The conceptualization of schizophrenia has evolved from Emil Kraepelin’s identification of “dementia praecox” as a distinct illness characterized by cognitive and functional deficits to the modern understanding of its complex nature. Recent research, including the “deficit syndrome,” highlights enduring negative symptoms that correlate with poor functional outcomes. Genetic epidemiologic studies reveal a strong heritable basis (60%–80%) for schizophrenia, with its polygenic architecture overlapping with various mental health disorders. This complexity raises questions about targeted precision medicine. Recent advancements in biobanks and neurogenomics research are providing valuable insights that aim to improve patient outcomes through enhanced genomic understanding.
Key points
- •
Schizophrenia, once rigidly separated from mood disorders, shows strong genetic overlap with bipolar disorder and depression, challenging traditional diagnostic boundaries.
- •
Schizophrenia is highly polygenic, with risk influenced by thousands of common variants with small effects and rare disruptive events linked to intellectual disability and autism.
- •
Beyond dopamine dysregulation, genetic evidence supports glutamatergic (NMDA receptor variants) and GABAergic (interneuron dysfunction) involvement in schizophrenia, reinforcing neurotransmitter-based hypotheses of disease pathophysiology.
- •
Risk is also shaped by immune dysregulation and neurodevelopmental disruptions, with genetic links to microglial activation and synaptic pruning, and some evidence implicating prenatal immune exposures.
- •
While individual risk prediction remains limited, advances in polygenic risk scoring and multi-omic approaches are paving the way for more precise, personalized schizophrenia risk assessment.
Introduction
The earliest and current prevailing conceptualizations of schizophrenia have centered on a distinct characteristic of illness marked by pronounced multi-domain deficits in cognition and functioning and occasional progressive decline. In the sixth edition of his textbook Psychiatrie (1899) , Swiss psychiatrist Emil Kraepelin argued that dementia praecox was a separate entity from “manic-depressive insanity.” Perhaps remarkably, for the times, Kraepelin inferred that dementia praecox was the consequence of “a definite disease process in the brain.” Almost a century later, William T. Carpenter, Jr., and colleagues described the “deficit syndrome” of schizophrenia, characterized by enduring negative symptoms that correlate with worse functional outcomes, above and beyond the influences of psychosis and environmental disadvantage.
In parallel, advances in population-scale genetic epidemiology have clearly demonstrated that there is a robust heritable basis of schizophrenia (60%–80%), but that its genetic architecture is highly polygenic and overlapping with an array of other conditions, including bipolar disorder, major depression, neuroticism, and anorexia nervosa. Genetic risk for schizophrenia also manifests in reduced lifetime years of education, and a host of somatic conditions, with bidirectional impacts on risk. This extreme polygenicity and broad pleiotropy seemingly precludes any singular or focal biologic cause underlying this highly heterogeneous clinical presentation, while also raising questions about potential targeted precision genomic medicine in psychiatry.
For a disorder characterized by profound heterogeneity and marked by diverse courses of illness (recovering, relapsing, chronic) and multiple influences in the form of cognitive and negative symptoms, how can modern genetics—with all of its nuance, and multiple biologic targets—realize benefit for patients? To address this question, we highlight how massive biobanks and cutting-edge neurogenomics research are continuously, uncovering insights about schizophrenia, including features shared with the general population and others that are unique. We frame these recent advancements within the context of improving patients’ outcomes, through identification of critical opportunities with genomic input.
“Gene mapping”: toward a unifying theory of schizophrenia
Genome-wide association studies (GWASs) have emerged as an unbiased method of identifying risk alleles with small-to-modest effect sizes. The GWAS approach harnesses the most abundant class of genetic variation, single nucleotide polymorphisms (SNPs), of which 100 million have been cataloged to date. Unlike candidate gene studies, GWAS is a “hypothesis-free” approach that does not posit a priori that certain genes are of functional consequence. The power of this technique allows for replications that consolidate information about important genes but also allows for understanding concurrent influences across the genome.
In neuropsychiatric disorders, the success of GWASs is exemplified by the trajectory of locus discovery in schizophrenia. The largest scale GWAS of schizophrenia to date included 67,390 cases and 94,015 controls and identified 270 independent signals distributed across the genome, only a fraction of which are attributable to a known functional variant in a protein-coding region. However, indexing these associations with biologic annotation has facilitated explorations of broader functional relevance, including predicted effects on gene expression in diverse tissues. In addition to enrichments of associations in regulatory elements (eg, enhancers) active in cortical and neuronal lineages, these analyses also implicated B lymphocyte lineages, lending support to a hypothesized role of immune functioning.
