Episode 252: Genetic and Environmental Influences of Schizophrenia
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Article Authors: Liam Browning, MD; Nicholas Fabiano, MD; David Puder, MD
Corresponding Author: David Puder, MD
Reviewers: Erica Vega, Joanie Burns, PMHNP-BC
Introduction
History of the Schizophrenia Diagnosis
For much of the 20th century, schizophrenia was treated as a distinct disease entity. In the late 1800s, Emil Kraepelin separately defined Dementia Praecox as an early-onset, degenerative psychotic illness, delineating it from manic-depressive insanity. Kraepelin’s classification emphasized an endogenous brain disorder with a chronic deteriorating course starting in early adulthood characterized by personality disillusionment, cognitive decline, and psychosis. His work set the stage for “Kraepelinian” thinking: the idea that schizophrenia is a single, unitary illness with a biological basis. In 1911, Eugen Bleuler renamed the condition schizophrenia, notably describing it as the “group of schizophrenias,” reframing it as a “splitting” of psychic functions rather than an inevitable dementing illness (McGlasahan, 2011). The neo-Kraepelinian revival of the 1970s (leading into DSM-III) renewed focus on reliable diagnostic criteria, placing emphasis on biological underpinnings of categorical diseases in an attempt to solidify psychiatry within the medical model.
Early genetic evidence strongly influenced this single disease entity concept. One of Kraeplin’s successors in the German Institute of Psychiatric Research, Ernst Rüdin, conducted psychiatry’s first large-scale family study in 1916 (Kendler & Klee, 2022). He examined 2732 siblings of 755 probands diagnosed with schizophrenia to ascertain whether it conformed to mendelian randomization. He found:
The morbid risk (MR; or rate of schizophrenia in a relative) to be between 5.4% and 7.7%, while the MR of “other psychoses” was 5.1%
The risk of schizophrenia in siblings increased with parental alcoholism, parental diagnosis of “other psychoses,” and a history of schizophrenia in 2nd and 3rd degree relatives.
Rüdin’s findings are remarkably close to Gottesman’s estimates of concordance (graph represents the upper bounds of current estimates):
Note. Reprinted from “Rüdin’s 1916 monograph: On the inheritance and primary origin of dementia praecox”, by Kendler & Klee, 2022, Schizophrenia Bulletin, 48(Suppl 1), S8–S19.
Yet Rüdin’s work soon became inextricably linked with the racial hygiene movement he helped found in Germany. He played a central role in drafting and scientifically legitimizing the Law for the Prevention of Genetically Diseased Offspring, which led to the forced sterilization of more than 400,000 people labeled “schizophrenic,” “manic-depressive,” or “feeble-minded.” He co-authored the official commentary justifying the law and later publicly praised Hitler for implementing “brilliant race-hygienic achievements.”
What Is Heritability?
While it is true that the majority (roughly 60-90%) of people with schizophrenia have no 1st or 2nd degree relatives with the disorder (Pedersen et al., 2025), this does not mean that schizophrenia is not heritable.
In genetics, heritability is a statistical measure that describes how much of the variation in a phenotype or risk for a condition across a population can be explained by genetic differences between individuals.
When we say that schizophrenia is highly heritable and has a heritability of 80%, it means that 80% of the difference in liability for schizophrenia in a population is associated with genetic variation. It does not mean that 80% of a person’s schizophrenia is “caused” by genes or that the environment only contributes to 20% of cases of schizophrenia. Heritability is about variation in groups, not causation within individuals.
Heritability also depends on the environment. When environmental conditions (like nutrition, stress, or parenting) are similar across a population, genetic differences account for more of the observed variation in traits. Conversely, in populations with wide environmental differences, the impact of genetics appears smaller.
Height is a good example. Despite height being highly heritable (about 80%), countries with high malnutrition rates are shorter on average. For instance, China lifted nearly 1 billion people out of poverty from the 1980s to today, and from 1985 to 2020, the average height of a 19-year-old male increased by 8 cm (3.1 in) (NCD-Risc, 2020), a change not explainable by genetics.
Even if a disorder is highly heritable, its phenotypic expression is not inevitable. The same principle applies to schizophrenia: heritability doesn’t tell us what’s inevitable, it tells us where the variance comes from.
Twin Studies
Modern estimates of twin-based heritability of schizophrenia ranges from 60-80% (Hilker et al., 2018).
