Early Life and Childhood Environmental Exposures, More Than Genetic Predisposition, Influence Age of Diagnosis in a Diverse Cohort of 2952 Patients With IBD.

BACKGROUND AND AIMS: Inflammatory bowel disease (IBD) develops from a combination of genetic and environmental factors. The aim of this study was to determine the contribution of established environmental risk factors and genetic risk on age of IBD diagnosis in a diverse cohort. METHODS: IBD patients in clinic completed detailed questionnaires. Blood was drawn for genetic analysis. Environmental risk factors and age of diagnosis were analyzed by ethnicity (Hispanic/Latinx or non-Hispanic White [NHW] individuals) and IBD subtype (ulcerative colitis or Crohn's disease [CD]). Weighted genetic risk scores and environmental risk scores were developed. We examined the relationship between environmental risk scores, genetic risk scores, and age of diagnosis. RESULTS: A total of 2952 patients were included: 58.9% had CD. A total of 46.83% were of Hispanic background. Early life exposures like cesarean delivery and being born in a developed country were associated with a younger age of IBD diagnosis. Childhood exposures such as frequent plastic water bottle use and having more than 1 bathroom at home were associated with a younger age of IBD. Hispanic and NHW individuals shared similar susceptibilities to environmental exposures. Environmental factors explained 21% of the variance in age of CD diagnosis and 39% in ulcerative colitis. In models incorporating genetic risk score and environmental risk score, the environment was the only significant factor associated with younger age of IBD diagnosis in all groups. CONCLUSIONS: Early life and childhood exposures impact IBD diagnosis and influence Hispanic and NHW individuals similarly. A cumulative environmental risk score contributes more to age of IBD diagnosis than genetic risk.

An evaluation of supervised methods for identifying differentially methylated regions in Illumina methylation arrays.

Epigenome-wide association studies (EWASs) have become increasingly popular for studying DNA methylation (DNAm) variations in complex diseases. The Illumina methylation arrays provide an economical, high-throughput and comprehensive platform for measuring methylation status in EWASs. A number of software tools have been developed for identifying disease-associated differentially methylated regions (DMRs) in the epigenome. However, in practice, we found these tools typically had multiple parameter settings that needed to be specified and the performance of the software tools under different parameters was often unclear. To help users better understand and choose optimal parameter settings when using DNAm analysis tools, we conducted a comprehensive evaluation of 4 popular DMR analysis tools under 60 different parameter settings. In addition to evaluating power, precision, area under precision-recall curve, Matthews correlation coefficient, F1 score and type I error rate, we also compared several additional characteristics of the analysis results, including the size of the DMRs, overlap between the methods and execution time. The results showed that none of the software tools performed best under their default parameter settings, and power varied widely when parameters were changed. Overall, the precision of these software tools were good. In contrast, all methods lacked power when effect size was consistent but small. Across all simulation scenarios, comb-p consistently had the best sensitivity as well as good control of false-positive rate.

coMethDMR: accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies with continuous phenotypes.

Recent technology has made it possible to measure DNA methylation profiles in a cost-effective and comprehensive genome-wide manner using array-based technology for epigenome-wide association studies. However, identifying differentially methylated regions (DMRs) remains a challenging task because of the complexities in DNA methylation data. Supervised methods typically focus on the regions that contain consecutive highly significantly differentially methylated CpGs in the genome, but may lack power for detecting small but consistent changes when few CpGs pass stringent significance threshold after multiple comparison. Unsupervised methods group CpGs based on genomic annotations first and then test them against phenotype, but may lack specificity because the regional boundaries of methylation are often not well defined. We present coMethDMR, a flexible, powerful, and accurate tool for identifying DMRs. Instead of testing all CpGs within a genomic region, coMethDMR carries out an additional step that selects co-methylated sub-regions first. Next, coMethDMR tests association between methylation levels within the sub-region and phenotype via a random coefficient mixed effects model that models both variations between CpG sites within the region and differential methylation simultaneously. coMethDMR offers well-controlled Type I error rate, improved specificity, focused testing of targeted genomic regions, and is available as an open-source R package.

An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer's Disease.

