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Mental illness is regarded as a concerning problem and genetic factors tend to develop a considerable contribution in the formation of mental issues incorporating epigenetic regulation (Ran et al., 2021). This epigenetic tends to impact the way a person reacts to their surrounding factor and might have a considerable impact on whether the individual formulates an issue of mental disorder as an outcome. Focusing on the increasing complexity associated with mental health many researchers have transformed their concern on the genetic aspect of mental disorders.
The focus of the current paper in specific is the bipolar disorder. Among these psychiatric disorders, bipolar disorder (BD) is a condition which causes severe episodes of mood swings with extreme emotional conditions. Affected people experience an extreme range of emotional spectrum with emotional highs (hypomania or mania) and lows (depression) (NIH, 2023). These episodes may occur on a rare basis or much often, depending on the intensity of the patient’s conditions. As a result of these extreme mood swings people experience critical impacts on their sleeping cycle, activities, decision-making ability, behaviour, thinking ability and so on. It is a much complex condition to study on for medical experts and it is a lifelong condition requiring significant medication, behavioural treatment and psychological counselling.
The significance of considering the topic is mainly due to the intriguing requirement of recognising the diverse aspects of mental disorders by evaluating the factors contributing to genetic influence of bipolar disorder and ensuring that significant prevention, as well as treatment approaches, can be recognised (Breeksema et al., 2021). The problem reflects the gap concerning the genetic impacts of the suspect ability as well as the progression of different mental health issues (Nearchou et al., 2020). The bipolar disorder issue consideration is complex as you develop considerable impact on not only the individual but also as well as societies resulting in the development of social economic pressure. The current treatment process generally lacks accuracy and a clear understanding associated with genetic elements to transform the diagnosis process (Austin, 2020). Focusing on this the research work would shed light on reflecting on the connection between mental illness as well as genetic factors.
The structure of the research work mainly incorporates a clear evaluation of the background and research question in the introduction chapter followed by the literature review chapter. Vital methods to meet the set research aim outlines in the methodology chapter followed by the result chapter to reflect on the findings and lastly conclusion develops as reflected in the image below.
As regarded by NIH (2023), different psychiatric disorders have been developed that have been present among families for generations incorporating ADHD, Austin, schizoparina, bipolar disorder, and major depression (LoPresti et al., 2020). These driver psychiatric syndromes have been regarded as of great concern for the overall medical community as there was no clear evaluation of the reason leading to such syndrome and the process of recognising the genetic factors leading to such diseases that make it complex to understand the mechanism and make the diagnosis process critical (Glahn et al., 2019). Different studies have critically outlined most of the psychiatric disorders followed by genetic aspects reflecting that individuals having a family history of depression are more likely to develop the issue of depression among themselves and such individuals' development of schizophrenia can take place 8 times more (APA, 2023). It was recognised that critical international research has been executed that reflected on the information associated with genome-wide association studies reflecting on 5 major issues. Additionally, the researchers found that all five illnesses had polymorphism linked to sickness in specific areas of chromosomes 3 as well as 10 (Wu et al., 2019). These locations are spread across multiple genes, as well as the underlying causes are still unknown. The closest connections to the illnesses were found in the suspicious region across chromosome 3. Additionally, this area has several variants that have been connected to schizophrenia as well as bipolar disorder in the past. Family is the primary area of importance. Any discussion on heredity always involves families (Lee et al. 2021). Families are able to take part in research investigations together with an individual participant.
Bipolar disorder, characterized by recurrent episodes of mania and depression, represents a complex psychiatric condition with a notable genetic component. Familial aggregation studies have consistently demonstrated the heritability of bipolar disorder alongside other psychiatric illnesses (NIH, 2023). The disorder's hereditary nature is evidenced by its tendency to run in families across generations, implying a substantial genetic contribution to its aetiology (NIH, 2023). This genetic susceptibility has spurred considerable interest in identifying specific genetic factors implicated in bipolar disorder, aiming to elucidate its underlying mechanisms and potentially inform more targeted therapeutic interventions. While some studies, such as those employing text mining techniques (Wu et al., 2019), have explored genetic markers in psychiatric disorders, there remains a critical need for a systematic review focused explicitly on consolidating and evaluating existing genetic evidence concerning bipolar disorder. There are different bipolar disorder syndromes and other related mental issues which have been indicated to have wide spectrum of genetic and hereditary tendencies. According to O'Connell and Coombes (2021), types of these disorders like Bipolar disorder I and II, cyclothymic disorder and such disorders have shown critical association among first degree relatives and offspring. These observations indicate possible hereditary processes involved in the development of BD. Moreover, Kato (2019) has highlighted possible genetic markers and variants associated with the development and pathogenesis of BD as a disorder. Several factors like FADS, EPA, DHA and such factors that have indicated these genetic associations Kato (2019). Gordovez and McMahon (2020) have indicated in their observation’s possible genetic susceptibility and epigenetic trends behind the development and mechanisms involved in BD. According to Scaini et al. (2020), there have been various gene-by-environment expressions associated with BD which have indicated towards genetic associations in BD development. These involve DNA methylation, chromatin remodelling, histone modifications, non-coding RNAs. More critically, the observations by Prata et al. (2019) has explored evidences of some direct genetic factors like AMBRA1, ANK3, ARNTL, CDH13, EFHD1, MHC, UGTIA1 and PLXNA2 which have common in many studies associated with the BD developments and evaluations.
The study aims to understand how bipolar disorder passes across generations within families and identify genetic factors associated with it. This research has significant implications for public health as it can guide preventive strategies, improve genetic counselling, and lead to personalized treatments. By uncovering specific genetic influences, it may enhance diagnostic tools, aid clinical management, and contribute to advancing mental health research and education.
Previous research has made significant consideration of the quantitative approach reflecting the statistical aspect. This has critically improved a clear recognition of hereditary bipolar issues and provided subjective experience gained by a person. However, there was no concern laid on a quantitative evaluation of the research area and concerning this the research work focuses on recognising the different factors that lead to mental conditions of bipolar disorder and its intriguing impact on society and family. The population group to be highly affected by the development of this research work is mainly those individuals having symptoms or going through bipolar disorder that is formulated due to genetic factors. Such individuals might encounter distinctive issues as well as experiences which have not been significantly determined within the existing literature reflecting the quantitative methods. The consideration of the quantitative lens is supported by clearly highlighting the way individuals manage and hole their situation Moreover the consideration of the quantitative process intends to focus on a clear evaluation of the human centre recognition associated with genetic-based mental illness. The consideration of a quantitative systematic review intends to shed light on the existing gap within the knowledge reflecting the issues encountered by individuals going through mental illness, providing insight into challenges and preferences as well as accessibility concerning existing intervention.
How does genetics influence bipolar disorder?
In the process of developing the Research question the concern has been laid on making utilisation of academic framework to formulate as well as evaluate the outline research question. There are two kind of framework incorporating “SPIDER framework” having elements like “sample”, “phenomenon of interest”, “design”, “evaluation” and “Research type” and the other one is PICO framework which incorporate “population”, “intervention”, “comparison”, “outcome” (Johnson et al., 2022). This research work intends to evaluate “the genetic influence on bipolar disorder” make optimum consideration of a quantitative systematic review for which consideration of the “PICO framework” resembles an effective to link with the outlined research question.
| Population/Problem | People suffering from bipolar disorder |
| Intervention/Exposure | Focusing on the genetics-induced bipolar disorder among the target population of bipolar disorder affected people |
| Comparison | Systematic review has been considered to critically outline the factors associated with genetic associations leading to bipolar disorder issues by incorporating a systematic meta-analysis. |
| Outcomes | A critical and systematic overview on the potential genetic influences and hereditary nature of BD as a mental disorder |
Table 1: PICO Framework
(Source: Self-created)
The focus of the current chapter is to summarise the key findings of the empirical literature that are found relevant in the context of the current research paper. During developing this chapter, the aim strictly was to evaluate a strong theoretical underpinning and empirical background for this study. This required critically analysing a series of literature (scholarly as well as non-scholarly) that are exploring the context of genetic factors behind mental disorders, the bipolar disorder and genetic or hereditary influence on this psychological disorder. The process of this critical analysis of the relevant literature is necessary to be developed to ensure that there is sufficient exploration of the current and on-going developments in this field. In this process, apart from scholarly literature like peer-reviewed journal and research articles and conference papers, it was also necessary to explore non-scholarly resources like government and reputed archives, reliable websites and so on. Moreover, there was a critical requirement of following a systematic search strategy to be followed to ensure that relevant and critical analysis of the existing literature.
The search strategy associated with the development of this literature review chapter has been a critically systematic process that considered relevant search keywords, Boolean operations and reputable databases to search from. It is critical to overview this entire process to understand the empirical foundation of the systematic review being developed in later chapters. There have been various relevant and useful keywords which were identified as crucial for the systematic search for finding the most relevant literature associated with the current context. The research context here is the genetic influence of bipolar disorder. Therefore, the critical keywords here include: “genetic factor”, “epigenetics”, “bipolar disorder”, “mental disorder” and so on. The search terms and their respective Boolean expressions used for the literature review here are as follows:
| Search term | Boolean Expression |
|---|---|
| Search term 1 | (genetic) and (factor) and ((bipolar) OR (mental)) and (disorder) |
| Search term 2 | (epigenetics) and ((bipolar) OR (mental)) and (disorder) |
Table 2: Search terms
(Source: Self-created)
There have been open or partially open accessed scholarly databases considered for the literature extraction process. These databases included various reputed databases like Google Scholar, PubMed, NIH and so on. Moreover, a filter of publication year (last five years) has also been used in this process to keep the inclusion as updated as possible, so that current and on-going developments can be evaluated. The entire search process of this literature findings for this chapter involves various inclusion and exclusion criteria and steps. This can be observed as follows:
Figure 1: Search flow chart
(Source: Self-created)
Mental illness is regarded as a concerning problem in the domain of public healthcare and healthcare as a whole. However, in recent times genetic factors has been gradually found to develop a considerable contribution in the formation of mental issues incorporating epigenetic regulation (Ran et al., 2021). This epigenetic trend of psychological conditions to impact the way a person reacts to their surrounding factor. Thus, these trends might have a considerable impact on whether the individual formulates an issue of mental disorder. The continuous increasing complexity associated with mental health and the recent epigenetic impacts revealed are making many researchers have transformed their concern on the genetic aspects of mental disorders (Austin, 2020).