The 80% figure of heritability is based on epidemiological studies comparing concordance rates in monozygotic (MZ) vs dizygotic (DZ) twins and adjusting for different environmental confounds.
If MZ twins (who share 100% of genes) are much more concordant than DZ twins (≈50% of shared genes), the excess similarity is attributed to genetics, assuming the twins are exposed to equal environments (more on this later).
MZ concordance ≈ 15–60%
DZ concordance ≈ 7–17%
According to the falconer formula: H2= 2 (rMz - rDz) =2(.50-.10)
→ h² ≈ 0.80.Interestingly, one study that followed MZ twins who were discordant for schizophrenia found a similar high risk of schizophrenia in their children even in the unaffected twin (16.8% and 17.4%). For discordant DZ twins, however, only the DZ twin’s children had greater risk of schizophrenia (17.4% vs. 2.1%) (Gottesman & Bertelsen, 1989).
Molecular Genetics and the Human Genome Project Give Rise to the Candidate-gene Era
Excitement about the prospect of discovering genes associated with schizophrenia grew following the identification of single gene disorders such as Huntington disease and with the Human Genome Project. The 1990s–2000s focused heavily on several dozen plausible genes associated with brain development (DISC1, NRG1), dopamine receptor genes (DRD4), dopamine metabolism (COMT), etc., finding numerous genes that increased risk for schizophrenia.
However, all of them were false positives due to small sample sizes and low replicability.
A 2015 meta-analysis (Farrell et al., 2015) concluded: “Large common-variant effects originally reported are highly unlikely to be true,” meaning the heritability of schizophrenia is more likely to be the result of multiple small effects from common variants.
Newer methods of estimating heritability (GWAS, PGS, etc.)
Genome wide association studies (GWAS) test hundreds of thousands of common genetic variants, single nucleotide polymorphism (SNPs), to find genetic associations with a phenotype of interest. Because it tests nearly the entire genome with sample sizes that have reached into the millions, it is far less subject to biases than candidate gene studies. This level of statistical power also enables heritability to be calculated by looking at how much of the trait’s variation across a population is due to shared genetic variants.
The largest GWAS on schizophrenia to date (Trubetskoy et al., 2022) included 76,755 individuals with schizophrenia and 243,649 controls and estimated heritability to be about 24% when summing the effects of all measurable SNPs.
However, when estimating heritability with the 287 SNPs that were statistically significant (p < 5 × 10⁻⁸), this figure dropped to only 2.3%.
The polygenic risk score (PRS), a summation of effect sizes of all identified SNPs with less stringent statistical significance (p < .05) was 7.3%.
Very Few Schizophrenia SNPs Code for Proteins
Of the 287 loci identified, only 16 SNPs were located in protein-coding or untranslated regions (UTRs). These 16 protein-coding variants are highly expressed in neurons, especially glutamatergic neurons in the cortex and hippocampus and cortical gabaergic interneurons.
Other identified SNPs of interest that did not reach statistical significance are implicated in synaptic structure, function, and formation.
Polygenic Risk Scores are not that useful (yet…)
SNP-based heritability was 0.24 (24%), but the polygenic risk score only explained:
7.3% of variance using SNPs with p < 0.05
2.4% when restricted to genome-wide significant SNPs
Again, SNP-based heritabilities represent the upper limit of a polygenic score.
Compared to SNP-heritabilities for other disorders
Bipolar is about 17-24% (Stahl et al., 2019)
Depression is about 9% (Wray et al., 2018)
SNP-based heritability for height is about 40-45% and PGS is about the same due >10,000 identified SNPs that reached genome-wide significance (Yengo et al., 2022). It can also be reliably used to predict height r = .7.
Meanwhile, current PRS for schizophrenia are not as useful. However, the highest percentile of PRS had an OR of 39 (95% CI=29–53) for schizophrenia compared to the lowest percentile of PRS.
PRS doesn’t reliably predict positive or negative symptoms or treatment resistance, with most studies demonstrating inconsistent findings (Owen et al., 2023). However PRS might be better at predicting cognitive symptoms at the population level, as a higher PRS is negatively correlated with scores on neuropsychological tests related to fluid intelligence, working memory, and executive functioning (r = -.21; Savage et al., 2018).
Portability problem
PRS of 8% in (white) European, drops to 7% in Latino, 6% in East Asian, and only 1.5% in those considered African American.
