[email protected]

New Order

 Genetic Variants in Schizophrenia Disorder

 Genetic Variants in Schizophrenia Disorder

Using a Genome-wide Association Study Writing instructions:

This paper for PhD level, bioinformatic class.

The paper should be attractive to the reader (write like telling a story) for the bioinformatic class.

  • Topic: Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.
  • Length of the paper: 1800 words + the abstract 200 words (total 2000 words excluding references). Cite at least 40 references for papers published in using Genome-wide association study (GWAS) to study Schizophrenia disorder through these years: 2012, 2013, 2015, 2016, 2017 and 2018 including the following references.

  • Use the paper attached in Word file “Paper as an example” as a stander for your writing.

The paper should include these references:

Paper for general information:

  1. Genetics of Schizophrenia: Overview of Methods, Findings and Limitations

Henriksen MG, Nordgaard J, Jansson LB. Genetics of Schizophrenia: Overview of Methods, Findings and Limitations. Front Hum Neurosci. 2017;11:322. Published 2017 Jun 22. doi:10.3389/fnhum.2017.00322

  1. Genome-wide association studies (GWAS) of schizophrenia: does bigger lead to better results? Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.

Bergen SE, Petryshen TL. Genome-wide association studies of schizophrenia: does bigger lead to better results?. Curr Opin Psychiatry. 2012;25(2):76-82.

Paper for Result section:

  • Avramopoulos D: Recent Advances in the Genetics of Schizophrenia. Mol Neuropsychiatry 2018;4:35-51. doi: 10.1159/000488679
  • Genome-wide association study identifies five new schizophrenia loci. Nat Genet. 2011;43(10):969-76. Published 2011 Sep 18. doi:10.1038/ng.940
  • International Schizophrenia Consortium, Purcell SM, Wray NR, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature. 2009;460(7256):748-52. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.

Format: The paper format and citation style should follow the Nature Formatting guide (https://www.nature.com/nature/for-authors/formatting-guide)

ORDER A PLAGIARISM-FREE PAPER HERE

The review paper should:

  • Abstract
  • Introduction
  • Material and method: describe the latest technologies and methods (focus on bioinformatics tools) in using GWAS to study Schizophrenia disorder.
  • Result (3pages include 2 figures): Summarize latest findings and results for using bioinformatics tool in GWAS to study Schizophrenia disorder (includ the attached papers).
  • Limitations and future directions: discuss the limitations and future directions in using GWAS to study Schizophrenia disorder.
  • Conclusion
  • References: list the cited references using Mendeley following the nature citation format.

The evaluation of review paper will be based on content, organization, grammar and spelling, and formatting. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.

Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder

Abstract

Schizophrenia (SZ) is a highly heritable brain disorder that affects approximately 1% of the population. The past decade recorded a huge growth in the field of schizophrenia genetic. Genome-wide association studies (GWAS) has been facilitated the discovery of the several common and rare variants in candidate genes associated with schizophrenia. As the size of GWAS samples have increased and the cost of NGS has decreased, numerous single nucleotide polymorphisms (SNPs) have been identified of this complex disease. Identifying the genetic underpinnings of complex diseases offers insight into the etiological mechanisms leading to manifestation of the disease and ultimately facilitate development of new treatment and prevention options. This review focuses on recent GWAS and their methods and results in schizophrenia genetics, and also addressing some limitations and challenges that confront this field of research. In short, the genetic architecture of schizophrenia has proven to be highly complex, heterogeneous and polygenic. The disease risk is constituted by numerous common genetic variants of only very small individual effect as well as by rare variants of larger effects. The future direction of GWAS is aligned with the technological advancement will continue to further our understanding of the aberrant processes leading to schizophrenia syndrome. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.

