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PubMed2026

Common genetic variants are associated with increased likelihood of latent co-occurring neurodevelopmental and mental health factors among autistic individuals.

Autistic individuals show elevated rates of co-occurring neurodevelopmental and mental health conditions, yet the genetic architecture of those comorbidities remains unclear. Using phenotypic (N = 74,204) and genetic (N = 17,582) data from the SPARK study, we investigated the factor structure, heritability, genetic correlation with autism (pleiotropy) and corresponding conditions in the general population (additivity). First, confirmatory factor analysis identified three correlated factors mirroring general population patterns: behavioural (ADHD, disruptive behaviour disorders), cothymic (depression, anxiety), and thought disorder (schizophrenia, bipolar). Second, all three factors had significant SNP heritabilities whilst rare variants were not associated with the tested factors in our sample. Third, polygenic scores and genetic correlations revealed positive shared genetics between the three factors and corresponding conditions in the general population but not with autism, supporting the additivity hypothesis. Fourth, within-family analyses (N = 5236 trios) demonstrated direct but not indirect genetic effects for the behavioural and cothymic factors. In sum, we find evidence for additive effects of other genetic factors in contributing to some latent co-occurring neurodevelopmental and mental health conditions in autism.

Journal Article↗

PubMed2026

Appreciating diversity: a review of the Iranian genomic landscape.

Understanding population structure is crucial for designing and interpreting human genetic studies. This is of particular importance for Iran as a large, ethnically diverse country whose population has often been treated as a genetically homogenous entity. Here, we synthesize published literature on the genetic structure of the Iranian population. We further complement this by recapitulating the geographic, historic, and ethnic background, by comparisons with neighboring countries, and by reviewing autozygosity in Iran. This synthesis confirms large genetic diversity, likely building upon an autochthonous component that was reshaped by multiple migrations. The substantial autosomal substructure falls apart into groups of largely shared genetic ancestry (Central Iranian Cluster) and those with substantial admixture in the past. Structure with respect to uniparental markers is less pronounced. We also find consistency for generally high but varying levels of autozygosity, influenced by ethnicity, residence, and socioeconomic factors. Finally, we recapitulate some examples for geographical differences in disease prevalence and (founder) mutation carrier frequency. Our synthesis emphasizes the need to account for this diversity in human genetic studies in the Iranian population. We provide conclusions for the design of such studies and state expectations on the transferability of genetic findings and genomic predictions, such as polygenic scores, within Iran as well as to neighboring countries. Iran's diversity and geographic location provide renewed motivation for conducting population genetic and ancient DNA studies as well as providing genomic reference resources in this part of the world.

Journal Article↗

PubMed2025

Heterogeneous effects of genetic variants and traits associated with fasting insulin on cardiometabolic outcomes.

Elevated fasting insulin levels (FI), indicative of altered insulin secretion and sensitivity, may precede type 2 diabetes (T2D) and cardiovascular disease onset. In this study, we group FI-associated genetic variants based on their genetic and phenotypic similarities and identify seven clusters with distinct mechanisms contributing to elevated FI levels. Clusters fall into two types: "non-diabetogenic hyperinsulinemia," where clusters are not associated with increased T2D risk, and "diabetogenic hyperinsulinemia," where T2D associations are driven by body fat distribution, liver function, circulating lipids, or inflammation. In over 1.1 million multi-ancestry individuals, we demonstrated that diabetogenic hyperinsulinemia cluster-specific polygenic scores exhibit varying risks for cardiovascular conditions, including coronary artery disease, myocardial infarction (MI), and stroke. Notably, the visceral adiposity cluster shows sex-specific effects for MI risk in males without T2D. This study underscores processes that decouple elevated FI levels from T2D and cardiovascular risk, offering new avenues for investigating process-specific pathways of disease.

Humans↗

PubMed2026

Consensus meta-analysis of genome-wide association studies for Alzheimer's disease and related dementias.