Driven by ever-increasing samples identification of rare, protein-coding variants are expanding. Purcell and colleagues and Fromer and colleagues reported enrichments of rare (<1 in 10,000) or de novo variants in genes encoding glutamatergic postsynaptic proteins and Fragile X mental retardation protein targets. These results converged with prior biologic insights from GWAS and copy number variant (CNV) studies, paralleling findings from autism and intellectual disability research and recent developments in neuropsychopharmacology. Genovese and colleagues addressed “ultrarare” variants that are unique to an individual, finding strong enrichment of disruptive and damaging variants in “constrained” genes. They further noted that this enrichment exceeded the de novo burden reported by Fromer and colleagues suggesting that rare variant effects in schizophrenia are inherited. More recently, the Schizophrenia Exome Sequencing Meta-Analysis (SCHEMA) Consortium aggregated whole-exome data for tens of thousands of patients and pinpointed 10 genes harboring rare risk variants for schizophrenia. A group from Cardiff University has shown that ultrarare, constrained variants impact not only an individual’s risk but also lead to worse neurocognition among patients , linking this special class of variation to factors closely related to everyday functioning—the target of many researchers in the field. ,
In the following sections, we review support for several unifying theories of schizophrenia, through the lens of efforts to identify “a gene” or “genes for” schizophrenia. These theories face daunting demands, in that they have to simultaneously explain the heterogeneity in symptomatology and functional outcomes seen in the disorder, but also to explain why a polythetic set of diagnostic criteria with negligible requirements for cross-case phenotypic can yield a syndrome that is marked by distal traits (cognitive deficits) that are present in essentially every identified case and many of their relatives.
The Dopamine Theory of Schizophrenia
The dopamine hypothesis posits that dysregulation of dopamine signaling and metabolism plays a crucial role in the development and manifestation of schizophrenia. This hypothesis originated in observations that chlorpromazine, which was initially introduced as a sedative, could alleviate psychosis. Carlsson and Lindqvist later proposed that antipsychotics exerted their effects by blocking dopamine receptors. This idea was subsequently refined to suggest that increased dopaminergic signaling in the mesolimbic pathway underlies positive symptoms, while reduced activity in the mesocortical pathway underlies negative symptoms and cognitive deficits. Following decades of inconclusive candidate gene studies, the DRD2 gene, encoding dopamine receptor D2—the target of antipsychotic drugs—was among 108 replicated schizophrenia loci in a landmark 2014 paper. The catechol-O-methyltransferase ( COMT ) gene has been extensively studied in the context of psychosis because its encoded enzyme degrades dopamine, without any convincing evidence of directly increasing risk for schizophrenia. Variation in COMT alleles (Val/Met) has been reported to correlate with severity of cognitive impairments in people with schizophrenia and their relatives, without increasing risk for expression of the full syndrome.
The Glutamate Theory of Schizophrenia
The glutamate (GL) hypothesis has replaced dopaminergic dysfunction as the leading hypothesized cause of schizophrenia. , The concept is that disrupted glutamatergic neurotransmission, particularly the N-methyl- d -aspartate (NMDA) receptor, plays a critical role in pathophysiology. Like the dopamine hypothesis, it had a pharmacologic origin, based on the effects of NMDA receptor antagonists such as PCP and ketamine. Like the dopamine hypothesis, the GL hypothesis has been supported by large-scale GWAS, most prominently implicating genes encoding metabotropic GL receptors. These include GL receptor 3 and subunits of NMDA receptor epsilon-1 (GRIN2A), as well as interacting components of postsynaptic machinery such as discs large homolog 2 that encodes postsynaptic density protein 93.
Large-scale studies have lent additional support for NMDA receptor genes, including ultrarare, protein-truncating, de novo, and damaging missense variants in GRIN2A and ionotropic receptor AMPA type subunit 3 (GRIA3), , supported by enrichment in genes that encode components of the synaptic machinery. ,
Transcriptomics studies in human postmortem brain tissue and induced pluripotent stem cells have added mechanistic support for GL dysfunction in schizophrenia. The CommonMind Consortium profiled gene expression in the dorsolateral prefrontal cortex of 258 patients and 279 controls and identified significant changes in the expression of genes involved in GL neurotransmission, including CLCN3 , and synaptic transmission more generally, including SNAP91 and TSNARE1 .
In a landmark study, Brennand and colleagues reprogrammed fibroblasts from 4 patients into pluripotent stem cells, subsequently differentiating these into neurons, and observed downregulated of GRIN2A , GRIK1 , GRIK4 , and GRM7 in the neurons. Interestingly, the expression of these receptors varies over the lifespan. Using 42 whole-brain samples spanning prenatal periods to adulthood from the BrainSpan project showed that GRIN2A is most highly expressed during the typical age of onset periods for schizophrenia, late childhood, and adolescence.
