👤 Ole A Andreassen

A narrow range of food consumption and/or restricted eating is a core feature of avoidant/restrictive food intake (ARFI) disorder. However, there is limited knowledge of developmental characteristics of children with ARFI and its etiological influences, which constrains research, prevention, and intervention efforts. To estimate the prevalence of ARFI phenotypes in a population-based sample, examine developmental characteristics across childhood, and investigate the genetic architecture of ARFI using genome-wide association analyses. This preregistered study used data from children born from 1999 to 2009 in the population-based Norwegian Mother, Father, and Child Cohort Study (MoBa), with mother-reported data on ARFI symptoms at 3 and 8 years and linkage with diagnostic data from population health registries. Data were analyzed from March 2024 to May 2025. Multiple items were used to identify children with broad ARFI. These children were subclassified into 3 groups based on symptom persistence: ARFI-broad transient (only at age 3 years), emergent (only at age 8 years), and persistent (ages 3 and 8 years). Children in these groups with 1 or more indicators of clinical significance (eg, nutritional deficiency) were further classified into ARFI-clinical subgroups. ARFI groups were compared across developmental characteristics from 6 months to 14 years. Genome-wide methods were used to examine single-nucleotide variant (SNV) heritability (SNV-h2), conduct genetic association analyses, and quantify genetic correlations with other phenotypes. Of 35 751 children with available ARFI assessments at 3 and 8 years (18 236 male [51%]), the prevalence of ARFI-broad persistent, transient, and emergent was 2129 (6.0%), 6338 (17.7%), and 3001 (8.4%), respectively. The prevalence of ARFI-clinical persistent, transient, and emergent was 624 (1.8%), 1157 (3.2%), and 484 (1.4%), respectively (2265 [6.3%] overall). Children with ARFI-broad persistent exhibited more developmental difficulties compared with children with no ARFI. SNV-h2 ranged from 8% to 16%. Two independent genome-wide significant loci were identified. For ARFI-clinical, a significant association was identified with ADCY3 (z = 5.42; P = 3.03 × 10-8). Small to moderate genetic correlations were observed for ARFI-broad, ARFI-clinical and mental health, cognitive/educational, anthropometric, food-associated, and gastrointestinal disorder phenotypes. This cohort study found that the prevalence of ARFI in the general pediatric population was substantial, and affected children had an associated elevated risk of developmental difficulties across multiple domains. Findings suggest a need for broad support interventions and advance understanding of the genetic underpinnings of ARFI. Show less

Cardiovascular (CV)- and lifestyle-associated risk factors (RFs) are increasingly recognized as important for Alzheimer's disease (AD) pathogenesis. Beyond the ε4 allele of apolipoprotein E (APOE), comparatively little is known about whether CV-associated genes also increase risk for AD. Using large genome-wide association studies and validated tools to quantify genetic overlap, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with AD and one or more CV-associated RFs, namely body mass index (BMI), type 2 diabetes (T2D), coronary artery disease (CAD), waist hip ratio (WHR), total cholesterol (TC), triglycerides (TG), low-density (LDL) and high-density lipoprotein (HDL). In fold enrichment plots, we observed robust genetic enrichment in AD as a function of plasma lipids (TG, TC, LDL, and HDL); we found minimal AD genetic enrichment conditional on BMI, T2D, CAD, and WHR. Beyond APOE, at conjunction FDR < 0.05 we identified 90 SNPs on 19 different chromosomes that were jointly associated with AD and CV-associated outcomes. In meta-analyses across three independent cohorts, we found four novel loci within MBLAC1 (chromosome 7, meta-p = 1.44 × 10 Show less

