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Chapter II: Literature Review

This section entails the introduction of the literature review. The importance of this section is to describe the importance of the literature review and the main areas, including the outline of the literature review, inclusion and exclusion criteria, and the research data base and search criteria.

1.0 Introduction

This chapter entails an analysis of the previous studies done in relation to the topic. The survey is based on books, scholarly articles, and any other essential materials, such as clinical guidelines. The review describes and summarizes the material objectively intending to clarify the previous concepts and ideas and establish gaps for future research. Also, the section comprises of a theoretical foundation for the study, which assists in the analysis of the materials. Through an evaluation of previous materials and researchers, the foundation of the current research is provided, including the justification of the research objectives and hypothesis. To the reader, this chapter will convey information regarding the strengths and weaknesses of the previous materials in relation to the current topic of study. Further, the reason for using the particular material in the review is provided as well as the insights from the specific source.

1.1 Outline of the Literature Review

This literature review chapter comprises of five main sections. The first section is the introduction to the chapter, where the purpose of the literature review is provided. In this section, the materials being used for the review will also be discussed with regard to their context and qualifications. This will be described in the inclusion and exclusion criteria. In the second section, it entails the theoretical framework that guides the research. This research uses the Biomedical model. According to Deacon and McKay (2015), mental disorders are the brain’s literal conditions. This implies that physical health conditions are similar to the mental ones. The difference between the two sets of conditions is the affected organ, which is the brain for mental illnesses. The theoretical framework section will, therefore, examine this theory in length, including the origin and its application in this research. Also, some of the studies that have previously used this theory will be evaluated.

The third section of the literature review will involve the literature analysis according to the research questions. This research is centered on three objectives or questions. The first one examines the specific genetic alterations associated with mental disorders. The second question entails the particular neural circuits related to the mental health functions, and the third question examines how the genetic research on neurobiology and mental health can be used to diagnose and treat the mental health conditions.

Multiple sources, selected through the inclusion and exclusion criteria, will be used for analyzing these three sections. In the fourth section, the gaps and summary of the literature analysis are provided, which describe the foundation of the main topic, the relationship between genetics and mental health disorders.’ This section will further involve a summary of the primary sources and their core insights. The final section entails all the resources that were used in the analysis.

1.2 Inclusion and exclusion criteria

The inclusion and exclusion criteria refer to the set of boundaries for the elements used in the research. They are established through one’s preferences and those of the study. According to Patino and Ferreira (2018), the inclusion criterion is the aspects of characteristics of the subjects or the papers that are important for their use in the research. Exclusion criteria, on the other hand, refer to the features that prompt for the removal of the material or the subject in the study. The inclusion criteria in the literature review entail the elements that warrant the sources to be considered in the review process. These will include a study published within the last five years, peer-reviewed, clinical guidelines, and books. The exclusion elements are characteristics that will result in the studies or the source not being considered in the literature review. In this review, the exclusion criteria entail the study being published in another language rather than English and research that contains the abstract only.

1.3 Research database and research criteria

The resources will be obtained from a wide range of databases. These include CINAHL, Cochrane Library, EMBASE, MEDLINE, PsychINFO, and Scopus. Dissertations and thesis will also be used, although at a limited level. This is based on promoting the quality of the review, which is influenced by the credibility and validity of the sources. In this regard, the majority of the materials used for the review will be peer-reviewed and clinical guidelines. The primary search engine Google and Google Scholar will also be used for the search.

The search will employ the BOOLEAN concept. According to Scells, Zuccon, and Koopman (2019), the Boolean search allows the researcher to combine words and phrases using modifiers or operators to provide relevant findings. The operators include OR, AND, and NOT. This will enable one to navigate the databases and establish relevant findings according to the research topic and objectives. In this research, the keywords and phrases are obtained from the topic and the three objectives.

The main words used in the search will include genetics, mental disorders, neural circuits, mental health functions, neurobiology, research, and treatment. The combination of the keywords for phrases that will be used in the search will include the association between genetic alterations and mental disorders, specific neural circuits associated with mental health functions, and genetic research on neurobiology and mental health. Technical skills will be crucial in navigating the databases. Among the main specifications in the databases are the studies being published since 2015 and the source being full. Essential to note is that there is no constrain in the quantitative and qualitative data for the review.

In summary, the above section describes the overview of the literature review, including the main sections or outline, the inclusion and exclusion criteria, and the search databases and criteria. The next part entails the theoretical framework used in the research, the Biomedical model.

2 Theoretical Framework

This section involves the theoretical framework used for the research. It defines the theory, its origin, and its importance in the study. The theoretical framework diagram that will be used for the research is also provided, including how the model relates to the research.

The theory being used in this research is the Biomedical, which is common and useful in mental health research. According to Osanloo and Grant (2016), the theoretical framework is among the core elements in the research process. The theory should be linked to the topic of study, developing the research questions, conceptualizing the literature review, and the analysis approach of the study data. Adom, Hussein, and Agyem (2018) describe a theoretical framework as a mandatory ingredient in research. Metaphorically, the theoretical framework is the blueprint of a house. Without the theory, the vision and structure of the study remain unclear. In research, the model allows for an organized flow from one section to another. The theoretical framework is derived from an existing theory as compared to the conceptual framework, which is a collection of connected concepts and logical structures to assist in providing a visual display or picture of the study.

• Overview and Origin of the Biomedical Theory

The Biomedical model of illness and health is dominant in the Western world’s medicine. The framework is centuries old. In the 1700s, Rene Descartes acknowledged that the body and mind are distinct entities. In contemporary society, this demonstrates the reason for different healthcare practitioners treating the body and mind. Also, this knowledge of the difference between the mind and body is the foundation of diverse research in these contexts.

Several individuals have contributed immensely to the development of the Biomedical model. Joseph Lister, for instance, in medical science, revealed that germs could cause death and illnesses (Horwitz, Hayes-Conroy, & Singer, 2017). John Dalton, on the other hand, noted that atoms make up matter, which is the foundation of additional research in physics (Talware, 2020). Notably, these are only a few sections that function under the Biomedical model, which has been in existence since the mid-19^th century.

The biomedical model involves the relationship between illness and health. One is considered either healthy or ill, and there exist no grey areas between the two. Acknowledging the illness patterns is based on symptoms and signs, as described by the patient. This aids the doctors in conducting a medical history where more investigations should be done. The pathology is among the method that guides the physicians and allow for the implementation of a treatment. This then allows the patient to be cured and recover. Under the Biomedical model, the doctor possesses sufficient knowledge and is competent in healthcare issues. The doctor, in this regard, is the gatekeeper and is held in high esteem in the community due to the profession. This knowledge is the foundation of assisting the patient to cure the illness.

This research is centered on the Biomedical model. According to Deacon (2013), this model posits that mental conditions are brain illnesses. It, therefore, emphasizes the pharmacological management that targets the biological anomalies. It is also a biological-focused strategy to practice, science, and policy that has dominated the healthcare sector for at least three decades. In mental health, there has been a significant rise in psychiatric medicines to treat mental health conditions. These illnesses, on the other hand, are termed as brain conditions emanating from chemical imbalances in the brain. The correction of these imbalances is through the use of drugs that are specific to the illnesses.

On the other hand, there is a significant gap in mental health practice and applying the Biomedical model. This is centered on the limited innovation and poor outcomes in mental health (Lake & Turner, 2017). Further, the Biomedical paradigm has impacted clinical psychology through psychotherapy research and the use of trial drugs for medication.

The application of this model is centered on its influence in psychiatry and the development of mental illnesses drugs. According to Beckett (2017), the Biomedical model posits that similar to how physical diseases are caused by a specific disease, the same concepts are applicable in the mental health conditions. The main assumption is that all illnesses result from a particular disease. Several biomedical explanations are known for causing mental health conditions. These include neurological challenges, genetics, and alcohol and substance abuse. In the neurological problems, for instance, damage or fault in the brain can be associated with the neurotransmitters.

Another similarity between the physical and mental illnesses is the existence of signs and symptoms for the specific disorder. For a depressed individual, for example, the signs and symptoms include a change in eating habits and reduced moods (Pinto et al., 2017). Also, these individuals exhibit alteration in sleep, such as an increase or reduced duration of sleep. These situations describe hypomania and insomnia, respectively.

The pharmacological treatment of mental health conditions, according to the Biomedical model, is centered on addressing the signs and symptoms, which are related to the abnormalities in the brain. For instance, Prozac is used as an antidepressant. Similar to how drugs are widely used in treating physical illnesses, the pharmacological approach is identified as a universal remedy for the majority of conditions (Beckett, 2017). The Biomedical model has been pivotal in psychiatry amid the increased criticism.

