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DOI: 10.1055/s-0043-1777849
Orchestration of Genetic Alterations in PSEN1 and PSEN2 Genes in Development of Alzheimer's Disease through Computational Analysis
Abstract
Dementia is a syndrome that can cause a number of progressive illnesses that affect memory, thinking, and ability to perform everyday tasks. Alzheimer's disease (AD) is the most common cause of dementia and represents a major public health problem. AD is a progressive disease, where in early stages there is mild memory loss and in late-stage patient loses the ability to carry on a conversation. AD (for which there is no exact cause and cure known so far) is the sixth leading cause of deaths in the United States. Every 68 second someone develops AD. This study focuses on protein structure modeling of genes presenilin 1 and 2 (PSEN1 and PSEN2) and their mutated forms (Asn141Tyr found in Chinese family, Gly34Ser identified in a Japanese patient, and Arg62Cys & Val214Leu identified in the Korean patients). It also involves wild and mutant type comparison, protein interaction studies, docking and phylogenetic history based on representative ortholog species and also sheds insight into the comparative evolutionary rates of coding sequence across various orthologs. This study gives a time and cost-effective analysis of genes (PSEN1 and PSEN2) underlying AD and genetic alterations that drive development and causes of disease.
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Introduction
Alzheimer's disease (AD) is the neurodegenerative brain disease and the most common type of dementia. Dementia is a syndrome that can cause number of progressive illnesses that affects memory, thinking, and ability to perform everyday tasks. The disease is named after Alois Alzheimer who in 1906 identified changes in brain tissue of women who had died of mental illness. After she died, he examined his brain and found amyloid plaques and tangles in her brain. These plaques and tangles are the main causes of AD. The destruction of the neurons affects other part of the brain that affects the patient ability to do daily tasks. In the final stage of AD, patients are bed-bounded and require round-the-clock care and result in ultimately becoming fatal. AD is the sixth leading fatal disease in United States more than breast and prostate cancer. AD is of two types: early-onset and late-onset. Early-onset AD can be present in people aged between 30 and 60 years. The main reason of it is inherited mutation. A child whose mother or father carries a genetic mutation for early-onset AD has a 50% chance of inheriting that mutation. Late-onset AD can be present in people of aged more than 60 years. The reason for late-onset AD is still not understood. AD symptoms vary among individuals. The most common initial symptom is losing the ability to remember new information. AD patients may experience depression, social withdrawal, changes in sleeping habits, and mood swings. AD progresses slowly in three general stages: mild, moderate, and severe ([Table 1]).
AD patients can also experience depression, social withdrawal, changes in sleeping habits, and mood swings. According to APRC (Alzheimer's Pakistan Rawalpindi Chapter) in Pakistan, there is no population-based study on neurological diseases like AD. Due to a lack of research, it is very difficult to calculate an accurate number of people suffering from this AD. However, there are estimated 1 million Pakistanis who are living with AD and other forms of dementia according to APRC. To date there is no cure for AD. There are some medicines that slow down its progress especially in the early stages and others can help with mood changes and other behavior problems. Four genes involved in causing AD are PSEN1, PSEN2, APP, and APOE. Until now more than 200 mutations in gene encoding presenilin 1 (PSEN1) are described throughout the world and less than 40 mutations in gene encoding presenilin 2 (PSEN2) have been identified so far. Many PSEN2 mutations were identified in European and in African populations. Only two were found in Korean populations and only four missense mutations in PSEN2 were found in Asia. PSEN2 mutations are not only described in AD patients but also in patients with other disorders like frontotemporal dementia, breast cancer, and Parkinson's disease with dementia. Here, we have summarized the PSEN2 missense mutations found in Asia.
Mostly imaging tests of the brain are in use to confirm that person is suffering from AD or not. Magnetic resonance imaging uses radio and magnets waves to make pictures of the brain and scans to show if someone has had a stroke or blood clots that might cause the symptoms. Positron emission tomography scan shows the plaques that build up in brain due to AD. To date there is no cure for AD. There are some medicines that slow down its progress especially in the early stages and others can help with mood changes and other behavior problems. The first drug that is approved by Food and Drud Administration for the treatment of Alzheimer's was tacrine (Cognex). It worked by slowing the breakdown of acetylcholine that helps nerve cells in the brain send messages to each other. In 2012, it was removed from market because it caused liver damage. Memantine (Namenda) is another drug that is used to slow down the Alzheimer's process by keeping brain cell from using too much of brain chemical called glutamate and protect against nerve damage. This drug has fewer side effects than other.
