Description
Mental disorders encompass a range of clinical phenotypes characterized by a clinically significant disturbance in an individual's cognition, emotion regulation, or behavior that reflects a dysfunction in the psychological, biological, or developmental processes underlying mental functioning. Mental disorders are usually associated with significant distress in social, occupational, or other important activities (APA, 2013).

This policy focuses on the genetic testing for the diagnosis of and/or susceptibility to mental health disorders. For pharmacogenetic testing for patients on therapies for mental health disorders, please refer to policy AHS-M2021 Pharmacogenetic Testing.

Background 
Mental health disorders cover a wide range of clinical phenotypes and are generally classified by symptomatology in systems such as the classification outlined in the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). In addition to counseling and other forms of behavioral treatment, treatment commonly involves 1 or more psychotropic medications aimed at alleviating symptoms of the disorder. Although there are a wide variety of effective medications, treatment of mental health disorders is characterized by relatively high rates of inadequate response. This often necessitates numerous trials of individual agents and combinations of medications to achieve optimal response.

Knowledge of the physiologic and genetic underpinnings of mental health disorders is advancing rapidly and may substantially alter the way in which these disorders are classified and treated. Genetic testing could potentially be used in several ways, including stratifying patients’ risks of developing a particular disorder, aiding diagnosis, targeting medication therapy, and optimally dosing medication.

Genes Relevant to Mental Health Disorders
Mental health disorders encompass a wide range of conditions: the DSM-5 includes more than 300 disorders. However, currently available genetic testing for mental health disorders is primarily related to 2 clinical situations:

1. Risk-stratifying patients for one of several mental health conditions, including schizophrenia and related psychotic disorders, bipolar and related disorders, depressive disorders, obsessive-compulsive and related disorders, and substance-related and addictive disorders.
2. Predicting patients’ response to, dose requirement for, or adverse effects from one of several medications (or classes of medications) used to treat mental health conditions, including: typical and atypical antipsychotic agents, selective serotonin reuptake inhibitors (SSRIs) and serotonin norepinephrine reuptake inhibitors, and medications used to treat addiction, such as disulfiram.

Panels of genetic tests have been developed and proposed for use in the latter clinical situation. Genes implicated in prediction of mental health disorders or their response to treatment and included in currently available panels are outlined in the following sections.

Serotonin Transporter
The serotonin transporter gene (SLC6A4) is responsible for coding the protein that clears serotonin metabolites (5-HT) from the synaptic spaces in the central nervous system (CNS). This protein is the principal target for many of the SSRIs. By inhibiting the activity of the SLC6A4 protein, the concentration of 5-HT in the synaptic spaces is increased. A common polymorphism in this gene consists of insertion or deletion of 44 base pairs in the serotonin-transporter-linked polymorphic region. These polymorphisms have been studied in relation to a variety of psychiatric and nonpsychiatric conditions, including anxiety, obsessive compulsive disorder, and response to SSRIs.

Serotonin Receptor
The serotonin receptor gene (5HT2C) codes for 1 of at least 6 subtypes of the serotonin receptor that is involved in the release of dopamine and norepinephrine. These receptors play a role in controlling mood, motor function, appetite, and endocrine secretion. Alterations in functional status have been associated with affective disorders such as anxiety and depression. Certain antidepressants (e.g., mirtazapine, nefazodone) are direct antagonists of this receptor. There is also interest in developing agonists of the 5HT2C receptor as treatment for obesity and schizophrenia, but such medications are not commercially available at present.

The serotonin receptor gene (5HT2A) codes for another subtype of the serotonin receptor. Variations in the 5HT2A gene have been associated with susceptibility to schizophrenia and obsessive-compulsive disorder and response to certain antidepressants.

Sulfotransferase Family 4A, Member 1
The sulfotransferase family 4A, member 1, gene (SULT4A1) encodes a protein that is involved in the metabolism of monoamines, particularly dopamine and norepinephrine.

Dopamine Receptors
The DRD2 gene codes for a subtype of the dopamine receptor, called the D2 subtype. The activity of this receptor is modulated by G proteins, which inhibit adenyl cyclase. These receptors are involved in a variety of physiologic functions related to motor and endocrine processes. The D2 receptor is the target of certain antipsychotic drugs. Mutations in this gene have been associated with schizophrenia and myoclonic dystonia. Polymorphisms of the DRD2 gene have been associated with addictive behaviors (e.g., smoking, alcoholism).

The DRD1 gene encodes another G protein — coupled receptor that interacts with dopamine to mediate some behavioral responses and to modulate D2 receptor — mediated events. Polymorphisms of the DRD1 gene have been associated with nicotine dependence and schizophrenia.

The DRD4 gene encodes a dopamine receptor with a similar structure; DRD4 polymorphisms have been associated with risk-taking behavior and attention-deficit/hyperactivity disorder.

Dopamine Transporter
Similar to the SCL6A4 gene, the dopamine transporter gene (DAT1 or SLC6A3) encodes a transporter that mediates the active reuptake of dopamine from the synaptic spaces in the CNS. Polymorphisms in this gene are associated with Parkinson disease, Tourette syndrome, and addictive behaviors.

Dopamine β-Hydroxylase
The dopamine β-hydroxylase (DBG) gene encodes a protein that catalyzes the hydroxylase of dopamine to norepinephrine. It is primarily located in the adrenal medulla and in postganglionic sympathetic neurons. Variation in the DBH gene has been investigated as a modulator of psychotic symptoms in psychiatric disorders and in tobacco addiction.

Gated Calcium Channel
The gated calcium channel gene (CACNA1C) is responsible for coding of a protein that controls activation of voltage-sensitive calcium channels. Receptors for this protein are found widely throughout the body, including skeletal muscle, cardiac muscle, and in neurons in the CNS. In the brain, different modes of calcium entry into neurons determine which signaling pathways are activated, thus modulating excitatory cellular mechanisms. Associations of polymorphisms of this gene have been most frequently studied in relation to cardiac disorders. Specific polymorphisms have been associated with Brugada syndrome and a subtype of long QT syndrome (Timothy syndrome).

