Isac, Maria Crina (2025), Genomic analysis of APP, PSEN1 and MAPT genes involved in the pathogenesis of Alzheimer’s disease, Cunoașterea Științifică, 4:4, 21-36, DOI: 10.58679/CS35521, https://www.cunoasterea.ro/genomic-analysis-of-app-psen1-and-mapt-genes/

 

Abstract

Neurodegenerative diseases, such as Alzheimer’s disease or other forms of dementia, represent a major challenge for global public health, and understanding the genetic mechanisms involved is essential for the development of diagnostic and treatment strategies. This work aims to study three key genes involved in the pathogenesis of neurodegeneration: APP (Amyloid Precursor Protein), PSEN1 (Presenilin 1) and MAPT (Microtubule Associated Protein Tau). The aim of the research is to analyze the classification of these genes, pathogenic genetic variations and frequent polymorphisms, as well as their impact on physiological and pathological processes. The methodology is based on a comparative analysis of data from the specialized literature and from genetic and expression databases, including GTEx, Human Protein Atlas, STRING and GeneMANIA platforms, as well as integrations from genome-wide association studies (GWAS). Specific types of pathogenic variations in each gene, correlated with distinct clinical phenotypes, were identified, and polymorphisms with a potential protective or susceptibility role were evaluated. The results highlight the differential distribution of gene expression in tissues relevant for neuronal function, their involvement in complex molecular networks and functional interactions, as well as possible mechanisms by which genetic variations may influence disease risk. The analysis emphasizes the importance of correlating genomic data with clinical phenotype for the identification of molecular markers useful in early diagnosis and personalization of therapeutic interventions. The work contributes to the understanding of the role of APP, PSEN1 and MAPT genes in neurodegeneration, providing an integrated synthesis of molecular and clinical data that can support translational research and medical practice.

Keywords: genetic variations, APP, PSEN1, MAPT, neurodegenerative diseases

Analiza genomică a genelor APP, PSEN1 și MAPT implicate în patogeneza bolii Alzheimer

Rezumat

Bolile neurodegenerative, precum boala Alzheimer sau alte forme de demență, reprezintă o provocare majoră pentru sănătatea publică globală, iar înțelegerea mecanismelor genetice implicate este esențială pentru dezvoltarea strategiilor de diagnostic și tratament. Această lucrare are ca obiect studiul a trei gene cheie implicate în patogeneza neurodegenerării: APP (Amyloid Precursor Protein), PSEN1 (Presenilin 1) și MAPT (Microtubule Associated Protein Tau). Scopul cercetării este de a analiza clasificarea acestor gene, variațiile genetice patogene și polimorfismele frecvente, precum și impactul lor asupra proceselor fiziologice și patologice. Metodologia se bazează pe o analiză comparativă a datelor provenite din literatura de specialitate și din baze de date genetice și de expresie, incluzând GTEx, Human Protein Atlas, platformele STRING și GeneMANIA, precum și integrări din studii de asociere la nivelul genomului (GWAS). Au fost identificate tipuri specifice de variații patogene în fiecare genă, corelate cu fenotipuri clinice distincte, și s-au evaluat polimorfisme cu potențial rol protector sau de susceptibilitate. Rezultatele evidențiază distribuția diferențiată a expresiei genelor în țesuturi relevante pentru funcția neuronală, implicarea acestora în rețele moleculare complexe și interacțiuni funcționale, precum și posibile mecanisme prin care variațiile genetice pot influența riscul de boală. Analiza subliniază importanța corelării datelor genomice cu fenotipul clinic pentru identificarea markerilor moleculari utili în diagnostic precoce și personalizarea intervențiilor terapeutice. Lucrarea aduce o contribuție la înțelegerea rolului genelor APP, PSEN1 și MAPT în neurodegenerare, oferind o sinteză integrată de date moleculare și clinice care poate sprijini cercetarea translatională și practica medicală.