According to Austin (2020), there are various psychiatric disorders which have been found as a result of heterogeneous and complex combinations of environmental as well as genetic factors. These disorders include many common conditions such as schizophrenia, depression, anxiety, and bipolar disorder. However, in usual practices there has been a lack of serious considerations in the clinical practices regarding these epigenetic trends of the psychological conditions. According to Austin (2020), apart from certain childhood neurodevelopmental issues (like intellectual disability or autism), there has not been much consideration of any genetic testing in such common psychiatric conditions. Moreover, the context of genetic counselling is an even less considered aspect despite the continuous growing interest among patient families (Austin, 2020). According to the critical findings by Austin (2020), studies have evidences to show that genetic counselling has the ability to empower communities and populations against certain common psychiatric conditions. However, there has not been widely or routinely offered interventions of genetic counselling in mental disorders.
According to Glahn et al. (2019), with time the critical findings have revealed in terms of the associations of genetic markers and factors of mental illnesses considering the heritability factor. Moreover, literature have found many common as well as rare genetic factors and variations which are associated with complex mental disease risks. All these factors make the studies on full range of allelic frequency distribution crucial for a critical and effective dissection of the genetic influences on mental illnesses (Ward et al., 2019). There have been various types of interventions like WGS or Whole Genome Sequencing to explored these scopes of genetic studies on psychiatric conditions which are being conducted recently (Maul et al. 2020).
The study by Wu et al. (2019) have also remarked on the heritability of common mental conditions and the complex interactions of environmental and genetic factors. However, Wu et al. (2019) have critically identified how difficult and complex it is to evaluate the correlation of genetic factors with mental disorders. Wu et al. (2019) have applied an advanced technical application of machine learning and text mining to reveal about 52 high frequency genes (as words) in mental disorder related studies. This shows how often certain genetic factors have emerged in mental disorder studies and interventions to highlight the importance of epigenetics in psychiatric research context. Genetic factors like 5-HTT, MAOA. SLC6A4 and CCK have emerged out of these studies, whereas many critical findings (like a close association between the genetic factors behind schizophrenia and affective disorder) have also been emerged (Wu et al., 2019).
In order to explore the current research context, it is necessary to establish a strong background context of the bipolar disorder as a psychological illness. The psychological illness of bipolar disorder (that was earlier known as manic depression) is a critical mental condition which causes severe episodes of mood swings with extreme emotional conditions (O'Connell and Coombes, 2021; NIH, 2023). The people who get affected by this disorder experience an extreme range of emotional spectrum with emotional highs (hypomania or mania) and lows (depression). These episodes may occur on a rare basis or much often, depending on the intensity of the patient’s conditions (O'Connell and Coombes, 2021). The extreme mood swings people experience critically impact their sleeping cycle, activities, decision-making ability, behaviour, thinking ability and so on (NIH, 2023). It is a much complex condition to study on for medical experts and it is a lifelong condition requiring significant medication, behavioural treatment and psychological counselling.
There have been several types of disorders that are usually associated with this disease such as bipolar I, bipolar II, cyclothymic and other types of associated psychological conditions (APA, 2023). The Bipolar I disorder is a condition, where at least one episode of emotional highs (mania) happens usually followed or preceded by a hypomanic or depressive episode (O'Connell and Coombes, 2021). In many cases, such mania can trigger a critical psychosis. On the other hand, in case of Bipolar II disorder people get at least one hypomanic and one major depressive episode. However, no such manic episode is followed in this type of disorder (O'Connell and Coombes, 2021). A cyclothymic disorder is commonly observed in children and teenagers, whereas periodic episodes of depressive (not much major) and hypomanic episodes (APA, 2023). There are also other types of critical forms of bipolar and related disorders that may get induced by alcohol, drugs, substance misuses or other mental conditions (APA, 2023). This includes issues like Cushing’s disease, multiple stroke or sclerosis. These are all different types of diagnosis of bipolar disorders with different intensities and population of targets. There are various severe and critical complications which have been faced by the patients having these issues that include substance abuse issues, suicidal tendencies, indirect financial or legal problems, issues in all kinds of relationships and poor academic or professional performances (APA, 2023). There have been different risk factors which have been explored over these years as significant in triggering such issues among the patients. These risk factors include periods of high stress or traumatic event, alcohol or drug abuse and first-degree relatives (i.e., where hereditary factors are being explored) (APA, 2023).
Therefore, critical discussions on the conditions associated with bipolar disorder have identified on-going explorations and interventions on hereditary factors regarding the bipolar disorders.
Critical discussions earlier in this chapter has indicated the risk factors associated with hereditary or genetic factors regarding bipolar disorder. A critique on these factors and associations would be much effective through exploration of how this aspect has been explored in the existing literature. Moreover, a critical analysis of the updated literature would help in understanding the current and on-going progress and developments to contribute to them. Current understandings on this matter as a research context is much limited by the limited research community. According to Kato (2019), earlier and current studies have mostly focused on the extensive roles of antidepressants, antipsychotic drugs and monoamines on the mechanisms associated with BD. There are also critical developments in the context of the elucidation of neural circuits (such as the abnormalities in calcium signalling or role of paraventricular thalamic nucleus) (Kato, 2019). However, in the recent decades after the discoveries made by GWAS (in 2007) focus has been critically shifted towards the genetic associations of BD (Kato, 2019). Several factors like FADS (fatty acid desaturase) 1/2, DHA (docosahexaenoic acid), EPA (eicosapentaenoic acid) and such influencers were found to be interacting with the BD mechanisms (Kato, 2019). These factors provoked the genetic interactions in the development of BD as a mental condition. This highlights how critical as a domain of research the genetic context of BD has gradually become for the developments of therapeutic interventions.
According to Gordovez and McMahon (2020), bipolar disorder, characterized by recurrent episodes of mania and depression, represents a complex psychiatric condition with notable genetic components. Hereditary aggregation studies have consistently demonstrated the heritability of bipolar disorder alongside other psychiatric illnesses over the recent years of research and developments (NIH, 2013). The disorder's hereditary nature is indicated by its tendency to run in families across generations, implying a substantial genetic contribution to its aetiology as highlighted by many investigators (NIH, 2013). These epigenetic trends and genetic susceptibility have spurred considerable interest in identifying specific genetic factors implicated in bipolar disorder, aiming to elucidate its underlying mechanisms and potentially inform more targeted therapeutic interventions.
According to Gordovez and McMahon (2020), among the research and developments domain of mental illnesses is considered to be bipolar disorder is considered as one of the most heritable conditions. However, there have been considerable challenges found in the elucidation of the genetic basis and factors behind this condition. Literature findings have suggested that the association, pathogenesis and mechanisms behind the genetic influence of the bipolar disorder is much complex (Gordovez and McMahon, 2020). Evidences of genetic markers of this disorder through Genome-Wide Association Studies or GWAS have much transformed the understandings and research context in this domain (Gordovez and McMahon, 2020). According to Gordovez and McMahon (2020), common genetic variants and markers when combined together have been found to be as risky as causing 25% of the heritability scenario of the disease, even if having low risks as individual factors. Moreover, there are also certain high-risk factors or markers which have been found in recent developments such as a much rare copy number variant on 16p11.2 chromosome (Gordovez and McMahon, 2020). However, researchers and investigators have speculated that to understand the overall genetic impacts and genetic associations in the bipolar disorder conditions it is required that large scale generational sequencing studies are developed (Gordovez and McMahon, 2020). Many such studies are on-progress to actively search for alleles that may confer substantial risks.
Considering the high frequency of heritability of the bipolar disorder, there have been several critical studies which have been developed in the recent times on the possible genetic associations. One such development by O'Connell and Coombes (2021) has highlighted that while BD has become a much common mental condition globally (with 50 million affected people), the genetic etiology has become a rapidly growing interest in the recent years. As criticised by O'Connell and Coombes (2021), the critically influencing factor behind this recent development has been the advances in methodologies and technologies such as adoption of large population-based biobanks and international consortiums. Moreover, another critical factor being remarked in this context is the genetic overlap of variants with many other mental disorders. However, the overall genetic architecture is still difficult to be fully characterised considering a significant lack in research outcomes and knowledge in this domain (O'Connell and Coombes, 2021). There are requirements of various kinds of critical studies which are required to be developed while evaluating these characteristics of BD. According to O'Connell and Coombes (2021), this includes ancestrally-diverse samples to avoid Eurocentric bias, incorporation of population biobanks, electric health records and registry data as well as studies on rare variations of BD. In order to develop effective therapeutic interventions based genetic risk predictions, it is much necessary to enrich this research domain with effective and useful research and development works by academics, professionals and experts.