An example of the critic is the relationship between psychiatric medications and other issues. These constitute the side effects. When managing social anxiety disorders, the patient may complain about the persistent fears of the performance and social instances, where one experiences embarrassment (Bastin et al., 2016). This is the foundation of accompanying the pharmacological management of the mental health conditions with non-pharmacological, including psychotherapy, which aid in alteration of the individual’s behaviors and thought processes.

2.2 Biomedical Model and Mental Health

The Biomedical model has played a significant role in psychiatry. According to Curtis-Warner (2020), through a doctoral dissertation that analyzed Foucault and Szasz’ writings on psychiatry, it is apparent that the knowledge and idea regarding the chemical imbalance downplay the previous and present environmental factors as the foundations of psychiatric conditions. The importance of biomedical knowledge is, therefore, based on addressing the causes of mental health issues, including these chemical imbalances.

Johnson (2017), through literature analysis, support these findings and note that biomedical knowledge has transformed psychiatric health care through anti-psychotic medications. The antidepressants, in this case, have been proved to be resourceful for depressed women. Johnson (2017), therefore, applauds the previous work by Hoffman and Hansen and offers a critical message that antidepressants are a symbolic replacement and demonstration that one day, depression will be eliminated. However, there is a need to explore further research on the impacts of the antidepressants on the people and the variation of the effects based on gender.

The biomedical model provides a foundation for future research on mental health and the importance of other dimensions, such as power-relations and environmental issues. Sercu and Bracke (2017), through interviews of inpatient use from Belgian psychiatric hospitals, found out the social structure has significant impacts on the stigma experiences of the individual and is related to the relationship between the service users and the care providers. Using the constructivist grounded theory approach, Sercu and Bracke (2017) showed that the mental health literacy concept is the framework to the findings regarding the relationship between social structure and stigma.

The biomedical model, therefore, allows for casting some light on maintaining the power relationships between the main stakeholders in the healthcare society, the healthcare providers, and the society in general. These findings are also supported by Arias et al. (2016) through semi-structured interviews in Ghana. Through a comparative approach for the data analysis, Arias et al. (2016) revealed that medications are essential in mental health. However, there are concerns over the long-term uses of these drugs, such as addiction. In addition, it is crucial to implement drugs alongside non-pharmacological management approaches.

The Biomedical model faces some criticisms in mental health, especially in the long-term uses. Arias et al. (2016) revealed that psychiatric medications are essential in addressing mental illnesses. However, their implementation should be alongside other strategies, including partnerships between the healthcare providers and the users. The key concerns, however, are on the long-term application of the psychiatric medication, which may result in overdependence. Similarly, Mali (2018), through a comparative assessment of the maternal health policies and maternal health in India, noted that the pharmacological management of health conditions remains essential in achieving the millennial development goals.

However, there is a need to expand the attention in the maternal health scope from biomedical to biopsychosocial. This will allow for the introduction of other approaches in healthcare, including the development of policies related to health care and management.

2.3 Application of the Theory in this Research

This research evaluates the relationship between genetics and mental health conditions. According to Beckett (2017), among the core causations of mental health conditions is genetics and neurological issues, including the neurotransmitters and damage to the brain. The biomedical model, therefore, aids in explaining this relationship. In the research questions, the genetic alterations are examined in relation to the mental conditions. The biomedical model thus helps in describing this relationship and alternations in the brain that result in mental health.

Another application of this model is establishing the treatment approaches in mental health. According to Strickland and Patrick (2014), mental illnesses result from physiological and measurable deviations from the normal healthy functioning of the brain, which explains the Biomedical model. The treatment approaches are implemented in addressing these deviations and challenges. The application of the model in this research is centered on the third objective, which involves the use of neurobiology genetic research and mental health assist in the treatment of mental health. The biomedical model will provide insights on the diagnosis and management approaches of the mental health conditions.

The application of the biomedical model in this research is demonstrated in figure 1 below. In Figure 1 below, the Biomedical model comprises five dimensions. Central to this model is mental health, which comprises of various disorders, such as autism, depression, anxiety, PTSD, and stress. On the outer part, the four areas of genetic alterations, neural circuits, diagnosis and treatment, and genetic research on neural biology and mental health are provided. These dimensions demonstrate how the different research objectives are related to the topic of mental health. 

 

 

Figure 1: Application of the Biomedical Model in this Research

In summary, this section examines the theoretical framework used in the research, the biomedical model. From the discussion, the model is centuries old, and studies that support the concept began in the 1700s, where the body and mind were revealed to be separate entities that function collaboratively for the body to execute its activities. The biomedical model in mental health considers the mental health illness as caused by disease. This causal relationship is based on genetics, abnormalities, and chemical imbalances in the brain, which result in diseases. The model, therefore, aids in understanding the link and the treatment approaches. The next section examines the associations between genetic alterations and mental disorders.

3 Associations Between Genetic Alterations and Mental Disorders

This section revolves around the first research question that involves the specific genetic alterations and their association with mental disorders. The section involves three subsections, including genetic alterations, mental health, and the relationship between the two. The importance of this section is to understand the particular genetic alterations that are related to the mental health conditions, which is the foundation of the treatment and management of the healthcare conditions using a pharmacological approach.

3.1 Genetic Alterations

The evolution of genomes has occurred over millions of years from the initial development of living organisms. As espoused by Custers et al. (2019), this evolution is the foundation of diversity in species. Mutations occurring naturally alongside the natural selections are the main elements that drive evolution. Understanding the underlying mechanisms that guide this evolution has increased significantly and is vital in defining the healthcare conditions and their mitigation. Additionally, the genome sequencing technology has enhanced the understanding of these alterations and how they influence the evolution, breeding, and domestication.

Lee et al. (2019) findings regarding the importance of genomic technologies in understanding the healthcare conditions and evolution recognize this knowledge and its impact in developing precision treatment. Through an analysis of 55 patients from January 2016 to October 2018, Lee et al. (2019) revealed that the knowledge on the DNA sequences aid in developing a tailored medication according to the individual’s condition. Further, technologies in genetic alterations have allowed for understanding the germline genomic aberrations and somatic among patients diagnosed with cancer.

Genetic alterations are changes in the DNA sequence, making up the gene. The impact of these changes is the result of a different sequence from that in other people. According to Chang et al. (2018), the genetic changes differ in size and can range from single DNA building blocks to a large one of the chromosomes, which involves multiple genes. There are two core classifications of genetic alterations. These include the hereditary and acquired. In hereditary alterations, they are inherited from the parent and exist throughout the individual’s life across all the virtual cells. These mutations, according to Ha (2017), are also referred to as germline mutations due to their existence in the parent’s cells.

During conception, the combination of cells results in a mutation of the others. In acquired alterations, they present at the individual’s life at a certain point and are not in every cell in one’s body. As espoused by Konnick and Pritchard (2016), these changes result from the environmental factors, including the UV radiation, and can occur due to the errors in the DNA copies during the division of cells. Essential to note is that the acquired alterations in the somatic cells, those that are not in the egg or spam cannot be passed through generations.

3.2 Mental Health Conditions

Mental disorders are those conditions that affect one’s feelings, thinking, behavior, and moods. They can be chronic or occasional. The conditions also affect one’s ability to function daily and relate with other people. Mental disorders differ. The common ones include depression, anxiety, eating, and post-traumatic stress disorder (PTSD). According to Freeman et al. (2017), there are no specific causes of mental health conditions. However, several factors contribute to the risks of mental illnesses. These include the individual’s mental illness history, genes, life experiences, biological factors, traumatic brain injury, and the mother’s exposure to toxic chemicals and viruses when pregnant. Also, one may be affected by alcohol and drug abuse and having other medical conditions, such as cancer. According to Kamimura et al. (2018), mental health conditions can affect all individuals regardless of their diversity, including age, gender, race, and ethnicity. The information regarding mental health conditions is vital in developing management plans, including pharmacological and non-pharmacological approaches.

The world health organization (WHO) describes mental conditions as characterized by various aspects, including emotions, behavior, perceptions, and abnormal thoughts. Also, there are concerns regarding the relationship with others. Some of the mental disorders, according to WHO, include bipolar disorders, depression, dementia schizophrenia, and developmental issues, such as autism (WHO, 2019). A key aspect in contemporary society is the rising mental health conditions, which affect the social, economic, and political dimensions.