Ankyrin 3
Ankyrins are proteins that are components of the cell membrane and interconnect with the spectrin-based cell membrane skeleton. The ANK3 gene codes for the protein Ankyrin G, which has a role in regulating sodium channels in neurons. Alterations of this gene have been associated with cardiac arrhythmias (e.g., Brugada syndrome). Polymorphisms of this gene have also been associated with bipolar disorder, cyclothymic depression, and schizophrenia.

Catechol O-Methyltransferase  
The catechol O-methyltransferase gene (COMT) codes for the COMT enzyme that is responsible for the metabolism of the catecholamine neurotransmitters, dopamine, epinephrine, and norepinephrine. COMT inhibitors (e.g., entacapone) are currently used in the treatment of Parkinson disease. A polymorphism of the COMT gene, the Val158Met polymorphism, has been associated with alterations in emotional processing and executive function and has also been implicated in increasing susceptibility to schizophrenia.

Methylenetetrahydrofolate Reductase
The methylenetetrahydrofolate reductase gene (MTHFR) is a widely studied gene that codes for the protein that converts folic acid to methylfolate. Methylfolate is a precursor for the synthesis of norepinephrine, dopamine, and serotonin. It is a key step in the metabolism of homocysteine to methionine, and deficiency of MTHFR protein can cause hyperhomocysteinemia and homocystinuria. The MTHFR protein also plays a major role in epigenetics, through methylation of somatic genes. A number of polymorphisms have been identified that result in altered activity of the MTHFR enzyme. These polymorphisms have been associated with a wide variety of clinical disorders, including vascular disease, neural tube defects, dementia, colon cancer, and leukemia.   

γ-Aminobutyric Acid A Receptor
The γ-aminobutyric acid A (GABA) receptor gene encodes a ligand-gated chloride channel composed of 5 subunits that responds to GABA, a major inhibitory neurotransmitter. Mutations in the GABA receptor have been associated with several epilepsy syndromes.

μ- and κ-Opioid Receptors
OPRM1 encodes the μ-opioid receptor, which is a G protein coupled receptor that is the primary site of action for commonly used opioids, including morphine, heroin, fentanyl, and methadone. Polymorphisms in the OPRM1 gene have been associated with differences in dose requirements for opioids. OPRK1 encodes the κ-opioid receptor, which binds the natural ligand dynorphin and a number of synthetic ligands.

Cytochrome P450 Genes
CYP2D6, CYP2C19, CYP3A4, CYP1A2, CYP2C9, and CYP2B6 code for hepatic enzymes that are members of the cytochrome P450 family and are responsible for the metabolism of a wide variety of medications, including many psychotropic agents. For each of these genes, polymorphisms exist that affect the rate of enzyme activity and, therefore, the rapidity of elimination of drugs and their metabolites. Based on the presence or absence of polymorphisms, patients can be classified as rapid metabolizers, intermediate metabolizers, and poor metabolizers.

P-Glycoprotein Gene
TheABCB1 gene, also known as the MDR1 gene, encodes P-glycoprotein, which is involved in the transport of most antidepressants across the blood-brain barrier. ABCB1 polymorphisms have been associated with differential response to antidepressants that are substrates of P-glycoprotein, but not to antidepressants that are not P-glycoprotein substrates.  

UDP-Glucuronosyltransferase Gene
The UDP-glucuronosyltransferase gene, UGT1A4, encodes an enzyme of the glucuronidation pathway that transforms small lipophilic molecules into water-soluble molecules. Polymorphisms in the UGT1A4 gene have been associated with variation in drug metabolism, including some drugs used for mental health disorders.  

Commercially Available Genetic Tests
Several test labs market either panels of tests or individual tests relevant for mental health disorders. The specific tests included in each panel are summarized in Table 1.

The Genecept™Assay (Genomind, Chalfont, PA) is a genetic panel test that includes genetic mutations and/or polymorphisms associated with psychiatric disorders and/or response to psychotropic medication. The test consists of a group of individual genes, and the results are reported separately for each gene. There is no summary score derived from this test. The test is intended as a decision aid for treatment interventions, particularly in the choice and dosing of medications. However, guidance on specific actions that should be taken following specific test results is vague. Interpretation of the results and any management changes as a result of the test are left to the judgment of the treating clinician.

The STA²R (SureGene Test for Antipsychotic and Antidepressant Response; SureGene, Louisville, KY) is a genetic panel that provides information about medication response, adverse event likelihood, and drug metabolism based on the results of the genetic panel. According to the manufacturer’s website, the test is recommended for initial medication selection, for patients who have poor efficacy, tolerability, or satisfaction with existing medications, and in cases of severe treatment failure.¹  

GeneSight® Psychotropic (Assurex Health, Mason, OH) is a genetic panel that provides information about genes that may affect a patient’s response to antidepressant and antipsychotic pharmacotherapy. According to the manufacturer’s website, following testing, the treating provider receives a report with the most common medications for the patient’s diagnosed condition categorized by cautionary level based on the results of the genetic panel, along with a report of the patient’s genetic variants.² Details are not provided about the algorithm the manufacturer uses generate risk levels.  

The Proove Opioid Risk panel (Proove Biosciences, Irvine, CA) is a panel to evaluate genes involved in the development of substance abuse or dependence and in response to medical therapy for substance abuse or dependence.

Pathway Genomics (San Diego, CA) offers the Mental Health DNA Insight™ panel, which is a single-nucleotide polymorphism-based array test that evaluates a number of genes associated with the metabolism and efficacy of psychiatric medications.

AltheaDx (San Diego, CA) offers a number of IDgenetix-branded tests, which include several panels focusing on polymorphisms that affect medication pharmacokinetics for a variety of disorders, including psychiatric disorders. Specific mutations included in the panel were not easily identified from the manufacturer’s website. 

