Discussion

We demonstrate that both SCZ and BPD have a theoretical basis for a diagnosis in response to the presence of certain AKAP11 variants; however, when applied practically to observed diagnosis frequencies, the possibility that SCZ has a correlation with these variants is weak.  One potential reason for this discrepancy is disagreements in the eukaryogenesis hypothesis \citep{Koonin2006}.  Current literature presents contradictions in the evolution of modern eukaryotic cells: some suggest that the ability for eukaryotic mRNA splicing is a consequence of intron interruption within genes, while others suggest that intron lineage had no effect on eukaryotic evolution \citep*{Belshaw2006}.  Previous studies on the AKAP11 correlation with mental disease focused solely on protein–coding exons and their role in disease pathogenesis.  On the contrary, our study chose to adopt a more outward approach which focused on the gene variants as a whole rather than solely exon interaction.  These inherent differences in approach represent differing results from eukaryogenesis hypotheses in that we considered introns and exons equally, though others have excluded introns from analysis.  Subsequent research must therefore be conducted to further investigate genetic modelling to provide a more comprehensive understanding of the underlying assumptions made in both models.
However, we obtained perfect overlap between SCZ and BPD when we apply high–risk variants to their expected amino acid frequencies, indicating of a strong correlation between AKAP11 and both of these diseases.  This suggests that the altered bonding of AKAP11 variants to group A­–kinase anchor proteins results in a higher probability of SCZ and BPD diagnosis.  Overall, we find that the correlation to AKAP11 is robust with BPD and moderate with SCZ.
The reason for a less significant effect when SCZ is applied to the Canadian population may be due to limitations in our model.  For example, variables in the genome annotations of each variant likely influenced our findings.  Namely, the results of the regression are based primarily on the consequence genome annotation as defined by Sequence Ontology to classify each variant.  While it is an accepted annotation tool, improvements are still being suggested to this annotation at the current date \citep{Eilbeck2005}.  As seen in Fig. \ref{378760}, there is a vast discrepancy between the probabilities that each variant will be placed in Class 4 between SCZ and BPD (as evidenced by the extreme scaling differences of the relative probabilities of both diseases).  Such a large variance in the class probabilities between SCZ and BPD is likely indicative that there may be differences in genome annotation, which is required for both theoretical and practical statistical testing.
Similarly, the study is limited by the fact that only the AKAP11 variants found in SCHEMA and BipEx were included in the analysis.  There were many differences between which variants were described in each data set.  Without identical data sets, it is impossible to get a complete analysis of the entire AKAP11 gene; as a result, both diseases have different data inputs for the logistic regression.  This therefore reduces the accuracy of comparing the results from two different regression tests to a single data set of the Canadian population.
The results of this statistical model have far­–reaching implications.  Individuals with a diagnosis of either disorder would require highly individualized treatment (\citealp{Goldberg2019}; \citealp{Vieta2010}) rather than a universalized system which assumes complete similarity between SCZ and BPD.  With respect to legislative consequences, it would be beneficial to invest in a more genetic approach to combating mental diseases.  For example, the genome editing CRISPR­–Cas–9 system has several applications, including mental illnesses such as schizophrenia and bipolar I disorder. Using such a method, precise and highly targeted edits of potentially threatening genetic alleles \citep*{Michael2021}, specifically AKAP11.  It is also necessary to better subsidize treatment facilities which specifically target at–risk demographics for these diseases.  We find that males under 30 and females between 50 and 55 may be particularly vulnerable, and this could aid in creating an improved system of finding and treating individuals affected with SCZ and BPD, respectively. Lastly, the efficiency of our methods could be improved for future research through a computer code (see Appendix) that compares data sets for high–risk AKAP11 variants and demographic diagnoses. This would allow for a more practical application of data for the global population rather than just the Canadian population.
Since our results suggest a strong correlation between AKAP11 and BPD and a slight correlation with SCZ, further research aimed at the genetic predispositions of mental disease will allow for more confident applications of genetic patterns as it relates to SCZ and BPD.