high-risk - high-reward situation. The challenges associated with this endeavor are real. Still, the application of genome-wide technologies to large numbers of cases and controls or to small, well-characterized families has started to be fruitful.Rare variants associated with AD have been shown to increase risk or cause disease, but also to protect against the development of AD. All of these can potentially be targeted for the development of new drugs.Multiple independent studies have now shown associations of rare variants in NOTCH3, TREM2, SORL1, ABCA7, BIN1, CLU, NCK2, AKAP9, UNC5C, PLCG2, and ABI3 with AD and suggested that they may influence disease via multiple mechanisms. These genes have reported functions in the immune system, lipid metabolism, synaptic plasticity, and apoptosis. However, the main pathway emerging from the collective of genes harboring rare variants associated with AD is the Aβ pathway. Associations of rare variants in dozens of other genes have also been proposed, but have not yet been replicated in independent studies. Replication of this type of findings is one of the challenges associated with studying rare variants in complex diseases, such as AD. In this review, we discuss some of these primary challenges as well as possible solutions.Integrative approaches, the availability of large datasets and databases, and the development of new analytical methodologies will continue to produce new genes harboring rare variability impacting AD. In the future, more extensive and more diverse genetic studies, as well as studies of deeply characterized families, will enhance our understanding of disease pathogenesis and put us on the correct path for the development of successful drugs.

An insight into Alzheimer’s disease and its on-setting novel genes

According to the World Health Organisation, as of 2019, globally around 50 million people suffer from dementia, with approximately another 10 million getting added to the list every year, wherein Alzheimer’s disease (AD) stands responsible for almost a whopping 60–70% for the existing number of cases. Alzheimer’s disease is one of the progressive, cognitive-declining, age-dependent, neurodegenerative diseases which is distinguished by histopathological symptoms, such as formation of amyloid plaque, senile plaque, neurofibrillary tangles, etc. Majorly four vital transcripts are identified in the AD complications which include Amyloid precursor protein (APP), Apolipoprotein E (ApoE), and two multi-pass transmembrane domain proteins—Presenilin 1 and 2. In addition, the formation of the abnormal filaments such as amyloid beta (Aβ) and tau and their tangling with some necessary factors contributing to the formation of plaques, neuroinflammation, and apoptosis which in turn leads to the emergence of AD. Although multiple molecular mechanisms have been elucidated so far, they are still counted as hypotheses ending with neuronal death on the basal forebrain and hippocampal area which results in AD. This review article is aimed at addressing the overview of the molecular mechanisms surrounding AD and the functional forms of the genes associated with it.