To better characterize the genetic architecture underlying Alzheimer's disease (AD) and related dementias (ADRD), we performed a meta-analysis of European-ancestry genome-wide association studies in 128,681 cases or proxy cases of ADRD and 849,833 (proxy) controls. We identified 91 genetic loci associated with ADRD risk, of which 16 are new and 56 are specifically detected in clinically diagnosed AD cases. We also provide a list of 18 loci (15 new) requiring further external validation. A polygenic score combining the effects of ADRD loci other than APOE was primarily associated with AD rather than non-AD pathology. Individuals in the tenth decile of the score exhibited a twofold increased risk of presenting with Braak neurofibrillary tangles stage of >4 and moderate-to-severe neuritic amyloid plaque pathology at death compared to individuals in the median score group. In conclusion, our study validated a large number of loci associated with the risk of clinically diagnosed AD, while further investigations are required to confirm the impact of the other loci on AD clinical diagnosis and of each locus on AD pathology.

Humans↗

PubMed2026

Genome-wide association analyses highlight the neuronal contribution to multiple sclerosis susceptibility.

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease. Previous genetic studies have identified susceptibility loci that primarily impact immune cells and microglia. Here we performed a multi-ancestry genome-wide association study of 20,831 MS cases and 729,220 controls and identified 236 susceptibility variants outside of the major histocompatibility complex, including four novel genomic loci. We also derived a polygenic score for MS; while optimized for European ancestry, it is informative for African American and Latino individuals. Integrating single-cell data from blood and brain tissue, we identified 76 candidate causal genes. Inhibitory neurons emerged as a key target cell type for MS-associated variants, with seven loci, including STAT3, displaying altered expression only in these cells. The STAT3 variant is also associated with cognition and white matter integrity in individuals with no MS and greater sNfL levels in individuals with MS, suggesting that MS susceptibility may reflect reduced central nervous system resilience to inflammatory challenges.

Humans↗

PubMed2025

Polygenic prediction of body mass index and obesity through the life course and across ancestries.

Polygenic scores (PGSs) for body mass index (BMI) may guide early prevention and targeted treatment of obesity. Using genetic data from up to 5.1 million people (4.6% African ancestry, 14.4% American ancestry, 8.4% East Asian ancestry, 71.1% European ancestry and 1.5% South Asian ancestry) from the GIANT consortium and 23andMe, Inc., we developed ancestry-specific and multi-ancestry PGSs. The multi-ancestry score explained 17.6% of BMI variation among UK Biobank participants of European ancestry. For other populations, this ranged from 16% in East Asian-Americans to 2.2% in rural Ugandans. In the ALSPAC study, children with higher PGSs showed accelerated BMI gain from age 2.5 years to adolescence, with earlier adiposity rebound. Adding the PGS to predictors available at birth nearly doubled explained variance for BMI from age 5 onward (for example, from 11% to 21% at age 8). Up to age 5, adding the PGS to early-life BMI improved prediction of BMI at age 18 (for example, from 22% to 35% at age 5). Higher PGSs were associated with greater adult weight gain. In intensive lifestyle intervention trials, individuals with higher PGSs lost modestly more weight in the first year (0.55 kg per s.d.) but were more likely to regain it. Overall, these data show that PGSs have the potential to improve obesity prediction, particularly when implemented early in life.

Adolescent↗

PubMed2026

Integrated multi-omics strategies for identifying novel therapies in psoriasis.

MOTIVATION: Psoriasis is a chronic, immune-mediated disorder with an unmet need for effective treatments. To systematically prioritize therapeutic targets, we integrated proteome-wide Mendelian randomization (MR) with expression validation in blood/skin, genetic susceptibility analysis, differential gene expression (DGE) from bulk and single-cell RNA sequencing (scRNA-seq), colocalization, pathway enrichment, and protein-protein interaction analyses. RESULTS: Proteome-wide MR identified 29 candidate protein targets (Bonferroni-corrected), all replicated in independent datasets. Fifteen targets showed significant expression associations in blood or skin. Eleven proteins-UBLCP1, IL23A, ASF1A, RARRES2, ICAM1, PRSS53, ICAM5, GCA, IL2RA, DBI, and NFKB1-exhibited consistent directional effects with their genes. Genetic susceptibility analysis confirmed 20 target-specific polygenic scores for psoriasis and five for psoriatic arthritis. DGE analysis identified 13 targets in bulk and 13 in scRNA-seq-primarily in keratinocytes and immune cells-with IL2RA, COMP, and A2ML1 dysregulated across both. Colocalization analysis implicated shared causal variants for psoriasis in ASF1A, CD8A, CTF1, IL7R, MMP12, RARRES2, XCL2, DBI, IL23A, IL2RA, SGSH, and TIMD4. Enrichment analyses highlighted involvement in cytotoxicity, immune regulation, and JAK-STAT signaling. Eighteen targets interacted with approved anti-psoriasis drugs. Notably, drugs targeting IL2RA, IL7R, CTF1, ICAM1, MMP12, NFKB1, CD8A, DDX58, IL12A, SGSH, and FAP are approved or in trials for other diseases, suggesting repurposing potential. Our integrative multi-omics approach prioritized 29 high-confidence targets, including 13 novel candidates (RARRES2, ASF1A, CTF1, DBI, B3GNT2, CD8A, TIMD4, CRTAM, SGSH, XCL2, DAPK2, A2ML1, and FAP). Several high-priority targets-such as IL2RA, IL23, MMP12, RARRES2, IL7R, and ICAM1-were supported across analytical layers. These findings provide a robust foundation for psoriasis drug development. AVAILABILITY AND IMPLEMENTATION: The code used for the analyses in this manuscript has been archived in Zenodo at [DOI: 10.5281/zenodo.19692128].