There are estimated 1 million Pakistanis who are living with AD and other forms of dementia according to APRC (Alzheimer's Pakistan Rawalpindi Chapter). The number of Americans suffering from AD is growing fast. An estimated 5.4 million Americans are suffering from AD. People aged 70 years who have AD have 61% chance to die before the age of 80 years. A worldwide estimation of dementia has been shown in [Fig. 1].
AD causes estimated 60 to 70% cases of dementia. It is a neurodegenerative disease that acts chronically getting worse with the passage of time[1] (World Health Organization, 2012). Short-term memory loss is the most common early event seen among the patients, which results in difficulty remembering the recent events.[1] With the development of disease, several events can occur that include loss of motivation, mood swings, unable to maintain self-care, and other behavioral issues including language problems.[1] (World Health Organization, 2012). As the condition worsens, the patient withdraws himself/herself from society as well as family.[1] Before the death of patients, body parts stop functioning gradually overtime (National Institute on Aging, 2011). It has been observed that life expectancy of AD can vary from patients to patient, but on average a period of 3 to 9 years between diagnosis and complete progression of disease is observed (Querfurth & LaFerla, 2010).[2]
Research over the years has shown that causes of AD are not well understood.[1] It is thought that 70% of the risk associated with the disease is genetic that involves several genes.[3] Risk factors other than genetics associated with this disease include a history of hypertension, head injuries, or depression.[1] The progression of disease is associated with tangles and plaques in the brain.[3] For the purpose of diagnosis, a history of illness, blood tests as well as cognitive testing with medical imaging can be used to rule out the other possible causes (National Institute for Health and Care Excellence (NICE), 2016). At initial stage, symptoms can be mistaken for normal aging.[1] For a proper and timely diagnosis, an examination of brain tissue can be helpful. However, it has been observed that physical as well as mental exercise and avoiding obesity can decrease the risk of AD.[4] However, research has shown that there are no effective medications or other such materials that decrease the risk of disease development (National Institute on Aging, 2006).
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Materials and Methods
A graphical representation of work done in current study has been shown in [Fig. 2]. Three-dimensional structures of PSEN1 and PSEN2 (wild and mutated forms) were built using I-Tasser. We used RAMPAGE server[5] for the evaluation of three-dimensional models (wild + Mutated) of protein. Meta-SNP[6] and PREDICT SNP[4] were utilized to estimate the effect of mutation on stability of protein and to determine whether the mutation has an impact on normal function of protein or not. The evolutionary history was inferred using the Neighbor-Joining method[7] using software MEGA.[8] Sequences of query gene PSEN1, PSEN2, and of all orthologs were collected through ensemble database. Sequence similarity of ortholog species with human gene sequence were analyzed through alignment using basic local alignment search tool) Johnson et al., 2008[4] [9] against the protein database to choose closest putative orthologous protein sequences. After sequence acquisition, pair-wise and multiple alignment was performed using ClustalW algorithm. The algorithm calculates similarity percentage between sequences and generates an alignment file that is further used as input file during tree reconstruction. The bootstrap consensus tree inferred from 1000 replicates is taken to represent the evolutionary history of the taxa analyzed. The branches were collapsed which corresponding to partitions reproduced in less than 50% bootstrap replicates. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) us shown next to the branches. P-distance method (chosen as a substitution model) was used to calculate evolutionary distances and these distances are in the units of the number of amino acid differences per site. The current analysis of PSEN1 and PSEN2 genes involved 16 amino acid sequences, that is, one target sequence of human gene and 15 ortholog species from different categories.[10]
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Results
The three-dimensional models of PSEN1 and PSEN2 are modeled by using I-Tasser ([Fig. 3A] and [B]). Mutations, Arg62Cys, Asn141Tyr, Gly34Ser, and Val214Leu, have been highlighted by superimposing the normal and mutated structures of PSEN2 (as shown in [Fig. 3C–F]). Evaluation of structures ([Table 2]) revealed that these are reliable as maximum number/percentage of amino acids lie in the favored region that is a sterically allowed area in Ramachandran plot. This analysis not only determined reliability of structures but also showed how normal structure changes upon mutation.[11] [12] [13]
Protein Stability Analysis
PREDICT SNP and Meta-SNP were also utilized to analyze effect of mutation on protein, results of which are shown in [Fig. 4]. PREDICT SNP combines six best performing prediction methods to provide more accurate and robust alternative to the predictions delivered by individual integrated tools. Mutations with deleterious effect correspond to natural variants with known clinical manifestation. This is in many cases accompanied by decreased stability of the protein. On the other hand, mutations predicted as neutral mostly correspond to natural variants without known negative effects. Meta-SNP also hires with it different predictors (PATHER, PhD-SNP, SIFT, and SNAP) to calculate mutation impact on normal protein. Value reported under each prediction ([Fig. 4]) is given below. Maximum number of predictors show it as disease causing which validate our result.