For height, the 40% PGS dropped to between 10–20% when applied to other genetic ancestries.
Rare Variants Are Not Captured by SNP Analyses
SNP analyses do not easily detect the influence of rare genetic variants present in <1% of the population, as GWAS studies use DNA microarrays that genotype common variants.
Copy number variants (CNVs) are deletions or duplications of large DNA segments that alter gene dosage; ultra-rare variants (URVs) are extremely rare (<0.01% frequency) point mutations or small insertions/deletions that disrupt protein-coding genes.
Current estimates suggest CNVs and URVs explain about 4% of schizophrenia liability.
People with schizophrenia may have a higher copy number variant burden than the general population. One study suggests about 4% of people with schizophrenia have copy number variants, compared to 2.3% in bipolar disorder, and 1.5% in healthy controls (Georgieva et al., 2014).
The most notable example is 22q11.2 deletion syndrome (DiGeorge Syndrome), a deletion in a segment of chromosome 22 containing 40-60 genes, including COMT, DGCR8, and TBX1, which are involved in dopaminergic signaling, microRNA processing, and neural development.
About 25–30% of individuals with a 22q11.2 deletion develop schizophrenia or a schizophrenia-spectrum disorder by adulthood — a 20–30-fold increase over the general population baseline risk (~1%).
However, only 0.3–0.6% of schizophrenia cases are estimated to have 22q11.2 deletions.
The SCHEMA meta-analysis (Singh et al., 2022) sequenced the exomes of over 120,000 people (24,248 cases; 97,322 controls) and found that rare mutations in 10 genes increase risk for schizophrenia (at exome-wide significance), with protein truncating variants and the most damaging missense mutations in these genes associated with ORs ~3–50.
These genes were found to be most highly expressed in synapses, with functions related to ion transport (CACNA1G, GRIN2A, and GRIA3), neuronal migration and growth (TRIO), transcriptional regulation (SP4, RB1CC1, and SETD1A), nuclear transport (XPO7), and ubiquitin ligation (CUL1, HERC1).
A glutamate receptor gene (GRIN2A) and a transcription factor gene (SP4) also had common variants identified in the GWAS study.
Since publication of this study, four other RCVs have been identified STAG1 (involved in chromosomal segregation), ZNF136 (transcriptional regulation), AKAP11 (synaptic structure) and SRRM2 (transcriptional regulation) (Chick et al., 2025; Liu et al., 2023).
Interestingly, CNVs and 5/14 of the identified genes with RCVs are also associated with autism and other neurodevelopmental disorders (Owen et al., 2023).
The Genomic findings in schizophrenia are not specific to schizophrenia
The polygenic architecture of schizophrenia — rethinking pathogenesis and nosology
Genetic overlap with schizophrenia-genetics increasing transdiagnostic risk
Genetic correlation with bipolar disorder (.7) and treatment resistant depression (.57), (Anttila et al., 2018; Xiong et al., 2025)
Missing Heritability Problem
Missing heritability (Génin, 2020) GWAS and PGS estimates of heritability are bound to be lower than heritability derived from twin studies due to multiple different factors (gene x gene interactions, non-additivity, underpowered estimates, etc.). It is more apparent in behavioral traits as opposed to anthropomorphic traits, such as height (Cheesman et al., 2017).
Using twin studies to measure heritability is limited by the Equal Environment Assumption, which is that identical twins and fraternal twins, if raised in the same family, will be subject to the same environment (i.e. same parenting style, same socioeconomic status, same schools, etc.). However, we know identical twins are treated more similarly than dizygotic twins (by parents, peers, society) and share a more similar environment in utero (almost always share one placenta vs. one or two for dizygotic twins), so the inter-sibling environmental variance is less for twins.
Likewise, there is probably something special about sharing 100% of one’s genes compared to 50%, as the effect of genetic-relatedness is probably non-linear due to gene-gene and gene-environment interactions. This is an example of how heritability of a phenotype is not only a product of direct genetic factors, such as through gene mutations coding for faulty proteins, but also indirect genetic factors, or ways in which genes predispose to environmental interactions that influence phenotypic expression. So, in effect, heritability estimates derived from twin studies are likely overestimates.