Cuvinte cheie: variații genetice, APP, PSEN1, MAPT, boli neurodegenerative

 

CUNOAȘTEREA ȘTIINȚIFICĂ, Volumul 4, Numărul 4, Decembrie 2025, pp. 21-36
ISSN 2821 – 8086, ISSN – L 2821 – 8086, DOI: 10.58679/CS35521
URL: https://www.cunoasterea.ro/genomic-analysis-of-app-psen1-and-mapt-genes/
© 2025 Maria Crina ISAC. Responsabilitatea conținutului, interpretărilor și opiniilor exprimate revine exclusiv autorilor.

 

Genomic analysis of APP, PSEN1 and MAPT genes involved in the pathogenesis of Alzheimer’s disease

Maria Crina ISAC[1]
isacmariacrina@yahoo.com

[1] Universitatea Alexandru Ioan Cuza Iași

 

Introduction

Alzheimer’s disease is the most common form of neurodegenerative dementia worldwide, affecting millions of people, especially in old age. It is characterized by progressive memory impairment, cognitive impairment and behavioral changes, with a significant impact on the patient and family, but also on health systems (Gerrish et al., 2012). Although environmental and lifestyle factors play an important role in the onset of the disease, there is a significant genetic and genomic substrate that contributes to its onset and progression. In recent decades, genomic research has highlighted a series of key genes involved in the pathogenesis of Alzheimer’s disease, both in hereditary and sporadic forms. Among the most studied genes are APP (amyloid precursor protein), PSEN1 (presenilin 1) and MAPT (microtubule-associated protein tau) (Cruchaga et al., 2012). The APP gene encodes a precursor protein from which beta-amyloid is formed, the main component of amyloid plaques, which are a characteristic marker in the brains of Alzheimer’s patients. Mutations in APP can lead to an overproduction of neurotoxic forms of beta-amyloid, triggering inflammatory and synaptotoxic processes (Sassi et al., 2014). PSEN1 is the gene that encodes a component of the γ-secretase complex, which is responsible for the cleavage of the APP protein. Mutations in this gene are associated with familial forms of early-onset Alzheimer’s disease, by altering APP processing and increasing the formation of more toxic beta-amyloid peptides (Aβ42) (Cruchaga et al., 2012). The MAPT gene is essential for the stabilization of neuronal microtubules. Its dysregulation leads to hyperphosphorylation of the tau protein and the formation of intracellular clumps called “neurofibrillar tangles”, another pathological sign characteristic of Alzheimer’s. Although MAPT is more commonly associated with other tauopathies, recent data suggest that it also contributes to susceptibility to Alzheimer’s disease, particularly through complex interactions with other genes and epigenetic factors (Jin et al., 2012).

In this context, genomic analysis of these three genes provides important insights into the understanding of the molecular mechanisms of the disease and opens directions for the identification of biomarkers and personalized therapeutic strategies.

Materials and Methods

This study is based on a comparative literature review and data mining from public genomic and transcriptomic databases, including GTEx, Human Protein Atlas, STRING, GeneMANIA, and GWAS Catalog. Genes APP, PSEN1, and MAPT were selected based on their known association with neurodegenerative diseases. Pathogenic variants and common polymorphisms were identified from peer-reviewed publications and curated databases (ClinVar, dbSNP), and classified according to their clinical relevance. Gene expression profiles were retrieved from GTEx and Human Protein Atlas, while protein-protein interaction networks were generated using STRING and GeneMANIA. Data were synthesized and interpreted in the context of current molecular and clinical evidence.

Results and Discussion

Classification of APP, PSEN1 and MAPT genes

The APP, PSEN1 and MAPT genes can be classified into several functional and genomic categories, depending on the chosen classification criterion. This classification is essential for understanding the role that these genes play in the pathogenesis of both Alzheimer’s disease and other neurodegenerative diseases.

1. By physiological function of the encoded proteins

APP is a gene that encodes a transmembrane glycoprotein. Aberrant cleavage of this protein leads to the generation of β-amyloid peptide, which is the main component of senile plaques in Alzheimer’s disease (Hardy & Selkoe, 2016).