Introduction

Genome-wide association studies (GWAS) have been performed on numerous human disorders and traits1. The understanding of complex disease such as schizophrenia has been mainly supported by GWAS data analysis.  Schizophrenia is a complex illness with a lifetime frequency of ~1%. The environmental risk factors and genetic factors play curtail role in this disease. Thus,  schizophrenia have been suggested to be highly polygenic disease in nature2. Generally, the symptoms are divided into three types3. First type is the positive symptoms include hallucinations and delusions of varying content. The second type is the negative symptoms include lack of mo­tivation, anhedonia, and flat affect. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder. The third type is the cognitive symptoms involve defects in attention, concentration, working memory, and critical thinking are the most incapacitat­ing, leading to significant disability3. The patient may have a different mix of the three types of symptoms lead­ing to an overall highly heterogeneous phenotype4. Despite continuing progress, current evidence of the exact underlying biological mechanisms of schizophrenia remain ambiguous. Schizophrenia can be a result of the mixtures among complex neurological features including dysfunction in neurotransmission, hippocampus, striatum and alteration in the signaling between brain regions5. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.

The genetic heritability is the most significant risk factor for developing this disease6. Moreover, the genetic basis of schizophrenia has long been known through its tendency to run in families, as well as through adoption studies and twin studies7. The revolution in the genetics methods were helps to detect genetic variants that contribute in the development of the schizophrenia disorder6. Numerous  genome-wide association studies (GWAS) have recognized single nucleotide polymorphisms (SNPs) associated with schizophrenia8. The disease risk is constituted by several common genetic variants of only very small individual effect as well as by rare variants of larger effects9. Therefore, identifying most of the common variants and rare variants is vital for prioritizing potential pathogenic targets for diagnose and drug discovery 10. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.

In the last decade, genetic research in schizophrenia has experienced a new dawn infused by a regained optimism due to newly developed in the molecular genetics, technological methods, statistical analysis and bioinformatic tools. The application of GWAS to schizophrenia has identified multiple disease susceptibility novel risk locus 10. As the size of GWAS samples has increased, more genes have been identified with high confidence that have begun to provide insight into the etiological and pathophysiological foundations of numerous disorders11. Associated genes can offer insight into the pathophysiological mechanisms giving rise to the disease phenotype and subsequently yield potential therapeutic targets11. In this review, examination of literature will be used to determine the growth and development of the in schizophrenia using GWAS field through focusing on genetic research and data. In addation, this review will focus on the trends in the bioinformatics research, especially on molecular sequence application, that are majorly used in interpretation changes in genetic locus. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder. Finally, we seek to articulate certain limitations and challenges that tend to be deemphasized in this field of psychiatric research.

Technologies and methods in Schizophrenia GWAS

GWAS assess to detect of variation across the entire genome, with the capacity to implicate specific variants in disease risk. The vast majority of genetic disorders are polygenic, involving multiple genes and multiple alleles within these genes. The GWAS can pool genotyping of many DNA samples offers a cost benefit. Meta-analysis (combining results) and mega-analysis (combining data) yield greater power to detect disease associations with the increased of the sample size12. However, merging samples does have potential drawbacks such as diminishing the ability to detect rare alleles. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder. This has given way to genotyping individual samples following waning genotyping costs and additional analytic possibilities12. Individual genotyping also allows for the potential detection of rare copy number variants including deletions and duplications.Several approaches have been used to investigate the associations between genetic variants or loci and the disorder. In  the earlier investigations of the schizophrenia, the associations between schizophrenia and genetic markers across the extended Major Histocompatibility Complex (MHC) locus has been used to discover a set of chromosomal deletions and duplications (copy number variants) with large effects on schizophrenia 13,14.

GWAS employ a case-control study design that can detect a robust polygenic effect between case and control status in a schizophrenia data set by computing scores for each subject that depend on association test results for large numbers of SNPs from a different schizophrenia data set15. The recent technological advances such as microarrays and chips have made it possible to quickly and inexpensively scan a million SNPs genome wide. The reasoning behind the GWAS approach is that if specific allele variants are found more frequently in patients than in their controls, then the allele variants may be indicative of a genetic association. To minimize the risk of Type I errors (false positives), most GWAS operate with a stringent threshold of significance (p < 5 *10-8)9.