Psoriasis↗

PubMed2025

Polygenic Risk Factors for Comorbid Diagnoses in Individuals with Substance Use Disorders: A Phenome-Wide Survival Analysis.

OBJECTIVE: Persons with substance use disorders (SUD) often suffer from additional comorbidities. Researchers have explored this overlap via phenome wide association studies (PheWAS). However, PheWAS are largely cross-sectional, limiting our understanding of whether diagnoses predate development of an SUD. We characterize whether polygenic scores (PGS) are associated with time to comorbid diagnoses in electronic health records (EHR) after the first documented SUD diagnosis. METHODS: Using data from All of Us (N = 393,596), we explored: 1) whether social determinants of health (SDoH) are associated with lifetime risk of SUD (N cases = 42,568) and 2) within a subset those with a diagnosed SUD and available genetic data SUD (N = 21,357), whether PGS for alcohol use disorders, cannabis use disorders, depression, externalizing, post-traumatic stress disorder, and schizophrenia were associated with subsequent diagnoses via a phenome-wide survival analysis. RESULTS: Multiple SDoH were associated with lifetime SUD diagnosis, with annual household income having the largest overall associations (e.g., <$10K annually vs $100K-$150K annually: OR = 3.89, 95% CI = 3.66, 4.13). There were 101 phenome-wide significant PGS associations with subsequent diagnoses across various bodily systems. PGSs for alcohol use disorders, post-traumatic stress disorder, and schizophrenia were each associated with time to their respective diagnoses. CONCLUSIONS: Social determinants, especially those related to income, have profound associations with lifetime SUD risk. Additionally, PGS for psychiatric conditions are associated with multiple post-SUD diagnoses within those with a SUD, suggesting PGS may capture information beyond lifetime risk, including timing and severity of comorbidities related to SUD.

Journal Article↗

PubMed2025

Genome-wide association meta-regression identifies stem cell lineage orchestration as a key driver of acne risk.

Over 85% of the population experience acne at some point in their lives, with its severity spanning a quantitative spectrum, from mild, transient outbreaks to more persistent, severe forms of the condition. Moderate to severe disease poses a substantial global burden arising from both the physical and psychological impacts of this highly visible condition. The analytical approach taken in this study aimed to address the impact of variation in the dichotomisation of acne case control status, driven by ascertainment and study design, on effect size estimates across independent genetic association studies of acne. Through a fixed intercept meta-regression framework, we combined evidence genome-wide for association with acne across studies in which case-control status had been ascertained in different settings, allowing for different severity threshold definitions. Across a combined sample of 73,997 cases and 1,103,940 controls of European, South Asian and African American ancestry we identify genetic variation at 165 genomic loci that influence acne risk. There is evidence for both shared and ancestry specific components to the genetic susceptibility to acne and for sex differences in the magnitude of effect of risk alleles at three loci. We observe that common genetic variation explains 13.4% of acne heritability on the liability scale. Consistent with the hypothesis that genetic risk primarily operates at the level of individual pilosebaceous units, a polygenic score derived from this case-control study of acne susceptibility is associated with both self-reported and clinically assessed acne severity in adolescence, further strengthening the link between genetic risk and disease severity. Prioritisation of causal genes at the identified acne risk loci, provides genetic validation of the targets of established and emerging acne therapies, including retinoid treatments. The identified acne risk loci are enriched for genes encoding downstream effectors of RXRA signalling, including SOX9 and components of the WNT and p53 pathways. Illustrating that the control of stem cell lineage plasticity and cellular fate are important mechanisms through which genetic variation influences acne susceptibility within the pilosebaceous unit.