Schizophrenia (SCZ) is associated with differences in subcortical brain volumes and intracranial volume (ICV). However, little is known about the underlying etiology of these brain alterations. Here, we explored whether brain structure volumes and SCZ share genetic risk factors. Using conditional false discovery rate (FDR) analysis, we integrated genome-wide association study (GWAS) data on SCZ (n = 82315) and GWAS data on 7 subcortical brain volumes and ICV (n = 11840). By conditioning the FDR on overlapping associations, this statistical approach increases power to discover genetic loci. To assess the credibility of our approach, we studied the identified loci in larger GWAS samples on ICV (n = 26577) and hippocampal volume (n = 26814). We observed polygenic overlap between SCZ and volumes of hippocampus, putamen, and ICV. Based on conjunctional FDR < 0.05, we identified 2 loci shared between SCZ and ICV implicating genes FOXO3 (rs10457180) and ITIH4 (rs4687658), 2 loci shared between SCZ and hippocampal volume implicating SLC4A10 (rs4664442) and SPATS2L (rs1653290), and 2 loci shared between SCZ and volume of putamen implicating DCC (rs4632195) and DLG2 (rs11233632). The loci shared between SCZ and hippocampal volume or ICV had not reached significance in the primary GWAS on brain phenotypes. Proving our point of increased power, 2 loci did reach genome-wide significance with ICV (rs10457180) and hippocampal volume (rs4664442) in the larger GWAS. Three of the 6 identified loci are novel for SCZ. Altogether, the findings provide new insights into the relationship between SCZ and brain structure volumes, suggesting that their genetic architectures are not independent. Show less

Recent genome-wide association studies (GWAS) and pathway analyses supported long-standing observations of an association between immune-mediated diseases and Parkinson disease (PD). The post-GWAS era provides an opportunity for cross-phenotype analyses between different complex phenotypes. To test the hypothesis that there are common genetic risk variants conveying risk of both PD and autoimmune diseases (ie, pleiotropy) and to identify new shared genetic variants and their pathways by applying a novel statistical framework in a genome-wide approach. Using the conjunction false discovery rate method, this study analyzed GWAS data from a selection of archetypal autoimmune diseases among 138 511 individuals of European ancestry and systemically investigated pleiotropy between PD and type 1 diabetes, Crohn disease, ulcerative colitis, rheumatoid arthritis, celiac disease, psoriasis, and multiple sclerosis. NeuroX data (6927 PD cases and 6108 controls) were used for replication. The study investigated the biological correlation between the top loci through protein-protein interaction and changes in the gene expression and methylation levels. The dates of the analysis were June 10, 2015, to March 4, 2017. The primary outcome was a list of novel loci and their pathways involved in PD and autoimmune diseases. Genome-wide conjunctional analysis identified 17 novel loci at false discovery rate less than 0.05 with overlap between PD and autoimmune diseases, including known PD loci adjacent to GAK, HLA-DRB5, LRRK2, and MAPT for rheumatoid arthritis, ulcerative colitis and Crohn disease. Replication confirmed the involvement of HLA, LRRK2, MAPT, TRIM10, and SETD1A in PD. Among the novel genes discovered, WNT3, KANSL1, CRHR1, BOLA2, and GUCY1A3 are within a protein-protein interaction network with known PD genes. A subset of novel loci was significantly associated with changes in methylation or expression levels of adjacent genes. The study findings provide novel mechanistic insights into PD and autoimmune diseases and identify a common genetic pathway between these phenotypes. The results may have implications for future therapeutic trials involving anti-inflammatory agents. Show less

Deletions within the neurexin 1 gene (NRXN1; 2p16.3) are associated with autism and have also been reported in two families with schizophrenia. We examined NRXN1, and the closely related NRXN2 and NRXN3 genes, for copy number variants (CNVs) in 2977 schizophrenia patients and 33 746 controls from seven European populations (Iceland, Finland, Norway, Germany, The Netherlands, Italy and UK) using microarray data. We found 66 deletions and 5 duplications in NRXN1, including a de novo deletion: 12 deletions and 2 duplications occurred in schizophrenia cases (0.47%) compared to 49 and 3 (0.15%) in controls. There was no common breakpoint and the CNVs varied from 18 to 420 kb. No CNVs were found in NRXN2 or NRXN3. We performed a Cochran-Mantel-Haenszel exact test to estimate association between all CNVs and schizophrenia (P = 0.13; OR = 1.73; 95% CI 0.81-3.50). Because the penetrance of NRXN1 CNVs may vary according to the level of functional impact on the gene, we next restricted the association analysis to CNVs that disrupt exons (0.24% of cases and 0.015% of controls). These were significantly associated with a high odds ratio (P = 0.0027; OR 8.97, 95% CI 1.8-51.9). We conclude that NRXN1 deletions affecting exons confer risk of schizophrenia. Show less