Background: The X chromosome is often omitted in disease association studies despite containing thousands of genes that may provide insight into well-known sex differences in the risk of Alzheimer's disease (AD). Objective: To model the expression of X chromosome genes and evaluate their impact on AD risk in a sex-stratified manner. Methods: Using elastic net, we evaluated multiple modeling strategies in a set of 175 whole blood samples and 126 brain cortex samples, with whole genome sequencing and RNA-seq data. SNPs (MAF > 0.05) within the cis-regulatory window were used to train tissue-specific models of each gene. We apply the best models in both tissues to sex-stratified summary statistics from a meta-analysis of Alzheimer's Disease Genetics Consortium (ADGC) studies to identify AD-related genes on the X chromosome. Results: Across different model parameters, sample sex, and tissue types, we modeled the expression of 217 genes (95 genes in blood and 135 genes in brain cortex). The average model R2 was 0.12 (range from 0.03 to 0.34). We also compared sex-stratified and sex-combined models on the X chromosome. We further investigated genes that escaped X chromosome inactivation (XCI) to determine if their genetic regulation patterns were distinct. We found ten genes associated with AD at p < 0.05, with only ARMCX6 in female brain cortex (p = 0.008) nearing the significance threshold after adjusting for multiple testing (α = 0.002). Conclusions: We optimized the expression prediction of X chromosome genes, applied these models to sex-stratified AD GWAS summary statistics, and identified one putative AD risk gene, ARMCX6.

Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC v1.0 BeadChip microarrays.

DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC v1.0 arrays. We conducted a comprehensive assessment of the EPIC v1.0 array probe reliability using 69 blood DNA samples, each measured twice, generated by the Alzheimer's Disease Neuroimaging Initiative study. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliability information for probes on the EPIC v1.0 array, will serve as a valuable resource for future DNAm studies.

An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer's Disease.

Background: The X chromosome is often omitted in disease association studies despite containing thousands of genes which may provide insight into well-known sex differences in the risk of Alzheimer's Disease. Objective: To model the expression of X chromosome genes and evaluate their impact on Alzheimer's Disease risk in a sex-stratified manner. Methods: Using elastic net, we evaluated multiple modeling strategies in a set of 175 whole blood samples and 126 brain cortex samples, with whole genome sequencing and RNA-seq data. SNPs (MAF>0.05) within the cis-regulatory window were used to train tissue-specific models of each gene. We apply the best models in both tissues to sex-stratified summary statistics from a meta-analysis of Alzheimer's disease Genetics Consortium (ADGC) studies to identify AD-related genes on the X chromosome. Results: Across different model parameters, sample sex, and tissue types, we modeled the expression of 217 genes (95 genes in blood and 135 genes in brain cortex). The average model R2 was 0.12 (range from 0.03 to 0.34). We also compared sex-stratified and sex-combined models on the X chromosome. We further investigated genes that escaped X chromosome inactivation (XCI) to determine if their genetic regulation patterns were distinct. We found ten genes associated with AD at p 0.05, with only ARMCX6 in female brain cortex (p = 0.008) nearing the significance threshold after adjusting for multiple testing (α = 0.002). Conclusions: We optimized the expression prediction of X chromosome genes, applied these models to sex-stratified AD GWAS summary statistics, and identified one putative AD risk gene, ARMCX6.

Distinct CSF biomarker-associated DNA methylation in Alzheimer's disease and cognitively normal subjects.

Background Growing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis. Methods We performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aß 42 , phosphorylated tau 181 (pTau 181 ), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset. Results We identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau 181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker. Conclusions Our study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.

Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC BeadChip microarrays.

DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC arrays. We conducted a comprehensive assessment of the EPIC array probe reliability using 138 duplicated blood DNAm samples generated by the Alzheimer's Disease Neuroimaging Initiative study. We introduced a novel statistical measure, the modified intraclass correlation, to better account for the disagreement in duplicate measurements. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliable information for probes on the EPIC array, will serve as a valuable resource for future DNAm studies.

Distinct CSF biomarker-associated DNA methylation in Alzheimer's disease and cognitively normal subjects.

BACKGROUND: Growing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis. METHODS: We performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aß42, phosphorylated tau181 (pTau181), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset. RESULTS: We identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker. CONCLUSIONS: Our study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.

Hepatic Arterioportal Fistula Following Liver Trauma: Case Series and Review of the Literature.

PURPOSE: Hepatic arterioportal fistula (HAPF) is an uncommon complication of hepatic trauma, which can manifest with abdominal pain and the sequelae of portal hypertension months to years after injury. The purpose of this study is to present cases of HAPF from our busy urban trauma center and make recommendations for management. METHODS: One hundred and twenty-seven patients with high-grade penetrating liver injuries (American Association for the Surgery of Trauma [AAST] - Grades IV-V) between January 2019 and October 2022 were retrospectively reviewed. Five patients were identified with an acute hepatic arterioportal fistula following abdominal trauma from our ACS-verified adult Level 1 trauma center. Institutional experience with overall surgical management is described and reviewed with the current literature. RESULTS: Four of our patients presented in hemorrhagic shock requiring emergent operative intervention. The first patient had postoperative angiography and coil embolization of the HAPF. Patients 2 through 4 underwent damage control laparotomy with temporary abdominal closure followed by postoperative transarterial embolization with gelatin sponge particles (Gelfoam) or combined Gelfoam/n-butyl cyanoacrylate. The final patient went directly for angiography and Gelfoam embolization after identification of the HAPF. All 5 patients had resolution of HAPF on follow-up imaging with continued post management for traumatic injuries. CONCLUSION: Hepatic arterioportal fistula can present as a complication of hepatic injury and manifest with significant hemodynamic aberrations. Although surgical intervention was required to achieve hemorrhage control in almost all cases, management of HAPF in the setting of high-grade liver injuries was achieved successfully with modern endovascular techniques. A multidisciplinary approach to such injuries is necessary to optimize care in the acute setting following traumatic injury.