Journal Article↗

PubMed2025

A simple approach for multiple observations improves power to detect genetic effects and genomic prediction accuracy.

Many datasets, including widely used biobanks, have more than one observation of numerous phenotypes for at least a portion of their sample. The majority of GWAS utilize only a single observation per individual, even when more than one observation may be available, and apply a standard model in which the additive allelic effect being estimated is assumed to be constant across the age or time range in the sample. Here, we test a set of simple approaches to utilize multiple observations per individual, under this same assumption. We find that utilizing the mean or median of the available observations rather than a single observation improves power to detect associated loci and enriched gene sets and yields higher out-of-sample polygenic score prediction accuracy. Despite growing biobanks, many deeply phenotyped samples are relatively small but have multiple observations. While explicitly modeling age- or time-dependent genetic effects can estimate time- or age-specific genetic effects, most GWAS apply a standard, additive-only model; a simple approach of using the mean or median can improve power by reducing "noise" in the phenotype, utilize standard, optimized software, and be particularly impactful for smaller samples, including samples of diverse genetic ancestry currently existing in widely used biobanks.

Journal Article↗

PubMed2025

Genome-wide association study of adolescent-onset depression.

Adolescent depression is a heritable psychiatric condition with rising global prevalence and severe long-term outcomes, yet its biological underpinnings remain poorly understood. We conducted the first genome-wide association study of adolescent-onset depression, comprising 102,428 cases (diagnosis or clinical symptom thresholds) and 286,911 controls, including diverse ancestries. Cross-ancestry meta-analysis identified 52 independent variants across 17 loci; European-only analysis found 61 variants at 29 loci, with a SNP-based heritability of 9.8%. Comparative analyses revealed two genes unique to adolescent-onset versus lifetime depression, enriched in neuronal subtypes, and two genes as potential drug repurposing targets. Polygenic scores were associated with adolescent-onset depression across ancestries, persistent depression trajectories, more severe outcomes, as well as reduced cortical volume, surface area and white matter integrity. Genetic correlation and Mendelian randomisation analyses support shared genetic liability and causal links with early puberty and modifiable health and behavioural risk factors. These findings uncover novel genetic loci and refine biological pathways underlying adolescent-onset depression, revealing age-specific mechanisms and early intervention opportunities.

Journal Article↗

PubMed2026

Agnostic polygenic prediction of weight loss after bariatric surgery.

A large interindividual variability in weight loss outcomes following bariatric surgery is reported. To ensure optimal management of patients, it is crucial to accurately identify candidates most likely to benefit the most from the intervention. Since genetic variants largely contribute to surgery response, polygenic scores (PGS) derived from genome-wide association studies (GWAS) could constitute valuable tools for clinical decision making. We developed and evaluated PGS to predict the weight loss response in 540 patients with a body mass index (BMI) of 35 kg/m2 or higher who underwent biliopancreatic diversion with duodenal switch. Summary statistics derived from BMI-derived GWAS, together with summary statistics from previously published GWAS of BMI and adiposity features, were used to construct, evaluate, and benchmark weight loss PGS. The full-adjusted BMI PGS model built in the entire cohort explained 39.6% of the mean-over-time excessive body weight loss (%EBWL), while the BMI-PGS built in the training dataset explained 38.9%. All benchmarked PGS based on BMI showed a significant relationship with mean-over-time %EBWL. These findings highlight the potential of BMI PGS in predicting weight loss after bariatric surgery and support their use as promising tools to improve the effectiveness of future antiobesity treatments.

Humans↗

PubMed2024

Polycystic Ovary Syndrome Physiologic Pathways Implicated Through Clustering of Genetic Loci.