Thyloth, Singh, and Subramanian (2016) also acknowledge the rising mental health disorders globally. These conditions account for about 13% of the global burden. The central gap, as noted by Thyloth et al. (2016), is the increasing number of studies that focus on the magnitude of the mental health burden, including the prevalence and incidence rates, losing the life expectancy, high mortality rates, and disability years. This demonstrates the central gap in evaluating the causes of the condition, specifically the relationship between genetic alterations and mental disorders.

Mental health disorders are caused by various aspects, including genetic changes and environmental issues. According to Yoshioka et al. (2016), through a web-based survey for 1000 Japanese adults, depression and schizophrenia are associated with several aspects, including the individual’s personality characteristics. Notably, these elements are related to one’s personal beliefs. Okpalauwaekwe, Mela, and Oji (2017) using a scoping review to evaluate the peer-reviewed articles to evaluate the attitudes and beliefs regarding mental health. The study revealed that mental health conditions are associated with physical, environmental, and personal factors. In addition, the lack of access to quality mental healthcare facilities results in poor outcomes.

In a different study, Abbas, Haider, and Shan (2019) used SPSS to analyze data from 500 patients selected through non-probability convenience sampling. From the evaluation, 27.29% of the individuals, which represented 131 out of the 500 patients from Fauji Foundation Hospital in Lahore, argued that the evil spirits cause mental health conditions. 20.62% of the respondents argued that illness was also a reason, and 72% noted that behavioral changes and seeking attention are the main causes of mental health conditions. These findings demonstrate that there are several causes of mental health conditions, which are based on the individual, environmental, and physical factors.

In summary, these two sections examine the genetic alterations and mental disorders in their individual contexts. From the analysis, genetic changes and mutations can ne hereditary or acquired. The difference in the two alterations is how the alterations are passed from an individual to another and also the origin of the alterations. The analysis of the mental health section reveals that mental disorders have become a global burden, according to WHO (2019). Also, there are several causes of mental health conditions, including genetic changes, environmental, social, and personal factors.

This information is important in demonstrating the gaps in the causes of mental health conditions. Notably, the majority of studies have focused on the prevalence rates rather than the causes.  The next section evaluates the specific genetic alterations that are associated with mental health.

3.3 Specific Genetic Alterations Associated with Mental Health

This section evaluates the association between genetic alterations and mental disorders. This relationship is based on the previous two sections, which show that genetic aspects are among the core causes of mental health conditions.

There is a significant relationship between genetic alterations and mental health conditions. According to Hakonarson et al. (2017), Autism (MIM [209850]) is a common and severe neuropsychiatric disorder that is characterized by abnormalities in communication skills, social behavior, behavioral disturbances, and abnormal repetitive movements. The etiology of the main forms of autism remains unknown. The main finding in most studies is that environmental hypotheses as a cause of autism is unsupported. However, there is an increasing number of studies that support the relationship between autism and genetic alterations. For children from parents that had autism, there is a 2-6% likelihood that the child will be autistic. Autism hereditability is currently estimated as above 90%.

Several upcoming theories relate autism with neural connectivity changes. In the imaging research and activity-dependent cortical development posit that autism results from the imbalance between the excitatory synaptic and inhibitory connections during development. Notably, the synapse is the primary unit of the neuronal connectivity. Therefore, autism is a condition of the neural connectivity and can be examined from the neural terms as a condition of synaptic connections. In genetic studies on autism, the mutations in the main proteins involved in the plasticity and synaptic development, including FMRP, neuroligins, and MeCP2 are found among people with autism, especially those with the two types of autism and mental retardations, Rett’s syndrome and Fragile-X. Hakonarson et al. (2017); therefore, notes that additional studies on the relationship between the endo-phenotypes and the genetic anomalies at the neural level are important in the future.

Schizophrenia is another condition described by genetic alterations. The condition, according to Calabrese, Riva, and Molteni (2016), is a debilitating and severe disorder that has a 1% prevalence. It presents mainly among individuals in their late adolescents and early childhood. The condition is described by the heterogeneous signs and symptoms, such as disordered speech and thoughts, hallucinations, and delusions. The condition is also described by an emotional range that is blunted, cognitive deficits, and anhedonia. A key challenge in this condition is the inability of the antipsychotic medications to treat all the symptoms and the significant side effects. This is the foundation of continuing research on therapeutic approaches.

The evaluation of schizophrenia etiology reveals the altered density of the dendritic spine. An interesting element regarding this alteration is that it appears particular for layer 3 of the Brodmann area (BA) and the lack of differences in layers 6 and 5. The structural abnormalities observed can either be due to impairment of the dendritic spines elaboration during the early development to a rising elimination of the spines. In the imaging studies, the gray matter volume reduces steadily among adolescents that are transitioning to schizophrenia as compared to those that have psychosis. Avramopoulos (2018) note that the last one decade has introduced significant progress in genetics and schizophrenia. This is centered on technological advances and wide collaborations.

Among the core findings in recent studies are rare and inherited coding and more than 100 loci harboring usual risk variants (Gratten, 2016; Nalls et al., 2019). Although the risk factors differ in the genetic variants, a concordance exists in the genes’ functions that are affected. An example is those that the RNA binds FMRP, which is a fragile X-related protein. The key challenge in understanding the genetic alterations is the inability to transform this knowledge into practice to assist the patients. However, there is a promise that the translational ability of these findings will occur in the next decade.

The mental disorders described by genetic alterations show the inheritability and altered changes. According to Harrison (2015), schizophrenia has a significant genetic element that is characterized by a sophisticated, non-Mendelian inheritance. The hereditability range of the condition is 65% to 80%. In recent studies, they have been essential in advancing the understanding of the risk loci, the genetic architecture, and the mechanisms through which the genetic risks have been conferred. Harrison (2015) study acknowledges the loci related to schizophrenia risk, similar to the study by Avramopoulos (2019).

The findings from both studies above (Harrison, 2015; Aramopoulos, 2019) reveal that Schizophrenia genes exist. However, there are still gaps in these discoveries. Fundamentally, the single nucleotide polymorphisms (SNPs) have insignificant effects and cumulatively describe the modest genetic predisposition fraction. The SNPs risks are non-coding, which implies that the biological significance is unclear, and the effects are mediated through influence on the gene monitoring.

There are also structural alterations related to depression and suicidal ideation in bipolar disorder (BD) and major depressive disorder (MDD). According to Wei et al. (2020), who evaluated the structural alterations in BD and MDD for 76 individuals with previous suicidal attempts through the diffusion tensor imaging (DTI), fractional anisotropy (FA), in various and main white matter bundles, such as fronto-occipital fasciculus (IFOF), corpus callosum (CC) and bilateral uncinated fasciculus (UF) was demonstrated among individuals with BD and MDD with suicidal attempt.

These results reveal that there are several structural alterations among individuals with suicidal attempts in depression. Schmaal et al. (2016) confirm these findings through a meta-analysis of the three dimensional (3D) magnetic resonance imaging (MRI) data. The data was obtained from 1728 patients with MDD and controls of 7199 individuals from 15 study samples globally. This study showed a robust but smaller hippocampal volume among the patients with MDD.

For schizophrenia and bipolar disorders, the molecular alterations of the serotonin aspects cause altered function in the pathway among the diseased individuals compared to the healthy ones. According to Baou et al. (2016). The alterations are researched using the post-mortem and molecular imaging approaches. From the relative data, the transcription of the serotonin pathway genes has been shown in different brain parts of the individuals. Among the psychotic patients, there are reduced levels of HTR1A, HTR2C, HTR2A, HTR6, and HTR7 in both schizophrenia and bipolar disorder compared to the healthy control patients. These findings are indicative of a reduced transcription of the various genes.

Another core finding from Baou et al. (2016) study is the mRNA levels of HTR1B among the BD and SZ individuals, MAO among SZ patients, and TPH in those that had BD being higher compared the control groups. However, there exists a gap in the studies based on the controversial and inconsistent findings. These differences demonstrate variations among the patients and people or limitations in the methodology used.

Genetic alterations are also associated with delirium and dementia. According to Massimo et al. (2017), through a randomized controlled trial (RCT) for 142 individuals, the objective to establish if the severity of delirium was related to Apolipoprotein E (APOE) genotype status and complexity in occupation, which measured cognitive reserve. From the analysis, using multilevel models, it was revealed that APOE allele presence was related to severe dementia at the baseline.