Disrupted GABAergic Signaling in Schizophrenia
The GABA (γ-aminobutyric acid) hypothesis proposes that dysfunctions in GABAergic transmission, especially at inhibitory interneurons, contribute to schizophrenia by disrupting the balance between excitatory and inhibitory activity in the brain. Across 21 distinct genes encoding subunits of the GABA receptors, there is inconsistent evidence supporting a direct link to schizophrenia, while recent support for GABAergic dysfunction comes from large-scale transcriptional studies.
Gandal reported downregulation in schizophrenia and autism of the GABA-synthesizing enzymes GAD1 and GAD2 and GABA transporters SLC6A1 and SLC24A3 , interneuron markers RELN and BIP , and key determinants of inhibitory neuron development such as DLX1 and lncRNA DLX6-AS1.
Immune Dysregulation
A longstanding GWAS observation is a signal emanating from the major histocompatibility complex on chromosome 6p22, which is enriched for immune-related genes. Of the 108 distinct loci from PGC, GWAS signals were enriched in enhancer elements active in tissues involved in acquired immunity, in particular CD19 and CD20 lineages of B lymphocytes. These findings are consistent with observations that pro-inflammatory cytokines are elevated in schizophrenia, and with studies linking severe infections , and autoimmune disorders to an increased risk for schizophrenia.
Chronic neuroinflammation could contribute to neuronal damage, synaptic dysfunction, and cognitive deficits. Further, dysregulated inflammatory control can increase vulnerability that can increase reactivity to environmental factors, such as early life trauma and other disadvantages increased in people with schizophrenia. These insights have clinical implications, including exploring anti-inflammatory treatments and adopting personalized medicine approaches tailored to individual immune profiles.
Furthermore, increased microglial activation in schizophrenia may also support a role for chronic inflammation. , In vivo imaging studies using PET have shown increased microglial activation in individuals with schizophrenia, supporting the presence of neuroinflammation. Studies have found differential ratios of brain cell types in individuals with schizophrenia compared to controls, including increases in proportions of astrocytes, pericytes, and PAX6 cells, and decreases in specific neuronal subtypes such as L5/6_IT_CAR3 and LAMP5. Relating these inflammation-related findings with neurodevelopmental hypotheses discussed earlier are findings that maternal infection and immune activation increase lifetime risk for various neuropathologies. ,
Neurodevelopmental Underpinnings
Current research points to disruptions in normal brain maturation processes as a cause of schizophrenia. In particular, aberrant synaptic pruning is a compelling explanation consistent with clinical, epidemiologic, and pathophysiological observations. , This is a normal developmental process whereby “extra” neurons and synaptic connections are eliminated to increase efficiency of neurotransmission. In a high-profile publication, Sekar and colleagues , demonstrated that increased expression of complement component 4 (C4) increases the risk of schizophrenia, with evidence supporting a mechanism of synaptic pruning. Sellgren and colleagues provided further evidence that microglia are more actively involved in synapse elimination in schizophrenia-focused models, reinforcing the idea that excessive synaptic pruning is a critical developmental factor.
Syndromal Presentations
CNVs are deletions or duplications of long stretches of DNA, possibly spanning multiple inherited or de novo protein-coding genes. Specific, rare (<1%) CNVs have been implicated in schizophrenia. These events confer greater risk than individual common SNPs (odds ratios, 2–60) but are observed in only fraction of patients (1.4%–2.5%). One of the best studied schizophrenia-related CNVs is deletions of 30 to 40 genes at chromosome 22q11.2 that cause the eponymous, DiGeorge, Shprintzen, and velocardiofacial syndrome. Carriers of the prototypical approximately 3 megabase deletion may present with characteristic facies, congenital heart defects, learning disabilities, and recurrent infections, while also bearing a 20 to 30 fold greater risk of a lifetime diagnosis of schizophrenia.
A study of 21,094 schizophrenia cases and 20,227 controls highlighted 1q21.1, 2p16.3, 3q29, 7q11.2, 15q13.3, 16p11.2, and 22q11.2 as significant CNV risk loci. Some studies have reported associations of schizophrenia-related CNVs with bipolar disorder, including duplications at 1q21.1 and 16p11.2, and deletions at 3q29, at generally reduced statistical significance.
