Do Genetic Variants Directly Shape Population-Level Schizophrenia Burden? A Global Genomic Analysis.

Area of Science:

• Population Genomics
• Psychiatric Epidemiology
• Complex Disease Genetics

Background:

• Schizophrenia presents a significant global health challenge with considerable geographic disparities in incidence, prevalence, and disability-adjusted life years (DALYs).
• While genome-wide association studies (GWASs) have identified numerous individual risk variants, the relationship between cross-population allele frequency differences and population-level disease burden remains unclear.

Purpose of the Study:

• To investigate the association between population-level allele frequencies and global variations in schizophrenia burden.
• To quantify the extent to which genetic variation explains cross-country differences in schizophrenia incidence, prevalence, and DALYs.

Main Methods:

• Integrated allele frequencies from the 1000 Genomes Project with Global Burden of Disease 2021 data (1990-2021) for 20 countries.
• Employed linear mixed-effects models to assess associations between allele frequencies and age-standardized burden metrics (incidence, prevalence, DALY rates).
• Utilized linkage disequilibrium-based clumping for independent signal identification, multi-omic annotation, and UK Biobank for polygenic risk score (PRS) validation.

Main Results:

• Identified 20, 20, and 14 independent single nucleotide polymorphisms (SNPs) significantly associated with age-standardized incidence rate (ASIR), prevalence rate (ASPR), and DALY rate (ASDR), respectively.
• Two loci, including variants within ADGRV1 and upstream of STAG1, overlapped with existing GWAS findings and collectively explained 13-22% of cross-country variation in burden.
• Genes implicated in neurodevelopmental and synaptic processes were identified; UK Biobank analyses showed higher PRSs for schizophrenia cases based on ASIR- and ASPR-associated SNPs.

Conclusions:

• Population-level allele frequency variation is significantly associated with global schizophrenia burden differences, explaining a substantial portion of cross-population variation.
• This population-genomic epidemiological framework provides a novel approach for studying complex diseases and understanding mental health disparities globally.