CONTEXT: Polycystic ovary syndrome (PCOS) is a heterogeneous disorder, with disease loci identified from genome-wide association studies (GWAS) having largely unknown relationships to disease pathogenesis. OBJECTIVE: This work aimed to group PCOS GWAS loci into genetic clusters associated with disease pathophysiology. METHODS: Cluster analysis was performed for 60 PCOS-associated genetic variants and 49 traits using GWAS summary statistics. Cluster-specific PCOS partitioned polygenic scores (pPS) were generated and tested for association with clinical phenotypes in the Mass General Brigham Biobank (MGBB, N = 62 252). Associations with clinical outcomes (type 2 diabetes [T2D], coronary artery disease [CAD], and female reproductive traits) were assessed using both GWAS-based pPS (DIAMANTE, N = 898,130, CARDIOGRAM/UKBB, N = 547 261) and individual-level pPS in MGBB. RESULTS: Four PCOS genetic clusters were identified with top loci indicated as following: (i) cluster 1/obesity/insulin resistance (FTO); (ii) cluster 2/hormonal/menstrual cycle changes (FSHB); (iii) cluster 3/blood markers/inflammation (ATXN2/SH2B3); (iv) cluster 4/metabolic changes (MAF, SLC38A11). Cluster pPS were associated with distinct clinical traits: Cluster 1 with increased body mass index (P = 6.6 × 10-29); cluster 2 with increased age of menarche (P = 1.5 × 10-4); cluster 3 with multiple decreased blood markers, including mean platelet volume (P = 3.1 ×10-5); and cluster 4 with increased alkaline phosphatase (P = .007). PCOS genetic clusters GWAS-pPSs were also associated with disease outcomes: cluster 1 pPS with increased T2D (odds ratio [OR] 1.07; P = 7.3 × 10-50), with replication in MGBB all participants (OR 1.09, P = 2.7 × 10-7) and females only (OR 1.11, 4.8 × 10-5). CONCLUSION: Distinct genetic backgrounds in individuals with PCOS may underlie clinical heterogeneity and disease outcomes.

Humans↗

PubMed2026

Genome-Wide Association Study of Contrast Media Hypersensitivity in Japanese Patients.

Iodinated contrast media (ICM), commonly used in radiological tests such as coronary angiography, can cause hypersensitivity reactions (HSRs). The mechanism of ICM HSRs is thought to be complex; while IgE-mediated allergic reactions appear to be involved, the details remain unclear. This study aims to elucidate the pathogenesis of ICM HSRs through genetic analysis. To date, a few case-control studies have been conducted exclusively on East Asians, but the results have been inconclusive and have not been replicated.We conducted a multistage GWAS for ICM HSRs in Japanese individuals. The study population comprised 153 cases with ICM HSRs (ranging from mild to severe form), 632 controls with no history of ICM-induced allergies, and < 38,721 individuals from the general population. We identified genome-wide significant association signals in the HLA region and also found that these signals originated from the three HLA alleles-B*52:01, C*12:02, DRB1*15:02-previously reported in a Korean candidate gene study. Using instrumental variable analysis with a polygenic score for pediatric asthma (PGSasthma) as a proxy, we demonstrated that ICM HSRs are associated with the allergic predisposition thought to be shared by asthma and ICM HSRs. There was a significant difference in the distribution of PGSasthma between ICM HSR patients and non-disease controls (per-SD odds ratio: 1.26, P = 0.021).Our genome-wide approach shows that HLA alleles are among the genetic factors underlying ICM HSRs. Furthermore, it provides evidence for the potential usefulness of predicting the risk of developing ICM HSRs based on allergic predisposition.

Allergic predisposition↗

PubMed2025

GWAS highlights the neuronal contribution to multiple sclerosis susceptibility.

Multiple Sclerosis (MS) is a chronic inflammatory and neurodegenerative disease affecting the brain and spinal cord. Genetic studies have identified many risk loci, that were thought to primarily impact immune cells and microglia. Here, we performed a multi-ancestry genome-wide association study with 20,831 MS and 729,220 control participants, identifying 236 susceptibility variants outside the Major Histocompatibility Complex, including four novel loci. We derived a polygenic score for MS and, optimized for European ancestry, it is informative for African-American and Latino participants. Integrating single-cell data from blood and brain tissue, we identified 76 genes affected by MS risk variants. Notably, while T cells showed the strongest enrichment, inhibitory neurons emerged as a key cell type. The expression of IL7 and STAT3 are affected only in inhibitory neurons, highlighting the importance of neuronal and glial dysfunction in MS susceptibility.