Multiple lines of evidence support large (>500 kilobases) deletions and an increased burden of CNVs (ie, the total length of genome affected by deletions and duplications) as risk factors for schizophrenia. A study by Bergen and colleagues found cases who carried a known CNV risk or large deletion had lower polygenic risk scores (PRSs) compared to cases who were noncarriers, as well as an association between increased CNV burden and lower PRS. These observations are consistent with an additive model of genetic risk. Subsequent work by Charney and colleagues indicated that rare CNV burden was not elevated in bipolar disorder participants but was higher among schizoaffective bipolar cases than “typical” bipolar disorder cases with or without psychosis.
Recently, the availability of large biorepositories has facilitated a broader examination of CNVs in neuropsychiatric disorders. An examination of 54 known schizophrenia-related and neurodevelopmentally relevant CNVs among 407,074 European ancestry individuals in UK Biobank demonstrated increased risk of depression among carriers of 1q21.1, 15q11.2-15q12, and 16p11.2 duplications. No significant relationship was observed between CNV burden and depression after excluding neurodevelopmental CNVs. Intriguingly, the same investigative team observed significant associations between 12 schizophrenia-related CNVs and cognitive performance among UK Biobank participants without a psychiatric diagnosis. Unfortunately, despite the large sample in UK Biobank, rigorous examination of CNV influences was precluded by inadequate numbers of individuals with verifiable diagnoses.
Polygenic risk scoring
Incremental Variance Explained
In its seminal paper in Nature , the International Schizophrenia Consortium reported that aggregate individual-level PRS constructed from genome-wide SNPs—including those that did not attain genome-wide significance—could explain approximately 3% of the variability in individual liability to schizophrenia. Subsequent PGC publications have shown a steady increase in the variance explained, with the 2014 study reporting approximately 7%, growing to 10%, and the most recent study reporting 20%. These findings highlight the growing accuracy and predictive power of PRS with increased sample sizes, and more comprehensive coverage of risk variants across the allele frequency spectrum.
Generalizability and Pleiotropy
PRSs have considerable promise but their application in clinical settings is impeded by issues of inadequate sensitivity and specificity. The generalizability of PRS across populations is influenced by the characteristics of the training data; scores derived from European ancestry participants show markedly reduced predictive power in non-European groups, , underscoring the need for more inclusive and diverse genomic studies across populations.
Pleiotropy, where a single gene influences multiple phenotypic traits, complicates the interpretation of PRS. Many studies have demonstrated that PRS can capture a broad spectrum of psychiatric traits and PRSs for schizophrenia have yielded replicable associations with nonpsychiatric traits, including positive associations with hepatitis and respiratory infections and negative associations with obesity-related traits, , including unselected populations.
Current PRS are not directly actionable in clinical settings, although a high PRS may warrant additional follow-up or increased vigilance, akin to a positive family history of illness. Wray and colleagues address this parallel directly in a 2021 primer on PRS, explaining that an individual with a family history of schizophrenia may or may not have a higher-than-average PRS, while a person with a higher-than-average PRS may not have any observable family history.
Relationships with Clinical Presentation
PRSs have been used to explore the relationship between genetic risk and clinical features within patients. Regarding symptomatology, considerable data indicate that increased PRS is associated with increased negative and disorganized symptoms. , Studies of the relationships between PRS and symptom severity and treatment resistance have yielded mixed results, , with some reports of significant associations with chronicity or hospitalization. , These inconsistent results may reflect biases in ascertainment or inclusion criteria and highlight the need for larger studies of treatment response and outcomes, with repeated clinical assessments.
Intriguingly, the severity of cognitive deficits in schizophrenia is more strongly associated with PRS for cognition in the general population than PRS for schizophrenia. , Similarly, a study of suicidal ideation and behavior in patients with schizophrenia and bipolar disorder yielded stronger associations with population-based PRS for suicidality and externalizing behaviors than PRS scores for schizophrenia. These relationships suggest that PRS indexing susceptibility to schizophrenia is less important for prediction of everyday outcomes than alternative genetic indices.
Other multi-omics approaches
Epigenetics
Epigenetics describes several mechanisms by which gene expression is regulated and modified without altering the DNA sequence. Key epigenetic mechanisms include DNA methylation, histone modification, and noncoding RNA interactions, which allows cells to respond dynamically to environmental and developmental cues. In particular, methylation is an epigenetic modification wherein a methyl group is added to a CpG dinucleotide; hyper-methylation or hypo-methylation can influence gene expression and high levels of methylation are observed in conserved regulatory elements such as promoters.