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PANTHER: Between 0 and 1 (if >0.5, mutation is predicted disease)
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PhD-SNP: Between 0 and 1 (if >0.5, mutation is predicted disease)
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SIFT: Positive value (if >0.05, mutation is predicted neutral)
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SNAP: Output normalized between 0 and 1 (if >0.5, mutation is predicted disease)
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Meta-SNP: Between 0 and 1 (if >0.5, mutation is predicted disease)
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Estimation of Evolution
This study showed the phylogenetic history of PSEN1 and PSEN2 based on representative ortholog species and also shed insight into the comparative evolutionary rates of coding sequence across various orthologs. Neighbor joining trees for PSEN1 and PSEN2 are shown in [Fig. 5] and both target genes show close relatedness with chimpanzee, macaque, and mouse. According to PSEN1 tree, human is making cluster with chimpanzee, mouse, and macaque with bootstrap value of 100. Other clusters with highest bootstrap value i.e., 100 include cluster of Fugu and zebrafish and Xenopus with anole lizard/chicken/platypus/opossum/rabbit/Hedgehog/guinea pig / chimpanzee / human/ macaque/ mouse. High bootstrap values of the clusters correspond to highest reliability. Tree is reconciling species divergence time. Fruit fly and Ciona intestinalis are as outgroup in this tree. Evolutionary time for the tree is 0.01. Human is making cluster with macaque with bootstrap value of 77 in PSEN2 gene tree ([Fig. 5]). Clusters with highest bootstrap value i.e.100 include cluster of Rabbit with Guinea Pig/ Hedgehog/ Mouse/ Chimpanzee/ Macaque/ Human and Fugu/Zebrafish with Xenopus with Chicken/Anoli Lizard/ Platypus/ Oppossum/ Rabbit/ Guinea Pig/ Hedgehog/ Mouse/ Chimpanzee/ Macaque/ Human. High bootstrap values of the clusters correspond to highest reliability. This gene tree is also reconciling species divergence time. Fruit fly and Ciona intestinalis are as outgroup in this tree. Evolutionary time for the tree is 0.02.
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Interaction Studies
PSENEN presenilin enhancer 2 homolog (ID: ENSP00000222266) with interaction score of 0.999 has been found to be closest relative for both genes ([Fig. 6]) as per stitch results. It consists of 101 amino acids. It is an essential subunit of the gamma–secretase complex, an endoprotease complex that catalyzes the intramembrane cleavage of integral membrane proteins such as Notch receptors and APP (β-amyloid precursor protein). It probably represents the last step of maturation of gamma-secretase, facilitating endoproteolysis of presenilin and conferring gamma-secretase activity. Dimplot results for the docking interactions of PSEN1 and PSEN2 with ligand (PSENEN) are shown in [Fig. 7A] and [B]. Interaction of mutated protein (Arg62Cys) with PSENEN as shown in [Fig. 8A] and [B] shows Asn141Tyr with PSENEN. [Fig. 9A] and [B] shows interaction of Gly34Ser with PSENEN and Val214Leu with PSENEN. Residues involved in hydrogen bonding and hydrophobic interactions for all types of interactions have been summarized in [Table 3]. Differences in residues and their positions involved in both types of docking interactions clearly revealed that how active site deviation occurred and effected protein interaction as a result of mutation.
Receptor Residues Involved in Hydrophobic Interactions are represented by brick red spoked arcs (), Hydrogen Bonding shown by Green dotted lines (). Receptor residues involved in H-bonding are shown in olive green color. Ligand residues involved in H-bonding are shown in blue color.
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Conclusion
The rich amount of genomic sequence data available enables computational analysis of target genes of interest and to provide important and useful insight into their normal and mutational pathway, their link with specific phenotypic characteristic as well as association with human disease. AD is a complicated neurodegenerative disorder whose causes and effects are yet to be understood. This study gives a time and cost-effective analysis of genes (PSEN1 and PSEN2) underlying AD and appears to help orchestrate the genetic alterations that drive development and causes of disease. Structures for normal and mutated forms of proteins have been modeled, compared, and analyzed with respect to impact. Mutational analysis provided insight into how changes in normal protein lead to disease state. Evolutionary relationship for both genes was determined by reconstruction of phylogenetics trees. Classification with respect to various orthologs explored the ancestor and descendent relationship.