Genome-wide association study of executive function in a multi-ethnic cohort implicates LINC01362: Results from the northern Manhattan study.

Executive function is a cognitive domain with sizable heritability representing higher-order cognitive abilities. Genome-wide association studies (GWAS) of executive function are sparse, particularly in populations underrepresented in medical research. We performed a GWAS on a composite measure of executive function that included measures of mental flexibility and reasoning using data from the Northern Manhattan Study, a racially and ethnically diverse cohort (N = 1077, 69% Hispanic, 17% non-Hispanic Black and 14% non-Hispanic White). Four SNPs located in the long intergenic non-protein coding RNA 1362 gene, LINC01362, on chromosome 1p31.1, were significantly associated with the composite measure of executive function in this cohort (top SNP rs2788328, ß = 0.22, p = 3.1 × 10-10). The associated SNPs have been shown to influence expression of the tubulin tyrosine ligase like 7 gene, TTLL7 and the protein kinase CAMP-activated catalytic subunit beta gene, PRKACB, in several regions of the brain involved in executive function. Together, these findings present new insight into the genetic underpinnings of executive function in an understudied population.

Distinct sex-specific DNA methylation differences in Alzheimer's disease.

BACKGROUND: Sex is increasingly recognized as a significant factor contributing to the biological and clinical heterogeneity in AD. There is also growing evidence for the prominent role of DNA methylation (DNAm) in Alzheimer's disease (AD). METHODS: We studied sex-specific DNA methylation differences in the blood samples of AD subjects compared to cognitively normal subjects, by performing sex-specific meta-analyses of two large blood-based epigenome-wide association studies (ADNI and AIBL), which included DNA methylation data for a total of 1284 whole blood samples (632 females and 652 males). Within each dataset, we used two complementary analytical strategies, a sex-stratified analysis that examined methylation to AD associations in male and female samples separately, and a methylation-by-sex interaction analysis that compared the magnitude of these associations between different sexes. After adjusting for age, estimated immune cell type proportions, batch effects, and correcting for inflation, the inverse-variance fixed-effects meta-analysis model was used to identify the most consistent DNAm differences across datasets. In addition, we also evaluated the performance of the sex-specific methylation-based risk prediction models for AD diagnosis using an independent external dataset. RESULTS: In the sex-stratified analysis, we identified 2 CpGs, mapped to the PRRC2A and RPS8 genes, significantly associated with AD in females at a 5% false discovery rate, and an additional 25 significant CpGs (21 in females, 4 in males) at P-value < 1×10-5. In methylation-by-sex interaction analysis, we identified 5 significant CpGs at P-value < 10-5. Out-of-sample validations using the AddNeuroMed dataset showed in females, the best logistic prediction model included age, estimated immune cell-type proportions, and methylation risk scores (MRS) computed from 9 of the 23 CpGs identified in AD vs. CN analysis that are also available in AddNeuroMed dataset (AUC = 0.74, 95% CI: 0.65-0.83). In males, the best logistic prediction model included only age and MRS computed from 2 of the 5 CpGs identified in methylation-by-sex interaction analysis that are also available in the AddNeuroMed dataset (AUC = 0.70, 95% CI: 0.56-0.82). CONCLUSIONS: Overall, our results show that the DNA methylation differences in AD are largely distinct between males and females. Our best-performing sex-specific methylation-based prediction model in females performed better than that for males and additionally included estimated cell-type proportions. The significant discriminatory classification of AD samples with our methylation-based prediction models demonstrates that sex-specific DNA methylation could be a predictive biomarker for AD. As sex is a strong factor underlying phenotypic variability in AD, the results of our study are particularly relevant for a better understanding of the epigenetic architecture that underlie AD and for promoting precision medicine in AD.

Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer's disease.