A number of schizophrenia risk loci are hypothesized to contribute to underlying pathophysiology via disruption of epigenetic regulation of gene expression. One noteworthy example is SETD1A ; losses of function variants in SETD1A are associated with approximately 35 fold increased risk of schizophrenia. This locus encodes a histone H3K4 methyltransferase that catalyzes methylation of histone H3 on lysine 4, an epigenetic mark associated with active transcription. In Setd1a-deficient mice, knockdown of LSD1 , a histone demethylase , can rescue the disease phenotype. This suggests a compensatory mechanism by which reduced “gene silencing” restores the balance of H3K4 methylation marks. A recent study by Zhao and colleagues demonstrated epigenetic control of quiescence in murine hippocampal cells. This process is disrupted by the deletion of Setd1a , resulting in activation and neurogenesis of neural stem cells.
The environment can influence epigenetic changes, described by some authors as “molecular scars” of exposures, influencing brain function and phenotypic variability. Epigenetic aging describes the progressive, aggregate changes in DNA methylation patterns overtime, which can be quantified as an individual’s “biologic age” and contrasted to their chronologic age. Recent studies have reported dysregulated epigenetic aging in schizophrenia. However, the extent to which these observations are driven by polygenic influences, enhanced vulnerability to stress, treatments for the illness, or physical health is an area of ongoing investigation.
Proteomics
Many GWAS findings are in noncoding genomic regions, with unclear significance. With advances in high-throughput proteomics technologies, it is becoming feasible to screen hundreds or thousands of low-abundance proteins from tissues, serum, and cerebrospinal fluid. These proteins may represent more actionable targets of therapeutic intervention than their encoding genes, given the complexity of alternative splicing, temporal variations in gene expression patterns, and posttranslational modifications. Given the demonstrably heritable basis of many expression levels of proteins, proteomics data can be used to “hone in” on associated genetic variation that co-localizes with protein quantitative trait loci. Next-generation proteomics studies are yielding compelling (and converging) evidence for specific molecular dysfunctions at the synaptic level.
Gene-by-environment interactions
Recent studies of Gene–by–environment interactions (GxE) are providing deeper insights into how genetic predispositions and environmental factors interplay to influence the course of schizophrenia. These findings have clinical and public health implications for understanding disease mechanisms, identifying at-risk individuals, and developing personalized interventions.
Cannabis use, particularly during adolescence, has been shown to interact with genetic risk factors to increase the risk for schizophrenia. A meta-analysis by Vaucher and colleagues confirmed that cannabis use is associated with increased risk, especially in individuals carrying risk variants in the AKT1 and COMT genes.
Living in urban areas has also been associated with an increased risk, potentially due to higher levels of social stress, pollution, and other urban-related factors. Research by Paksarian and colleagues found that PRSs for schizophrenia are higher in individuals who grew up in urban environments, suggesting a GxE interaction.
Adverse exposures during development are of particular interest and are typically thought to confer a profound “insult” to neurodevelopment. For example, Canetta and colleagues showed that maternal influenza infection during pregnancy interacted with genetic risk factors to elevate the risk in offspring, as did maternal malnutrition in the Dutch Hunger Winter in 1944 to 1945. Recent advances have enabled researchers to use PRS to identify individuals more susceptible to environmental influences. For example, a study by Trotta and colleagues demonstrated that PRS for schizophrenia interacts with childhood adversities to risk for and severity of psychotic symptoms. Research has also shown that childhood adversity can lead to epigenetic modifications, including DNA methylation changes, that influence vulnerability as well as contribute to worse outcome subtypes, such as persistent suicidal ideation and serious metabolic syndrome.
Clinical relevance and opportunities of genomics strategies
Quantifying Risk
Family history and risk in biologic relatives
Familial clustering is an epidemiologic hallmark of schizophrenia, with first-degree relatives of affected persons having an 8 to 10 fold increased risk relative to the baseline population prevalence. The best data on familial risk to date are derived from the national registries of Sweden and Denmark. For example, Lichtenstein and colleagues linked the Swedish national multigeneration and hospital discharge registers, identifying over 9 million individuals in more than 2 million families between 1973 and 2004. First-degree relatives—parents, children, and siblings—of persons with schizophrenia had substantially higher risks of developing schizophrenia. Half-siblings had higher risk than the general population, which was less than full siblings. Similarly, adopted children with an affected biologic parent also had higher risk of developing schizophrenia.
It is critical to keep population genetics and concordance in particular, in perspective. Although the risk for concordance for the full syndrome may only be 10% to 15% across pairs of first-degree relatives, about 50% of these first-degree relatives have some maladjustment and reduced functioning. Thus, additional predictions must add to that 50% accuracy base rate. A critical predictive target is discrimination between cases who initially are seen because of appearing to be having a prodromal experience and eventually developing psychosis (<20%) and those who do not. Among those who do not develop psychosis half appear to recover, but the others have persistent maladjustment including cognitive and functional deficits (see for a review). The data suggest that risk prediction has to consider all outcomes, and one with persistent negative symptoms, cognitive deficits, and disability leads to low quality of life. Individuals with this syndrome, classically referred to as “schizotypal personality disorder,” have challenges in functional abilities and poor lifelong employment outcomes. There is notable homogeneity among these “nonconverting nonremitters,” including very low lifelong risk for psychosis, this outcome may be a future treatment target, particularly if specialized medications targeting cognition or negative symptoms are approved for schizophrenia.