Table 1: Genes Included in Genetic Panels for Mental Health Disorders

Gene	Polymorphisms Included in Commercially Available Test Panels
	Genecept Assay	STA2R (SureGene)	GeneSightRx Psychotropic	Proove Opioid Risk	Mental Health DNA Insight
SULT4A1		X
SLC6A4 (serotonin transporter)	X	X	X	X	X
5HT2C (serotonin receptor)	X		X
5HT2A (serotonin receptor)				X
DRD1 (dopamine receptor)				X
DRD2 (dopamine receptor)	X			X	X
DRD4 (dopamine receptor)				X
DAT1 (dopamine transporter)				X
DBH (dopamine β-hydroxylase)				X
CACNA1C (gated calcium channel )	X
Ankyrin 3	X
COMT (catechol O-methyltransferase)	X			X
MTHFR	X			X
GABA				X
OPRK1 (ĸ-opioid receptor)				X
OPRM1 (µ-opioid receptor)	X			X
CYP450 genes
CYP2D6	X	X	X		X
CYP2C19	X	X	X		X
CYP3A4	X		X		X
CYP1A2	X		X		X
CYP2C9	X		X		X
P2B6	X		X		X
UGT1A4					X
ABCB1
MC4R	X
ADRA2A	X
BDNF	X
GRIK1	X

In addition, several labs offer genetic testing for individual genes, including MTFHR (GeneSight Rx and other laboratories), CYP450 genes, and SULT4A1.

Regulatory Status
The Genecept Assay, STA²R test, the GeneSight Psychotropic panel, the Proove Opioid Risk panel, and the Mental Health DNA Insight panel are laboratory-developed tests that are not subject to U.S. Food and Drug Administration approval. Clinical laboratories may develop and validate tests in-house (“homebrew”) and market them as a laboratory service; such tests must meet the general regulatory standards of the Clinical Laboratory Improvement Act.

Related Policies
20438 Cytochrome p450 Genotyping
20482 Genetic Testing for Inherited Thrombophilia

Policy

1. Genetic testing for mutations associated with mental health disorders and/or genetic testing panels for mental health disorders  is investigational/unproven and therefore considered NOT MEDICALLY NECESSARY in all situations, including, but not limited to, the following:
   1. To confirm a diagnosis of a mental health disorder in an affected individual
   2. To predict future risk of a mental health disorder in an asymptomatic individual

Benefit Application
BlueCard/National Account Issues
No applicable information

Table of Terminology 

Term	Definition
5HT2C	5-hydroxytryptamine 2C
AACAP	American Academy of Child and Adolescent Psychiatry
AAP	American Academy of Pediatrics
ACSM5	Acyl-coenzyme A synthetase
ADHD	Attention Deficit Hyperactivity Disorder
ANK3	Ankyrin-3
APA	American Psychiatric Association
APOB	Apolipoprotein B
ASD	Autism spectrum disorder
ATXN8OS	Ataxin 8 opposite strand
BD	Bipolar disorder
BDNF	Brain-derived neurotrophic factor
CACNA1C	Calcium voltage-gated channel subunit alpha1 C
CCDC24	Coiled-coil domain containing 24
CELF4	CUGBP Elav-like family member 4
CHD1L	Chromodomain-helicase-DNA-binding protein 1-like
CIR	Circular ribonucleic acid
CLIA ’88	Clinical Laboratory Improvement Amendments of 1988
CMA	Cellular micronutrient assay
CMS	Centers for Medicare & Medicaid Services
CNV	Copy number variation
CpG	5'—C—phosphate—G—3'
CQI	Committee on Quality Issues
CRHR1	Corticotropin-releasing hormone type 1
CUGBP	CUG triplet repeat ribonucleic acid binding protein 1
DMPK	DM1 protein kinase
DNA	Deoxyribonucleic acid
DRD1	Dopamine receptor 1
DRD2	Dopamine receptor 2
DRD4	Dopamine receptor 4
DSM	Diagnostic and Statistical Manual of Mental Disorders
DSM-IV	Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition
EPA	European Psychiatric Association
ESR1	Estrogen receptor 1
FDA	Food and Drug Administration
GABA	Gamma-aminobutyric acid
GLAD-PC	Guidelines for Adolescent Depression in Primary Care
GRIK3	Glutamate receptor ionotropic kainate 3
GWAS	Genome-wide association study
HSPA1A	Heat shock 70 kDa protein 1
HSPA1L	Heat shock 70 kDa protein 1
ISPG	International Society of Psychiatric Genetics
ITIH3	Inter-alpha-trypsin inhibitor heavy chain H3
ITIH4	Inter-alpha-trypsin inhibitor heavy chain H4
LCD	Local coverage determinations
LDT	Laboratory-developed tests
LNCRNAS	Long non-coding ribonucleic acid regions
LOH	Loss of heterozygosity
LPAR5	Lysophosphatidic acid receptor 5
MAD1L1	Human Accelerated Region 3
MDD	Major depressive disorder
MHC	Major histocompatibility complex
mRNA	Messenger ribonucleic acid
MVP	Major vault protein
NDAL	Neurodevelopmental Disorders Across the Lifespan
NSDUH	National Survey on Drug Use and Health
OCD	Obsessive compulsive disorder
OPRM1	µ-opioid receptor gene
PGX	Pharmacogenetic
SAMHSA	Substance Abuse and Mental Health Services Administration
SATB1	Special AT-rich binding protein 1
SCZ	Schizophrenia
SLC6A4	Serotonin transporter gene
SNP	Single nucleotide polymorphism
SULT4A1	Sulfotransferase family 4A member 1
SYNE1	Spectrin repeat containing nuclear envelope protein 1
TAD	Topologically associated domain
TDO2	Tryptophan 2,3-dioxygenase
TOCS	Toronto Obsessive-Compulsive Scale
TRE	Tandem repeat expansion
TrkB	Tropomyosin receptor kinase B
TWAS	Transcriptome-wide association study
VA/DOD	Veterans Affairs/Department of Defense
WASL	Wiskott-Aldrich syndrome like
WBP1L	WW Domain Binding Protein 1 Like
WGS	Whole genome sequencing
ZMYM2	Zinc finger MYM-type protein 2

Rationale
Mental health disorders are believed to be caused by a variety of factors, including the environment, neurochemistry, and inherited traits (APA, 2013). These disorders can affect daily living and may be accompanied by many symptoms including fatigue, insomnia, sudden weight loss, and an overall depressed mood (HQO, 2017). According to the 2020 National Survey on Drug Use and Health (NSDUH), approximately 52.9 million (21.0%%) American adults had a mental illness in 2020 (SAMHSA, 2021). Further, about half of Americans will meet the criteria for a DSM-IV disorder sometime in their lifetime, with first onset usually in childhood or adolescence (Kessler et al., 2005). 