Occupational complexity, on the other hand, had no significant association with baseline severity of dementia. The findings of this study, especially the relationship between genetic alterations and delirium and dementia, were affirmed by Massimo et al. (2017) through the HumanMethulation 450 BeadChip Kit in three cohorts that were independent. From the 87 inpatients that had or lacked delirium and 21 neurosurgery patients, there was a significant correlation between DNA methylation (DNAm) of the pro-inflammatory cytokine genes and delirium. Massimo et al. (2017) further introduce the concept of age, which results in neurotrophic genes epigenetic modulation. This knowledge plays an important role in understanding the pathophysiology and etiology of delirium.

Delirium, similar to schizophrenia and depression, is associated with various risk factors. As espoused by Mahanna-Gabrielli et al. (2018), there is an increasing interest in melatonin in delirium treatment, which is also associated with sleep disturbance. Notably, the melatonin receptor 1B gene can result in the polymorphism of the rs10830963 single nucleotide. This genetic alteration can result in the pathological dysfunction of the receptor and is also related to the delayed melatonin offset in the morning.

The changes in the genes are also influenced by external aspects, such as surgery, especially among aged individuals. This was confirmed by Guo et al. (2020) through the assessment of 244 old patients that met the inclusion and exclusion criteria. Using orthogonal partial least squares-discriminant analysis, it was revealed that the metabolic abnormalities, such as deficiency in fatty acids (ω3 and ω6), oxidative stress, tricarboxylic cycle, and the imbalance between AAA and BCAA contribute significantly to POD development. These findings demonstrate the effect of genetic alterations in mental disorders.

Anxiety and stress are also related to genetic alterations. Agusti et al. (2018), for instance, found that B. pseudocatenulatum CECT 7765 may play an important role in the comorbid depressive behavior with overweight and obesity through regulation of the immune mediators and endocrine of the gut-brain axis. The genetic alterations also aid in understanding the risk factors associated with one’s vulnerability to developing stress-induced psychopathologies. Weger and Sandi (2018) provide an analysis of the relationship between genetic changes and stress and anxiety. These findings add to the vast literature regarding the impacts of genetic modifications and changes and mental disorders.

Savage et al. (2017) also outline the various SNPs that are related to anxiety. Among the common SNP studied is the serotonin transporter, which is denoted by SERT or 5-HTT. Notably, the 5-HTT is encoded by the SLC6A4 gene, and the transcription is modulated through a repetitive sequence. The 5-HTTLPR is expressed as a long or short allele. Savage et al. (2017) further note that the short allele results in the synthesis of the 5-HTT protein compared to the longer one. This is associated with the high concentration of the serotonin in the synaptic cleft. The lower expressing 5-HTTLPR short variant allele is related to the trait anxiety in different human studies.

3.4 Summary and Gap

The section above demonstrates the relationship between genetic alterations and mental disorders. In the disorders examined, including depression, bipolar, schizophrenia, delirium, dementia, anxiety, and stress, there is a significant relationship between the genetic changes and the occurrence of these conditions. Among the core discoveries from the analyzed studies is the influence of other factors in the genetic changes. These include other diseases, age, environment, and surgery.

A major finding from the analysis is the impact of hereditary and acquired genetic changes to mental health conditions. For instance, Ha (2017) note that the genetic mutations in the parent cells are transferred to the children through the fusion of these cells. This demonstrates the high risk of individuals from parents with mental health conditions. On the other hand, there is lack of specific causes of the mental conditions as described by Freeman et al. (2017). The genetic factors are not independent factors that cause these conditions. There are other elements, which have to be considered, including the environment, alcohol and substance abuse, and other disorders.

Across the different conditions, including delirium, dementia, and depression, the studies do not identify the specific genetic alterations that are associated with the conditions. Therefore, it is essential to conduct further research to define the specific alterations associated with the conditions. According to Hakonarson et al. (2017), several studies associate autism with genetic alterations. However, there are no specific sources or materials that outline the diverse genetic alterations related to autistic development. It is, therefore, essential to conducting further research that will outline the specific genetic alterations related to mental disorders, which is the foundation of the first research question in this study. This information will be essential in understanding the pathophysiology of the different conditions, which further informs the treatment approaches.

Research Question 1: Which specific genetic alterations are associated with mental disorders?

In summary, this section examines the existing literature on genetic alterations associated with mental disorders. There were three sub-sections, including mental disorders, genetic alterations, and the relationship between genetic alterations and mental disorders. The next section evaluates the particular neural circuits associated with mental health functions.

4 Specific Neural Circuits Associated with Mental Health Functions

This section is based on the second objective of the research. Specifically, it evaluates the specific neural circuits that are associated with mental health functions. There will be three main subsections, including the definition of the neural circuits, mental health functions, and the relationship between the two.

4.1 Neural Circuits

This section examines the meaning of neural circuits and involved concepts and areas. The discussion entails the role of the brain and the importance of neural circuits in one’s brain and cognitive function. Notably, neural circuits involve the function of the neurons to convey messages.

Neural circuits are ensembles that process particular types of information. According to Raman, Rotondo, and O’Leary (2019), neurons do not operate in isolation. Rather, they are organized into circuits for processing information. Neural circuits vary significantly in the arrangement and according to the function intended. The synaptic connections defining a circuit comprise a dense tangle of axons, dendrites, and terminals, which comprise of the neuropil. The neuropil in the nerve cell bodies is the area, where the majority of the synaptic connective happens.

The information flow direction across the different neural circuits is essential to understand, which aids in promoting one’s knowledge regarding the functions of the neural circuits. Afferent neurons, for instance, are the nerve cells that transfer data towards the CNS (Chien et al., 2019). The efferent neurons, on the other hand, are responsible for carrying information from the spinal cord or the brain, which is away from the circuit in question. Another important aspect is the interneurons, also referred to as the local circuit neurons. The three classes comprising of interneurons, afferent, and efferent neurons are the primary constituents of the circuits.

The responsibility of the brain is reflected in the actions, thoughts, and perceptions of the individual. Besides the wide array of the processes conducted by the brain, including emotions and memory, the elementary units are the synaptic junction and the nerve cell. One’s behavior, therefore, is influenced by these neurons and synapses. In the brain, the cerebral cortex is an important area that is involved in all cognitive functions. Notably, the individual neurons in the cortex can establish more than 10,000 links with the brain cells. This connection, according to Rosch et al. (2018), between the local group of neurons, defines the primary computation unit, which is described as the cortical microcircuit. The brain comprises of millions of neurons. Their responsibility is to transmit the information. This is achieved by transmitting electrical impulses along the axons. Most of these axons are encompassed in the myelin sheath, which transmits the electrical signals (Micheva et al., 2016). This is also done along the axons.

Neural circuits are both anatomical and function entities. Fundamentally, the brain depends on these circuits for information interpretation regarding the world. This is reflected in the individual’s ability to learn and control the movements. However, Koch et al. (2016) note that it is challenging for researchers and scientists to identify the specific cells that are involved in a particular task since the nerve cell are joined tightly, resulting in an intricate network. For the brain to establish the course of action, the brain cells function together. This also applies to the possibility of emotions and actions. The next section describes the mental health functions, and subsequently, the association with the neural circuits.

4.2 Mental Health Functions

This section describes mental health functions. The discussion commences by understanding the concept of mental health, which entails the individual’s overall wellbeing. This is followed by mental health disorders and their management, which involves both pharmacological and non-pharmacological strategies.

Mental health involves the overall wellbeing of an individual. According to Fjermestad et al. (2020), mental health comprises the person’s social, emotional, and psychological welfare. It impacts how one acts, thinks, or feels. Mental health also determines how the individual addresses anxiety, stress, and relationship with others. Across all stages of life, mental health plays an important role in influencing a person’s decision making. Metal health challenges may present across various experiences. These include issues with the thought process, behavior, and moods. Several factors influence one’s mental health. These include life experiences, biological, and family history.

It is important for one to establish if there are issues with mental health by identifying the signs and symptoms. Examples include sleeping more or less, deviating from the normal activities, low energy, hopelessness, helplessness, taking alcohol and drugs more, poor social relationships, and moods (Chang et al., 2020). These clinical manifestations are important in describing the mental condition that the one is facing and developing a management plan.

Poor mental health function is reflected in the illnesses and disorders, which impair the individual’s quality of life and daily activities. According to Healthy People 2020, addressing mental health disorders is essential in promoting one’s productivity, achieving fulfilling relationships, and enhancing one’s ability to change and cope with life challenges. Mental health function is also important in one’s contribution to society or the community. Mental disorders, on the other hand, are defined by the individual’s inability to behave according to social norms and impaired functioning. These disorders also contribute to various issues, including death, disability, and pain.