The basis behind GWAS is the ‘‘common-disease common-variants’’ hypothesis, which suggests that schizophrenia is mainly associated with common genetic variants (SNPs). As a result, large-scale GWAS have identified more than 100 risk loci9. However, most of these common alleles confer only relatively small risk (typically odds ratios <1.2) but cumulatively they have been estimated to explain between a quarter and half of the variance in genetic liability16. In other words, a proportion of the variance in genetic liability is apparently not accounted for by common genetic variants. Addressing this issues, the ‘‘common-disease rare-variants’’ hypothesis proposes that highly penetrant, rare (<1%) genetic variants, including copy number variations (CNVs), single nucleotide variants (SNVs), and small insertions and deletions (indels), contribute to the genetic component of schizophrenia17. The two hypotheses are complementary to each other. In the following, we briefly address some of the most significant result in Schizophrenia genetic variants using GWAS data. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.

Findings and results in Schizophrenia GWAS

GWA studies have enabled in developing genetic sequencing structures essential in determining bioinformatics applied in multidisciplinary fields. The technology improvement has contributed to enhancing genetic data collection, analysis, distribution and formulation of dependable genomic research by biologists18. The GWAS for schizophrenia begin in the relatively large collaborative case and control sample. A two-step analysis to reduce geno­typing cost, and including bipolar disorder patients in an effort to in­crease power, this study reported a single association around the ZNF804A gene, a gene that has been replicat­ed in subsequent studies19. This was followed by a larger study combining data from multiple others to reach ∼13,000 cases and 35,000 controls and reporting three genomic loci including the Human Leukocyte Antigen (HLA) region on chromosome 6 and near the genes TCF4 and NRGN on chromosomes 18 and 11, respectively20. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder. Similar study by the International Schizophrenia Con­sortium also reported on the HLA association as well as significant genetic overlap with bipolar disorder (BPD), but not to multiple non-psychiatric diseases15. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.

The most essential step was beginning by collecting samples and genotyping of cases and controls into larger consor­tia. Following by the establishing the Psy­chiatric Genomics Consortium (PGC) network in or­der to achieve the statistical power necessary for robust discovery. The PGC published its first GWAS in 2011 identifying five new loci for schizophrenia using a discovery sample of 21,856 Europeans and 29,839 independent subjects for replication21. The strongest new finding was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of adult neurogenesis and neuronal maturation 22, suggesting it may contribute to schizophrenia via perturbed developmental processes. Known functions of its four associated targets, such as the expression of CSMD1 in the nerve growth cone, initiation of neuronal differentiation by TCF4 23, and the role of voltage-gated calcium channel genes such as CACNA1C in interneuron development24, support this idea. In a joint analysis with a bipolar disorder sample (16,374 cases and 14,044 controls), three loci reached genome-wide significance: CACNA1C, ANK3 and the ITIH3-ITIH4 region21. Many other important papers followed until most recently in 2014 they published on 36,989 cas­es and 113,075 controls, combined available schizophrenia GWAS samples into a single analysis and successfully identified 128 independent schizophrenia associations, spanning 108 risk loci of genome-wide significance, 83 of which were novel findings25. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder. The au­thors mapped the variants onto epigenetic marks charac­teristic of active enhancers in 56 tissues and cell lines. As expected, they found enrichment in brain tissue enhanc­ers (highest in midfrontal and angular gyrus), but also in tissues with important roles in immunity (highest in CD19 and CD20 B cells)4. The same group also developed an analytical framework to use summary statistics data from this GWAS to identify and rank common gene/ functional pathways between schizophrenia, BD, and major depressive disorder (MDD). They reported asso­ciations for the histone methylation pathway as well as for immune and neuronal signaling and postsynaptic density26. One of the comprehensive analysis used genome-wide (SNP) data to identify specific variants underlying genetic effects shared between the five disorders in the Psychiatric Genomics Consortium including: autism spectrum disorder, attention deficit-hyperactivity disorder, bipolar disorder, major depressive disorder, and schizophrenia. Their results have shown that specific SNPs are associated with a range of psychiatric disorders of childhood onset or adult onset and pathway analysis also supported a role for calcium channel signaling genes for all five disorders27. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.