Treating mental illness is challenging because people with a mental health disorder often avoid asking for professional help due to stigma associated with the condition. Further, when these individuals do seek treatment, a combination of therapies is often required, including psychotherapy (such as cognitive behavioral therapy), one or more medications (such as antidepressants), or both (HQO, 2017). 

Panels of genetic tests have been developed and proposed for use in the diagnosis of mental illnesses and in the identification of asymptomatic high-risk individuals. Gatt, Burton, Williams, and Schofield (2015) state, “major efforts have been directed at family-based association and case control studies to identify the involvement of candidate genes in the major disorders of mental health. What remains unknown is whether candidate genes are associated with multiple disorders via pleiotropic mechanisms, and/or if other genes are specific to susceptibility for individual disorders.”

Mood Disorders 
Mood disorders primarily encompass depressive disorders, bipolar disorders, and their ilk. According to the 2020 National Survey on Drug Use and Health (NSDUH), approximately4.1 million adolescents experienced a major depressive episode (SAMHSA, 2021). Diagnosis of a depressive disorder has traditionally depended on a clinical history and examination, as screening tools do not provide a diagnosis. Symptoms of this set of disorders include anhedonia, depressed mood, fatigue, insomnia, and more (Lyness, 2020).

Biological testing has seen mixed utility. Identifying co-morbid conditions or drugs of abuse is necessary for management of these disorders, but other avenues such as identifying those predisposed to depression without other clinical symptoms need further data (Lyness, 2020). The impact of any one gene on depression has been limited thus far; depression usually requires significant environmental influences in addition to numerous genetic effects to manifest. Several genetic features such as certain loci on chromosome 10, polymorphisms in corticotropin-releasing hormone type 1 receptor gene (CRHR1), and many more have been suggested by studies to correlate with depressive disorders, but these results are typically not replicated. Malfunction of several neurotransmitters such as serotonin, dopamine, GABA, glutamate, and norepinephrine is typically involved with major depressive disorders (Krishman, 2021).

Epigenetic changes have also been associated with depression and suicide. An epigenetic change is a functional modification of a gene by methods such as methylation. Lockwood, Su, and Youssef (2015) report that many researchers have identified a relationship between depression and suicide; specifically, the hypermethylation of BDNF (Brain-derived neurotrophic factor) and TrkB (tropomyosin receptor kinase B) have been associated with suicide in several studies.

Direk et al. (2017) performed a meta-analysis of two genome-wide association meta-analyses to examine any genetic associations with a broad depression phenotype (encompassing both major depressive disorder and depressive symptoms). The “discovery” stage (two previous studies) included 70017 items, and the “replication” stage of the meta-analysis included 28328 items. One novel locus on chromosome 3 was found to correlate with the broad depression phenotype, and this finding was replicated on an independent sample and on the meta-analysis of both the discovery and replication stages (Direk et al., 2017).

Wray et al. (2018) performed a genome-wide association meta-analysis to identify loci related to major depressive disorder (MDD). The authors investigated a total of 135,458 cases and 344,901 controls and found a total of 44 “independent and significant loci.” An important association found was genetic risk of MDD with education, high body mass and schizophrenia. The authors concluded that a “continuous measure of risk” belies the clinical phenotype of MDD (Wray et al., 2018).

Persons affected by bipolar disorders experience both depressive and manic symptoms; on the other hand, unipolar disorder patients characteristically experience only depressive or manic symptoms. Bipolar disorders, such as bipolar I disorder and bipolar II disorder, may present with similar symptoms to major depression. However, bipolar I disorder presents with more severe manic episodes than bipolar disorder II (Bobo, 2017). As with depressive disorder, several genetic features have been associated with bipolar disorder. Corticotropin releasing hormone signaling, endothelin 1 signaling, glutamate signaling, and phospholipase C signaling have all been investigated as possible links to bipolar disorder. A calcium channel regulator, CACNA1C has seen consistent association with bipolar disorder as well. Other genetic components, such as gene expression and epigenetic features, have been studied (Stovall, 2020). Hughes et al. (2018) has reported that Ankyrin-3 (ANK3) is one gene that is consistently associated with bipolar disorder by multiple genome-wide association studies.

Ikeda, Saito, Kondo, and Iwata (2018) performed a meta-analysis of genome‐wide association studies on bipolar disorder. Twenty-six studies encompassing over 200,000 subjects were included. The authors found a total of 39 single nucleotide polymorphisms (SNPs) with genome-wide significance. However, their primary conclusion was “that the effect size of the susceptibility SNP is extremely small (e.g., odds ratio ~ 1.2), and the magnitude was similar to that of SCZ [schizophrenia] and MDD [major depressive disorder].” The authors also stressed “that common genetic variants do not have a large impact on the diagnosis for BD [bipolar disorder]” (Ikeda et al., 2018).

Stahl et al. (2019) published a genome-wide association study (GWAS) focusing on bipolar disorder. A total of 20,352 cases and 31,358 controls of European descent were evaluated, and a follow up analysis (with an additional 9,412 cases and 137,760 controls) was performed on the 822 variants with a P value of 1 x 10-4. Eight of 19 variants that were genome-wide significant (P < 5 x 10-8) in the discovery GWAS were not significant in the combined analysis. Overall, 30 loci were found to be genome-wide significant, and 20 of these loci were newly identified. Notable and significant loci included genes encoding ion channels, neurotransmitter transporters, insulin secretion regulation, and synaptic items. The authors noted that bipolar I disorder is more correlated with schizophrenia while bipolar II disorder is more correlated with major depressive disorder (Stahl et al., 2019).

Qi et al. (2020) completed an integrative analysis of a GWAS and a regulatory SNP annotation dataset that included 20,352 cases of bipolar disorder and 31,358 controls in the first dataset, and 7,481 cases of bipolar disorder and 9,250 controls in the second dataset. A comparative analysis of the two datasets was completed. The authors note that “After the integrative analysis, we identified 52 TFBRs [including transcription factor binding regions] target genes, 44 TADs [topologically associated domains] target genes, 55 CIRs [circular RNAs] target genes and 21 lncRNAs [long non-coding RNA regions] target genes for BD [bipolar disorder]” (Qi et al., 2020). Some of the most important genes identified include ITIH4, ITIH3, SYNE1 and OPRM1; this study shows that regulatory SNPs are important in the development of bipolar disorder.