Managing mental disorders is dependent on the specific condition. However, the treatment approaches are classified into pharmacological and non-pharmacological categories (O’Doherty et al., 2020). A combination of these approaches is vital in managing the disorders effectively. This involves the use of medicines and therapy, such as cognitive-behavioral therapy.  

4.3 Specific Neural Circuits Associated with the Mental Health Functions

This section describes the association between specific neural circuits and mental health functions. The literature related to this topic examines how various mental health conditions, including autism, schizophrenia, and depression, can be explained from the perspective of the neural circuit.

Neural circuits profoundly describe social behavior. This was described by Fernandez, Mollinedo-Gajate, and Penagarikano (2018), who noted that magnetic resonance imaging research among humans has aided in understanding the connectivity of the brain structures and their relationship with cognitive function and one’s behavior. From the molecular neurobiology context, one’s brain activities are controlled by the neuronal circuits, which are further modulated by the neuromodulators and neurotransmitters. These findings are essential in understanding social disorders and functioning, including autism. This argument is asserted by Chen et al. (2018) through MRI data of 58 young children. Through 29 individuals with Autism spectrum disorder (ASD) and 29 healthy controls, Chen et al. (2018) showed that there are two atypical functional connectivity (FC) circuits that are related to ASD. Notably, these circuits are associated with the restricted behavioral scores and social benefits. These circuits comprised of the sensorimotor and social processes among young children. This knowledge is essential in understanding brain connectivity and the disorder onset.

The neural circuits associated with mental conditions, such as Autism, are based on the specific symptoms and signs of the condition. According to Fuccillo (2016), through a descriptive review, the two signs and symptoms domains related to autism are regulation of the motor output and social behavior. However, it remains unclear whether Autism symptomatology is a representation of the abnormalities or the dysfunction of the brain networks. This study demonstrates the need for further studies in understanding the specific neural circuits that are associated with Autism.

On the other hand, Fuccillo (2016) argues that the striatal function increases the appreciation of the disease hallmarks, such as motivational state, behavioral flexibility, attention, and goal-directed learning. Among the core neural circuits related to Autism is canonical neural circuits, whose dysfunction is significantly associated with Autism symptomatology. These findings were confirmed by Van de Cruys et al. (2018) through a test of a single fundamental prediction model for low-level perception. For all the 11 individuals with autism spectrum disorders, they demonstrated a significant orientation bias, and the canonical neural computation circuit was essential in explaining this relationship. These two studies demonstrate the relationship between canonical neural circuit and autism, which is essential in determining the treatment strategies for the condition.

Understanding the particular neural circuits related to the mental health condition is a key milestone in determining the psychopathology of a condition. This is reflected in anxiety and depression. According to Rodman et al. (2019), through a longitudinal sample of 151 individuals aged 8-17 years, individuals that were effective in modulating the amygdala reactivity and recruiting the prefrontal control regions demonstrated a low risk of depression with time. Contrary, there was no relationship between neural functioning and depression for those who had a history of maltreatment.

In another study, Williams (2017) espouses that complex cognitive, emotional, and self-reflective functions depend on the connectivity and activation of the major neural circuits. These information networks are essential in understanding the taxonomy of anxiety and depression. This study introduces another element of biotypes or specific profiles of the dysfunction of the neural circuits. The biotypes in this regard are described as the dysfunction extents or profiles on the large circuits. Similar to Autism, understanding the neural circuits associated with anxiety and depression is important in determining the treatment mechanisms of the conditions. Williams (2017) provides a suggestion for future studies, which should focus on translating the neuroscience findings into the real world or clinical practice.

The connections between the brainstem and the frontal cortex have presented as key candidates in understanding the neural circuits related to depression. As argued by Post and Warden (2018), the major depressive disorder can be reflected in a combination of various symptoms, including losing interest in daily life, sadness, and the individual’s inability to engage in goal-oriented behaviors. From animal models, the prefrontal-neuromodulator circuit changes have provided sufficient insights into research on depression. Other regions that have been implicated in understanding the specific neural circuits associated with depression are ventral and dorsal prefrontal areas.

In a different research, Kato et al. (2016) examines the causes of major depression from the animal context, and note that genetic mutations are significant risk factors to the condition, as well as Schizophrenia. The study by Kato et al. (2016) offers insights on the need to consider a wide range of issues that are related to depression and other mental conditions. The neural circuits related to these disorders can, therefore, be explained from the gene mutations contexts. These findings, therefore, provide vast knowledge on the development of management strategies, including drugs.

Neural circuits control the emotional behaviors and feeding. Through recent technology on neuroscience, the relationship between the neural circuits in the emotional responses and feeding has been established. According to Sweeney and Yang (2017), the related brain regions demonstrating this relationship are amygdala and hippocampus. These findings provide a template for future studies on emotions and feeding. Some of the specific neural circuits related to the mental health functions of emotions and feeding activities are ARC^AGRP_, which regulates the emotional processes according to the environmental conditions and the dynamic energy demands.

These neural circuits play an important role in fostering a positive energy balance. Feeding behavior, on the other hand, is modulated by the LH^{glutamatergic} and LH^GABAergic, which exert the opposing impact on the individual’s emotional and feeding behavior. The role of the hippocampus is to control feeding through the interactions of the neural circuits with the lateral hypothalamus and lateral septum. The amygdala circuits are responsible for integrating the homeostatic inputs. These findings are asserted by Barbieri et al. (2020), who provide the relationship between various regions of the brain and neural circuits related to feeding and emotional behavior. In particular, parasubthalamic nucleus (PSTN) is involved in the gating feeding behavior.

There is a significant relationship between neural circuits and the physical, mental, and social wellbeing of the individual. Through an opinion article, Zeltser (2018) outlines the neurodevelopmental framework that demonstrates the crosstalk between the neural circuits and the behavioral modalities, such as food intake, which shape the individual’s future and behavioral responses to the surrounding. In this framework, Zeltser (2018) identifies the hypothalamic circuits as essential in maintaining the energy balance and the behavioral response. Benekareddy et al. (2018) confirm these findings and notes that the individual’s behavior and response to the social environment is related to various regions of the brain and specific neural circuits. Specifically, the lateral habenula (LHb) gets direct input from the prefrontal cortex (PFC), which controls the individual’s social preferences. Another key finding was that the LHb inhibition has the ability to prevent the induced social deficits through the PFC activation.

Neural circuits dynamics have also introduced vast ideas on the pharmacological electrical and genetic interventions. As noted by Rajasethupathy, Ferenczi, and Deisseroth (2016), insights on the nervous system activity have allowed the development of pharmacologic interventions on various mental health conditions, including depression, through evoking the brain-wide seizure activities. An example is the extracellular stimulation of the neurons using electrical current, which results in membrane depolarization.

Gao et al. (2018) findings on the impacts of electrical stimulation also reveal the importance of the therapy in postoperative delirium (POD) management. Through an evaluation of 64 aged patients, Gao et al. (2018) demonstrated that the transcutaneous electrical stimulation (TEAS) has a significant positive impact on POD. It may also aid in decreasing the neuro-inflammation by reducing the permeability of the blood-brain barrier (BBB). Such discoveries demonstrate the importance of understanding the specific neural circuits associated with mental health functions. However, further research is required to understand how electrical simulations can be exploited to promote delirium management.

The deep brain simulations (DBS) can also be applied in addressing behavioral deficits. Through a poly I:C schizophrenia rat model to understand the impacts of the nucleus accumbens (Nacc) and medial prefrontal cortex (mPFC) on the behavioral schizophrenia deficits, Bikovsky et al. (2016) demonstrated that stimulation in these two targets had an impact on the metabolic system. In line with previous studies, including Zeltser (2018) and Barbier et al. (2020), Bikovsky et al. (2016) found out that the neural circuits and activities in the brainstem and septal area increased with the simulations, which is important in schizophrenia management.

Murray and Anticevic (2017), through a review of the computational modes and neuroimages, show that the thalamus is implicated in schizophrenia and neuropathology. These findings are sufficient evidence of the changing thalamocortical dynamics, including the oscillatory power and functional connectivity in mental health conditions. However, there are still challenges to associating the neuroimaging biomarkers to the neural circuit mechanisms, which provide the foundation for further research. The neural circuit activities in the thalamic and cortical structures are, therefore, important to consider in schizophrenia.