In addition to identifying multiple genes associa­tions, the GWAS also has led to a novel ap­proach in the study of the genetics of complex diseases such as the development of polygenic risk scores (PRSs)4. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder. In a paper reporting an early schizophrenia GWAS that identified the HLA locus as mentioned above, the authors performed an additional analysis where they used the GWAS results as a reference dataset to calculate PRSs on other independent datasets8. The author used the following method to formally demonstrate a long-sus­pected genetic overlap between schizophrenia and BD that is also supported by CNV and rare variant data.  The first step in this method was selecting variants from the GWAS at some significance threshold and assigns to their alleles risk. Next, calculating a PRS for each individual based on the genotypes of the individuals in the target data set at these loci. The final score is mostly driven by true risk loci since most of the selected loci are not genome-wide significant, and many are false positives. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder. As the reference GWAS and the target samples become larger, PRSs will gain power that may allow us to understand how behavioral and other phenotypes relate to each other at the level of the gene28.

The limitations and future directions

GWA studies is a powerful method to discover a numerous number of the genetic louse’s associated with schizophrenia. However, the benefits of these discoveries will only be appreciated once we begin to understand the disease mechanisms that underlie these associations. There are a number of ob­stacles through using of GWAS analysis to study schizophrenia such as It is not clear which genes and isoforms are regulated by such variants and under what conditions and time during development the regulation is occur­ring. In the GTEx database for example many of the GWAS variants are not identified as eQTLs in the includ­ed tissues. Another obstacle is that the effect of GWAS variants on the risk is quite small, with most carriers of risk alleles being healthy. It is therefore un­likely to observe a phenotype even if one could imitate the exact same biological effect in a model organism. Despite the obstacles, new biological studies are already emerging from the GWAS results. Many studies have begun to link variants to specific genes as eQTLs and experimentally follow them up to understand the biological consequences of these variants. The assess to investigate the signaling pathway and discover a new genes involve in this pathway. As we under­stand the basis of each genetic association, their common elements, the differences between them, and their inter­play with the environment, we will likely soon make leaps in prevention, treatment, and management tailored to the individual patient. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.

Conclusion

The GWA studies have experienced challenges and limitations, especially in case size and grouping, lack of appropriate sample size and computational stratification problems. Irrespective of challenges and limitation, GWA studies through technological development has promising future direction. Many findings from schizophrenia GWAS have been replicated and several of these findings have reached meta-analytic genome-wide significance. The robust associations between schizophrenia and the 100 susceptibility loci, the identified CNVs and SNVs are promising on optimal understanding for this disease. Also, the importance of the thousands of common alleles of only a very small effect, which do not individually achieve significance, but which collectively form a substantial polygenic component of schizophrenia risk, should not be underestimated. Hopefully, these results will pave the way to truly novel, actionable, therapeutic knowledge. Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.