Millins et al. (2021) performed a GWAS including 41,917 participants with bipolar disorder and 371,549 controls. 64 associated genomic loci were identified. “Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN.” The authors note that there is a high, yet imperfect, correlation between the associated loci between bipolar type I and type II (Mullins et al., 2021). 
McCarthy et al. (2021) conducted a prospective single-blind study determining the efficacy of genetic guided pharmacological treatment of treatment-resistant depression in veterans. The study included 182 veterans with treatment-resistant depression. Participants had other mental health disorders including bipolar disorder, major depressive disorder, and post-traumatic stress disorder. Patients were randomly assigned to a control group or a pharmacogenetic (PGX) group. The pharmacogenetic group received treatment pharmacogenetic testing during clinical decision-making. The control group received treatment as usual. “The PGX group improved marginally faster compared to TAU, but the difference was not statistically significant.” Only PTSD patients benefited from pharmacogenetic testing (McCarthy et al., 2021). 

Psychotic Disorders 
Psychosis of the mind is loosely defined as a disconnection with reality. Psychotic disorders primarily include schizophrenia, schizotypal disorder, and delusional disorder. Other psychiatric conditions, such as bipolar disorder, may include psychotic symptoms. Major psychotic symptoms include delusions (loosely defined as “strongly held false beliefs that are not typical of the patient’s cultural or religious background”), hallucinations, thought disorganization, agitation, and more. Diagnosis of these psychotic disorders typically involves excluding other possible causes of these symptoms. Once other causes (such as foreign substances or other pathological conditions) have been ruled out, a psychiatric disorder should be considered (Marder, 2021).

Genetic risk factors have been modestly associated with schizophrenia, as heritability studies (twin studies, adoption studies, et al.) have demonstrated useful results. However, the specific genes involved in the etiology of schizophrenia have yet to be identified. Other pathological risk factors, such as environmental (infections, inflammation, and even immigration) and neurological (dopamine, glutamate, GABA, et al.), have been proposed to contribute to schizophrenia and this realm of disorders (Fischer, 2020). 
The Schizophrenia Working Group of the Psychiatric Genomics Consortium performed a “multi-stage schizophrenia genome-wide association study of up to 36989 cases and 113075 controls.” A total of 108 SNPs were found to associate independently with schizophrenia. The authors noted that “associations were enriched among genes expressed in tissues that have important roles in immunity,” and suggested that this result “provided support for the speculated link between the immune system and schizophrenia” (Ripke et al., 2014).

Gandal et al. (2018) performed meta-analyses of transcriptomic studies covering five major psychiatric disorders, including schizophrenia (SCZ), autism spectrum disorder (ASD), bipolar disorder (BD), alcoholism, and depression, and compared cases and controls to identify co-expressed gene modules. Patterns of shared and distinct gene-expression perturbations were identified across these conditions. The degree of sharing of transcriptional dysregulation is related to polygenic (SNP–based) overlap across disorders, suggesting a substantial causal genetic component. This comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness demonstrates pathways of molecular convergence. The authors note, “we have replicated broad transcriptomic and cell-type specific patterns independently for ASD, SCZ and BD, providing an organizing pathological framework for future investigation of the mechanisms underlying specific gene and isoform-level transcriptomic alterations in psychiatric disease” (Gandal et al., 2018).

Huckins et al. (2019) performed a transcriptomic imputation to identify associations between schizophrenia and gene expression. A total of 40,299 cases and 65,264 controls were evaluated, and 413 genic associations were found. Sixty-seven non-MHC [major histocompatibility complex] genes were identified, of which 14 were not within previous GWAS loci. Finally, 36 biological pathways were recognized as having a potential association with the clinical phenotype (Huckins et al., 2019).

Kowalczyk et al. (2018) completed a study with 1,080 Polish subjects (401 with schizophrenia and 679 healthy controls). The purpose of the study was to determine if genetic variants in the HSPA1A (rs1008438, rs562047) and HSPA1L (rs2075800) genes are associated with the risk of development of paranoid schizophrenia. While previous studies have reported an association between HSPA1A and HSPA1B SNPs and schizophrenia symptomatology, no statistically significant relationships were identified in this study (Kowalczyk et al., 2018).

Guan et al. (2020) completed a study which researched the relationship between the WBP1L (WW Domain Binding Protein 1 Like) gene and schizophrenia. An initial group of 2,128 patients with schizophrenia and 3,865 controls were recruited for this study; a second group of 1,052 patients with schizophrenia and 2,124 controls also participated. Thirty-two SNPs located in the WBP1L gene were analyzed. “To conclude, SNPs rs4147157 and rs284854 were associated with SCZ [schizophrenia] in the Chinese Han population. Additionally, rs4147157 was significantly associated with specific symptom features of SCZ” (Guan et al., 2020).

Mojarad et al. (2021) studied how whole genome sequencing (WGS) broadens the range of copy number variants that play a clinical role in schizophrenia. Genomic data of 259 schizophrenic adults was analyzed for any rare high-impact variants including single nucleotide variants, insertions/deletions, and tandem repeat expansions. (TREs). This study identified more TRE variants (one in DMPK; two in ATXN8OS) and an ultra-rare loss-of-function SNVs in ZMYM2 which suggests that it plays a bigger role in schizophrenia than previously thought. Of the 233 patients with no pathogenic copy number variants, WGS identified 26 individuals with pathogenic rare copy number variants and 17 individuals with other types of rare high-impact variants that have potential clinical relevance. This indicates that individuals with schizophrenia, including many with no broadly defined learning disability, had a high-impact small number variant or TRE that was not detectable by CMA, but it was detected by WGS. The authors conclude that this study provides "important evidence of the enhanced performance of WGS compared to CMA in the detection of genome-wide clinically relevant variants, and an initial indication of features that could help identify individuals with schizophrenia who are most likely to benefit from clinical genetic testing and genetic counselling” (Mojarad et al., 2021). 