Genetic counseling for schizophrenia represents a crucial intersection between clinical practice and genomic medicine, addressing both the significant global heritability and complex genetic underpinnings of the disorder. According to some, genetic counseling is increasingly vital for providing patients and families with a framework for understanding the interaction between genetic factors and environmental influences. However, this intervention faces challenges, including ethical considerations related to privacy and the potential for discrimination, as well as the need for comprehensive genetics education to effectively guide patients through the complexities of genomic data (Gurung & Prata, 2019). This counseling could help in managing the psychological impact of familial risk but also assist informed decision-making concerning health and reproduction. These challenges illustrate that the delicate balance counselors must maintain between support and ethical responsibility in the genomic era.
Preclinical Biomarkers
Recent research has also leveraged schizophrenia PRS to better study developmental underpinnings in nonpsychotic individuals. In one example, Meyers and colleagues examined the relationship between PRS and white matter connectivity in a cohort of children and adolescents assessed longitudinally with electroencephalography. The authors reported significant, positive associations between PRS and parietal–occipital, central–parietal, and frontal–parietal alpha coherence measures, especially in young men between the age of 15 and 19 years. Another study using MRI observed that higher schizophrenia PRS was associated with increased cortical thickness among typically developing children in adolescents, mirroring the patterns of cortical thinning observed in patients, and hearkening earlier descriptions of “dysmaturation” in schizophrenia.
Direct-to-Consumer Genetic Testing
Multiple for-profit companies have advertised diagnostic genetic testing for schizophrenia, clearly contradicting current research and prevailing opinions of qualified experts. Such false claims about genetic risk prediction are unethical and characterized by deceptive marketing practices, unsubstantiated claims, a lack of regulatory approval, and poor transparency about how variants translate into real-world risks. We have already highlighted the limitations of individual-level PRS (see “PRS”). Later, we highlight a particularly unsettling example of how commercially available genetic screening services are seeking to exploit fears and hopes for their own profit.
Embryonic screening
Services for embryonic screening claim to use selected genetic markers reflecting increased risk in order to test embryos prior to implantation during in vitro fertilization. Screening can include specific CNVs or estimated PRS but is controversial due to ethical, social, and scientific validity concerns. Ethical concerns and societal implications include the exacerbation of stigma, social inequalities, and the psychological impact on individuals born from selected embryos.
Pharmacogenomics
Psychiatric pharmacogenomics is an evolving field aiming to tailor psychiatric medication based on individual genetic profiles, enhancing efficacy and minimizing adverse effects. We briefly review the state-of-the-science, with vignettes on clozapine metabolism and a recent implementation of pharmacogenomic screening by the largest US health care provider.
Cytochrome P450 enzymes
To date, a centerpiece of pharmacogenetics has been the study of cytochrome P450 enzyme genes, which harbor variants that influence the metabolism, response, and side effects of medications and can guide dosing to balance toxicity or efficacy (Zhou and colleagues, 2010). In particular, CYP2D6 and CYP2C19 are involved in the metabolism of many antipsychotic medications, with carriers of specific variants classified into “metabolizer phenotypes” (poor, intermediate, extensive, and ultrarapid metabolizers). The Food and Drug Administration has offered guidance on dosing, suggesting that doses of aripiprazole and brexpiprazole are reduced by 50% for patients classified as CYP2C19 poor metabolizers, and a further reduction to 25% if a patient is also taking a CYP3A4 such as clarithromycin (an antibiotic) or ritonavir (an antiretroviral). Less specific cautions are advised for CYP2D6 poor metabolizers taking risperidone, haloperidol, or perphenazine, given a noted increased likelihood of adverse side effects due to elevated metabolites. Randomized clinical trials to date have not yielded resounding support for routine CYP screening in patients treated with antipsychotics, though new, larger multisite trials are currently underway in the Netherlands.
Clozapine metabolism
Studies have also explored using genetic markers to predict the risk of clozapine adverse events (AEs) such as weight gain or agranulocytosis (Mulder and colleagues, 2017). Clozapine is widely underutilized in the United States, largely reflecting exaggerated fears of AEs such that many patients who could likely benefit from clozapine are instead treated with other medications that can cause similar weight gain and metabolic syndrome without clozapine’s benefits.