Understanding the different phenotypes involved in mental health functions is essential in determining the sophisticated relationships between the neural circuits, genes, and behaviors. This was described by Cao et al. (2016) through a literature review of the recent, current, and future advances and directions in the functional connectivity for schizophrenia in various cognitive domains. Cao et al. (2016) note that presently, there are potential connectivity phenotypes that link the neuroimaging measures of the neural circuit interactions. Beyond the default mode network (DMN), which mainly entails the posterior cingulate cortex, patients with schizophrenia demonstrate abnormalities in the PFC connectivity during the resting situation, which maps into three unique circuits, including the PFC-PFC striatum coupling, PFC-limbic, and PFC-striatum coupling. Also, impaired cerebellum connectivity is associated with schizophrenia.

Sigurdsson (2016) provides more insights into the neural circuits in schizophrenia. However, this author notes that the insights are not exhaustive and do not fully reveal the disruption of the neural circuits in the disease, which is vital in understanding the pathophysiology and treatment mechanisms of the disease. Nevertheless, common themes in the neural circuits of the condition include the imbalance between inhibition and excitation, synaptic plasticity deficits, long-range synchrony disruptions, and dopaminergic signaling abnormalities. These findings have contributed significantly to understanding the pathophysiology of the condition.

Chandelier cells (ChCs) play an important role in neural circuits for mental functions and are essential in defining the occurrence of schizophrenia and epilepsy. According to Sigurdsson (2016), ChC connectivity fosters the precise and powerful modulation of the major pyramidal cell populations, which suggests that the ChCs play a critical role in the brain functions. Notably, the dysfunctions in the ChC connectivity have a significant relationship with brain conditions, including schizophrenia and epilepsy. Sigurdsson (2016), suggests future studies to understand the role of the ChCs in the cortical microcircuit, such as whether they are excitatory or inhibitory.

In a different study, Lu et al. (2017) provide a detailed explanation of how ChCs influence brain activities and communication. Lu et al. (2017) demonstrated that the GABAergic ChCs innervate PCs at a high initiation site and selectively modulate the PCs projecting to the basolateral amygdala (_BLAPC). The role of the ChCs is not limited to the directional inhibition. Notably, it also controls the hierarchy in communication between global networks. However, these two studies recommend further research to further understand the role of the ChCs in the brain networks and the application of this knowledge to understanding the pathophysiology of the different mental health conditions and establish the treatment mechanisms.

4.4 Summary and Research Gap

The analysis above demonstrates the role of neurons in the brain, which is to process information. As described by Raman et al. (2019), neural circuits are important in transferring information in the brain and controlling one’s actions. Notably, the circuits are both functional and anatomical entities. The key finding in the analysis above is the role of specific neural circuits in the mental health functions, including behavioral and social activities. Notably, different mental health conditions have specific neural circuits.

Another finding is the importance of various parts of the brain for the neural circuits and the mental health conditions. This knowledge is important in understanding the pathophysiology of the conditions and their treatment. However, there are no studies that specify the neural circuits for different conditions. Further research is, therefore, required to obtain this information, which will be important in translating neuroscience into clinical studies. The second research question, therefore, is;

Research Question 2: What specific neural circuits are associated with mental health functions?

In summary, this section comprises of three subsections, including the neural circuits, mental health functions, and the relationship between the two. From the evaluation, although there are several studies that provide the link between the neural circuits and the mental health functions, there is a need for further studies to specifically identify these circuits, the involved brain parts, and the cells. This is the foundation of the second research question. The next section entails an evaluation of how genetic research on neurobiology and mental health can be used in the diagnosis and treatment of mental disorders.

5 The Importance of Genetic Research on Neurobiology and Mental Health in the Diagnosis and Treatment of Mental Disorders

This section entails an evaluation of how studies on neurobiology and mental health can be implemented in the diagnosis and treatment of mental conditions.  From the previous two sections, it is apparent that knowledge of neuroscience is important in understanding the pathophysiology of mental disorders. This knowledge is also essential in developing a treatment for the unique symptoms of mental health. In this section, the existing literature on this subject is expounded, including the diagnosis and management of these illnesses. This section contains three sections, including neurobiology, diagnosis and management of the mental illnesses, and the relationship between these two settings.

5.1 Genetic Research on Neurobiology

Neurobiology is an increasing realm in scientific studies. Among the core contexts in the research is the importance of neurons and cells, which are responsible for relaying, communicating, and integrating information. Neurobiology further aids in understanding the structure of the brain. According to Goriounova and Mansvelder (2019), some of the important areas of study are the volume changes in the gray matter throughout one’s childhood to adulthood and the rearrangement of the synapses and dendrites among the neurons. The changes in the gray matter further allow one to understand how age, experience, and hormonal differences are related. Genetic research, on the other hand, is concerned with the DNA and how the environmental factors and genes are related to diseases and illnesses. According to WHO, the importance of genetic research is ever-transforming and indispensable, especially in the diagnosis and management of disorders, non-communicable diseases, and infectious conditions (Haque et al., 2016). Among the key areas of genetic research are gene therapy, genetic testing, genetic databanks, and reproductive genomics.

Genetic research is important in understanding neurodevelopment and the relationship with the individual’s growth and mental health conditions. According to Wray et al. (2018), through a meta-analysis of a genome-wide association of 135,458 and 344,901 cases and controls respectively, the genetic results are related to the clinical features of major depressive disorder (MDD). The cases, however, exhibit different brain regions and anatomic differences. During the specific phases of brain development, several biological and gene pathways are active (Lam et al., 2017; Okbay et al., 2016). The majority of these genes are implicated in the developmental delays and intellectual disabilities. In particular, there are genes characterized by known mutations and major impacts on mental diseases.

Okbay et al. (2016), for instance, shows the transcriptome and SNP data that demonstrate the above-baseline expression throughout the individual’s life and high levels of expression in the brain during prenatal development. Genetic research on neurobiology also aids in understanding the behavioral and social changes in an individual. In addition, knowledge aid in establishing educational attainment. Okbay et al. (2016) introduce the importance of phenotypes in understanding neuropsychiatric conditions and cognition.

This section examines the meaning of genetic research on neurobiology and its importance. According to the findings, genetic research, which is the study of human DNA, plays an important role in comprehending the environmental factors and genes that influence the occurrence of diseases. Neurobiology, on the other hand, assists in understanding the structure of the brain and cells, which provide sufficient insights into the occurrence of diseases, their diagnosis, and management. The next section examines the diagnosis and treatment of mental conditions.

5.2 Diagnosis and Treatment of Mental Illnesses

This section evaluates the evaluation and management strategies of the mental conditions. Notably, there are several mental disorders, including autism, depression, dementia, stress, and anxiety. Their evaluation and management are unique to the condition’s signs and symptoms. This section, therefore, examines how the conditions can be evaluated and their management, including the pharmacological and non-pharmacological approaches.

The diagnosis of mental health conditions is based on the identification of the specific signs and symptoms that the individual exhibits. The Diagnostic and Statistical Manual of Mental Disorders (DSM) is an important handbook that is used by psychiatrists and clinicians in the US to diagnose the psychiatric conditions (American Psychiatric Association 2020). Despite the development of these approaches by the DSM, there are several challenges that affect the ability to diagnose an individual and develop an effective management strategy. According to Krystal and State (2014), the primary challenge is the rudimentary comprehension of the neural mechanisms of emotion, behavior, and cognition. In addition, there is a limited understanding of the pathophysiological system as a medical discipline. Further, the mental health realm still lacks the objective measures of the biomarkers and psychopathology to delineate the diseases and the normal state of the individual.

Another significant setback in the diagnosis of mental health conditions is the influence of the cultural and social norms alongside the stigma among the patients. Rayan and Fawaz (2018) use data from 203 individuals from Lebanese university to evaluate the stigma, attitudes, misconceptions, and cultural issues associated with mental illnesses. From the findings, stigma and cultural issues are significant setbacks to assessing mental health disorders. In addition, there are several misconceptions regarding these diseases. The roles of mental health nurses are to address the mental conceptions and avert the stigma associated with mental health conditions. This will allow more patients to present to healthcare facilities for evaluation and treatment plans.

Lopez et al. (2018) share similar findings regarding the impact of stigma in the assessment and management of the conditions. Through baseline data from 319 Hispanic patients, Lopez et al. (2018) found out that primary care settings are the common gateway to the identification of undiagnosed mental health disorders among Hispanic women with other conditions. This study introduces another key aspect that is associated with a limited diagnosis of mental health disorders. This entails the mental health literacy of these individuals. It is, therefore, essential to establish ways through which these setbacks can be addressed, such as enhancing the patients’ awareness.

