Decoding schizophrenia: insights and impacts from genetic discoveries

In a recent review published in Molecular Psychiatry, a group of authors decoded schizophrenia's genetic architecture, explored its overlap with other disorders, and addressed the challenges and future directions for inclusive and advanced genetic research.

Genomic findings in schizophrenia and their implications
Study: Genomic findings in schizophrenia and their implications. Study: Lightspring/Shutterstock.com

Background 

Schizophrenia, a psychiatric disorder with a 1% lifetime prevalence, is characterized by a complex spectrum of symptoms that disrupt brain function. Schizophrenia's diagnosis, based on diverse symptoms and blurred boundaries with other conditions, underscores its heterogeneity, complicating treatment primarily managed with antipsychotics.

These drugs, however, fail to address all symptoms and are ineffective for about 30% of patients, underscoring the urgent need for better therapies.

Further research is crucial due to schizophrenia's high heritability and complexity, the indistinct boundaries with other psychiatric conditions and wellness, the current treatments' limitations, and the urgent need for therapeutic advances rooted in a deeper understanding of its genetics and pathophysiology.

Genetic architecture of schizophrenia

Common genetic variants and their influence

Recent large-scale Genome-Wide Association Studies (GWAS) reveal common variants' role in schizophrenia, with over 300,000 individuals highlighting 287 associations, including the ZNF804A gene locus.

These variants, each with minor effects, collectively account for minimal disorder variance, emphasizing schizophrenia's extreme polygenicity. Many remain undiscovered, often situated near genes vital for brain function and synaptic structure, indicating their potential importance in the disorder.

Significance of rare genetic variants

Rare copy number variants (CNVs) play a pivotal role in schizophrenia, with anomalies like the 22q11.2 deletion posing significant risk factors, albeit in a limited number of cases. Conversely, certain CNVs, including the 22q11.2 duplication, exhibit protective attributes against schizophrenia, marking a potential therapeutic frontier.

Furthermore, exome-sequencing underscores the influence of rare coding variants (RCVs) in schizophrenia. Specific RCVs linked to the disorder remain elusive due to research constraints; however, an aggregation of these variants in neurologically pertinent genes among affected individuals highlights promising avenues for impending investigations and interventions.

Understanding schizophrenia's heritability: knowns and unknowns

Genetic contributions and gaps in understanding

Schizophrenia, a complex psychiatric disorder, has a heritability estimated at 60–80%, primarily attributed to inherited alleles. However, the distribution of this heritability across different alleles is not fully understood.

Current data reveals that alleles detectable through GWAS significantly contribute to about 25% of the heritability, while RCVs and large rare CNVs each account for approximately 2%.

Despite these insights, there is a substantial gap between explained heritability and estimates from classical genetic studies, suggesting the existence of alleles not yet detectable with current technology.

Advancements in whole-genome and long-read sequencing technologies are anticipated to bridge this gap, providing insights into rare non-coding alleles and other elusive genetic factors.

The impact of ancestry on genomic studies

Schizophrenia research predominantly involves participants of European descent, highlighting a lack of diversity. Studies involving other ancestries, like East Asians, suggest a common genetic architecture across populations.

However, the effectiveness of polygenic risk scoring, a tool with potential healthcare applications, varies significantly among ethnicities. Addressing this Eurocentric bias is crucial for equitable healthcare and might enhance discovery due to variations in allele frequencies across populations.

Pleiotropy and overlapping genetic risks

Genetic overlap, or pleiotropy, is evident among psychiatric disorders, with shared risk alleles indicating biological commonalities. Schizophrenia shows a significant genetic correlation with bipolar disorder, and both conditions share clinical features. However, they are not entirely synonymous, indicating distinct biological underpinnings.

Furthermore, schizophrenia's genetic risk overlaps more with neurodevelopmental disorders (NDDs) like intellectual disability, autism, and attention deficit hyperactivity disorder (ADHD), especially concerning rare alleles.

Symptomatic heterogeneity and transdiagnostic observations

Schizophrenia's symptomatic spectrum, varying in cognitive and psychiatric expressions, partially aligns with individual Polygenic Risk Scores. The absence of this trend in positive symptoms highlights the disorder's etiological diversity, necessitating expansive genetic research approaches.

Cognitive impairment and schizophrenia: a complex interplay

Cognitive deficits, a hallmark of schizophrenia, profoundly affect patients' lives, with approximately 5% of schizophrenia susceptibility potentially linked to common alleles influencing cognition.

Despite schizophrenia's negative genetic tie with cognitive abilities, polygenic risk scores (PRS) yield inconsistent cognitive predictions among affected individuals. Specific genetic variations, including CNVs and ultra-rare variants, are associated with reduced cognitive performance.

Interestingly, premorbid cognitive decline primarily correlates with general Intelligence Quotient Polygenic Risk Scores (IQ PRS), with minimal impact from common schizophrenia-specific alleles yet a notable influence from rare risk alleles.

The relationship between genetic predisposition in schizophrenia and cognitive trajectory post-onset demands further exploration.