Recent genetic studies have made significant strides in understanding the metabolism of clozapine, particularly in relation to neutropenia. Legge and colleagues identified the Duffy-null genotype as a key factor in assessing clozapine-related neutropenia in individuals of African ancestry. Pardiñas and colleagues , identified critical pharmacogenomic variants and drug interactions through genetic analysis, providing insights into the metabolic pathways of clozapine and, in a separate paper, conducted a comprehensive pharmacokinetic and pharmacogenomic analysis using UK clinical monitoring data. Lastly, Kelly and colleagues conducted a 6 month multinational clinical trial focusing on the neutrophil response to clozapine in patients of African descent, offering valuable data for personalized treatment approaches.
The Veterans affairs Pharmacogenomics Action for Cancer Survivorship program
Pharmacogenomics Action for Cancer Survivorship (PHASER) is a recent initiative of the US Department of Veterans Affairs (VA) to provide pharmacogenomic testing for up to 250,000 veterans at approximately 50 VA health care sites over 5 years. PHASER tests for variants affect how patients metabolize or respond to around 40 different medications, including antidepressants, opioids, and antiplatelet agents. This information is used by health care providers to select the most appropriate medications and dosages for their patients, with the aim of reducing AEs and optimizing treatment outcomes.
In addition to genetic testing results, PHASER includes tools to help health care providers interpret results and adjust medication plans accordingly, as well as alerts integrated into the patients’ EHRs to notify providers about potential drug–gene interactions. It also includes a quality improvement program to enhance the understanding of how pharmacogenomic testing can be best utilized across the VA system, by studying factors that affect the uptake and use of these data in clinical settings.
Despite not specifically investigating antipsychotic medicines, results from the PHASER program could potentially lead to pharmacogenomics becoming a routine part of care, which could lead to its broader implementation in other areas of health care.
Targeting Inflammation
Identifying patients with high levels of inflammation or specific inflammatory markers could help tailor anti-inflammatory treatments to those who are likely to benefit. This approach aligns with the principles of personalized medicine, aiming to optimize treatment outcomes. Anti-inflammatory treatments may reduce neuroinflammation by modulating the activity of microglia and decreasing the production of pro-inflammatory cytokines. , , By reducing inflammation, these treatments may enhance synaptic plasticity and neurogenesis, leading to improvements in cognitive function and overall brain health.
Several clinical trials have investigated the use of minocycline, a tetracycline antibiotic with anti-inflammatory properties, with some studies suggesting that minocycline can reduce negative and cognitive symptoms when used as an adjunct to antipsychotic medications. However, a more recent study of first-episode patients failed to demonstrate any progressive improvement of negative or other symptoms in early psychosis.
Nonsteroidal anti-inflammatory drugs (NSAIDs), such as aspirin and celecoxib, have also been evaluated in schizophrenia. For example, a meta-analysis of randomized controlled trials found that NSAIDs, particularly celecoxib, may have benefits for overall symptom severity, but effect sizes were negligible.
Tocilizumab, an IL-6 receptor antagonist, has been explored for its potential in treating schizophrenia. IL-6 is a pro-inflammatory cytokine implicated in the pathophysiology of schizophrenia. A pilot study evaluating tocilizumab in patients with schizophrenia showed some improvements in cognitive function and reductions in inflammatory markers.
One intervention strategy that is applied to cardiac disease, frailty, and recently to Alzheimer’s disease (AD) is mesenchymal allogenic stem cell therapy (mASC). Infusions of mASC induce a profound reduction of inflammatory responses across inflammatory cytokine markers. Such therapies have been proposed for use in other neuropsychiatric conditions with predominant inflammation, such as treatment-resistant depression.
The microbiome
Several studies have observed changes in the gut microbiome, including differences in the abundance of specific bacterial taxa, in individuals with schizophrenia compared to healthy controls. These changes are linked to several hypotheses about the pathogenesis of schizophrenia, such as inflammation and neurochemical imbalances involving tryptophan metabolites and brain-derived neurotrophic factor implicating the “gut-brain axis.” However, there is considerable inconsistency in findings regarding overall microbial richness and diversity.
There is growing interest in the potential of probiotics and prebiotics as adjunct treatments. These interventions aim to restore healthy microbiota balance, which could potentially alleviate some symptoms of schizophrenia. However, the evidence is at best preliminary, and more rigorous clinical trials are needed to establish their efficacy and safety. Genomic researchers need to avoid putting the cart before the horse in terms of suggestions for new treatments.