Attention Deficit Hyperactivity Disorder (ADHD)
Attention deficit hyperactivity disorder (ADHD) is one of the most common childhood behavioral disorders, which often continues into adulthood. Evaluation of this disorder typically includes medical, developmental, educational, and psychosocial examination, and this condition is often comorbid with other psychiatric disorders, such as anxiety or substance use. Symptoms typically include inattention, impulsivity, restlessness, and other dysfunction in certain environments, for example, in school (Krull, 2019).

The exact pathology of ADHD is unknown. A combination of genetic, environmental, and neurological factors has been suggested to contribute to the condition, but no definitive correlations have been found. Genes, such as serotonin transporters, dopamine receptors, and glutamate receptors, have all been linked to ADHD development, and possible genetic basis has been supported by twin and family studies (Bukstein, 2021).

Middeldorp et al. (2016) performed a genome-wide meta-analysis to “investigate the genetic overlap of ADHD symptom scores with ADHD diagnosis.” The authors examined the “genome-wide single nucleotide polymorphisms (SNPs) and ADHD symptom scores were available for 17,666 children (< 13 years of age) from nine population-based cohorts.” SNP-based heritability was estimated at 5-34%, but there were no genome-wide significant SNPs. However, three genes were found to have a gene-wide significant association, and one of these genes (WASL) was involved in neuronal development (Middeldorp et al., 2016).

Qi et al. (2019) analyzed a GWAS dataset of 20,183 patients with ADHD and 35,191 healthy controls. This tissue specific transcriptome-wide association study (TWAS) identified 148 relevant brain tissue genes related to ADHD (including TDO2, CHD1L and KIAA0319L); in the mRNA expression datasets, 11 common genes were identified (including ACSM5, CCDC24 and MVP) (Qi et al., 2019). These genes may help to further the understanding of the underlying genetic mechanisms of ADHD.

Meijer et al. (2020) studied DNA methylation related to ADHD and associated traits via an epigenome-wide association study. Blood samples were used from participants in the NeuroIMAGE study. Samples from participants with ADHD (n=35) and samples from healthy controls (n = 19) were analyzed. The researchers found that “methylated regions provided significant findings showing that hypermethylated regions in the APOB and LPAR5 genes were associated with ADHD persistence compared to ADHD remittance” (Meijer et al., 2020). Both genes are involved in cholesterol signaling. It is important to note that this study included a rather small sample size. The authors conclude by stating that “Although we do not wish to draw conclusions before replication in larger, independent samples, cholesterol signaling and metabolism may be of relevance for the onset and/or persistence of ADHD” (Meijer et al., 2020).

In an epigenome-wide association study, Rovira et al. (2020) studied epigenetic dysregulation in adults with ADHD. This study found one CpG site and four regions that are methylated in 103 patients and 100 controls. This study observed whether smoking status, polygenic risk burden, or exposure to stressful life events had an impact on the methylation pattern of ADHD at the CpG site. Stressful life events, polygenic risk burden, and smoking status had no impact on the methylation pattern in ADHD subjects. The authors conclude that "these findings support a role of DNA methylation in ADHD and emphasize the need for additional efforts in larger samples to clarify the role of epigenetic mechanisms on ADHD across the lifespan” (Rovira et al., 2020).

In the 2021 World Federation of ADHD International Consensus Statement, it is stated that “ADHD is rarely caused by a single genetic or environmental risk factor, but most cases of ADHD are caused by the combined effects of many genetic and environmental risks each having a very small effect.” The guidelines state that ADHD often has a polygenic cause: a combination of many genetic variants, each with a small effect (Faraone et al., 2021).

Anxiety Disorders
Anxiety disorders, including general anxiety disorder, phobias, and obsessive-compulsive disorder, are characterized by excessive and persistent worrying that is hard to control and causes significant distress and/or impairment. According to the 2017 NSDUH, approximately 31.1% of American adults will experience an anxiety disorder at some point in their lives (SAMHSA, 2021). In addition to the characteristic worry, anxiety sufferers may also experience other somatic symptoms, such as increased fatigue (Baldwin, 2021). 

Several genetic factors have been suggested to contribute to this condition. Neurotransmitter receptors, transporters, and pathways have all been associated with generalized anxiety disorder. Other metabolites, such as 5-hydroxyindoleacetic acid, have been explored. Furthermore, twin studies have demonstrated degrees of heritability; estimates are typically in the range of 30% heritability (Baldwin, 2021; Bennett, 2019).

Smith et al. (2016) performed a genome-wide analysis on neuroticism (a common personality trait in anxiety disorders) for over 106,000 patients. A total of nine novel loci were found to have significant associations with neuroticism. These loci included genes involving glutamate receptor ionotropic kainate 3 (GRIK3), corticotropin-releasing hormone receptor 1 (CRHR1), CUGBP (CUG triplet repeat RNA binding protein 1) elav-like family member 4 (CELF4) and more (Smith et al., 2016).

Levey et al. (2020) studied the genetics of anxiety disorders and symptoms using the Million Veteran Program, which is one of the world’s largest biobanks. Both the Generalized Anxiety Disorder 2-item scale and physician diagnoses were used to identify individuals with an anxiety disorder (n = 199,11 and n = 224,330 respectively). The strongest genome-wide signals were identified on chromosome 3 (rs4603973) near SATB1, on chromosome 6 (rs6557168) near ESR1 and on chromosome 7 (rs56226325) near MAD1L1 (Levey et al., 2020). Further, MAD1L1 “may have implications for genetic vulnerability across several psychiatric disorders” (Levey et al., 2020).

Below is a table summarizing selected genes and their potentially associated mental health conditions:

Gene(s)	Mental Health Conditions
	MDD	Bipolar Disorder	Psychotic Disorders	Anxiety Disorders	ADHD
Serotonin Pathway (SLC6A4, 5HT2C, et al.)	X			X	X
Dopamine Pathway (DRD1, DRD2, DRD4, et al.)	X		X		X
Glutamate Pathway	X	X	X	X	X
GABA Pathway	X		X
SULT4A1 (GeneReview, 2019)			X
CACNA1C (gated calcium channel)		X
Corticotropin Pathway (CRHR1, et al.)	X	X		X
Androgen Receptor Signaling Pathway (ANK3, et al.)		X

Papastergiou et al. (2021) performed a single-blind randomized controlled study evaluating the difference between pharmacogenetic guided and standard antidepressant treatment for depression and anxiety. The study included 213 participants, all diagnosed with major depressive disorder and/or generalized anxiety disorder. Pharmacogenetic guided treatments were based off pharmacist recommendations using patient drug profiles and medical histories. Patient-reported depression, anxiety, disability, and treatment satisfaction were recorded at zero, one, three-, and six-months following treatment initiation. Overall, results “improved for participants who received pharmacogenomics guided treatment more so than they did for participants who received standard treatment” (Papastergiou et al., 2021).