PSEN1 encodes a membrane-integrated protein that functions as a catalytic subunit of the γ-secretase complex. This enzyme is responsible for APP processing under physiological and pathological conditions (De Strooper et al., 1999).

MAPT encodes the protein tau, which is involved in the stabilization of neuronal microtubules. Tau undergoes hyperphosphorylation and forms neurofibrillary tangles under pathological conditions (Iqbal et al., 2005).

2. According to the class of encoded proteins:

APP encodes a precursor of a transmembrane protein.

PSEN1 encodes an enzyme that acts as a subunit of a protein complex.

MAPT encodes a microtubule-associated structural protein.

3. By involvement in pathology

All three genes are involved in neurodegenerative diseases:

The APP and PSEN1 genes are associated with early-onset familial Alzheimer’s disease, as they have mutations that cause increased levels of Aβ42 (Hardy et al., 1998).

MAPT is predominantly involved in frontotemporal dementias and other tauopathies, although changes in its expression can also be observed in Alzheimer’s (Ghetti et al., 2015).

Description of genes of interes

1. APP gene (Amyloid Precursor Protein)

The APP gene encodes a type I transmembrane protein, expressed mainly in the central nervous system. This protein is proteolytically processed through two main pathways: the non-amyloidogenic pathway and the amyloidogenic pathway (Haass et al., 2012). Within the latter, sequential cleavage by β-secretase and γ-secretase generates the β-amyloid peptide (Aβ), the main component of senile plaques in Alzheimer’s disease. The gene is located on chromosome 21 (21q21.3), this is particularly relevant in the context of trisomy 21 (Down syndrome), where excessive expression leads to an increased predisposition for the early development of Alzheimer’s disease (Wiseman et al., 2015). Mutations in APP are implicated in familial forms of early-onset Alzheimer’s disease, particularly in regions that influence the generation of Aβ42, the most toxic form of the peptide (Goate et al., 1991). Thus, APP is considered a major causal gene in familial Alzheimer’s.

2. PSEN1 Gene (Presenilin 1)

The PSEN1 gene encodes presenilin 1, a transmembrane protein that is part of the γ-secretase complex, involved in the final cleavage of the APP protein (De Strooper et al., 1998). Mutations in PSEN1 can alter the processing of the APP protein, leading to increased levels of Aβ42, the neurotoxic form associated with amyloid aggregates. PSEN1 is located on chromosome 14 (14q24.3) and is the most common gene implicated in early-onset familial Alzheimer’s disease. Hundreds of pathogenic mutations are known, most of which have direct effects on γ-secretase activity (Sherrington et al., 1995). In addition to its role in pathogenesis, PSEN1 is also involved in autophagy, calcium homeostasis and Notch signaling pathways, suggesting a broader spectrum of cellular disorders in the context of Alzheimer’s disease (Annaert & De Strooper, 2002).

3. MAPT Gene (Microtubule Associated Protein Tau)

The MAPT gene encodes the protein tau, which stabilizes neuronal microtubules. Under normal conditions, tau regulates microtubule assembly and dynamics, but under pathological conditions, it becomes hyperphosphorylated, forming insoluble aggregates known as “neurofibrillar tangles” (NFTs), which are a hallmark of Alzheimer’s disease and other tauopathies (Iqbal et al., 2005). MAPT is located on chromosome 17 (17q21.31) and has multiple isoforms generated by alternative splicing. The H1 haplotype variant is associated with increased risk for Alzheimer’s and other neurodegenerative diseases (Myers et al., 2007). Compared to APP and PSEN1, mutations in MAPT are more often associated with frontotemporal dementias, but altered expression and aggregation of tau are also key components in the pathogenesis of Alzheimer’s disease (Ghetti et al., 2015).