Journal Article↗

PubMed2024

Increased Genetic Risk for β-Cell Failure Is Associated With β-Cell Function Decline in People With Prediabetes.

Partitioned polygenic scores (pPS) have been developed to capture pathophysiologic processes underlying type 2 diabetes (T2D). We investigated the association of T2D pPS with diabetes-related traits and T2D incidence in the Diabetes Prevention Program. We generated five T2D pPS (β-cell, proinsulin, liver/lipid, obesity, lipodystrophy) in 2,647 participants randomized to intensive lifestyle, metformin, or placebo arms. Associations were tested with general linear models and Cox regression with adjustment for age, sex, and principal components. Sensitivity analyses included adjustment for BMI. Higher β-cell pPS was associated with lower insulinogenic index and corrected insulin response at 1-year follow-up with adjustment for baseline measures (effect per pPS SD -0.04, P = 9.6 × 10-7, and -8.45 μU/mg, P = 5.6 × 10-6, respectively) and with increased diabetes incidence with adjustment for BMI at nominal significance (hazard ratio 1.10 per SD, P = 0.035). The liver/lipid pPS was associated with reduced 1-year baseline-adjusted triglyceride levels (effect per SD -4.37, P = 0.001). There was no significant interaction between T2D pPS and randomized groups. The remaining pPS were associated with baseline measures only. We conclude that despite interventions for diabetes prevention, participants with a high genetic burden of the β-cell cluster pPS had worsening in measures of β-cell function.

Humans↗

PubMed2026

Multi-omic signatures of genetic mechanisms inform on type 2 diabetes biology and patient heterogeneity.

Type 2 diabetes (T2D) is a heterogeneous disease shaped by genetic pathways related to insulin resistance and β-cell dysfunction, but how this heterogeneity is reflected molecularly remains unclear. We integrated partitioned polygenic scores (pPS) with proteomic and metabolomic profiling to define molecular signatures of T2D and their clinical relevance. We analyzed UK Biobank participants with genomic, proteomic, and metabolomic data. In a disease-free training subset, we used LASSO regression to identify multi-omic signatures associated with each pPS by jointly modeling proteins and metabolites. In an independent testing set, we constructed multi-omic scores and examined their associations with clinical traits and diabetes-related outcomes. Mediation analyses were used to investigate putative causal pathways. Key findings were evaluated in the Multi-Ethnic Study of Atherosclerosis (MESA). We identified distinct multi-omic signatures that capture the molecular architecture of T2D genetic risk across physiological subtypes. Compared with genetic scores alone, multi-omic pPS showed larger effect sizes and better disease discrimination. These scores recapitulated subtype-specific physiology and were associated with T2D risk. The Beta-Cell 2 multi-omic score showed marked stratification for insulin use, which was replicated in MESA, where it also predicted future insulin use. Mediation analyses implicated lipoprotein remodeling and fatty acid metabolism in the Lipodystrophy 1 cluster, accounting for 30-45% of the total effect of pPS on T2D risk. Integrating process-specific genetic risk with circulating multi-omic profiles reveals biologically distinct endotypes of T2D and supports a framework for improved patient stratification and risk assessment.

Journal Article↗

PubMed2026

Mapping Focal and Generalized Effects of Common Genetic Variants on Human Brain Structure.

Genome-wide association studies (GWAS) have advanced the quest to understand how specific genetic variants influence human brain structure and function. Recent work has identified hundreds of common variants associated with subcortical brain volumes, sparking interest in how these genetic markers overlap across brain networks. While this can be estimated by hierarchical clustering of the genetic correlation matrix to identify modular patterns of shared architecture, no brain-wide maps of these effects are available. To address this, we computed polygenic scores (PGS) from loci associated with ten brain volume regions of interest (ROIs): nine major subcortical structures and intracranial volume, with each locus weighted by its association with regional volume. In an independent sample from the discovery GWAS, we performed large-scale segmentation of 3D volumetric T1-weighted MRI scans using voxel-based morphometry (VBM) to map 3D profile of regions where gray matter volume (GMV) was associated with each PGS. We found statistically significant, localized effects for PGS defined for the amygdala, thalamus, and basal ganglia, but PGS for brainstem volume was associated with widespread differences throughout the brain. These brain-wide maps reveal patterns consistent with both localized and distributed genetic influences, offering a novel approach to interpret the genomic architecture of brain structure.

GWAS↗