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Conflict of Interest
None declared.
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References
- 1 Burns A, Iliffe S. Alzheimer's disease. BMJ 2009; 338: b158
- 2 Todd S, Barr S, Roberts M, Passmore AP. Survival in dementia and predictors of mortality: a review. Int J Geriatr Psychiatry 2013; 28 (11) 1109-1124
- 3 Ballard C, Gauthier S, Corbett A, Brayne C, Aarsland D, Jones E. Alzheimer's disease. Lancet 2011; 377 (9770): 1019-1031
- 4 Bai YF, Tian J, Quan WX, Maeda K. Association of mutations of presenilin-2 gene and sporadic Alzheimer's disease. J Chinese Med University 2011; 40: 357-363
- 5 Lovell MA, Xie C, Markesbery WR. Decreased glutathione transferase activity in brain and ventricular fluid in Alzheimer's disease. Neurology 1998; 51 (06) 1562-1566
- 6 Capriotti E, Fariselli P, Casadio R. I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res 2013; 42 (Web Server issue): W306-W310
- 7 Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 1987; 4 (04) 406-425
- 8 Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 2011; 28 (10) 2731-2739
- 9 Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990; 215 (03) 403-410
- 10 Berchtold NC, Cotman CW. Evolution in the conceptualization of dementia and Alzheimer's disease: Greco-Roman period to the 1960s. Neurobiol Aging 1998; 19 (03) 173-189
- 11 Levy-Lahad E, Wasco W, Poorkaj P. et al. Candidate gene for the chromosome 1 familial Alzheimer's disease locus. Science 1995; 269 (5226): 973-977
- 12 Youn YC, Bagyinszky E, Kim H, Choi BO, An SS, Kim S. Probable novel PSEN2 Val214Leu mutation in Alzheimer's disease supported by structural prediction. BMC Neurol 2014; 14 (01) 105
- 13 Zatti G, Ghidoni R, Barbiero L. et al. The presenilin 2 M239I mutation associated with familial Alzheimer's disease reduces Ca2+ release from intracellular stores. Neurobiol Dis 2004; 15 (02) 269-278
Address for correspondence
Publication History
Article published online:
09 January 2024
© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)
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References
- 1 Burns A, Iliffe S. Alzheimer's disease. BMJ 2009; 338: b158
- 2 Todd S, Barr S, Roberts M, Passmore AP. Survival in dementia and predictors of mortality: a review. Int J Geriatr Psychiatry 2013; 28 (11) 1109-1124
- 3 Ballard C, Gauthier S, Corbett A, Brayne C, Aarsland D, Jones E. Alzheimer's disease. Lancet 2011; 377 (9770): 1019-1031
- 4 Bai YF, Tian J, Quan WX, Maeda K. Association of mutations of presenilin-2 gene and sporadic Alzheimer's disease. J Chinese Med University 2011; 40: 357-363
- 5 Lovell MA, Xie C, Markesbery WR. Decreased glutathione transferase activity in brain and ventricular fluid in Alzheimer's disease. Neurology 1998; 51 (06) 1562-1566
- 6 Capriotti E, Fariselli P, Casadio R. I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res 2013; 42 (Web Server issue): W306-W310
- 7 Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 1987; 4 (04) 406-425
- 8 Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 2011; 28 (10) 2731-2739
- 9 Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990; 215 (03) 403-410
- 10 Berchtold NC, Cotman CW. Evolution in the conceptualization of dementia and Alzheimer's disease: Greco-Roman period to the 1960s. Neurobiol Aging 1998; 19 (03) 173-189
- 11 Levy-Lahad E, Wasco W, Poorkaj P. et al. Candidate gene for the chromosome 1 familial Alzheimer's disease locus. Science 1995; 269 (5226): 973-977
- 12 Youn YC, Bagyinszky E, Kim H, Choi BO, An SS, Kim S. Probable novel PSEN2 Val214Leu mutation in Alzheimer's disease supported by structural prediction. BMC Neurol 2014; 14 (01) 105
- 13 Zatti G, Ghidoni R, Barbiero L. et al. The presenilin 2 M239I mutation associated with familial Alzheimer's disease reduces Ca2+ release from intracellular stores. Neurobiol Dis 2004; 15 (02) 269-278