Genomic analysis of selected genes

Pathogenic mutation analysis

The genetic basis of familial Alzheimer’s disease involves rare but major mutations in the APP, PSEN1 and MAPT genes. These pathogenic variations affect the homeostasis of amyloid proteins and tau protein, and this leads to toxic aggregations and neuronal degeneration.

Types of pathogenic genetic variations (mutations)

Genetic variations in the APP gene

1. Pathogenic SNPs in APP

The APP gene is located on chromosome 21, is directly involved in the production of β-amyloid peptide. Point mutations can lead to changes in the cleavage sites of secretases or favor the formation of Aβ42, the form involved in the aggregation of amyloid plaques.

– c.2149G>A (p.Val717Ile) – pathogenic missense mutation, it affects cleavage by γ-secretase, leading to Aβ42 accumulation (Goate et al., 1991, Nature).

– c.2062T>G (p.Ile692Val) – rare, associated with early onset (HGMD, 2023).

2. Deletions/Insertions in APP

Deletions and insertions in APP are rarer, but when they occur, they can produce frameshifts and truncated proteins.

-c.2032_2033del (p.Lys678fs) – 2-base deletion, produces a short and dysfunctional protein (Goate et al., 1991, Nature).

Insertions in splicing regions can affect messenger RNA processing.

3. APP gene duplication

A mechanism of pathogenesis is the duplication of the entire APP gene, which leads to overproduction of the protein and implicitly to the formation of amyloid plaques. In 2006, this change was described by Rovelet-Lecrux et al., in patients with early Alzheimer’s and cerebral amyloid angiopathy.

Genetic variations in PSEN1

The PSEN1 gene, located on chromosome 14q24.3, encodes the catalytic subunit of γ-secretase. The gene that is most frequently involved in familial early-onset Alzheimer’s.

1. Pathogenic SNPs in PSEN1

– c.263C>T (p.Pro88Leu) – pathogenic missense mutation described in ClinVar (ClinVar ID: RCV000083623.1).

– c.548G>A (p.Gly183Arg) – alters γ-secretase function and increases the Aβ42/Aβ40 ratio (Sherrington et al., 1995).

2. Insertions and deletions in PSEN1

– c.548_549insT – insertion that induces frameshift and affects protein stability (Sherrington et al., 1995).

– Rare deletions can occur in exonic regions, but also in the promoter, affecting expression.

Genetic variations in MAPT

The MAPT gene, located on chromosome 17q21.31, encodes the tau protein. Although it is better known for its role in other tauopathies, its mutations can significantly influence Alzheimer’s pathogenesis.

1. SNPs in MAPT

– c.1216C>T (p.Arg406Trp) – pathogenic missense variant associated with abnormal tau protein aggregation (Hutton et al., 1998).

– c.1270G>A (p.Val424Ile) – considered of uncertain significance, but frequently investigated (ClinVar, 2024).

2. Insertions/Deletions

Insertions in exons 10 or 13 can affect the balance of tau isoforms (3R vs 4R), which is critical in neurodegeneration (Hutton et al., 1998).

3. MAPT haplotypes (H1 vs H2)

The H1 haplotype, which contains a ~900 kb inversion, is associated with increased risk for neurodegenerative diseases. It is a functionally neutral structural variation in most of the population, but a genomically relevant risk factor. (Hutton et al., 1998).

Normal genetic variations (common polymorphisms)

Normal genetic variations, known as polymorphisms, are changes in the DNA sequence that occur naturally in the population, without being clearly associated with pathologies. These generally include single nucleotide polymorphisms (SNPs), microsatellites, neutral insertions/deletions, and can influence response to treatment, risk for certain diseases, or phenotypic characteristics without directly causing the disease.

Polymorphisms in the APP gene

Within the APP gene, numerous common SNPs have been reported in the general population, without having a clear pathogenic significance.

rs63750847 – does not modify the encoded amino acid and is classified as benign (ClinVar, 2024).

Other polymorphisms, such as those in the promoter or 3′ UTR regions, can influence the level of gene expression, with potential implications in predisposition.