Many mental health disorder panel tests are produced for pharmacogenetic purposes. However, Invitae has developed the Mendelian Disorders with Psychiatric Symptoms Panel to identify “late onset inborn errors of metabolism that can result in psychiatric symptoms”; this test can analyze up to 207 genes in hopes to provide “the appropriate clinical and psychological management to achieve the best possible outcome for the patient” (Invitae, 2022). 

In a GWAS, Burton et al. (2021) studied the relationship between pediatric OCD traits and genetic variants. 5018 Caucasian children were genetically tested for OCD traits using the Toronto Obsessive-Compulsive Scale (TOCS). The locus, rs7856850, within the intron of protein tyrosine phosphatase δ, was found to be associated with OCD traits. In addition, this study established a possible role of the 9p24.1 region in OCD which is the strongest linkage of pediatric OCD. The authors conclude that "OC traits and OCD share genetic risk, suggesting that the TOCS is capturing traits that are likely to be on a continuum with OCD” (Burton et al., 2021).

American Academy of Pediatrics (AAP) 
The AAP (Zuckerbrot et al., 2018) published Guidelines for Adolescent Depression in Primary Care which state that the nine depression criteria outlined by the DSM-IV have been shown to cluster together, run in families and have a genetic basis, but does not recommend specific genetic testing (Zuckerbrot et al., 2018).

American Psychiatric Association (APA) (APA, 2016, 2020)
In their Practice Guidelines For The Psychiatric Evaluation of Adults (3rd Edition), the APA does not make any specific recommendations regarding genetic testing for any psychiatric condition (APA, 2016).

The APA has released a practice guideline for the treatment of patients with schizophrenia. A table is provided in these guidelines titled “assessments to monitor physical status and detect concomitant physical conditions.” The table includes the following relevant recommendation:

• Genetic testing: “Chromosomal testing, if indicated based on physical exam or history, including developmental history e” (APA, 2020).

International Society of Psychiatric Genetics (ISPG)
The ISPG “does not recommend direct-to-consumer genetic testing for medical purposes in patients with psychiatric illness or their families, or in healthy individuals concerned about risk or treatment for psychiatric disorders” (ISPG, 2019).

The ISPG does not recommend using “polygenic risk scores” or “risk allele burden testing” (large numbers of genetic variants considered in aggregate) to identify high-risk individuals or to diagnose psychiatric patients. No recommendation was provided for the analysis of copy number variants for adults with mental illness (ISPG, 2019).

European Network Adult ADHD and the Section for Neurodevelopmental Disorders Across the Lifespan (NDAL) of the European Psychiatric Association (EPA) 
These joint guidelines include statements on the genetic component of ADHD. Genetic variants associated with the D4 and D5 dopamine receptor genes typically provided the most consistent findings, but other candidate genes have not shown consistent trends in genome-wide association studies. Several loci have been found to have genome-wide significance, and further research may detect more genomic variants with more genetic samples. Copy number variants have also been suggested to contribute to the condition, but findings are inconsistent (Kooij et al., 2019).

American Academy of Child and Adolescent Psychiatry (AACAP) Committee on Quality Issues (CQI) 
The CQI noted that although many different genetic features (loci, genes, copy number variants) have been associated to various degrees with schizophrenia, genetic testing is only recommended if there are “associated dysmorphic or syndromic features” (AACAP, 2013).

In clinical practice guidelines for the assessment of children with anxiety disorders, AACAP states that “At present, there is no clear role for pharmacogenomic testing in medication selection, although this may change as additional evidence accumulates” (Walter et al., 2020).

US Department of Veterans Affairs/Department of Defense (VA/DoD) 
The VA/DoD published a clinical practice guideline for the management of major depressive disorder. This guideline states that “Additional research is required in the use of genetic testing to aid in the selection of the most appropriate medication for a specific patient. Currently, there is insufficient evidence to support the routine use of genetic testing for the selection of one antidepressant over another” (VA/DoD, 2016).
 

References 

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24. Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry, 62(6), 593-602. doi:10.1001/archpsyc.62.6.593
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26. Kowalczyk, M., Kucia, K., Owczarek, A., Suchanek-Raif, R., Merk, W., Paul-Samojedny, M., & Kowalski, J. (2018). Association Studies of HSPA1A and HSPA1L Gene Polymorphisms With Schizophrenia. Arch Med Res, 49(5), 342-349. doi:10.1016/j.arcmed.2018.10.002
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29. Levey, D. F., Gelernter, J., Polimanti, R., Zhou, H., Cheng, Z., Aslan, M., . . . Stein, M. B. (2020). Reproducible Genetic Risk Loci for Anxiety: Results From approximately 200,000 Participants in the Million Veteran Program. Am J Psychiatry, 177(3), 223-232. doi:10.1176/appi.ajp.2019.19030256
30. Lockwood, L. E., Su, S., & Youssef, N. A. (2015). The role of epigenetics in depression and suicide: A platform for gene-environment interactions. Psychiatry Res, 228(3), 235-242. doi:10.1016/j.psychres.2015.05.071
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33. McCarthy, M. J., Chen, Y., Demodena, A., Leckband, S. G., Fischer, E., Golshan, S., . . . Kelsoe, J. R. (2021). A prospective study to determine the clinical utility of pharmacogenetic testing of veterans with treatment-resistant depression. J Psychopharmacol, 35(8), 992-1002. doi:10.1177/02698811211015224
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38. Papastergiou, J., Quilty, L. C., Li, W., Thiruchselvam, T., Jain, E., Gove, P., . . . Pojskic, N. (2021). Pharmacogenomics guided versus standard antidepressant treatment in a community pharmacy setting: A randomized controlled trial. Clin Transl Sci, 14(4), 1359-1368. doi:10.1111/cts.12986
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Coding Section  