According to Scaini et al. (2020), there are much complex neurobiological developments that are associated with BD that associates signalling pathways, biochemical changes and various neuroimaging findings with genetic components. Interactions among several genetic, environmental and neurochemical factors has been presumed by literature (Scaini et al., 2020). According to Scaini et al. (2020), study evidences have suggested very strong genetic components associated with BD that can have heritability rates as high as 70-80%. The increasing risks of BD among first-degree relatives and offspring have also suggested strong genetic associations. Gradually more and more studies are coming up with significant genetic findings associated with BD and inherited familial environment. According to Scaini et al. (2020), there have several critical epigenetic mechanisms encompassing multiple pathways that have been found to be mediating gene-by-environment interactions and modulating gene expressions leading to related symptoms. These include DNA methylation, chromatin remodelling, histone modifications, non-coding RNAs and so on (Scaini et al., 2020). The evidences of critical genetic and epigenetic association of BD has been eventually coming up recent studies and are difficult to be ignored. On the other hand, in their studies Scaini et al. (2020) have highlighted a critical gap regarding the investigations on rare variants associated with BD.
Apart from the genetic and epigenetic associations of BD, there have also been developments on the genetic overlaps of BD with other mental disorders. According to Prata et al. (2019), one such critical mental condition is Schizophrenia, whereas several common genetic markers have been found to be common and critical in both the disorders. According to Prata et al. (2019), these factors include AMBRA1, ANK3, ARNTL, CDH13, EFHD1, MHC, UGTIA1 and PLXNA2. These common factors found associated as common variants interacting with both the disorders have provoked a critical interest and focus on the research domain of BD genetics. Moreover, Robinson and Bergen (2021) in their studies have also predicted possible mechanism of interactions between environmental and genetic risk factors that overall, between the two diseases. These findings are becoming more and more critical day-by-day considering their possible inputs in the psychiatric therapeutic applications of the BD condition.
The overall critical literature development in this chapter has found many critical factors which associates with the genetic context of BD. However, in order to realise possible and practical therapeutic applications there are still certain critical knowledge gap which have been highlighted to be overcome by research and development efforts in this domain.
While some studies, such as those employing text mining techniques (Wu et al., 2019), have explored genetic markers in psychiatric disorders, there remains a critical need for a systematic review focused explicitly on consolidating and evaluating existing genetic evidence concerning bipolar disorder. There has been a critical knowledge gap in the context of the genetic factors and influences on BD which has been found in the recent literature. It is critical to note that GWAS has revealed a critical arena of genetic and epigenetic mechanisms associated with mental disorder. Further, the hereditary index of BD has found to be one of the highest among various mental disorders. Therefore, the genetic association of BD has been a critical factor of research and development in the recent times. However, this area of development has been much recent and still a lot of developments and investigations are required as highlighted here. Moreover, there are also certain very less explored factors like the rare genetic variants and their association with BD. All these factors make the current research context a critical research scope for the current research paper aiming to contribute critically on the domain.
This section of the research paper meticulously outlines the philosophical underpinnings of the study investigating the genetic impacts on bipolar disorder. It details the chosen research methodology (quantitative systematic review), the researcher's positionality and its influence, the guiding positivist paradigm, and the specific stances on ontology (constructed) and epistemology (critical realism), culminating in a discussion of the core axiological values guiding the research.
In order to gain a thorough understanding of the genetic impacts on bipolar disorder (BD), a quantitative systematic review approach is considered to be the most appropriate. The positivist theoretical framework frequently serves as a guidance for choosing research methodologies and methodology. Quantitative research techniques, which gather data using controlled tools like experiments or surveys, are in line with positivism (Ratelle, Sawatsky and Beckman, 2019). It aims to prove discoveries that may be applied broadly and causal linkages.
The selection of a quantitative systematic review is in line with the goals of this investigation. A quantitative method enables a coherent synthesis of the available data, particularly considering the emphasis on genetic factors. This is especially important when trying to make generalisations regarding the hereditary components of bipolar disorder such as brain chemistry, medication and drug usage (Kerner, 2014). In contrast to qualitative methods that explore the complexity of individual experiences, a quantitative systematic review offers a thorough and impartial examination of the combined data (Mohajan, 2020). The research approach does not entail gathering primary data; instead, it involves examining the body of current literature. This choice is based on the understanding that a substantial amount of research has previously been done on bipolar disorder, especially with a genetic focus. The research guarantees that the most recent and reliable data are included in the analysis by limiting the search to papers published within the previous ten years (since 2013) and only taking into account peer-reviewed publications and trustworthy internet resources.
The precise research questions and the nature of the study's aims provide the justification for using a quantitative technique in this investigation. First and foremost, the study attempts to methodically explore and evaluate the hereditary components of bipolar disease, looking for trends, correlations, and statistical relationships across a sizable body of pertinent literature. Moreover, quantitative components including demographic characteristics, treatments, comparisons, and outcomes are highlighted by the PICO framework that was used to formulate the study question (Aslam and Emmanuel, 2010). A quantitative systematic review is well suited to the PICO framework's organised format, allowing for a thorough and fact-based examination of the hereditary components of bipolar disorder.
Although the study uses a quantitative systematic review technique to examine the role of genetics in bipolar disorder, it is important to recognise that there are inherent limits and constraints. First off, the study's scope is limited since it might not include all of the information that is currently accessible on the topic due to its dependence on peer-reviewed papers and existing literature. Moreover, the lack of direct interaction with human subjects through questionnaires or interviews restricts the breadth of knowledge on personal experiences with bipolar disease (White, 2020). The quantitative systematic review's reliance on aggregated data may overlook complex qualitative components that are crucial for a complete knowledge of the issue (White, 2020). Furthermore, excluding out non-online or non-peer reviewed materials might cause publication bias and result in the loss of important insights from other sources. It is important to be aware of this restriction since it might affect how thorough the results are.
As an analytical tool, positionality enables the researcher to evaluate their impact on the study in a critical manner (ORCID, 2020). According to MASSOUD (2022), it encourages openness about presumptions and prejudices, which strengthens the reflexivity and rigour of the quantitative study. Through the clear acknowledgment of positionality, the researcher offers readers important context-specific insights on the research.
The researcher is conscious of their positionality, which entails acknowledging how their individual experiences, values, and opinions may influence the course of the study. The researcher's expertise in both genetics and mental health provides a sophisticated knowledge of the issues inherent in this systematic study. The researcher aims for transparency and reflexivity throughout the study and is aware of the possible influence of personal opinions on the interpretation of results (Wilson, Janes and Williams, 2022). Research question formulation is influenced by positionality. Given the researcher's knowledge in genetics, a more concentrated investigation into particular genetic markers or pathways linked to bipolar disorder may result. The questions emphasise clarity and relevance to the larger scientific community, reflecting a grasp of the complexity involved in genetics.
Positionality is made clear in the literature review, when the selection and interpretation of previous studies may be influenced by the researcher's pre-existing knowledge and attitudes. Although the review strives for impartiality, it recognises that the researcher's position may have an impact on the information synthesis and that bias must be minimised consciously. Ethical issues are influenced by the positionality of the researcher. The researcher is dedicated to respecting ethical concepts like autonomy, beneficence, non-maleficence, and justice because they are aware of their own ideals. According to Savolainen et al. (2023), this dedication influences choices on which research to include or exclude according to the rigour of their ethics and compliance with these standards.
The systematic review holds a place in the larger context of bipolar disorder genetic research. It is presented as a continuous synthesis with the goal of adding to the current scientific conversation (Yip, 2023). The study emphasises the significance of openness in methodology and interpretations while acknowledging its influence in directing future investigations. The researcher engages in reflexivity—a continuous process of self-awareness and critical analysis of how personal opinions may affect the research—to counter any biases resulting from positionality. Reflexivity acts as a mitigating element, allowing the researcher to make intentional decisions that increase the validity and reliability of the systematic review (Olmos-Vega et al., 2022). This self-awareness contributes to the study's rigour and allows for a more nuanced and fair examination of the intricate interactions between genetics and mental health.
As a paradigm, positivism is based on the idea that observable and quantifiable occurrences may provide insight into the social realm (Park, Konge and Artino, 2020). Finding the factual rules regulating this objective reality—which is assumed to exist independently of human perception—is the aim of this approach (Park, Konge and Artino, 2020). The positivist paradigm is well-suited to the quantitative systematic review because it places a strong focus on objective patterns, reproducible methods, and numerical data.
Quantitative approaches that emphasise numerical data, statistical analysis, and broadly applicable patterns are supported by positivism (Pilcher and Cortazzi, 2023). Quantitative data from several studies must be combined and synthesised as part of a systematic method to address the research topic about genetic implications on bipolar disorder. For this reason, positivism offers a methodological framework that is ideal (Nyein et al., 2020). The selected research paradigm acknowledges an objective, external world that may be investigated and comprehended by means of empirical observation. The goal is to find patterns and demonstrate causal linkages in the context of genetic impacts on mental health, ly bipolar disorder. The objective of positivism is objectivity, which is in line with the goal of finding universal truths in the quantitative data (Uher and Zwicker, 2017). The collection of knowledge via methodical, repeatable investigation is encouraged by positivism. The goal of the quantitative systematic review is to advance our knowledge of the role that heredity plays in bipolar disorder. Through the synthesis of current quantitative data, the study upholds positivism's objective of methodically accumulating cumulative knowledge.
Naturalism, on the other hand, emphasises a more interpretative and subjective approach while recognising that reality is socially constituted. Fan, Monte and Chang (2021) state that it frequently makes use of qualitative techniques that investigate meaning, context, and personal experiences. Naturalism is useful in some research contexts, but it does not fit in well with the goals of a quantitative systematic review, which are to identify overarching patterns in the quantitative literature that already exist and to concentrate on objective, quantifiable outcomes.
Tesar (2020) identifies two schools of philosophy that are connected to the methods used in social science research. These are the fields of ontology, which studies what makes up social reality, and epistemology, which investigates how individuals come to understand the world around them (Ejnavarzala, 2019). Therefore, it is crucial for the researcher to take into account their philosophical decision-making process in every research project. The researcher has taken a constructed ontological stance in the study of the genetic impacts on bipolar disorder (Hamilton and Pinnegar, 2015). The decision to adopt a constructed ontology fits in nicely with the research's focus on comprehending genetic influences in the context of social and cultural elements.