A study by Lambert et al. (2013) showed that certain SNPs in APP may have a minor role in susceptibility, but are not considered direct pathogenic mutations [PMID: 24162737].

Polymorphisms in the PSEN1 gene

In PSEN1, most mutations are rare and associated with early-onset Alzheimer’s disease, but there are also frequent variants with neutral effect. For example:

rs165932 – an intronic SNP, frequently detected in European and African populations, with no proven effect on protein function (dbSNP, 2024).

rs7523 – located in the 3’UTR region, possibly involved in regulating messenger RNA stability, but with high frequency and benign classification (Ensembl, Release 110).

Such variations are useful in large-scale association studies (GWAS) to identify risk haplotypes.

Polymorphisms in the MAPT gene

The MAPT gene presents a considerable diversity of polymorphisms, this is reflected in the existence of two major haplotypes: H1 and H2. These are common and influence the structure of the genomic region through an inversion of approximately 900 kb (Stefansson et al., 2005).

In European populations, the H1 haplotype has a high frequency and has been associated with an increased risk for several neurodegenerative diseases, including Alzheimer’s and Parkinson’s disease [PMID: 16244653].

SNPs such as rs1052553 are used to differentiate the H1/H2 haplotypes.

In addition, other SNPs located in introns or regulatory regions can modulate gene expression without inducing structural changes in the tau protein.

Genomic interpretation

Common polymorphisms are not direct causes of Alzheimer’s disease, but they play an important role in individual variability and may influence the response to environmental factors, drugs, or overall risk. Their identification and study contribute to the development of a personalized genomic basis for understanding disease susceptibility and developing prevention or treatment strategies (Visscher et al., 2017).

Gene expression in relevant tissues (GTEx / Human Protein Atlas)

Analysis of gene expression of genes involved in Alzheimer’s disease, such as APP, PSEN1, and MAPT, provides detailed information about their role in normal brain function and disease pathogenesis. Data from the GTEx and Human Protein Atlas databases allow for an extensive assessment of expression levels in different brain regions.

APP Gene Expression

The APP gene is widely expressed throughout the brain, with high levels in both hippocampal and cortical regions. Data extracted from GTEx show that APP expression is detected in all brain tissues analyzed, thus highlighting its essential role in normal neuronal functioning.

PSEN1 Gene Expression

PSEN1 is ubiquitously expressed in the brain, with moderate levels in cortical regions and basal ganglia. According to the Human Protein Atlas data, cytoplasmic granular expression is indicated in most brain tissues, supporting its involvement in the processing of membrane proteins, including APP.

MAPT Gene Expression

Fig1. APP gene tissue expression profile (GTEx)

MAPT is predominantly expressed in the central nervous system, with high levels in the hippocampus, cerebellum and cerebral cortex. According to the GTEx and Human Protein Atlas data, MAPT expression is particularly intense in the cerebral cortex, suggesting an important role in microtubule stabilization and synaptic function.

Integrating GWAS Data – Genomic Involvement in Susceptibility

Genome-Wide Association Studies (GWAS) have been instrumental in identifying common genetic variants associated with the risk of Alzheimer’s disease. In contrast to the rare, high-impact mutations observed in genes such as APP, PSEN1, and MAPT, variants discovered through GWAS have modest effects, but they nevertheless contribute to population susceptibility and may highlight novel regions of genomic interest.

The APP, PSEN1, and MAPT genes have been extensively analyzed in international research projects such as the International Genomics of Alzheimer’s Project (IGAP) and the Alzheimer’s Disease Sequencing Project (ADSP). Certain polymorphisms in MAPT have been associated with sporadic forms of Alzheimer’s disease, supporting a multifunctional role for this gene in neurodegeneration (Allen et al., 2016).

Through the analysis of GWAS data, it identified the 17q21.31 region, where the MAPT gene is located, as being significantly associated with an increased risk of Alzheimer’s disease and frontotemporal dementia. In addition, the rs242557 polymorphism in this region is considered an independent risk marker, it affects the expression and alternative splicing of MAPT (Kunkle et al., 2019).