References

  1. Visscher, P. M., Brown, M. A., McCarthy, M. I. & Yang, J. Five years of GWAS discovery. Am. J. Hum. Genet. 90, 7–24 (2012).
  2. Lichtenstein, P., Yip, B. H., Björk, C. & Pawitan, Y. NIH Public Access. 373, (2014).
  3. Cooper, J. Diagnostic and Statistical Manual of Mental Disorders (4th edn, text revision) (DSM-IV-TR). The British Journal of Psychiatry 179, (2001).
  4. Wei, L. K., Au, A., The, L. K. & Lye, H. S. Recent advances in the genetics of hypertension. Adv. Exp. Med. Biol. 956, 561–581 (2017).
  5. Millier, A. et al. Humanistic burden in schizophrenia: A literature review. J. Psychiatr. Res. 54, 85–93 (2014).
  6. Egerton, A., Modinos, G., Ferrera, D. & McGuire, P. Neuroimaging studies of GABA in schizophrenia: A systematic review with meta-analysis. Transl. Psychiatry 7, 1147–10 (2017). Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.
  7. Joober, R. & Boksa, P. S0040162516306722 @ www.sciencedirect.com. 27, 336–347 (2002).
  8. Purcell, S. M. et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009).
  9. Henriksen, M. G., Nordgaard, J. & Jansson, L. B. Genetics of Schizophrenia: Overview of Methods, Findings and Limitations. Front. Hum. Neurosci. 11, 1–9 (2017).
  10. Zuk, O., Hechter, E., Sunyaev, S. R. & Lander, E. S. The mystery of missing heritability: Genetic interactions create phantom heritability. Proc. Natl. Acad. Sci. 109, 1193–1198 (2012).
  11. Liley, J. & Wallace, C. A Pleiotropy-Informed Bayesian False Discovery Rate Adapted to a Shared Control Design Finds New Disease Associations From GWAS Summary Statistics. PLoS Genet. 11, 1–26 (2015).
  12. Bergen, S. E. & Petryshen, T. L. Genome-wide association studies of schizophrenia: Does bigger lead to better results? Curr. Opin. Psychiatry25, 76–82 (2012).
  13. Ph, D., Holmans, P. A. & Association, S. P. G. NIH Public Access. 169, 1309–1317 (2013). Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.
  14. Douglas F. Levinson, M.D., Jubao Duan, Ph.D., Sang Oh, M.Sc., Kai Wang, Ph.D., Alan R. Sanders, M.D., Jianxin Shi, Ph.D., Nancy Zhang, Ph.D., Bryan J. Mowry, M.D., F.R.A.N.Z.C.P., Ann Olincy, M.D., Farooq Amin, M.D., C. Robert Cloninger, M.D., Jeremy M. S, M. D. HHS Public Access. 168, 302–316 (2015).
  15. Dubois, A. Notes sur la classification des Ranidae(Amphibien Anoures). Bull. Mens. la Société Linnéenne Lyon 61, 305–352 (1992).
  16. Arnedo, J. et al. Uncovering the hidden risk architecture of the schizophrenias: Confirmation in three independent genome-wide association studies. Am. J. Psychiatry 172, 139–153 (2015).
  17. Article, S. AUTHOR’S PROOF Schizophrenia: a common disease caused by multiple rare alleles. 6–11 (2003).
  18. Portelli, M. A., Hodge, E. & Sayers, I. Genetic risk factors for the development of allergic disease identified by genome-wide association. Clin. Exp. Allergy 45, 21–31 (2015).
  19. O’Donovan, M. C. et al. Identification of loci associated with schizophrenia by genome-wide association and follow-up. Nat. Genet.40, 1053–1055 (2008).
  20. Stefansson, H. et al. Europe PMC Funders Group Common variants conferring risk of schizophrenia. Pmc 460, 744–747 (2011).
  21. Ripke, S. et al. Genome-wide association study identifies five new schizophrenia loci. Nat. Genet. 43, 969–978 (2011).
  22. Gladwyn-Ng, I. et al. Bacurd1/Kctd13 and Bacurd2/Tnfaip1 are interacting partners to Rnd proteins which influence the long-term positioning and dendritic maturation of cerebral cortical neurons. Neural Dev. 11, 1–8 (2016).
  23. Kirov, G. et al. Comparative genome hybridization suggests a role for NRXN1 and APBA2 in schizophrenia. Hum. Mol. Genet. 17, 458–465 (2008). Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.
  24. Ouedraogo, A. Standard et standardisation: La normativité variable en droit international. Quebec J. Int. Law 26, 156–186 (2013).
  25. Ripke, S. et al. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014).
  26. Network, T. HHS Public Access. Nat. Neurosci. 18, 199–209 (2015).
  27. Diaries, S. et al. NIH Public Access. 381, 1371–1379 (2014).
  28. Mistry, S., Harrison, J. R., Smith, D. J., Escott-Price, V. & Zammit, S. The use of polygenic risk scores to identify phenotypes associated with genetic risk of bipolar disorder and depression: A systematic review. J. Affect. Disord. 234, 148–155 (2018). Using a Genome-wide Association Study (GWAS) to Discover Genetic Variants in Schizophrenia Disorder.