According to Guala and Hindriks (2023), constructed ontology makes it possible to investigate how individual, societal, and cultural viewpoints influence reality. This point of view aids in understanding how societal and cultural influences affect how bipolar disease is seen and experienced in the context of mental health. Acknowledging the created aspect of reality means accepting its dynamic nature. This is especially helpful in the realm of genetics, as new scientific findings and cultural viewpoints are always changing our knowledge of the hereditary impacts on mental health. Different viewpoints are acknowledged in a built ontology. This is in line with the need for inclusion in mental health research, as comprehending the complexity of bipolar disorder depends critically on individual experiences and society norms.
Critics contend that a created ontology might overly subjectively influence the study, jeopardising the objectivity of the conclusions (Gavrilova and Leshcheva, 2015). Keeping a certain level of impartiality while balancing different points of view becomes difficult (Gavrilova and Leshcheva, 2015). When reality is seen as manufactured, interpretation of the data might become complex. Researchers may encounter difficulties resolving divergent interpretations that result from various created realities.
There are several theories in epistemology that explain how individuals come to know reality. Three things need to be considered: first, knowledge must be understood; second, it must only be assessed through credible sources; and third, a variety of approaches should be used to address an issue or provide an answer (Zhang, 2022). The researcher takes a critical realism approach to epistemology. This decision aligns with the study goals since it acknowledges the impact of social constructions on our understanding while allowing for an investigation of the role that genetics may play in bipolar disease.
Between constructivism's emphasis on subjectivity and positivism's rigid objectivity, critical realism finds a middle ground (Maksimović and Evtimov, 2023). This is beneficial because it acknowledges the existence of an objective reality while also admitting the significance of human interpretation in comprehending it. Empirical research methodologies are in line with critical realism (Maksimović and Evtimov, 2023). This is important when looking at genetic issues since it makes it possible to use scientific methods to look at patterns and regularities in the data. Developing interventions and tactics based on factual facts is made possible by the practical recognition that there is an objective reality that extends beyond personal perceptions. This is a big benefit in mental health research, where real-world applications are crucial.
Interpreting results becomes more challenging when objective reality and interpretative components are acknowledged. It might be difficult for researchers to separate the subjective from the objective (Kivunja and Kuyini, 2017). Critics contend that, particularly when it comes to complicated phenomena like mental health, critical realism may err on the side of reductionism (Rahman, 2016). It is a constant struggle to strike a balance between preserving academic rigour and conveying the richness of lived experiences. Within the framework of socially created realities, this research's constructed ontological perspective and critical realism epistemological attitude offer a strong foundation for investigating the genetic implications on bipolar disorder (Yucel, 2018). These philosophical decisions support the goals of comprehending the intricate interactions between cultural constructs and genetic elements that influence how we perceive mental health.
Axiology is a wide term that pertains to the study of values and a discipline of philosophy. It critically investigates a broad range of pre-existing, overlapping ethical issues about what constitutes goodness, morality, responsibility, and values. In the field of our study on the genetic components of bipolar disorder, axiology is crucial in forming the moral perspectives, ethical concerns, and values that direct our investigation of this intricate topic.
The axiological attitude of the researcher is based on the values of autonomy, beneficence, non-maleficence, and justice, which are frequently maintained in social and health care settings. These principles act as moral benchmarks, guaranteeing that the study respects the rights, dignity, and well-being of those with bipolar disorder and the general public (Fahlquist, 2021). From an axiological perspective, autonomy occupies a major place in the research, indicating a dedication to upholding the rights and choices of individuals (Varkey, 2021). Recognising the autonomy of individuals who took part in the main studies that served as the research's foundation is part of this. The principle of autonomy guarantees that the interpretation and synthesis of facts are carried out with the highest regard for the objectives of the original authors and the variety of viewpoints that are expressed in the literature.
The researcher's dedication to making a constructive contribution to our understanding of the genetic impacts on bipolar disease is guided by the concept of beneficence. The research endeavours to offer insights that might guide future research, therapeutic practices, or policy, eventually helping those with bipolar disorder and the mental health community by analysing and analysing the available data. The concept of non-maleficence emphasises the axiological significance of disseminating research findings responsibly (Nurgaliyeva et al., 2018). By presenting results in an uncomplicated way, avoiding sensationalism, and taking precautions to prevent data misunderstanding, the researcher upholds the principle of non-maleficence. This dedication helps combat stigma related to mental health and avoids possible harm to public understanding.
In the axiological framework, justice is central to the idea of impartial and equitable data interpretation. By offering a fair synthesis, avoiding selective reporting, and recognising the variety of viewpoints found in the original studies, the researcher upholds the concept of justice. Neeleman (2018) states that this dedication helps to promote a more fair portrayal of the complexity pertaining to hereditary impacts on bipolar disease. Axiology acknowledges the value of moral competencies in negotiating the moral ambiguities surrounding genetic research (West and Schill, 2022). The researcher values thoughtful decision-making, cultural sensitivity, and ethical awareness. The researcher is guided by moral competencies while addressing potential biases, selecting data in an ethical manner, and making sure the research complies with strict ethical guidelines.
Adopting these axiological ideals has several benefits, such as advancing moral research procedures, advancing the field, and defending people's rights and well-being. However, since values may affect the researcher's perspective, there may be possible drawbacks in the form of subjectivity in interpretation. In order to minimise possible drawbacks, subjectivity and objectivity must be balanced (Lysova et al., 2023). The ontological viewpoint used in this research goes towards a constructed understanding of reality. An awareness of how reality is shaped by social and individual perceptions, experiences, and interpretations is made possible by a constructed ontological position, which acknowledges the dynamic and complex character of mental health, particularly bipolar disorder (Jain and Mitra, 2023). The benefit is in accepting the variety of lived experiences, recognising other viewpoints, and advancing a more nuanced understanding of the role that heredity plays in bipolar disease. The difficulty, though, could be in balancing the possible subjectivity that a constructed reality introduces in order to prevent undue bias in the interpretation of the data (Radianti et al., 2020). As a result, the axiology that directs this study demonstrates a dedication to moral standards and ideals that place a high priority on the welfare, autonomy, and justice of those who are impacted by bipolar disease.
This study aims to provide a complete analysis of and insight into the role played by genetics in the initiation and advancement stages of bipolar disorder. This also consists of an in-depth discussion about bipolar disorder, its critical aspects, and its causes with a focus on genetic predispositions.
The purpose of this study is to conduct an evidence-based analysis on the role genetics play in bipolar disorder. This will entail a critical analysis of contemporary and valid bipolar disorder research findings and statistics focusing on the genetic perspectives. Such goals are aimed at a comprehensive analysis of the bipolar disorder concept, identification of crucial genetic and non-genetic factors as well as critical reflection on how genes participate in cases related to damage progression and manifestation (Varkey, 2021). Taking into consideration empirical evidence from genetic studies, epidemiological data, clinical trials and patient results the study strives to consider a holistic view of bipolar disorder genetics. Also, the study aims to utilize these evidence-based observations and recommendations for effective treatment options in order to improve personalized medicine approaches of managing bipolar disorder.
Scholars of bipolar disorder genetics show promising prospect for investigating and treating this dynamic psychosomatic condition. From a clinical viewpoint, it provides an opportunity for early diagnosis and tailor-made treatment regimens that favorably influence the success of bipolar patients. Genetic knowledge allows healthcare providers to establish risks, choosing appropriate intervention methods and providing prognostic information.
In terms of policy, this study can guide the formulation of mental health policies that take into account bipolar disorder genetic susceptibility (Lysova et al., 2023). It can also shape policies pertaining to genetic counseling, insurance coverages and non-discrimination management making sure that there is equitable access of health resources in medicine.
In addition, from an investigative point of view, genetic analysis in bipolar disorder belonging to the realm of a bigger picture that is psychiatric genetics. It provides useful information that can be used in further studies to identify new therapeutic targets. In the end, this study falls in line with such a way of precision medicine aimed at finding more realistic and individualized ways to treat bipolar disorder as well as other mental health diseases.
| Criteria | Inclusion | Exclusion |
|---|---|---|
| Age Range | Adults (18 years and older) | Children and adolescents |
| Diagnosis | Confirmed diagnosis of bipolar disorder | Other psychiatric or neurological disorders |
| Family History | Presence of a family history of bipolar disorder | No family history of bipolar disorder |
| Informed Consent | Informed consent for genetic testing and data analysis | Lack of informed consent |
| Ethnicity and Ancestry | Diversity of ethnic backgrounds considered | Not specified ethnic diversity |
| Medication Status | Medication use documented | Influence of medication on genetic markers considered |
| Comorbidities | No significant comorbid psychiatric or medical conditions | Presence of significant comorbidities |
| Mental Capacity | Participants must have the mental capacity to provide informed consent | Lack of mental capacity to understand and consent |
| Data Privacy | Measures in place to protect participant data | Insufficient data privacy and confidentiality measures |
| Recruitment Source | Clearly defined source of participant recruitment | Source of recruitment not specified |
| Sample Size | Desired sample size for statistical power | No consideration of sample size |
| Follow-up | Consideration for long-term follow-up and treatment monitoring | No provision for follow-up or treatment monitoring |
Table 3: Inclusion and exclusion criteria
“Start by electing keywords and synonyms related to bipolar disorder and genetics. Relevant terms include” "bipolar disorder," "manic-depressive disorder," "genetics," "genetic factors," and "genetic markers."
“Boolean operators” (and, OR, NOT) to combine and refine search terms. For example, use "bipolar disorder and genetics" to locate articles discussing both aspects.