Environmental Factors Impacting Risk of Schizophrenia
Preconception Factors
Although schizophrenia is highly heritable, it is plausible that de novo germline mutations can increase risk for schizophrenia. One of the most well-known factors that increase germline mutations is parental age, because, as we age, the function of DNA repair mechanisms, epigenetic regulation (methylation/demethylation), and cell replication tends to decline. For example, most people are aware that older women are more prone to giving birth to children with Down syndrome, and this is a result of the egg not separating chromosome correctly when dividing in meiosis.
Paternal Factors
Men produce sperm continuously throughout their lives, meaning there is a greater chance that de novo mutations, or DNA mutations that occur throughout one’s life due to radiation or errors in DNA replication that are not corrected, can accumulate in the stem cells that give rise to sperm cells. This means, as these cells accumulate mutations, these can be passed down to the offspring and increase the risk for disorders like autism, achondroplasia, marfan syndrome, and potentially schizophrenia.
According to cohort studies from Swedish national patient registries, advanced paternal age (>50 years) has been associated with increased risk of schizophrenia in their offspring compared to 20-29 year old fathers OR 2.96 (95% CI: 1.52–5.77) (Zammit et al., 2003) and 5.85 (2.91 to 11.74) (Sipos et al., 2004). However, the number of births to fathers over 55 in one study were quite limited (only 4 total cases of schizophrenia out of 187 births). Furthermore, parental psychiatric factors were not always adequately controlled for, as impulsivity and low executive functioning can increase risk of risky sexual behaviors.
Meanwhile, advanced maternal age has not consistently been linked to increased risk of schizophrenia (Merikangas et al., 2017), perhaps due to less time to accumulate mutations before infertility, compared to men.
Prenatal exposure
Prenatal stress
Dutch Hunger Winter Famine (1944-1945) (Hoek et al., 1998): Cohort of Dutch individuals exposed in utero to maternal stress and malnutrition from the sudden Nazi occupation and embargo of food from the Netherlands in February-May of 1945. Some regions were limited to 1000 calories/day during these months. People who were conceived during the peak of the famine (February-May) and born in October-December of that year were twice as likely receive an ICD-8,9 schizophrenia diagnosis (RR 2.0; 95% CI 1.2-3.4), in both males (RR 1.9; 95% CI 1.0-3.7) and females (RR 2.2; 95% CI 1.0-4.7) by 1970-1992, when the participants were 24-48 years old (confirmed by national psychiatric registry). There were also an increased number of congenital neurodevelopmental defects in the cohort, suggesting nutritional deficiencies altered CNS development.
Note. Reprinted from “The Dutch Famine and schizophrenia spectrum disorders”, by Hoek et al., 1998, Social Psychiatry and Psychiatric Epidemiology, 33, 373–379.
Holocaust (1939-1945): Offspring of parents exposed to genocide (e.g., in utero or early postnatal for the parent). No increased risk of developing schizophrenia, but a worse course if schizophrenia occurs, with higher psychiatric re-hospitalization rates (HR = 1.48-1.74, depending on maternal/paternal exposure timing). Exposure is preconception for the child, reflecting parental trauma.
Chinese Great Famine (1959-1961): Cohort born in rural areas during famine years, exposed at conception/early gestation. RR = 1.68-2.25 (higher in severe famine regions); 2-fold increase tied to famine severity, no effect in urban areas.
Arab-Israeli Six-Day War (1967): Jerusalem cohort exposed to war stress in second month of gestation (early first trimester). RR = 2.3 overall (95% CI: 1.1-4.7); sex-specific: RR = 4.3 for females (95% CI: 1.7-10.7), RR = 1.2 for males (95% CI: 0.4-3.8).
Yom Kippur War (October 1973, Israel): Cohort from the Israel Psychiatric Registry (n=88,829 births 1973-1976), examining in utero exposure to maternal stress from the surprise Arab attack and war. No significant increase in schizophrenia risk (RR = 0.99, 95% CI: 0.73-1.33 overall; similar across trimesters). Suggests acute war stress alone may not elevate risk, possibly due to shorter duration compared to chronic events (Selten et al., 2003).
Prenatal Infections
Maternal infections (influenza, bacterial, CMV and toxoplasmosis) have been linked to increased risk of schizophrenia in offspring, but ORs/HRs have been modest (usually around 1.2), even in cases that required hospitalization and when cases were limited to the first trimester (Cheslack-Postava & Brown, 2022).
