Skip to main content

Biotechnology and Bioinformatics Applications in Alzheimer’s Disease

  • Chapter
  • First Online:
Biological, Diagnostic and Therapeutic Advances in Alzheimer's Disease

Abstract

Alzheimer’s disease is one of the most severe types of dementia that causes problems with memory, thinking, and behavior. Biotechnology and bioinformatics are nowadays involved in the establishment of advanced methods of diagnosis and treatment, including molecular medicine, personalized medicine, gene identification and manipulation, as well as neural engineering. Next-generation sequencing is one of the strongest tools for studying genetic diseases and gene mutations. Additionally, brain-computer interface could be used in the near future to assist people with paralysis or other related disorders and physical injuries to move toward into a better way of life, restoring memory or improving the way of everyday life. This chapter aims to provide an overview of the most common and an advanced application of biotechnology and bioinformatics in Alzheimer’s including the genome-wide association studies and the role of microbiome detection in Alzheimer’s disease.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Alexiou A, Mantzavinos VD, Greig NH, Kamal MA (2017) A Bayesian model for the prediction and early diagnosis of Alzheimer’s disease. Front Aging Neurosci 9:77. https://doi.org/10.3389/fnagi.2017.00077

    Article  PubMed  PubMed Central  Google Scholar 

  • Blennow K, deLeon MJ, Zetterberg H (2006) Alzheimer’s disease. Lancet 368(9533):387–403

    Article  CAS  Google Scholar 

  • Bodily PM, Fujimoto MS, Page JT, Clement MJ, Ebbert MT, Ridge PG, Alzheimer’s Disease Neuroimaging Initiative (2016) A novel approach for multi-SNP GWAS and its application in Alzheimer’s disease. BMC Bioinf 17(Suppl 7):268. https://doi.org/10.1186/s12859-016-1093-7

    Article  Google Scholar 

  • Callaway E (2012) Alzheimer’s drugs take a new tack. Nature 489:13–14. https://doi.org/10.1038/48901

    Article  CAS  PubMed  Google Scholar 

  • Chatzichronis S, Alexiou A, Simou P, Matzavinos V, Tsiamis V et al (2019) Neurocognitive assessment software for enrichment sensory environments. J Proteomics Bioinform 12:018–028. https://doi.org/10.4172/0974-276X.1000492

    Article  Google Scholar 

  • Chen H, Chan DC (2009) Mitochondrial dynamics – fusion, fission, movement, and mitophagy-in neurodegenerative diseases. Hum Mol Genet 18(R2):R169–R176

    Article  CAS  Google Scholar 

  • Chen H, McCaffery JM, Chan DC (2007) Mitochondrial fusion protects against neurodegeneration in the cerebellum. Cell 130(3):548–562

    Article  CAS  Google Scholar 

  • Deming Y, Filipello F, Cignarella F, Hsu S, Mikesell R, Li Z, Del-Aguila JL, Dube U, Farias FG, Bradley J, Cantoni C, Benitez B, Budde J, Ibanez L, Fernandez MV, Blennow K, Nellgard B, Zetterberg H, Heslegrave A, Johansson PM, Svensson J, Lleo A, Alcolea D, Clarimon J, Rami L, Molinuevo JL, Suarez-Calvet M, Morenas-Rodriguez E, Kleinberger G, Ewers M, Brett TJ, Haass C, Harari O, Karch CM, Piccio L, Cruchaga C (2018) The MS4A gene cluster is a key regulator of soluble TREM2 and Alzheimer disease risk. bioRxiv 352179. https://doi.org/10.1101/352179

  • Gardner A et al (2009) Differences at brain SPECT between depressed females with and without adult ADHD and healthy controls: etiological considerations. Behav Brain Funct 5(1):37

    Article  Google Scholar 

  • Herwig U, Satrapi P, Schönfeldt-Lecuona C (2003) Using the international 10-20 EEG system for positioning of transcranial magnetic stimulation. Brain Topogr 16:95–99. https://doi.org/10.1023/B:BRAT.0000006333.93597.9d

    Article  PubMed  Google Scholar 

  • Ibsen S et al (2015) Sonogenetics is a non-invasive approach to activating neurons in Caenorhabditis elegans. Nat Commun 6:8264. https://doi.org/10.1038/ncomms9264

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lau T, Gwin J, Ferris D (2012) How many electrodes are really needed for EEG-based mobile brain imaging? J Behav Brain Sci 2(3):387–393. https://doi.org/10.4236/jbbs.2012.23044

    Article  Google Scholar 

  • Levitin A (2011) Introduction to the design and analysis of algorithms, 3rd edn. Pearson Education Limited, Harlow