“Analyse suitable academic databases for the field, such as PubMed, PsycINFO, Scopus, and Web of Science. Specialized genetics databases may also be considered”.
Employ filters offered by databases to narrow down results. Filters may include publication date, study type (e.g., clinical trials, reviews), and language.
Develop search strings using keywords and Boolean operators. Examples include:
"bipolar disorder and genetics"
"genetic factors in bipolar disorder"
"bipolar disorder genetic markers"
"genetic susceptibility to bipolar disorder"
Ensure comprehensiveness by using truncation or wildcards to broaden the search. For instance, "genet*" captures variations that includes "genetic" and "genetics."
Examine initial search results and refine the search strategy based on article relevance. Additional keywords and subject terms may be identified from relevant articles.
Conduct citation searches by reviewing reference lists of relevant articles to uncover additional sources that may not have appeared in initial searches.
Explore grey literature sources such as conference abstracts and preprint archives for recent and unpublished research.
Maintain a record of the search strategy, including databases used, search strings, and the number of results retrieved at each stage. This documentation ensures transparency and reproducibility.
Consider setting up alerts or RSS feeds for search terms to receive notifications of newly published research.
Involving this research, the study selection process for genetics of bipolar disorder utilizes a meticulous and thorough approach to specify as well as select suitable primary quantitative articles. This process will be started through an intensive search of academic databases, according to the already predetermined strategy. This primary search will result in a fairly long list of articles that may be relevant. Then, a thorough analysis of the titles and abstracts will be performed to determine whether these articles meet all inclusion criteria specified above. Articles that are clearly not what the predefined criteria require based on title and abstract information will be rejected. After this preliminary sift, the full text papers of those articles that remain will be retrieved and undergo rigorous scrutiny.
In this phase evaluation will be done on inclusion criteria, which could include age of participants genetic status design bipolar disorder and diagnostic confirmation. Once these criteria are met, the chosen articles will proceed to data extraction process in which relevant information on study design, methodology sample size and investigated genetic factors as well key findings’ would be systematically collected. Then, depending on the study design in question, quality assessment tools or criteria will be used to evaluate each included study’s level of bias and possible sources thereof. Thus, a blend of discoveries from the chosen papers will be executed, accentuating genetic factors related to bipolar sickness and outlining shared subjects all through research examinations. The example comprising of 10 primary quantitative exploration distributions that meet every single arranged measure and enormously add to top to bottom examination on genetics in bipolar sickness will be the result of this work escalated concentrate on determination strategy. To guarantee the authenticity and validity of the review determination process, there will be receptiveness and rigid documentation all through. The rundown may that includeswise be upgraded by checking references and considering sources from the dark writing.
Assessing the incorporated examinations' quality is a urgent initial phase in affirming the genetics of bipolar sickness concentrate on results. Utilizing suitable evaluation instruments, we do a purposeful examination of each and every chose primary quantitative exploration paper. Survey points incorporate exploration configuration, test size thought, potential inclinations or cutoff points during result appraisal, and moral issues. The aftereffects of an evaluation help in the understanding of discoveries by giving knowledge into the benefits and faults of each exploration. This thorough method guarantees that the exploration is upheld by solid proof and sustains the discoveries of the concentrated on the genetic parts of bipolar sickness.
Prejudice evaluation and decrease is a significant point in the field of bipolar disorder genetics research. Each chosen fundamental quantitative examination article is painstakingly inspected to distinguish and eliminate predisposition, which could prompt issues with the legitimacy and dependability of the outcomes. Determination inclination, estimation predisposition, revealing of bewildering factors, and moral issues with fitting example size, legitimacy, and dependability result estimations are a couple of these. By intently looking at these parts, analysts might keep unseen side effects from influencing their plans and examination techniques. This stringent method also enables more reliable conclusions regarding the genetic basis of bipolar disorder, which helps progress in studying this complex condition.
|
Article Name and author |
Study design and aim |
Study size |
Study Outcomes |
||||
|
Intervention group (n) |
Control group(n) |
RR or |
CI |
||||
|
Bruce, H.A., Kochunov, P., Mitchell, B., Strauss, K.A., Ament, S.A., Rowland, L.M., Du, X., Fisseha, F., Kavita, T., Chiappelli, J., Wisner, K., Sampath, H., Chen, S., Kvarta, M.D., Seneviratne, C., Postolache, T.T., Bellon, A., McMahon, F.J., Shuldiner, A. and Elliot Hong, L. (2019). Clinical and genetic validity of quantitative bipolarity. Translational Psychiatry, [online] 9(1), pp.1–8. doi:https://doi.org/10.1038/s41398-019-0561-z. |
“Case-control genome-wide association studies” |
176 |
310 |
134 |
1780 |
0.88 |
0.94 |
|
Contreras, J., Hare, E., Chavarría, G. and Raventós, H. (2018). Quantitative genetic analysis of anxiety trait in bipolar disorder. Journal of Affective Disorders, 225, pp.395–398. doi:https://doi.org/10.1016/j.jad.2017.08.023. |
Anxiety State and Trait Inventory |
321 |
619 |
51 |
1390 |
15.20 |
0.0009,0.060 |
|
Greenwood, T.A. (2020). Creativity and Bipolar Disorder: A Shared Genetic Vulnerability. Annual Review of Clinical Psychology, 16(1). doi:https://doi.org/10.1146/annurev-clinpsy-050718-095449. |
large genome-wide association |
298 |
43 |
29 |
4397 |
0.75 |
0.71 |
|
Li, X., Ma, S., Yan, W., Wu, Y., Kong, H., Zhang, M., Luo, X. and Xia, J. (2022). dbBIP: a comprehensive bipolar disorder database for genetic research. Database: The Journal of Biological Databases and Curation, [online] 2022, p.baac049. doi:https://doi.org/10.1093/database/baac049. |
Functional genomic data |
21.1 |
161 |
43 |
1695 |
0.05 |
0.8 |
|
Huang, Y., Liu, Y., Wu, Y., Tang, Y., Zhang, M., Liu, S., Xiao, L., Tao, S., Xie, M., Dai, M., Li, M., Gui, H. and Wang, Q. (2022). Patterns of Convergence and Divergence Betiten Bipolar Disorder Type I and Type II: Evidence From Integrative Genomic Analyses. Frontiers in Cell and Developmental Biology, 10. doi:https://doi.org/10.3389/fcell.2022.956265. |
single nucleotide polymorphism |
449 |
364 |
978 |
6781 |
0.6 |
0.1 |
|
Orrù, G. and Carta, M.G. (2018). Genetic Variants Involved in Bipolar Disorder, a Rough Road Ahead. Clinical Practice and Epidemiology in Mental Health, 14(1), pp.37–45. doi:https://doi.org/10.2174/1745017901814010037. |
cross genomic study |
134 |
57 |
44 |
2000 |
1.14 |
1.27 |
|
Hu, B., Cha, J., Fullerton, J.M., Hesam-Shariati, S., Nakamura, K., Nurnberger, J.I. and Anand, A. (2022). Genetic and environment effects on structural neuroimaging endophenotype for bipolar disorder: a novel molecular approach. Translational Psychiatry, [online] 12(1), p.137. doi:https://doi.org/10.1038/s41398-022-01892-3. |
structural brain endophenotype |
64 |
119 |
55 |
966 |
0.4 |
0.2 |
|
Bonacina, G., Carollo, A. and Esposito, G. (2023). The Genetic Side of the Mood: A Scientometric Review of the Genetic Basis of Mood Disorders. Genes, 14(2), p.352. doi:https://doi.org/10.3390/genes14020352. |
scientometric |
189 |
211 |
544 |
5371 |
1.00 |
5.00 |
|
Guglielmo, R., Miskowiak, K.W. and Hasler, G. (2021). Evaluating endophenotypes for bipolar disorder. International Journal of Bipolar Disorders, [online] 9, p.17. doi:https://doi.org/10.1186/s40345-021-00220-w. |
Log-That includeslihood Ratio algorithm |
51 |
49 |
31 |
196 |
0.5 |
0.06 |
|
Oraki Kohshour, M., Papiol, S., Ching, C.R.K. and Schulze, T.G. (2022). Genomic and neuroimaging approaches to bipolar disorder. BJPsych Open, [online] 8(2). doi:https://doi.org/10.1192/bjo.2021.1082. |
single nucleotide polymorphism |
123 |
549 |
200 |
3000 |
1.5 |
1.59 |
Table 2: Data collection from the measured outcomes of the included studies.
|
Article and Author |
Use of Randomization (Selection Bias) |
Recruitment Concealment (Selection Bias) |
Blinding of Study Subjects and Staff (Performance Bias) |
Blinding of Result Evaluation (Detection Bias) |
Incomplete Data of the Results (Attrition Bias) |
Omission of Outcome Data (Reporting Bias) |
Other Forms of Bias |
|
Bruce, H.A., et al. (2019) |
+ |
+ |
+ |
+ |
+ |
+ |
- |
|
Contreras, J., et al. (2018) |
+ |
+ |
+ |
+ |
+ |
+ |
- |
|
Greenwood, T.A. (2020) |
+ |
+ |
+ |
+ |
+ |
+ |
- |
|
Li, X., et al. (2022) |
+ |
+ |
+ |
+ |
+ |
+ |
- |
|
Huang, Y., et al. (2022) |
+ |
+ |
+ |
+ |
+ |
+ |
- |
|
Orrù, G., and Carta, M.G. (2018) |
+ |
+ |
+ |
+ |
+ |
+ |
- |
|
Hu, B., et al. (2022) |
+ |
+ |
+ |
+ |
+ |
+ |
- |
|
Bonacina, G., Carollo, A., and Esposito, G. (2023) |
+ |
+ |
+ |
+ |
+ |
+ |
- |
|
Guglielmo, R., Miskowiak, K.W., and Hasler, G. (2021) |
+ |
+ |
+ |
+ |
+ |
+ |
- |
|
Oraki Kohshour, M., et al. (2022) |
+ |
+ |
+ |
+ |
+ |
Table 3: Quality evaluation for the risk of bias in the each of the included studies
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Large genome-wide association (GWA) studies have begun to progress as of late, examining a huge number of varieties across the genome in a huge number of bipolar disorder patients contrasted with sound controls. Thirty special genomic regions over a genome-wide importance P esteem limit of 5 × 10−8 are found in the greatest hereditary examination of bipolar disorder to date (29,764 bipolar patients and 160,118 controls), offering great opportunities for qualities adding to sickness risk.