Gene Therapies
Gene therapies involve strategies manipulating underlying genetic pathways contributing to a disease and are actively being explored for conditions like AD, Parkinson’s disease (PD), and cancers. However, intervening at the genetic level, particularly in the brain, raises significant ethical, technical, and safety issues that must be thoroughly addressed before such approaches can be considered in clinical settings. Targeting a specific element of the immune system in the brain requires high specificity to avoid off-target effects that could impair normal brain functions or immune responses elsewhere in the body. Furthermore, given the strong evidence for a neurodevelopmental basis of schizophrenia, are genetic clues more likely to pinpoint therapeutic or prophylactic targets for intervention? Consider the hypothetical example of a therapy that involves using RNA interference technologies to reduce C4A expression in the brain during early adulthood prior to a diagnosis of schizophrenia. Under what circumstances might it be ethical or advisable to target disease processes that may not manifest later as psychosis? Clearly the answer has to consider risks: tens of millions of middle-aged people without a profile of substantial cardiac risk have been treated with stain medications, largely because rates of AEs are so small.
Parkinson’s disease: a test case for successful gene therapy?
Viral gene therapy delivers genes that can modify the brain environment or replace dysfunctional genes. An example includes the delivery of the GAD gene in patients with PD to increase GABA production, potentially mitigating symptoms. In schizophrenia, drug-based approaches that modulate GABAergic function could be potential treatments. For example, enhancing GABA-A receptor function with positive allosteric modulators or increasing GABA synthesis with agents targeting GAD enzymes could help restore the balance between excitatory and inhibitory neurotransmission. However, technological advancements are needed to overcome the inherent challenges of posed by drug delivery across the blood–brain barrier.
Addressing Functional Deficits
Disability in schizophrenia encompasses all domains of real-world outcome and originates from several causes. The illness-related causes include cognitive deficits and negative symptoms, the genomics of which have been investigated, including in the general population. Other contributors to disability include environmental disadvantages, because poverty, racial discrimination, and reduced access to medical care commonly accrue in individuals with schizophrenia. Interestingly, there have been some suggestions of direct genomic influences on functioning and studies from the UK biobank have identified correlates of reduced competence in complex outcomes such as employment. Further, social outcomes are clearly influenced by a number of factors that are genomically related, including social approach or avoidance motivation. Studies have found that overlap of shared schizophrenia features between concordant family members is highest for everyday disability, compared to features such as psychotic symptoms and that occupational dysfunction is among the most concordant traits within affected and unaffected family members. Complex traits such as educational attainment have been studied in detail and examining the PRS for everyday disability is no longer an impossible task. One would expect that contributors to a PRS for disability would include genomic factors affecting educational attainment, but also behavioral traits such as persistence, optimism, and negative loadings for substance abuse and impulsive behavior.
Epilogue and future directions
Schizophrenia poses a significant public health burden, in terms of costs, disability, quality of life, and personal burden leading to suicidal behavior. While modern genetics has driven rapid improvements in our understanding of the complex underpinnings of schizophrenia, transformative mechanistic insights continue to be thwarted by insidious pathophysiological processes and the infinitesimal genetic architecture of their underlying genetic drivers. A notable challenge remains the scarcity of detailed and longitudinal clinical data for participants across demographic factors, a gap which, if left unaddressed, will further hinder our progress. Finally, as multiple genes of small influence may be associated with the origin of the illness, capitalizing on pleiotropic influences across illness features may be a path forward to identify treatments that impact on limited, but critical, subsets of illness features in schizophrenia.
Clinics care points
- •
Schizophrenia has a strong but complex genetic basis – It is highly polygenic with substantial genetic overlap across psychiatric conditions. Rare variants and common polygenic risk scores (PRS) contribute, but PRS are not yet clinically actionable.
- •
Dysregulation in dopamine, glutamate, and immune pathways underlies schizophrenia – Genetic and pharmacologic evidence supports the dopamine (DRD2) and glutamate (NMDA receptor) hypotheses, while immune dysfunction and neuroinflammation may play a more insidious role in onset and progression.
- •
Environmental factors can influence risk – Factors like cannabis use, urban living, maternal infections, and childhood adversity increase risk for schizophrenia. Individuals with genetic predisposition may be especially vulnerable.
- •
Pharmacogenomics holds promise but is not yet standard practice – CYP450 enzyme variants affect antipsychotic metabolism, but routine genetic testing for schizophrenia treatment remains investigational.
- •
Precision medicine is still limited, but multi-omics approaches are advancing – Emerging insights from transcriptomics, epigenetics, and the gut microbiome may help develop novel biomarkers and targeted treatments in the future.
Related posts:
Stay updated, free articles. Join our Telegram channel
Full access? Get Clinical Tree