Mental health conditions can be managed through various approaches, including pharmacological and non-pharmacological. However, the management strategy is informed by the signs and symptoms and the specific situation. Drug therapy entails the use of psychoactive drugs, which are commonly used by psychiatrists and other healthcare practitioners (Bhui, 2017). The widely used antidepressant classes are selective serotonin reuptake inhibitors (SSRIs), including sertraline, fluoxetine, and citalopram. Other classes include serotonin-norepinephrine reuptake inhibitors (SNRIs), including duloxetine, venlafaxine, and desvenlafaxine and norepinephrine-dopamine reuptake inhibitors, such as bupropion (Stockmann et al., 2018). The tricyclic antidepressants, including nortriptyline and amitriptyline, are rarely used currently due to the side effects. However, the drugs can be used when the patient has chronic pain interfering with work and other activities. These drugs are used to relieve specific types of pains.

The drugs are specific to the conditions. Antipsychotic drugs, for instance, such as thiothixene, chlorpromazine, and haloperidol, are effective in managing psychotic conditions, including behavioral problems and schizophrenia (Saha et al., 2016). Presently, other psychotic drugs have been developed, which are referred to as second-generation antipsychotics for initial treatment of the conditions. Newer drugs include quetiapine, cariprazine, olanzapine, and ziprasidone. According to Shah et al. (2018), clozapine is used more for individuals that do not respond to antipsychotic medications. To treat anxiety conditions, such as phobias and panic disorders, SSRIs and antianxiety medications, including diazepam, clonazepam, and lorazepam, are widely used as well as other antidepressants (Rincon-Cortes et al., 2018). Bipolar disorders and moods can be treated using stabilizers, such as valproate, topiramate, carbamazepine, and lithium.

Brain therapies are also effective in treating mental health disorders. The electroconvulsive therapy (ECT), for instance, involves the use of electrodes, which are placed on the individual’s head when the person is under anesthesia (Oltedal et al., 2018). The electrical shocks are then delivered to the brain, which induces the seizure in brief. This treatment approach is common for individuals with severe depression. However, there are side effects to the electrotherapy.

In a different study, Griffiths and O’Neill-Kerr (2019) evaluated the people’s perspectives regarding the ECT and noted that the majority of individuals are concerned with memory loss as the risks and side effects. Weiner and Reti (2017) offer a different opinion and updates regarding this intervention and note that the memory loss and stigmatization that surrounds this treatment approach is not a concern anymore. In the current mental health management, the ECT approach has been enhanced and is safer. Further, it rarely results in complications. This has been achieved through the use of muscle relaxants and anesthetics.

Psychotherapy is also majorly used in addressing mental health. According to Stillman et al. (2019), psychotherapy is commonly used in addressing mental health conditions. This is achieved by addressing individual behavior and thoughts. Through creating an accepting and empathetic atmosphere, the therapist assists the individual to establish the causes of the mental health condition and the possible alternatives. These insights aid in changing the behavior and attitude of the individual thus the individual lives a satisfying and fuller life.

For psychotherapy to achieve its function, there should be collaborative care between the psychotherapist and the patient. Dumesnil, Apostolidis, and Verger (2018), through a semi-structured interview of 32 general practitioners in Southeastern in France, established that enhancing the collaboration between the GPs and the patients is essential in implementing psychotherapy. This is vital in improving the individual’s recovery from mental health conditions.

This section examined the diagnosis and treatment of mental health conditions. From the evaluation, there are several diagnostic approaches for the mental health conditions, according to the DSM, which are based on the signs and symptoms of the condition. Also, treatment approaches are specific to mental health disorders. A wide range of management strategies for mental health disorders exists including the use of drugs, ECT, and psychotherapy. However, several approaches should be considered in enhancing mental health management. For instance, the collaboration between the psychiatrist and the patient is imperative to promote mental health treatment. The following section evaluates the importance of genetic research on neurobiology in the evaluation and treatment of mental disorders.

5.3 Importance of Genetic Research on Neurobiology in the Diagnosis and Treatment of Mental Disorders

This subsection examines the importance of genetic research on neurobiology in the diagnosis and treatment of mental conditions. In the previous section, the meaning of genetic research has been provided as well as the diagnosis and treatment of the mental conditions. This section, therefore, links these two areas according to the present literature.

Studies on neurobiology are essential in promoting knowledge of psychiatry. According to Schildkrout, Benjamin, and Lauterbach (2016), the role of neuroscience knowledge is to facilitate the expanded strategies to the diagnosis and development of treatment approaches to mental health patients. The increasing research regarding the brain has the potential of enhancing the neuropsychiatric skills that can be applied in enhancing the management of the mental conditions. The broad research, therefore, aid in understanding the brain and the entire body, which is important in determining the specific treatment for the disorder.

In another study by Kong, Dunn, and Parker (2017), the importance of psychiatric research is not a straight forward aspect. This is based on the increasing ethical challenges associated with genomics research. This study confirms and contradicts the role of genetic research in the diagnosis and management of mental conditions. Similar to Schildkrout et al. (2016), psychiatric research is important in enhancing psychiatric practice. The impacts are further categorized into three contexts of political, social, and economics of the patient. Through research, healthcare providers have enhanced their knowledge of the factors leading to mental health risks and challenges. However, there is a need for further studies to understand the ethics associated with mental health conditions. In addition, there is a need to understand the importance of clinician-patient relationships and priorities in funding.

Genetic research from both humans and animals has contributed to understanding the diagnosis and treatment of addiction. In a literature analysis by Volkow and Boyle (2018), genetic research has aided in understanding the neuro-circuitry delineation that occurs due to addiction. These findings have been important in understanding the circuits mediating the motivation, rewards, executive control, and processing of emotions. In addition, the core challenge is the inability of the individual to distinguish the short-term and long-term targets, allowing the individual to prioritize the behavior. Further, genetic research allows for the healthcare providers to understand brain development and the importance of the environment and genes in the brain activities and function. This information aid in developing effective tools for the diagnosis, prevention, and treatment of the alcohol and substance abuse.

Uhl, Koob, and Cable (2019) support the role of neurobiology in understanding the diagnosis and prevention of the addiction. The advances in neuroscience and research, in addiction, have aided in the successful description of the neurobiological alterations that occur when there are transitions from recreational alcohol and substance use to addiction or disorder. Neurobiology has therefore provided sufficient information on the key consequences and drivers of substance abuse for different populations, including the vulnerable ones. Uhl et al. (2019) findings support those by Kong et al. (2017) on the importance of neurobiology in policy development. The implications of the findings transcend beyond the development of treatment approaches to policymaking. This is based on the knowledge regarding the effect of addiction in one’s brain.

Neuroclinical evaluations are central in conceptualizing the nosology of addiction disorders and the occurrence of psychiatric conditions. This is described by Kwako et al. (2016), who note that there are three main domains related to the addiction cycles. These include incentive salience, executive function, and negative emotionality. Through the genetic, clinical, epidemiologic, and treatment studies, these domains can be measured for more insights on the temporal and cross-population variation in addictive disorders, environmental influences, and gene identification. Knowledge is also important in improving the prevention and treatment of the condition.

Similar to addictive disorders, research on neurobiology is essential in understanding the biological, social, and psychological elements associated with post-traumatic stress disorder (PTSD). This is described by Ross et al. (2017), who note that traumatic events can result in various behaviors related to PTSD. Through genetic research on neurobiology, healthcare providers can have a better understanding of the circuit dysregulation framework, including between the limbic and prefrontal cortex structures. In PTSD, Ross et al. (2017) note that genetic factors play a vital role in understanding the factors associated with the condition. This knowledge is also essential in transforming future care of the mental health condition, including PTSD.

Genetic research on neurobiology has helped in understanding the pathophysiology of mental health disorders, such as stress and anxiety. According to Goddard (2017), through literature analysis, it was established that various studies have been done to advance the diagnosis and treatment of the condition. However, the pathophysiology is elucidated and the current neurobiological studies have aided in understanding the risk factors associated with the condition. These include genetic vulnerability, temperament, and chronic stress. The National Institute of Mental Health Research Domain Criteria has, therefore, enhanced the understanding of the pathophysiology of the mental conditions, which is essential in the decision making regarding the diagnosis and treatment approaches.