GWASs on bipolar disorder patient information and delivered essential discoveries (P < 5 × 10−8). The examinations are made sense of in the passages that follow. Regardless of the way that the principal GWAS on bipolar sickness neglected to give critical outcomes at the foreordained edge, it start our survey with a fast outline of its decisions (Oraki Kohshour et al., 2022). The principal GWAS on bipolar disease had around 3000 controls and 2000 English patients when it was delivered in 2007. The most emphatically connected SNP with bipolar disorder found by this GWAS was rs420259 (P = 6.3 × 10−8) on chromosome 16p12. No expansive critical SNP was found for the condition (Oraki Kohshour et al., 2022). At this locus, PALB2, NDUFAB1, and DCTN5 are found. While NDUFAB1 encodes a subunit of mind-boggling I of the mitochondrial respiratory chain and DCTN5 encodes a protein engaged with the intracellular vehicle, PALB2 is associated with the soundness of significant atomic designs.
The therapeutic treatment of this disorder involves managing recurrent episodes of mania or hypomania and depression which is a complex psychiatric condition. Bipolar disorder management is not an easy task since it can be episodic and have the capacity to trigger mood instability. For effective treatment, it should include not only immediate symptom relief but also long-term stabilization of moods to prevent relapses. This paragraph emphasizes evidence-based treatment modalities and the advent of novel strategies for bipolar disorder, pointing to personalised medicine. Pharmacotherapy continues to underpin bipolar therapy. Manic and depressive episodes are widely treated with mood stabilisers including lithium, valproate, and lamotrigine. In particular, lithium has shown efficacy in terms of prevention and suicide risk reduction. In order to assist mood stabilisers during acute manic phases, antipsychotic medications such as aripiprazole and olanzapine are prescribed in addition. Similarly, antidepressants are used carefully in depressive episodes and often treated with mood stabiliser to prevent mania. Emerging trends include precision medicine in bipolar disorder treatment. Some biomarkers that are involved with treatment response have been found through genetic research. For instance, specific gene variants such as CACNA1C have been associated with lithium response. Pharmacogenomic testing can therefore help select the best medicine for individual patients and reduce trial-and-error process of finding effective treatments.
The other important element of bipolar disorder treatment is psychotherapy. CBT is well established in conjunction with cognitive distortions and medication adherence improvement. IPSRT aims to stabilize a daily routine for regulating circadian rhythms with the goal of preventing mood episodes. Family-focused therapy (FFT) is a treatment that uses family members along the way to enhance communication as well as support networks. Bipolar disorder is effectively managed through lifestyle interventions. Mood stability can also be facilitated through regular exercise, a balanced diet as well as enough sleep. Psychoeducation is very important for patients and their families as it allows them to detect early warning signals and follow the treatment regimens. Individuals that use mood tracking apps or journals for monitoring their mood can benefit from timely intervention.
Novel treatments provide hope for better results. Chronotherapy, which encompasses light exposure and manipulating sleep patterns, has shown to be a promising treatment option for bipolar depression. Novel therapies such as ketamine are being investigated for the provision of immediate alleviation to depressive symptoms. In terms of treatment-resistant cases, TMS and ECT are proposed.
About 310 Old Guard Amish or Mennonite individuals from multigenerational families were given the Quantitative Bipolarity Scale (QBS); 110 of these individuals had mental determinations (20 BP, 61 significant burdensome disorders (MDD), 3 insane ailments, and 26 other mental illnesses). The fluctuation parts strategy was utilised to figure out the familial conglomeration of QBS to decide shared family impacts and heredity (Bruce et al., 2019). In contrast with MDD (16.7 ± 2.0), other mental analyses (7.0 ± 1.9), and no mental finding (6.0 ± 0.65), the QBS score was significantly higher in BP members (31.5 ± 3.6) (all p < 0.001). There are no prominent contrasts in age or sex proportions across the analytic gatherings. In contrast with different gatherings, the BP gathering's QBS score was impressively higher [F3,305 = 30.3, p < 0.001] (Bruce et al., 2019). The QBS score of patients with BP (31.5 ± 3.6, mean ± s.e.) contrasted fundamentally from that of subjects with MDD (16.7 ± 2.0), other mental determination (7.0 ± 1.9), and no mental conclusion (6.0 ± 0.65) (all p < 0.001), as per post-hoc testing.
Anxiety element has been displayed to fit the accompanying depictions of an endophenotype of bipolar disorder type I (BPI): 1) relationship with BPI (quality score most noteworthy among BPI members, F = 15.20 [5,24], p = 0.009), 2) affirmation of state autonomy by test-retest in 321 subjects, and 3) co-isolation inside families A hereditary association of 0.20 (SE = 0.17, p = 3.12 × 10−5) was found with BPI, and heritability of 0.70 (SE: 0.060), p = 2.33 × 10-14, was that includeswise noticed (Contreras et al., 2018). The major depressive disorder (59%), specific phobia (10%), panic disorder (11%) and no pivot I sickness (18%) are the chief DSMIV psychiatric findings of the 568 patients from the drawn-out families. A lot of the 61 families had at least one BPI family member, 77% had multiple BPI people, and 26 % had at least four influenced individuals. 340 (or 55%) of the 618 members are female (Contreras et al., 2018). 43.25 was the typical age during the meeting.
The information provided in the tables below provides helpful data regarding demographics and illness characteristics of study subjects, as well as important correlations between different factors and brain structure measures pertaining to BD. It is clear in Table 1 that there are significant disparities between people without BDS and those with it. The differences between the two groups include age, parental history of BD, reported childhood adversity and a drug abuse history; these factors all demonstrate statistically significant variations. Furthermore, there are differences in race composition, whereby a bigger percentage of African Americans is found within the BDS group.
In addition, table1 shows the effects of genetics and environment characteristics in the study population. Interestingly, PRS and MPS differ substantially between the two groups which could signal a correlation of these genetic variants with BD. These results offer useful information regarding the relationship between genetic and environmental components in BD. Table 2 describes the significant correlations between genetic or environmental variables with measures of brain structure. These organisations offer a further insight into the possible neurobiological foundations of BD. Significantly, the negative correlations of PRS with left accumbens and right putamen as well as positive correlation between MPS and left accumbens suggest that these factors may regulate particular areas in brain implicated in BD.
In addition, the corrected analysis presented in Table 2 considers a number of covariates that makes their observed correlation even stronger. However, these results provide evidence of the role that genetics and environment play in understanding BD pathophysiology. Furthermore, the tables provide a summary of the study results highlighting BD’s complex nature and possible genetic or environmental causes. More studies and investigations are required to understand the complicated mechanisms behind this dynamic disease.
The ROC curve is an evaluation tool in determining the performance of a diagnostic test. The red, green and blue lines indicate the discriminating power of QBS in distinguishing bipolar disorder from non-bipolar psychiatric illness, a major depressive state against a control group. A great test result would be demonstrated by a curve that forms the top left corner in an ideal situation (Radianti et al., 2020). The AUC is the measure of discrimination between two diagnostic groups and its values not shown in this figure.
Table 1 represents ‘Demographic and clinical data by diagnostic category (bipolar disorder, major depressive disorder, psychotic disorders , other psychiatric illnesses vs control)’. The key findings are as follows:
Sample Size (N): This study involves having different sample sizes across groups such that the control group is 200 participants.
Gender: As the proportion of males/females, varying among groups but the p-value does not point to a significant difference.
Age: Standard errors are presented for average ages. Age is different among groups, but not on the same scale ( p-value = 0.35 ).
QBS Score: The asterisk (*) and the p-value of 2 × 10^−21 also indicate a very strong ability to discriminate between bipolar disorder and other conditions.
Subscores: The QBS also has mood fluctuation, depression, and mania subscores. Each of these subscores has a significantly higher value for the bipolar group as indicated by asterisks (*) and very small p-values.
The asterisks (*) indicate statistical difference from the control group and probably for all other psychiatric groups, but the details of such comparison are not specified in this graphic. The remarkably low p-values of the QBS score and sub scores suggest that these variables are significantly different for the bipolar disorder group, compared with both control and other psychiatric groups. Therefore it can be possibly concluded that QBS is capable to distinguish bipolar disorder in clinical or research setting as a powerful measure. The results of this study might go a step further in explaining the differences between bipolar disorder and other psychiatric disorders, providing new treatment options that would be specifically designed for each individual.
Bipolar disorder is a highly complicated mental health condition marked by mania or hypomania and depression has attracted massive genetic research. Detailed information on the underlying mechanisms of genetic effects in bipolar disorders is essential for development of new approaches to its aetiology and treatment. A major factor to be taken into account is the heritability of bipolar disorder. Twin and family studies have shown that those with a higher probability of creating bipolar disorder than those without the illness are the individuals who have family members with the disorder. These information have over and over highlighted a significant genetic part. These discoveries feature the disorder's familial bunching and show how genetic legacy adds to its transmission.