Birth Complications
An influential meta-analysis of eight prospective population studies conducted by Cannon and colleagues (2002) showed various obstetric complications, including low birth weight (<2000g), emergency c-section, congenital abnormalities, uterine atony each being associated with greater than 2-fold increased risk of schizophrenia in adulthood. However, there is a concern about shared genetics or risk behaviors: for instance, mothers with schizophrenia may be more likely to have obstetric problems (due to factors like prenatal neglect or medication), which could confound the association. Dalman et al. (1999) mitigated this by adjusting for maternal psychiatric history, and still found an effect for preeclampsia, suggesting the association is not purely genetic.
Childhood
ACES
Empirically-derived dimensions of childhood adversity and cumulative risk: associations with measures of depression, anxiety, and psychosis-spectrum psychopathology (Gizdic et al., 2023)
Varese et al. (2012) conducted a meta analysis on the risk of psychotic symptoms or diagnosis with ACE exposure using 41 cross-sectional, case-control, and prospective studies, totaling over 75,000 participants. Results demonstrated an overall effect of increased risk of psychotic symptoms or diagnosis in adulthood OR = 2.78 (2.34–3.31).
Within this review, a number of studies controlled for general demographic and clinical confounds such as comorbid psychopathology, ethnicity, educational attainment, IQ, drugs use, genetic liability (eg, family history of psychosis or other psychiatric disorder), and urbanicity.
Two other prospective studies have been conducted since:
Methods
Prospective pre-birth cohort following 3752 children from birth to 5, 14, and 21. Completed diagnostic interview at age 21 (YASR Behavior Checklist and CIDI)
Used child protection records for cases of abuse or neglect up to age 14
Results
Adjusting for childhood ADHD symptoms, substance use at age 14, and other covariates, exposure to abuse or neglect increased the odds of ever having received a DSM-IV diagnosis at age 21 by 1.65 (1.00–2.71) for one verified exposure to abuse or neglect and 2.29 (1.16–4.55) for two exposures.
Croft et al. (2019) did not use a psychotic disorder diagnosis, but rather an interview assessing lifetime incidence of psychotic-like symptoms in 4433 participants of the AVON longitudinal study, who were followed from birth to age 18.
Exposure to any trauma increased odds of ever experiencing psychotic symptoms by age 18 years (aOR 2.91 [2.15-3.93]), controlling for parental psychiatric history, family history of psychiatric disorder, and living conditions.
They also found a dose-response relationship (1.70 [1.54-1.87]) with each trauma exposure. Interestingly, this effect was most notable in the older age group.
0-4.9 y - 1.82 (.87-3.80)
5-10.9 y -1.60 (1.42-1.80)
11-18 y - 1.86 (1.64-2.10)
Poverty and Socioeconomic Status
Methods
Nationwide, register-based cohort of ≈ 2.1 million individuals born in Sweden (1963-1983).
Assessed social adversity by five census-recorded socioeconomic adversities before age 18:
Living in rented (vs. owned) housing
Low parental socioeconomic status
Single-parent household
Parental unemployment
Household receiving social-welfare benefits
Follow-up for first inpatient diagnosis of schizophrenia-spectrum or other non-affective psychotic disorder from ages 10-39 y (hospital records 1987-2002).
Results
Note. Reprinted from “Social adversity in childhood and the risk of developing psychosis”, by Wicks et al., 2005, The American journal of psychiatry, 162(9), 1652–1657.
Urbanicity
Pedersen et al., 2025: The increased risk of urbanicity may be attributable to a latent factor, such as pollutants, family structure, socioeconomic factors, stress, etc.
Cannabis use (see also episode 240)
The potency of cannabis is increasing, with THC content increasing by 5x over the last 2 decades (4% to 20%).
High potency and regular cannabis use is associated with an elevated risk of psychosis → 0.5% of people who use cannabis experience a cannabis-induced psychosis.
The risk of cannabis-induced psychosis is elevated with high potency THC (>10%), daily use, younger age, male, or history of a mental disorder.
>50% of people with cannabis-induced psychosis recover within 24 hours, but those with prolonged symptoms have hospitalization rates up to 76%.
A population-based retrospective cohort study of 9.8 million found that an ED visit for cannabis use or cannabis-induced psychosis was associated with a 14- and 242-fold increased risk of developing a schizophrenia-spectrum disorder within 3 years
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