In another study by Cosgrove, Kelsoe, and Suppes (2016), it was established that genetic research on neurobiology has helped in understanding the pathophysiology of the Bipolar disorder, which is a heterogeneous condition. Cosgrove et al. (2016) used mice to understand the impacts of psychostimulants, including amphetamine on the motor activity of the individual. Through the findings of a black Swiss mouse, there are several insights, including the importance of the candidate biological systems, such as CLOCK and GRIK2 genes. In addition, the kinase pathway, which is extracellular signal-related, is involved in the illness pathophysiology. Similar to Goddard (2017), Cosgrave et al. (2016) acknowledge the importance of these findings to the National Institute of Mental Health Research Domain Criteria initiative is to assist in the identification of the build blocks of sophisticated conditions, including the bipolar. This is aimed at unveiling the neurobiology of every disorder.

Maki-Marttunen et al. (2019) contribute to the importance of genetic research in neurobiology and mental health conditions and note that the recent advances in neuroscience and genetics have significantly aided in understanding the brain processes and the disease mechanisms. This is important in linking the clinical symptoms, one behavior, and genetic findings. Similar to Cosgrave et al. (2016), Maki-Marttunen (2019) notes that the research on genetics and neurobiology is central in discovering the disease pathology. Through the neuroimaging, biophysical psychiatry, and modeling the condition’s networks, the genetic studies on neurobiology has enhanced the global knowledge on the functional properties, circuits, and neuron activity. These findings are essential in deriving the interpretable biomarkers and further advancements of the field.

Zhao and Castellanos (2016) evaluate the factors that have influenced the understanding of the brain and genetics in mental health conditions, including autism, attention-deficit, and schizophrenia. Among the core elements is the discovery of science in Big Data, which has enabled researchers to transition from descriptive psychiatric science to numerical, which is important in advancing the understanding of psychiatric conditions. This study confirms the importance of genetic research and adds the importance of Big Data technologies, which has promise in understanding the psychiatric conditions. On the other hand, healthcare providers and researchers should demonstrate competence in the application of these technologies. This will aid in their application for further research.

Mental health conditions are diverse and are characterized by varying signs and symptoms. Genetic research on neurobiology, therefore, aid in understanding the gaps and opportunities in the molecules, cells, genes, and physiology, which contribute to the treatment and prevention approaches. According to Cha et al. (2016), through an evaluation of how research impacts the knowledge and understanding of suicidal ideation and behaviors among young people, it was found out that the studies have enhanced the etiological understanding of the person’s malleable mechanism and etiology. These findings are the foundations of developing psychotherapeutic prevention and treatment strategies to the mental conditions, including suicide and changes in behavior and moods. These approaches are technological-based. However, Cha et al. (2016) note that there is a need for further studies to continue advancing the operationalization and conceptualization of suicide thoughts and behaviors.

Although genetic research has helped in understanding the genes, cells, and circuits involved in mental health conditions, the way through which the genetic knowledge can be applied to inform patient management remains elucidated. This was discussed by Stickel et al. (2017) to evaluate alcohol dependence and liver disease. The study revealed three major genes in alcohol dependence, including TM6SF2, PNPLA3, and MBOATJ. However, the functional interplay between the genes remains under-evaluated. Further research is, therefore, recommended to understand the pathophysiology of the conditions, which will also inform the patient management.

Genetic research on neurobiology has provided valuable information on the new treatments in various mental health conditions, which enhances the patient’s wellbeing. These studies have helped in establishing the opportunities and challenges related to the short and long-term management of the symptoms, which is important in identifying further treatment approaches. As noted by Trenkwalder et al. (2018), concerning the restless legs syndrome, which is also referred to as Willis-Ekbom disease, a neurological condition that is affected by genetic interactions and environmental complexities, genetic data has aided in getting more knowledge on the pathophysiology of the disease. The clinical studies on iron preparations, pregabalin, and gabapentin enacarbil have enhanced the knowledge on the treatment options and the long-term management of these symptoms. However, further studies are required to understand the effectiveness of these management approaches and the pathophysiology of the conditions.

In another study by Cleveland et al. (2016), it was shown that the impacts of treatment and management options vary according to the person’s genetics. Through genetically informed assessment of the prevention approaches, it is possible to understand the causes of the social challenges and provide new insights on the prevention and the outcomes. This knowledge is important in providing a detailed explanation of the merits provided by the preventive approaches and genetically informed studies. However, further research is required in genetics and neurobiology for a better understanding of the management strategies.

5.4 Summary and Gap

This section entails an overview of the current literature on the impacts of genetic studies on neurobiology and mental health in diagnosing and treating mental disorders. From the evaluation, neurobiology is an increasing area of scientific research, which aid in understanding the impacts of cells and neurons in conveying information. Genetic research on neurobiology has provided insights into the DNA and the diagnosis and management of the mental health conditions (Goriounova & Mansvelder, 2019; Haque et al., 2016). This knowledge has further helped in establishing the biological and genetic issues related to the mental health conditions, including pathophysiology, prevention, and management of the disorders.

Genetic research on neurobiology has provided sufficient insights on the knowledge about mental health, from the importance of neurons and cells to the neural circuits related to specific mental conditions. These include schizophrenia, depression, dementia, alcohol addiction, and stress (Schildkrout et al., 2016; Kong et al., 2017; Volkow & Boyle 2018). However, there is a need for further research on how genetic research on neurobiology can be applied in the diagnosis, prevention, and treatment of the mental disorders, which is the foundation of the third research question.

Research Question 3: How can genetic research on neurobiology and mental health be used to diagnose and treat mental disorders?

6 Summary

This literature review entails an evaluation of the existing information regarding the relationship between genetics and mental health conditions. The literature evaluation is based on six sections. In the introduction section, it entails an overview of the chapter. The literature review uses materials that are less than five years old, including peer-reviewed, clinical guidelines, and credible websites, such as those belonging to the world health organization. The five years’ limitation was essential in ensuring that the literature was current. The time was part of the inclusion and exclusion criteria. The materials were obtained from various databases, including MEDLINE, Cochrane, and CINAHL.

The research is based on three main objectives, which inform some of the sections. In the first objective, it entails the evaluation of the genetic alterations and how they are associated with mental conditions. The disorders, in this regard, include depression, autism, stress, anxiety, PTSD, and dementia. In the second research objective, it entails the particular neural circuits related to the mental health functions. Under this objective, the role of the brain, neurons, and neural circuits are examined with regards to the individual’s mental health wellbeing. In the third objective, it involves how the genetic research on neurobiology and mental health can be applied in the diagnosis and treatment of the mental health conditions.

A key part of the literature review is the theoretical framework that guides the study. This literature is centered on the Biomedical model. This model has been in existence for centuries, and it is commonly used in healthcare. The model’s origins include a distinction of the body and the brain and the knowledge of atoms in matter (Horwitz et al., 2017; Talware, 2020). The Biomedical model entails the relationship between health and illness. In the mental health context, the mental conditions are brain illnesses, and the management is based on sufficient knowledge regarding the pathophysiology of the disorders.

There is diverse literature on the relationship between genetic alterations and mental health disorders. In autism, for instance, some of the genetic alterations knowledge entails FMRP, neuroligins, and MeCP2 (Hakonarson et al., 2017). The literature analysis further shows that there are inherited and rare coding, and at least 100 loci harboring the common risk variants (Gratten, 2016; Nalls et al., 2019). Notably, the genetic alterations are unique to the mental health conditions, including major depressive disorders, schizophrenia, and dementia. However, there is a need for further research to establish the actual alterations associated with the conditions.

The knowledge of neural circuits and their association with mental health functions has aided in understanding the pathophysiology of the conditions, which informs the diagnosis and management of the disorders. Similar to the research on genetic alterations, there are specific neural circuits related to the different mental conditions. Autism, for instance, is explained from the atypical functional connectivity (FC) circuits, which are associated with the social and behavioral aspects (Chen et al., 2018). Another important finding is the importance of the activation and connectivity of the major neural circuits, which explains the occurrence and complexities of the emotional, cognitive, and social disorders. Further research is, however, required for more understanding on the specific neural circuits related to the different mental health conditions.

The knowledge from neurobiology and genetic studies has played an essential role in understanding the pathophysiology of mental health conditions. In addition, this research has been insightful in the diagnosis and treatment of the different mental conditions (Schildkrout et al., 2016; Kong et al., 2017; Volkow and Boyle, 2018). These insights have been essential in understanding the specific medications, psychotherapy, and other approaches that can be used in managing the mental health conditions. However, there are challenges, especially on the use of technology in neuroscience and the translation of the knowledge into the actual clinical management of the conditions, which is also a key foundation of this research.