For PSEN1, although pathogenic mutations are more frequently involved in familial forms of early-onset Alzheimer’s, GWAS data show that no common SNPs with significant association have been identified to date in the general population. Highlighting its rare but highly penetrant character in monogenic forms (Sherrington et al., 1995).

In the case of the APP gene, GWAS studies have suggested the existence of regulatory variants in intergenic regions or in promoter areas that influence the transcription level of the gene. In addition, protective variants, such as rs63750847 (c.673C>T, p.Ala673Thr), have been reported to reduce the risk of Alzheimer’s disease by decreasing beta-amyloid formation (Jonsson et al., 2012).

Correlating GWAS data with functional, type-specific (eQTL) and epigenetic data allows the construction of a complex genomic picture of Alzheimer’s disease susceptibility. This complex method may lead to the identification of new therapeutic targets and a more precise assessment of individual genetic risk.

Gene Interactions and Functional Networks (STRING, GeneMANIA)

The interpretation of gene interaction networks provides an overview of the functional role of genes involved in the pathogenesis of Alzheimer’s disease. In this regard, tools such as STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) and GeneMANIA allow the investigation of connections between the genes of interest, APP, PSEN1 and MAPT, and other genes involved in relevant biological pathways such as microtubule regulation, autophagy, amyloid precursor protein processing and cell signaling pathways.

Interaction networks – STRING

Using the STRING database, protein interaction networks were generated for the APP, PSEN1 and MAPT genes. The network combines experimental data, computational predictions, co-expression and information from the scientific literature. The results showed that:

APP directly interacts with BACE1, ADAM10, APLP1/2 and presenilins, indicating its central involvement in the amyloidogenic pathway (Fig. 2)

PSEN1, a component of the γ-secretase complex, interacts with NOTCH1, NCSTN, APH1A and PEN2, reflecting its role in cellular signaling and differentiation processes.

MAPT is connected to microtubule-associated proteins (TUBB, TUBA1A), but also to kinases such as GSK3B, CDK5 and MARK2, involved in tau phosphorylation – a critical event in neurodegeneration.

Fig 2. Protein interaction network for APP and associated genes (STRING v12)

This network highlights the functional convergence of these genes on fundamental cellular processes such as protein homeostasis, axonal transport and synaptic plasticity, all of which are altered in Alzheimer’s disease.

Predictive Networks – GeneMANIA

Using GeneMANIA, additional functional interactions were identified, based on co-expression, co-localization, shared metabolic pathways and associated phenotypic traits. The analysis shows that

APP and PSEN1 are co-expressed with genes involved in intracellular calcium regulation (CALM1, ATP2A2) (Fig. 3).

MAPT is strongly connected with genes associated with the stabilization of neuronal cytoarchitecture and neuronal protein synthesis.

These functional networks show that the pathogenesis of Alzheimer’s disease is not due to the isolated activity of these genes alone, but rather results from a complex imbalance of the molecular networks in which they are involved, Alzheimer’s being a multifactorial disease.

Fig 3. Functional interactions and gene correlations (GeneMANIA)

Diagnosis and therapy in the case of genetic variations of APP, PSEN1 and MAPT

Knowledge of genetic variations of the genes of interest has opened a new perspective in what constitutes early diagnosis and the development of personalized therapeutic strategies for Alzheimer’s disease.

Genetic diagnosis involves the analysis of the APP, PSN1 and MAPT genes in patients with early onset. This is done using NGS technology that allows the rapid identification of pathogenic variants (Bird, 2008) (Landrum et al., 2018). The resulting information is interpreted with databases such as ClinVar, to assess the clinical impact of mutations. To support molecular diagnosis, biomarkers from cerebrospinal fluid, such as Aβ42 and phosphorylated tau, can be obtained.