Besides, the complex genetic starting points of bipolar illness are confounded by its polygenic person. Bipolar disorder is unquestionably not brought about by a solitary quality, but instead the consequence of numerous genetic varieties, every one of which has an irrelevant effect. Through genome-wide association studies, various genomic loci have been connected to bipolar ailment, giving an understanding of the complex genetic cosmetics of this condition. The genetic assortments influence a wide scope of ordinary exercises, for example, mind limit and synaptic equilibrium, which add to the complicated person of this issue. Pleiotropy is one of the extra genetic parts that makes sense of the co-event of different mental disorders with bipolar disease. Assortments of bipolar sickness are frequently pleiotropic, meaning they influence specific phenotypic qualities. This conduct progresses how we might interpret the comorbidity between bipolar sickness and different circumstances that includes extreme depression and schizophrenia. That includes clinical qualities and symptomatology seen in numerous illnesses are ascribed to comparative genetic gamble factors, which incorporate the complex genetic design hidden close to home medical conditions. Support in a quality climate is fundamental since inborn issues that includes liquor compulsion and problematic rest examples might set off or compound character emergencies, particularly in the people who are genetically inclined toward them. This smart worldview catches the substance of utilizing a multimodal approach in the finding and treatment of bipolar disease, considering both regular and genetic elements. Second, the aftereffects of genetic testing affect treatment methodologies.
Without a doubt, bipolar disease isn't brought about by a solitary quality rather, it is the consequence of a few genetic varieties, and each one of elements has little importance. Various genomic districts have been connected to bipolar disorder through genome-wide association studies, giving knowledge into the perplexing genetic cosmetics of this disease. These genetic varieties influence a wide scope of run-of-the-mill exercises, for example, mind limit and synaptic equilibrium, which add to the complicated person of this issue. Pleiotropy is one of the extra innate parts that makes sense of the co-event of different mental disorders with bipolar ailment. Assortments of bipolar sickness are frequently pleiotropic, meaning they influence specific phenotypic attributes. This conduct progresses how we might interpret the comorbidity between bipolar sickness and different circumstances that includes serious depression and schizophrenia. Support in a quality climate is fundamental since intrinsic issues that includes liquor dependence and disconnected rest examples might set off or worsen character emergencies, particularly in the people who are genetically inclined toward them. This calculating worldview catches the embodiment of utilizing a multimodal approach in the conclusion and treatment of bipolar disease, considering both normal and genetic elements. Second, the aftereffects of genetic testing affect treatment methodologies. Genetic markers connected to mind-set stabilizer responsiveness have been recognized by numerous medical publication which might make the way for customized treatment in the treatment of bipolar disease. This specific viewpoint reveals insight into how genetic data might prompt superior restorative outcomes and demonstrates that there is a developing spotlight on settling the secret of how genetics adds to treatment-safe bipolar sicknesses.
The inner ring with coloured segments indicates different techniques of gene analysis, such as the Genome-Wide Association Studies (GWAS), eQTL expression quantitative trait loci and so on. The outer circle displays the human chromosomes, featuring some specific genes that can be connected to bipolar disorder. These genes are linked to techniques of their detection, including GWAS, CNV (Copy Number Variants), and others. The “Polyevidence scoring” indicates that these genes were scored based on evidence obtained from different sources or types of analyses. This includes biological pathways that exhibit high levels of significant association with genes which have a heavy polyevidence score, suggesting those specific pathways may play relevant roles in the genesis of bipolar disorder. The table indicates the GO term category, the particular pathway; raw p-value of association to adjust P adj multiple testing.
PGC2 and PGC3 GWAS datasets.
An analysis module referred to in the text is an analyzing and interrogative interface for data stored within dbBIP, a database that appears to be related with bipolar disorder. It consists of several different tools including LocusZoom for local associations, eQTL and tQLT outcomes as well as expression profiles in specific areas or phases of brain development. It also contains the PPI (Protein- Protein Interaction) analysis and visualization tools that includes ECharts.js that use these features to create a network of interactions between proteins coded by query genes.
The supporting text details several analyses conducted to determine genes and pathways associated with bipolar disorder types I and II. They detail important genes and pathways that have been enhanced or found through various kinds of analysis, including GWASCC-GWASTTwas in both blood tissues as well as brain areas. The text also mentions several supporting tables and figures, which presumably contain further detailed information regarding these results.
7 Years | PhD
This later section covers Mendelian randomization analysis aimed to shed light on the correlation between bipolar disorder and lithium response in treatment (Orrù and Carta, 2018). It describes the inference of causality based on SNPs correlated with response to lithium use. The findings seem to indicate that there exists a positive and statistically significant relationship between BD I with response of lithium by using the weighted median method but not when making use of inverse variance weights (IVW). The results for BD II were insignificant. MR-Egger and MR-PRESSO tests show the occurrence of horizontal pleiotropy, which implies that genetic variants for bipolar disorder may have modified ILI response through pathways other than direct effect on this condition.
Research trying to grasp the hereditary construction of psychological maladjustments has experienced limited results while utilizing the unmitigated demonstrative order. Endophenotypes are a well-known subject of study for researchers. Endophenotypes, similar to the quantitative anxiety score, may assist with recognizing pointlessness qualities and show the fundamental natural cycles in BPI that are controlled by hereditary qualities. Worldwide, bipolar disorder (BP), which influences around 1% of the populace, causes serious disability (Contreras et al., 2018). With an expected 40-80% heritability, BP is visited as a profoundly heritable disorder.
Although outcomes from case-control genome-wide association studies (GWAS) have been difficult to repeat, they have uncovered numerous loci and are beginning to reveal insight into the hereditary helplessness of this multifaceted polygenic condition (Guglielmo, Miskowiak and Hasler, 2021). The majority of BP hereditary examinations use conclusions to pick the review bunch. Although this portrayal is significant for the clinical administration of circulatory strain patients, it is hazy whether this aggregate ought to be utilized to search for qualities that increment pulse risk. People who are hereditarily pointless yet don't show BP might be neglected or erroneously allocated to the control gatherings (Guglielmo, Miskowiak and Hasler, 2021). As per our hypothesis, bipolarity doesn't just appear in bipolar disorder (BP), however, it might that includeswise be a heritable subclinical element that recognizes BP from other mental disorders. Bipolarity is essentially more extreme in BP than it is in non-bipolar individuals.
A scope of illnesses, including bipolar disorder, are ordered in light of the degree and example of hyper and discouraged episodes (Greenwood, 2020). The most serious sort of bipolar I sickness, known as bipolar I disorder, is portrayed by the presence of something that includes one hyper episode enduring no less than seven days in the course of one's life or side effects adequately extreme to require hospitalization. Major depressive episodes are common among the majority of people with bipolar disorder, while they are excessive for diagnosis (Greenwood, 2020). Times of hypomania, a lesser sort of lunacy, enduring no less than four days are sprinkled with intermittent episodes of significant gloom that are the sign of bipolar II sickness. The mildest sort of bipolar disorder, known as cyclothymic disorder, is portrayed by intermittent mood swings among discouraged and hypomanic side effects that keep going for something that includes two years and do not completely fit the demonstrative models for hypomanic and depressive episodes.
To distinguish the most conceivable natural cycles associating and isolating BD I and II, the practical explanation was finished. The Sub-atomic Marks Data set (MsigdB) surveyed improvement for the qualities planned to all (up-and-comer, qualities nearest to endlessly lead) SNPs in the found common loci utilizing a hypergeometric test that was coordinated into FUMA (Hu et al., 2022). Qualities without a particular Entrez ID and pathways including under two qualities were disposed of. A Benjamini-Hochberg bogus disclosure rate (BH FDR) of 0.05 was utilized to change the findings (Hu et al., 2022). The Illumina Methylation EPIC BeadChip was utilized for DNA Methylation estimation from fringe blood tests as per the producer's suggested strategy. GenomeStudio's methylation information yield was exposed to additional examination utilizing the R minfi. Device (Hu et al., 2022). CpG tests with (1) an unfortunate detection rate at P<0.01 and (2) a dot include <3 in something that includes 5% of the examples were eliminated during quality control.
Moreover, the genetics of bipolar disorder (BD) is a two-sided bridge between neurobiology and psychological expression. Bipolar disorder is a broad spectrum mental health condition which involves extreme mood swings, mania and depression. However, researching the genetic bases of this disease is not just about curiosity; it has a possible future promise to crack its mysteries regarding etiology and treatments strategies as well paving way for precision medicine.
The table of pleiotropic loci also implies particular genetic markers that are applicable to BD type I and II. Of interest, SNPs in genes including ZNF184, RPL10AP3 and SLC25A17 are associated with the two conditions according to ConjFDR. The z scores also indicate the strength and nature of these relationships. For instance, inverse genetic correlations with BD I and II would be suggested by a negative Z-score for the former condition and positive one for the latter. Such results highlight the genetic heterogeneity and that while BD I and II are unique, these disorders may share some common underlying genetics which could explain for overlap in clinical presentation. Gene-based analysis identifies strongly significant genes that differentiate BD I and II after performing stringent multiple testing corrections. Among the candidate genes for BD I that emerged, include CACNA1C, MADLl and TMEM258 with points toward mechanisms involving calcium channel signaling and perhaps cellular division as well membrane structure which is important to neuronal function ad plasticity. On the contrary, SLIT3 was significantly associated with BD II only which may indicate different genetic pathways in these two forms of bipolar disorder.
Thus, such differences might reflect the diversity of clinical features and treatment outcomes between BD I and II. To provide further details, the pathway analysis revealed several significantly enriched pathways in BD I such as neuron parts and calcium channel activity (Orrù and Carta, 2018). These results conform to the neurobiological models that propose ionic channels’ maladjustment in mood disorder pathophysiology. The only enriched pathway of BD II,“Hirsch cellular transformation signature up,” may highlight a specific set of cellular processes attributed to this subtype.