Understanding course and treatment resistance in schizophrenia

Indicators of a more severe schizophrenia trajectory, like frequent or prolonged hospitalizations, show high familial correlation and association with elevated schizophrenia PRS. The relationship between common genetic variants and treatment-resistant schizophrenia (TRS) remains ambiguous, potentially due to variations in study designs and TRS definitions.

However, more extensive studies suggest similarities in the genetic architecture of TRS and non-TRS schizophrenia, with TRS potentially linked more strongly to neurodevelopmental origins. Genetic research points towards a high burden of certain rare variants in TRS individuals, but the findings are not uniform. More definitive conclusions await further research and replication of existing studies.

Genetic insights and the evolutionary paradox of schizophrenia

Despite its significant impact on reproductive success, schizophrenia persists in populations, presenting an evolutionary paradox. The frequency of high-risk, high-impact mutations is balanced by new mutations, as supported by studies on risk-associated CNVs. Though individual high-impact variants are rare, the breadth of genes implicated in schizophrenia means these collective variations occur more frequently than expected. Common alleles, theoretically subject to positive selection due to pleiotropic effects, are actually found to be underrepresented in schizophrenia associations.

Predominantly, purifying selection characterizes schizophrenia risk variants, but the effect is mild for those identified by GWAS, permitting these alleles to persist through a mutation-selection-drift model. Some loci may exhibit positive or balancing selection, but overall, the data indicates a primary role for purifying selection in the genetic epidemiology of schizophrenia.

Redefining psychiatric research through genetic overlap

Psychiatric disorders exhibit genetic overlaps, challenging traditional diagnostic boundaries and demanding approaches beyond current categories. Rather than discarding diagnosis-centric research, we need supplementary methods focusing on symptoms, cognition, etiology, or environmental factors.

This requires robust genomic data and nuanced phenotyping, while the genetic complexity in conditions like schizophrenia necessitates careful interpretation of genetic risk.

Schizophrenia on the neurodevelopmental spectrum

Genetic ties between schizophrenia, autism, and ADHD indicate a shared neurodevelopmental origin. 

The uneven distribution of rare genetic mutations suggests a continuum of disorders influenced by mutation load and common genetic variant accumulation. This advocates for a transdiagnostic approach, reshaping clinical perspectives and nosology.

Neurobiology informed by genetics

Schizophrenia reflects widespread neural disturbances, especially synaptic dysfunctions, rather than being confined to specific brain areas. This theory, supported by brain imaging, relates to its diverse symptoms and cognitive impacts. Symptoms correlate with dysfunctions in various neural circuits, implying varied consequences of neural anomalies.

Genetic insights prompt research using animal and cellular models, though the pleiotropy of risk mutations indicates these models do not mirror distinct diagnoses but rather general neurodevelopmental aberrations, emphasizing the importance of an integrated understanding.

Journal reference:
Vijay Kumar Malesu

Written by

Vijay Kumar Malesu

Vijay holds a Ph.D. in Biotechnology and possesses a deep passion for microbiology. His academic journey has allowed him to delve deeper into understanding the intricate world of microorganisms. Through his research and studies, he has gained expertise in various aspects of microbiology, which includes microbial genetics, microbial physiology, and microbial ecology. Vijay has six years of scientific research experience at renowned research institutes such as the Indian Council for Agricultural Research and KIIT University. He has worked on diverse projects in microbiology, biopolymers, and drug delivery. His contributions to these areas have provided him with a comprehensive understanding of the subject matter and the ability to tackle complex research challenges.    

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Kumar Malesu, Vijay. (2023, October 22). Decoding schizophrenia: insights and impacts from genetic discoveries. News-Medical. Retrieved on November 22, 2024 from https://www.news-medical.net/news/20231022/Decoding-schizophrenia-insights-and-impacts-from-genetic-discoveries.aspx.

  • MLA

    Kumar Malesu, Vijay. "Decoding schizophrenia: insights and impacts from genetic discoveries". News-Medical. 22 November 2024. <https://www.news-medical.net/news/20231022/Decoding-schizophrenia-insights-and-impacts-from-genetic-discoveries.aspx>.

  • Chicago

    Kumar Malesu, Vijay. "Decoding schizophrenia: insights and impacts from genetic discoveries". News-Medical. https://www.news-medical.net/news/20231022/Decoding-schizophrenia-insights-and-impacts-from-genetic-discoveries.aspx. (accessed November 22, 2024).

  • Harvard

    Kumar Malesu, Vijay. 2023. Decoding schizophrenia: insights and impacts from genetic discoveries. News-Medical, viewed 22 November 2024, https://www.news-medical.net/news/20231022/Decoding-schizophrenia-insights-and-impacts-from-genetic-discoveries.aspx.

Comments

  1. Johann Popper Johann Popper United States says:

    Hi. Victim of Schizophrenia here. Numerous MRIs and other tests at ostensibly top notch research hospitals in the developed world, all come back "normal", except for slightly low levels of copper. Staff acts like normal tests are normal for a very abnormal, suffering person. Why this gap between science journalism, which consistently reports numerous detectable brain abnormalities in victims of Schizophrenia, whereas practitioners regularly run tests and report to patients no detectable abnormalities?

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Study identifies a potential treatment for Sandhoff and Tay-Sachs diseases