Unlocking Genetic Brain Data: Studying Homozygous and Heterozygous Profiles
- Kenneth Anshewitz
- Aug 18, 2024
- 5 min read
Updated: May 22
INTRODUCTION
Abstract
This study aims to determine whether homozygous or heterozygous populations are more inclined to develop brain diseases like schizophrenia by exploring genetic and neuroimaging data. Using Kernel and/or MEG brain imaging combined with epigenetic testing via TruAge, we will identify biomarkers that could lead to earlier diagnosis and intervention. The study capitalizes on the genetic homogeneity of homozygous populations, which may quickly highlight gene-brain structure relationships, and the genetic diversity of autistic populations, which offers a broad spectrum of brain structure variations. Additionally, we will examine the role of RNA alterations, sex-specific brain development differences, and structural abnormalities associated with autism. The outcomes may contribute to more precise diagnostic criteria and targeted therapeutic strategies for schizophrenia and autism.
Background
Autism Spectrum Disorder (ASD) and schizophrenia are complex neurodevelopmental and psychiatric conditions with overlapping genetic and neurological pathways. Autism is highly heritable, with significant genetic contributions from both common variations and spontaneous mutations. Schizophrenia, though distinct in its manifestations, may share some of these genetic factors. This study focuses on determining whether homozygous or autistic populations are more inclined to develop schizophrenia, leveraging the genetic homogeneity of homozygous populations and the diversity of autistic populations.
Brain Structure in Autism
Research has identified key differences in brain structure between autistic and non-autistic individuals:
Hippocampus: Enlargement in children and adolescents with autism, though its persistence into adulthood is unclear.
Amygdala: Conflicting findings regarding size, with some studies indicating smaller amygdalae in those with anxiety and others showing early developmental enlargement.
Cerebellum: Reduced brain tissue in the cerebellum, which plays a role in cognition and social interaction, beyond its traditional motor coordination functions.
Cortex: Different cortical thickness patterns in autistic individuals, linked to neuron alterations during development.
Genetic Findings in Autism So Far
UCLA Health (2023): Identified seven genes (PLEKHA8, PRR25, FBXL13, VPS54, SLFN5, SNCAIP, TGM1) potentially increasing autism risk, supported by rare inherited DNA variations.
16p11.2 Deletions/Duplications: MRI studies (2017) identified structural abnormalities in individuals with 16p11.2 chromosomal site variations, a common genetic cause of autism.
Recent studies also suggest RNA alterations may be causative rather than consequential in autism, with significant gene expression changes observed across various cortical regions.
Sex-Specific Differences in Autism
Research indicates significant sex-specific differences in brain development, with autistic girls showing a thicker cortex at age 3 and faster cortical thinning into middle childhood compared to boys. These differences could influence the study's outcomes.
Objective
This study aims to determine whether homozygous or autistic populations are more inclined to develop brain diseases like schizophrenia.
Identify genetic and neurological markers associated with schizophrenia risk.
Explore whether RNA alterations in autism are causative or consequential.
Investigate the influence of sex-specific brain development on these outcomes.
Rationale for Population Selection
Homozygous Populations: Offer genetic homogeneity, allowing researchers to quickly identify which genes cause specific brain structures, leading to a clearer understanding of gene-brain structure relationships.
Autistic Populations: Provide genetic diversity, covering a wide range of brain structures, and offering a broader spectrum for understanding neurological variability and its impact on schizophrenia risk.
METHODS
Study Design
A cross-sectional study design will compare brain imaging and genetic data between homozygous and autistic populations to assess schizophrenia risk. A longitudinal component may be added to monitor changes over time, particularly concerning RNA alterations and cortical development.
Population Selection
Homozygous Population: Individuals from genetically isolated populations, chosen for their reduced genetic diversity, allowing clearer identification of gene-brain structure relationships.
Autistic Population: Individuals diagnosed with autism, selected to provide a diverse genetic and neurological dataset, representing the broad spectrum of brain structures associated with ASD.