The TWAS analyses performed in blood and brain regions provide an enticing taste of what peripheral biomarkers (for example, those identified via analysis of blood samples) can find potential use as well as CNS processes within BD. With NMB and FADS1 as the top loci for BD I in blood and brain, respectively, both neuromodulators and lipid metabolism seem to play a significant role in BD pathology. In these analyses, the lack of substantial results for BD II may indicate a more complicated or unclear genetic basis to this condition. In the brain region-specific analysis, genes such as FADS1, PLEC and ITIH4 were found to be prominent among others in various brain regions including hypothalamus amygdala and cerebellum. Such areas are famed for their contribution to mood control and cognitive processing. The results suggest that genetic disturbances to these regions could contribute towards the mood dysregulation seen in BD.
Genetic Influence on Bipolar Disorder
Studies of the heritability of BD suggest that it is highly inherited, with twin studies showing much higher concordant rates for identical twins than for fraternal ones This heritability implies a significant genetic component; however, the inheritance pattern is rather complicated and not based on one gene. Instead, BD seems to be polygenic as several genes contribute small effects (Lysova et al., 2023). To date, GWAS has shown that numerous loci are linked to BD including CACNA1C and ANK3 suggesting a possible role of calcium channel signaling pathways. These results support the idea that disturbance of neuronal excitability may be a cause for mood disorders.
Impact of Pleiotropy
BD is also closely related to the idea of pleiotropy, which means that one gene can affect several phenotypic traits. Genetic variants that could increase BD risk may also influence other systems in the body or predispose to other disorders. As such, it adds a layer of complexity to the genetics but lends insight into larger physiological effects BD-associated genes and possible comorbidities.
Gene-Environment Interactions
Although genetics provide a foundation for vulnerability to BD, environmental factors play an important role as stimuli in the emergence of such disorders. Life events that are accompanied by stress, substance use disorders and temporal variation in sleeping patterns may trigger or aggravate episodes, especially for genetically predisposed people (Forstner et al., 2020). This gene-environment interaction highlights the need for an interdisciplinary perspective in understanding and treatment of BD.
Treatment Implications
As far as treatment, hereditarily based information about BD is beginning to penetrate pharmacogenomics, the field wherein hereditary data influences solution and measurement proposals. For instance, hereditary changes related to the reaction to state-of-mind stabilizers, for example, lithium might give a more powerful and individualized way to deal with treating psychological maladjustment (Forstner et al., 2020). Hereditary creators might have the option to distinguish people who will answer well to lithium, which could abbreviate the time span a patient requirements take it. Lithium is a fundamental piece of the treatment for BD.
Future Directions
Future examination of BD is supposed to coordinate genetic information with complete clinical attributes and other organic markers notwithstanding therapeutic treatments. Quality factors that might be related to BD might be found in huge biobanks and data sets, including the Mental Genomics Consortium (andreassen et al., 2023). Moreover, the improvement of CRISPR innovation will empower the exhibition of useful examinations that explain the elements of qualities in mind circuits and conduct.
Single nucleotide polymorphism (SNP)- level strategies are utilized in the exploration to distinguish related and remarkable hereditary loci. The following stage was utilizing transcriptome-wide association examination (TWAS) to recognize practical qualities communicated in specific cerebrum districts and blood (Oraki Kohshour et al., 2022). it next directed a cross-phenotype examination, which included contrasting the hereditary design of four unmistakable psychiatric highlights and exploring conceivable causal connections between two BD subtypes and lithium reactions. SNP-level proof recognized significant quality sets engaged with calcium channel movement, neuronal and synapsed signals that separated two subtypes, and three genomic loci SLC25A17, ZNF184, and RPL10AP3 shared by BD I and II, as it ll as one locus (MAD1L1) (Oraki Kohshour et al., 2022). TWAS information distinguished numerous qualities that express diversely in different pieces of the cerebrum and impact BD I and II (core accumbens for BD I). As per cross-phenotype examinations, significant burdensome disorders and schizophrenia have ceaseless hereditary designs with BD I and II, which helps span the holes created by the polarity of mental sicknesses.
Following the cycle framed by the Worldwide Schizophrenia Consortium utilizing PRSice v1.25, the genotype information went through extra quality control (QC) (HWE p < 1e-20, indels, and copied SNPs eliminated). Around 10.9 million SNPs with ascription R2 > 0.3, and MAF >0.01 were held and used to compute the polygenic gamble score for BD. The Bipolar Disorder Working Group of the Psychiatric Genomics Consortium gathered the gamble SNPs and their related impact size loads from the GWAS for bipolar disorder (Orrù and Carta, 2018). The number of hazard alleles duplicated by the suitable loads for the arrangement of SNPs picked at a maximally educational p-value threshold (pT) was added together to decide the PRS for every member. Utilizing a 0.01 augmentation, we initially determined the polygenic gamble scores for pTs going from 0.01 to 0.5. From that point forward, various strategic relapse models were worked to decide how every PRS connected with the family-ancestry positive and negative classifications (Orrù and Carta, 2018). The downstream association analyses utilized the PRS at pT = 0.07, which created the main contrast between the groups.
Chapter 7: Conclusion and Recommendations
6.1 Conclusion
In conclusion, the study of bipolar disorder’s genetic origins is one complex and intriguing site in psychiatrical research. Bipolar disorder with severe mood modifications, manic episodes and times of depression has been a mystery to the researchers and clinicians for a long time. Although environmental factors clearly contribute to the onset and progress of the disorder, genetic components are also clear.
Twin studies have shed much light on the heritability of bipolar disorder, whereby more often identical twins were concordant than fraternal ones. This result implies that genetic aspects significantly predispose people to bipolar disorder. Nevertheless, the genetic structure of disorder is far from straightforward. Rather, it seems to be a polygenic trait in which many genes play minor roles with regard to the bipolar disorder onset.
Several genetic loci related to bipolar disorder have been discovered in recent GWAS. Research has identified genes, such as CACNA1C and ANK3 potential factors included in the disorder which suggests calcium channel pathways along with neuronal excitability. These results provide important information about the neurobiological processes that may contribute to bipolar disorder.
The phenomenon of pleiotropy where a single gene is responsible for more than one trait or condition makes the bipolar disorder genetics even harder to understand. In addition, some of the genetic variants contributing to bipolar disorder also affect other physiological systems possibly resulting in comorbidities and shared mechanism pathways with mental disorders.
Gene-environment interactions also accentuate the complex interrelationship between genetic vulnerability and environmental stimuli in cause of bipolar disorder. Triggering factors could include stressful life events, substance use disorders and disruptions in sleep patternse especially for those genetically predisposed.
The integration of genetic information into treatment strategies represents a clinical breakthrough. The field of pharmacogenomics, which examines how genes affect an individual’s response to medications, promises personalized treatment for individuals with bipolar disorder. Genetic markers correlated with efficacy of mood stabilizers such as lithium help develop more specific treatment strategies. In the long term, progress in studies of bipolar disorder is to be achieved by combining genetic information with other biological indicators and extensive clinical phenotypes. Big biobanks and consortia, such as the Psychiatric Genomics Consortium , constitute incredible tools for understanding disease genetic contributions.
6.2 Recommendations
Following this broad analysis of the genetics behind bipolar disorder, some general recommendations can be outlined that should guide future research protocols along with practical clinical procedures and public health efforts. To begin with, improved cooperation in the scientific community should be promoted. Moreover, incentivising research organisations ,geneticists and mental health professionals to collaborate in order to share data vastly increases the reach of GWAS. It should go global to obtain different genetic samples and strong statistical analyses.
Secondly, it is mandatory to focus on genetic education and awareness. This includes the creation of educational campaigns for both healthcare providers and the general population to create awareness regarding genetic determinants that trigger bipolar disorder. It is also imperative to train genetic counselors and mental health professionals with the necessary skills to interpret and passing across this information in an understandable language by patients.
Third, melding genetics with clinical practice calls to order. The development of effective protocols for routine genetic testing among bipolar disorder cases will significantly allow early identification and individualized management. Treatment plans based on genetic data should guide the choice of medications and dosages in order to improve the quality of personalized care.
Finally, genetic practices need to be addressed with a wide lens in terms of ethics. This involves obtaining informed consent for genetic testing, privacy protection of individuals and collecting their information responsibly. Moreover, support for equal opportunities in genetic testing and counseling should be addressed to eliminate healthcare inequality.
Collectively, these four recommendations are designed to promote better genetic research use along with educating the public about genetics; assist in implementing responsible gene implementation into clinical practices and enhancing ethical standards of genetics. Through the provision of these guiding principles, we can make progress in our understanding and management of bipolar disorder such that those affected by this complicated condition benefit accordingly.
6.3 Limitations of the study
This study has a limitation in that it is primarily built around the secondary quantitative meta-analysis which investigates on genetics of bipolar disorder. One important limitation is the heterogeneity in data quality between the included primary studies. The heterogeneity in the analysis that may arise due to differences and variations made during measurements, sample sizes, or study designs can influence the validity of results. Furthermore, publication bias is also a threat since studies with positive or significant results are that includes to be published while suppressing other negative reports that may interfere with the outcomes of the meta-analysis. It is true that managing heterogeneity, harmonising data and while dealing with the lack of control over primary study design are intrinsic challenges to meta-analysis. In addition, although meta-analysis can determine correlations but not causality underscores that more integrative investigational or longitudinal research is needed. Even with these deficiencies, secondary quantitative meta-analysis is an important method of summarising existing genetic data about bipolar disorder that would provide a summative overview; generate hypotheses for further inquiry.
6.4 Conflict of interest
In the case of this study, there are no conflicts of interest to report. The authors declare no financial or personal conflicts that might have affected the results of this work. The authors of this research have adopted objectivity and transparency throughout, fulfilling their purpose to advance scientific knowledge in the area of genetics and bipolar disorders.
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