    Google Scholar 

  • Luo S, Lu JY, Liu L (2016) Divergent lncRNAs regulate gene expression and lineage differentiation in pluripotent cells. Cell Stem Cell 18(5):637–652

    Article  CAS  Google Scholar 

  • Lustbader JW et al (2004) ABAD directly links Abeta to mitochondrial toxicity in Alzheimer’s disease. Science (New York, NY) 304(5669):448–452

    Article  CAS  Google Scholar 

  • Mantzavinos V, Alexiou A (2017) Biomarkers for Alzheimer’s disease diagnosis. Curr Alzheimer Res 14(11):1149–1154

    Article  CAS  Google Scholar 

  • Marioni RE, Harris SE, McRae AF et al (2018) GWAS on family history of Alzheimer’s disease. Transl Psychiatry 8:99

    Article  Google Scholar 

  • Martin LJ (2010) Mitochondrial and cell death mechanisms in neurodegenerative diseases. Pharmaceuticals 3(4):839–915

    Article  CAS  Google Scholar 

  • Mattsson N (2009) CSF biomarkers and incipient Alzheimer disease in patients with mild cognitive impairment. JAMA 302:385

    Article  CAS  Google Scholar 

  • Mattsson N (2010) CSF biomarkers and incipient Alzheimer disease in patients with mild cognitive impairment. JAMA 302(4):385–393. https://doi.org/10.1001/jama.2009.1064

    Article  Google Scholar 

  • Minter MR, Hinterleitner R, Meisel M, Zhang C, Leone V, Zhang X, Oyler-Castrillo P, Zhang X, Musch MW, Shen X, Jabri B, Chang EB, Tanzi RE et al (2017) Antibiotic-induced perturbations in microbial diversity during post-natal development alters amyloid pathology in an aged APPSWE/PS1ΔE9 murine model of Alzheimer’s disease. Sci Rep 7(1):10411. https://doi.org/10.1038/s41598-017-11047-w

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Petersen RC, Doody R, Kurz A et al (2001) Current concepts in mild cognitive impairment. Arch Neurol 58(12):1985–1992

    Article  CAS  Google Scholar 

  • Rao AA, Reddi KK, Thota H (2008) Bioinformatic analysis of Alzheimer’s disease using functional protein sequences. J Proteomics Bioinform 1:036–042. https://doi.org/10.4172/jpb.1000007

    Article  CAS  Google Scholar 

  • Ridge PG, Karch CM, Hsu S, Arano I, Teerlink CC, Ebbert M, Gonzalez Murcia JD, Farnham JM, Damato AR, Allen M, Wang X, Harari O, Fernandez VM, Guerreiro R, Bras J, Hardy J, Munger R, Norton M, Sassi C, Singleton A, Younkin SG, Dickson DW, Golde TE, Price ND, Ertekin-Taner N, Cruchaga C, Goate AM, Corcoran C, Tschanz J, Cannon-Albright LA, Kauwe J, Alzheimer’s Disease Neuroimaging Initiative (2017) Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimer’s disease resilience. Genome Med 9(1):100. https://doi.org/10.1186/s13073-017-0486-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sanchez-Mut JV et al (2018) PM20D1 is a quantitative trait locus associated with Alzheimer’s disease. Nat Med 24:598–603

    Article  CAS  Google Scholar 

  • Visser PJ, Verhey FR (2008) Mild cognitive impairment as predictor for Alzheimer’s disease in clinical practice: effect of age and diagnostic criteria. Psychol Med 38(1):113–122

    Article  CAS  Google Scholar 

  • Vogt NM, Kerby RL, Dill-McFarland KA, Harding SJ, Merluzzi AP, Johnson SC, Carlsson CM, Asthana S, Zetterberg H, Blennow K, Bendlin BB et al (2017) Gut microbiome alterations in Alzheimer’s disease. Sci Rep 7(1):13537. https://doi.org/10.1038/s41598-017-13601-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wang X et al (2008) Amyloid-beta overproduction causes abnormal mitochondrial dynamics via differential modulation of mitochondrial fission/fusion proteins. Proc Natl Acad Sci U S A 105(49):19318–19323

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mahmoud A. Ali .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ali, M.A., Alexiou, A., Ashraf, G.M. (2019). Biotechnology and Bioinformatics Applications in Alzheimer’s Disease. In: Ashraf, G., Alexiou, A. (eds) Biological, Diagnostic and Therapeutic Advances in Alzheimer's Disease. Springer, Singapore. https://doi.org/10.1007/978-981-13-9636-6_12

Download citation

Publish with us

Policies and ethics