Inclusion/Exclusion Criteria
Inclusion: Participants must have a clinical diagnosis of autism or belong to an homozygous population. Age will be controlled to reduce confounding variables.
Exclusion: Exclude participants with significant neurological disorders unrelated to autism or schizophrenia, substance abuse history, or conditions that could confound imaging or genetic results.
Data Collection
MEG/Kernel: Magnetoencephalography (MEG) or Kernel Flow will be used to capture brain activity patterns, with a focus on regions implicated in schizophrenia and autism (e.g., the cortex, hippocampus, amygdala).
Procedure: Participants will undergo MEG scans while performing tasks that engage brain regions related to working memory, emotional processing, and sensory integration.
TruAge Epigenetic Testing: Blood or saliva samples will be collected for epigenetic analysis, focusing on DNA methylation patterns associated with aging, autism, and schizophrenia.
RNA Analysis: RNA sequencing will be conducted to explore alterations in gene expression across the cortex, particularly in regions associated with sensory processing and schizophrenia risk.
Data Analysis
Imaging Analysis: Kernel-based methods and machine learning will analyze brain imaging data, identifying non-linear relationships and potential biomarkers for schizophrenia and autism.
Genetic Analysis: Genetic data will be analyzed to identify correlations between specific gene variations and brain structure abnormalities, with particular attention to 16p11.2 deletions/duplications.
RNA Analysis: RNA sequencing data will be compared to brain imaging results to determine whether RNA alterations precede or follow structural brain changes.
RESULTS
Expected Results
We anticipate that our study will yield more precise and reliable associations between genetic factors, particularly inbreeding, and the risk of developing schizophrenia. Previous research, such as the 2012 study by University of Colorado scientist Keller, suggested a 17% increase in the odds of developing schizophrenia for every additional percent of the genome showing evidence of inbreeding. However, Keller was unable to replicate these findings in a 2016 study, refuting his initial 2012 study, but raised concerns about the impact of confounding factors, particularly the inconsistent establishment of control groups across different studies.
By utilizing more stringent controls and carefully curated data, our study aims to overcome these limitations and provide clearer insights into the genetic underpinnings of schizophrenia. Specifically, we expect to identify distinct genes and brain structures associated with inbreeding that contribute to the development of schizophrenia. This approach will allow us to clarify the relationship between genetic homogeneity and schizophrenia risk, potentially leading to more accurate diagnostic tools and targeted therapeutic strategies. Our study’s rigorous methodology should mitigate the issues of confounding results and provide a more definitive understanding of how inbreeding influences schizophrenia and other neurodevelopmental disorders.
DISCUSSION
Interpretation of Findings
The findings will provide insight into whether homozygous or autistic populations are more prone to developing schizophrenia. The genetic homogeneity of homozygous populations may offer clear evidence of gene-brain structure relationships, while the diversity of autistic populations will provide a broad spectrum of brain structures, contributing to a deeper understanding of how genetic diversity influences schizophrenia risk.
Sex-Specific Differences
Considering sex-specific brain development differences will allow us to determine if these contribute to variations in schizophrenia and autism risk, potentially informing more tailored intervention strategies.
Genetic Influence on Brain Structure
This study’s focus on both homozygous and autistic populations will help identify genetic factors influencing brain structure and their role in schizophrenia. This could lead to the development of diagnostic tools that move beyond behavioral criteria, incorporating genetic and brain imaging data for more precise autism and schizophrenia diagnoses.
Future Directions
Identification of Causative Genes: Future research should focus on pinpointing the specific genes responsible for structural brain manifestations in both schizophrenia and autism.
Early Detection and Intervention: Developing earlier, more affordable detection methods for schizophrenia and autism, combining behavioral therapy with potential pharmaceutical interventions, will be a key outcome of this research.
Conclusion
This study offers a unique approach to understanding the genetic and neurological factors that predispose homozygous and autistic populations to schizophrenia. By leveraging the strengths of both population types, we aim to develop more precise diagnostic and therapeutic strategies, ultimately improving outcomes for individuals at risk of schizophrenia and autism.
References
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