In the therapeutic context, mutations in PSEN1 and APP are targets for different γ-secretase and β-secretase inhibitors (Li, Liu & Selkoe, 2019). MAPT mutations are addressed by anti-tau therapies such as antibody therapy, kinase inhibitors and vaccines (Cummings, 2019).

Currently, many emerging technologies such as CRISPR/Cas9 offer promising prospects, but these are still in the research phase.

Genetic counseling remains essential in interpreting and communicating consistent results to patients, taking into account personal and family implications.

Conclusions

Genomic analysis of the APP, PSEN1 and MAPT genes has highlighted their importance in the pathogenesis of Alzheimer’s disease, especially in hereditary forms. Identification of pathogenic mutations and their association with gene expression as well as clinical data is essential in providing a correct diagnosis. By integrating data from genomic databases such as ClinVar, GTEx and CWAS, the potential of genomics in the development of personalized therapies and in the deep understanding of neurodegenerative mechanisms is highlighted.

Bibliography

1. Allen, M., Carrasquillo, M. M., Funk, C., Heavner, B. D., Zou, F., Younkin, C. S., … & Ertekin-Taner, N. (2016). Human whole genome genotype and transcriptome data for Alzheimer’s and other neurodegenerative diseases. Scientific data, 3(1), 1-10.
2. Annaert, W., & De Strooper, B. (2002). A cell biological perspective on Alzheimer’s disease. Annual review of cell and developmental biology, 18(1), 25-51.
3. Bird, T. D. (2008). Genetic aspects of Alzheimer disease. Genetics in medicine, 10(4), 231-239.
4. Cruchaga, C., Chakraverty, S., Mayo, K., Vallania, F. L., Mitra, R. D., Faber, K., … & NIA-LOAD/NCRAD Family Study Consortium. (2012). Rare variants in APP, PSEN1 and PSEN2 increase risk for AD in late-onset Alzheimer’s disease families. PloS one, 7(2), e31039.
5. Cummings, J., Blennow, K., Johnson, K., Keeley, M., Bateman, R. J., Molinuevo, J. L., … & Vellas, B. (2019). Anti-tau trials for Alzheimer’s disease: a report from the EU/US/CTAD task force. The journal of prevention of Alzheimer’s disease, 6(3), 157-163.
6. De Strooper, B., Annaert, W., Cupers, P., Saftig, P., Craessaerts, K., Mumm, J. S., … & Kopan, R. (1999). A presenilin-1-dependent γ-secretase-like protease mediates release of Notch intracellular domain. Nature, 398(6727), 518-522.
7. Gerrish, A., Russo, G., Richards, A., Moskvina, V., Ivanov, D., Harold, D., … & Williams, J. (2012). The role of variation at AβPP, PSEN1, PSEN2, and MAPT in late onset Alzheimer’s disease. Journal of Alzheimer’s Disease, 28(2), 377-387.
8. Ghetti, B., Oblak, A. L., Boeve, B. F., Johnson, K. A., Dickerson, B. C., & Goedert, M. (2015). Frontotemporal Dementia Caused by MAPT mutations: A chameleon for neuropathology and neuroimaging. Neuropathol Appl Neurobiol, 41(1), 24-46.
9. Goate, A., Chartier-Harlin, M. C., Mullan, M., Brown, J., Crawford, F., Fidani, L., … & Hardy, J. (1991). Segregation of a missense mutation in the amyloid precursor protein gene with familial Alzheimer’s disease. Nature, 349(6311), 704-706.
10. Haass, C., Kaether, C., Thinakaran, G., & Sisodia, S. (2012). Trafficking and proteolytic processing of APP. Cold Spring Harbor perspectives in medicine, 2(5), a006270.
11. Hardy, J., & Selkoe, D. J. (2002). The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science (New York, N.Y.), 297(5580), 353–356. https://doi.org/10.1126/science.1072994