Code	Number	Code Description
CPT	81400	Molecular pathology procedure, Level 1 (e.g., identification of single germline variant [e.g., SNP] by techniques such as restriction enzyme digestion or melt curve analysis)
	81401	Molecular pathology procedure, Level 2 (e.g., 2 – 10 SNPs, 1 methylated variant, or 1 somatic variant [typically using nonsequencing target variant analysis], or detection of a dynamic mutation disorder/triplet repeat)
	81402	Molecular pathology procedure, Level 3 (e.g., > 10 SNPs, 2 – 10 methylated variants, or 2 – 10 somatic variants [typically using non-sequencing target variant analysis], immunoglobulin and T-cell receptor gene rearrangements, duplication/deletion variants of 1 exon, loss of heterozygosity [LOH], uniparental disomy [UPD])
	81403	Molecular pathology procedure, Level 4 (e.g., analysis of single exon by DNA sequence analysis, analysis of > 10 amplicons using multiplex PCR in 2 or more independent reactions, mutation scanning or duplication/deletion variants of 2 – 5 exons)
	81404	Molecular pathology procedure, Level 5 (e.g., analysis of 2 – 5 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of 6 – 10 exons, or characterization of a dynamic mutation disorder/triplet repeat by Southern blot analysis)
	81405	Molecular pathology procedure, Level 6 (e.g., analysis of 6 – 10 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of 11 – 25 exons, regionally targeted cytogenomic array analysis)
	81406	Molecular pathology procedure, Level 7 (e.g., analysis of 11 – 25 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of 26 – 50 exons)
	81407	Molecular pathology procedure, Level 8 (e.g., analysis of 26 – 50 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of > 50 exons, sequence analysis of multiple genes on one platform)
	81408	Molecular pathology procedure, Level 9 (e.g., analysis of > 50 exons in a single gene by DNA sequence analysis)
	81479	Unlisted molecular pathology procedure
	0290U	Pain management, mRNA, gene expression profiling by RNA sequencing of 36 genes, whole blood, algorithm reported as predictive risk score Proprietary test: MindX Blood Test™ - Pain Lab/Manufacturer: MindX Sciences™ Laboratory/MindX Sciences™ Inc
	0291U	Psychiatry (mood disorders), mRNA, gene expression profiling by RNA sequencing of 144 genes, whole blood, algorithm reported as predictive risk score Proprietary test: MindX Blood Test™ - Mood Lab/Manufacturer: MindX Sciences™ Laboratory/MindX Sciences™ Inc
	0292U	Psychiatry (stress disorders), mRNA, gene expression profiling by RNA sequencing of 72 genes, whole blood, algorithm reported as predictive risk score Proprietary test: MindX Blood Test™ - Stress Lab/Manufacturer: MindX Sciences™ Laboratory/MindX Sciences™ Inc
	0293U	Psychiatry (suicidal ideation), mRNA, gene expression profiling by RNA sequencing of 54 genes, whole blood, algorithm reported as predictive risk score Proprietary test: MindX Blood Test™ - Suicidality Lab/Manufacturer: MindX Sciences™ Laboratory/MindX Sciences™ Inc
	0294U	Longevity and mortality risk, mRNA, gene expression profiling by RNA sequencing of 18 genes, whole blood, algorithm reported as predictive risk score Proprietary test: MindX Blood Test™ - Longevity Lab/Manufacturer: MindX Sciences™ Laboratory/MindX Sciences™ Inc
ICD-10-CM		Investigational for relevant diagnoses.
ICD-10-PCS		Not applicable. ICD-10-PCS codes are only used for inpatient services. There are no ICD procedure codes for laboratory tests.
Type of Service
Place of Service

Procedure and diagnosis codes on Medical Policy documents are included only as a general reference tool for each policy. They may not be all-inclusive.

Appendix

Appendix Table 1. Categories of Genetic Testing Addressed in Policy No. 204110

Category	Addressed
1. Testing of an affected individual’s germline to benefit the individual
1a. Diagnostic	X
1b. Prognostic	X
1c. Therapeutic	X
2. Testing cancer cells from an affected individual to benefit the individual
2a. Diagnostic
2b. Prognostic
2c. Therapeutic
3. Testing an asymptomatic individual to determine future risk of disease	X
4. Testing of an affected individual’s germline to benefit family members
5. Reproductive testing
5a. Carrier testing: preconception
5b. Carrier testing: prenatal
5c. In utero testing: aneuploidy
5d. In utero testing: mutations
5e. In utero testing: other
5f. Preimplantation testing with in vitro fertilization

This medical policy was developed through consideration of peer-reviewed medical literature generally recognized by the relevant medical community, U.S. FDA approval status, nationally accepted standards of medical practice and accepted standards of medical practice in this community, Blue Cross Blue Shield Association technology assessment program (TEC) and other nonaffiliated technology evaluation centers, reference to federal regulations, other plan medical policies, and accredited national guidelines.

"Current Procedural Terminology © American Medical Association. All Rights Reserved" 

History From 2013 Forward     

07/28/2022	Annual review, no change to policy intent. Updating coding, description, rationale and references.
07/26/2021	Annual review, no change to policy intent. Updating description, rationale and references. Removing guidelines as that information is included in the rationale.
03/08/2021	Interim review to correct typo.
07/22/2020	Annual review, combining the two policy statements into one statement; this does not change the intent of the policy. Also updating coding.
07/12/2019	Annual review, rephrasing policy verbiage for clarity, no change to policy intent.
07/25/2018	Annual review, no change to policy intent.
07/17/2017	Annual review, no change to policy.
04/25/2017	Updated category to Laboratory. No other changes.
07/12/2016	Annual review, no change to policy intent. Updating background, description, rationale, references and appendix 1.
07/16/2015	Annual review, no change to policy intent. Clarifying language added to policy statement: "To confirm a diagnosis of a mental health disorder in an affected individual." Updated background, description, rationale and references. Added coding and Appendix 1.
07/14/2014	Updated title, description, background, regulatory status, rationale and references. Policy verbiage updated to state: "Genetic testing for mutations associated with mental health disorders (see Table 1) is considered investigational in all situations."
01/07/2014	NEW POLICY