12. Hutton, M., Lendon, C. L., Rizzu, P., Baker, M., Froelich, S., Houlden, H., … & Heutink, P. (1998). Association of missense and 5′-splice-site mutations in tau with the inherited dementia FTDP-17. Nature, 393(6686), 702-705.
13. Iqbal, K., Alonso, A. D. C., Chen, S., Chohan, M. O., El-Akkad, E., Gong, C. X., … & Grundke-Iqbal, I. (2005). Tau pathology in Alzheimer disease and other tauopathies. Biochimica et Biophysica Acta (BBA)-molecular basis of Disease, 1739(2-3), 198-210.
14. Jin, S. C., Pastor, P., Cooper, B., Cervantes, S., Benitez, B. A., Razquin, C., … & Cruchaga, C. (2012). Pooled-DNA sequencing identifies novel causative variants in PSEN1, GRN and MAPT in a clinical early-onset and familial Alzheimer’s disease Ibero-American cohort. Alzheimer’s research & therapy, 4, 1-9.
15. Jonsson, T., Atwal, J. K., Steinberg, S., Snaedal, J., Jonsson, P. V., Bjornsson, S., … & Stefansson, K. (2012). A mutation in APP protects against Alzheimer’s disease and age-related cognitive decline. Nature, 488(7409), 96-99.
16. Kunkle, B. W., Grenier-Boley, B., Sims, R., Bis, J. C., Damotte, V., Naj, A. C., … & Rotter, J. I. (2019). Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nature genetics, 51(3), 414-430.
17. Lambert, J. C., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., … & Foroud, T. M. (2013). Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nature genetics, 45(12), 1452-1458.
18. Landrum, M. J., Lee, J. M., Benson, M., Brown, G. R., Chao, C., Chitipiralla, S., … & Maglott, D. R. (2018). ClinVar: improving access to variant interpretations and supporting evidence. Nucleic acids research, 46(D1), D1062-D1067.
19. Li, S., Liu, L., & Selkoe, D. (2019). Verubecestat for Prodromal Alzheimer’s Disease. The New England Journal of Medicine, 381(4), 388-388.
20. Myers, A. J., Gibbs, J. R., Webster, J. A., Rohrer, K., Zhao, A., Marlowe, L., … & Hardy, J. (2007). A survey of genetic human cortical gene expression. Nature genetics, 39(12), 1494-1499.
21. Sassi, C., Guerreiro, R., Gibbs, R., Ding, J., Lupton, M. K., Troakes, C., … & Alzheimer’s Research UK Consortium. (2014). Investigating the role of rare coding variability in Mendelian dementia genes (APP, PSEN1, PSEN2, GRN, MAPT, and PRNP) in late-onset Alzheimer’s disease. Neurobiology of aging, 35(12), 2881-e1.
22. Sherrington, R., Brynjolfsson, J., Petursson, H., Potter, M., Dudleston, K., Barraclough, B., … & Gurling, H. (1988). Localization of a susceptibility locus for schizophrenia on chromosome 5. Nature, 336(6195), 164-167.
23. Sherrington, R., Rogaev, E. I., Liang, Y. A., Rogaeva, E. A., Levesque, G., Ikeda, M., … & St George-Hyslop, P. H. (1995). Cloning of a gene bearing missense mutations in early-onset familial Alzheimer’s disease. Nature, 375(6534), 754-760.
24. Stefansson, H., Helgason, A., Thorleifsson, G., Steinthorsdottir, V., Masson, G., Barnard, J., … & Stefansson, K. (2005). A common inversion under selection in Europeans. Nature genetics, 37(2), 129-137.
25. Visscher, P. M., Wray, N. R., Zhang, Q., Sklar, P., McCarthy, M. I., Brown, M. A., & Yang, J. (2017). 10 years of GWAS discovery: biology, function, and translation. The American Journal of Human Genetics, 101(1), 5-22.
26. Wiseman, F. K., Al-Janabi, T., Hardy, J., Karmiloff-Smith, A., Nizetic, D., Tybulewicz, V. L., … & Strydom, A. (2015). A genetic cause of Alzheimer disease: mechanistic insights from Down syndrome. Nature reviews neuroscience, 16(9), 564-574.