To better understand DNA methylation in Alzheimer's disease (AD) from both mechanistic and biomarker perspectives, we performed an epigenome-wide meta-analysis of blood DNA methylation in two large independent blood-based studies in AD, the ADNI and AIBL studies, and identified 5 CpGs, mapped to the SPIDR, CDH6 genes, and intergenic regions, that are significantly associated with AD diagnosis. A cross-tissue analysis that combined these blood DNA methylation datasets with four brain methylation datasets prioritized 97 CpGs and 10 genomic regions that are significantly associated with both AD neuropathology and AD diagnosis. An out-of-sample validation using the AddNeuroMed dataset showed the best performing logistic regression model includes age, sex, immune cell type proportions, and methylation risk score based on prioritized CpGs in cross-tissue analysis (AUC = 0.696, 95% CI: 0.616 - 0.770, P-value = 2.78 × 10-5). Our study offers new insights into epigenetics in AD and provides a valuable resource for future AD biomarker discovery.

Ancestral risk modification for multiple sclerosis susceptibility detected across the Major Histocompatibility Complex in a multi-ethnic population.

The Major Histocompatibility Complex (MHC) makes the largest genetic contribution to multiple sclerosis (MS) susceptibility, with 32 independent effects across the region explaining 20% of the heritability in European populations. Variation is high across populations with allele frequency differences and population-specific risk alleles identified. We sought to identify MHC-specific MS susceptibility variants and assess the effect of ancestral risk modification within 2652 Latinx and Hispanic individuals as well as 2435 Black and African American individuals. We have identified several novel susceptibility alleles which are rare in European populations including HLA-B*53:01, and we have utilized the differing linkage disequilibrium patterns inherent to these populations to identify an independent role for HLA-DRB1*15:01 and HLA-DQB1*06:02 on MS risk. We found a decrease in Native American ancestry in MS cases vs controls across the MHC, peaking near the previously identified MICB locus with a decrease of ~5.5% in Hispanics and ~0.4% in African Americans. We have identified several susceptibility variants, including within the MICB gene region, which show global ancestry risk modification and indicate ancestral differences which may be due in part to correlated environmental factors. We have also identified several susceptibility variants for which MS risk is modified by local ancestry and indicate true ancestral genetic differences; including HLA-DQB1*06:02 for which MS risk for European allele carriers is almost two times the risk for African allele carriers. These results validate the importance of investigating MS susceptibility at an ancestral level and offer insight into the epidemiology of MS phenotypic diversity.

Sex-specific DNA methylation differences in Alzheimer's disease pathology.

Sex is an important factor that contributes to the clinical and biological heterogeneities in Alzheimer's disease (AD), but the regulatory mechanisms underlying sex disparity in AD are still not well understood. DNA methylation is an important epigenetic modification that regulates gene transcription and is known to be involved in AD. We performed the first large-scale sex-specific meta-analysis of DNA methylation differences in AD neuropathology, by re-analyzing four recent epigenome-wide association studies totaling more than 1000 postmortem prefrontal cortex brain samples using a uniform analytical pipeline. For each cohort, we employed two complementary analytical strategies, a sex-stratified analysis that examined methylation-Braak stage associations in male and female samples separately, and a sex-by-Braak stage interaction analysis that compared the magnitude of these associations between different sexes. Our analysis uncovered 14 novel CpGs, mapped to genes such as TMEM39A and TNXB that are associated with the AD Braak stage in a sex-specific manner. TMEM39A is known to be involved in inflammation, dysregulated type I interferon responses, and other immune processes. TNXB encodes tenascin proteins, which are extracellular matrix glycoproteins demonstrated to modulate synaptic plasticity in the brain. Moreover, for many previously implicated genes in AD neuropathology, such as MBP and AZU1, our analysis provided the new insights that they were predominately driven by effects in only one sex. These sex-specific DNA methylation differences were enriched in divergent biological processes such as integrin activation in females and complement activation in males. Our study implicated multiple new loci and biological processes that affected AD neuropathology in a sex-specific manner.

Epigenome-wide meta-analysis of DNA methylation differences in prefrontal cortex implicates the immune processes in Alzheimer's disease.

DNA methylation differences in Alzheimer's disease (AD) have been reported. Here, we conducted a meta-analysis of more than 1000 prefrontal cortex brain samples to prioritize the most consistent methylation differences in multiple cohorts. Using a uniform analysis pipeline, we identified 3751 CpGs and 119 differentially methylated regions (DMRs) significantly associated with Braak stage. Our analysis identified differentially methylated genes such as MAMSTR, AGAP2, and AZU1. The most significant DMR identified is located on the MAMSTR gene, which encodes a cofactor that stimulates MEF2C. Notably, MEF2C cooperates with another transcription factor, PU.1, a central hub in the AD gene network. Our enrichment analysis highlighted the potential roles of the immune system and polycomb repressive complex 2 in pathological AD. These results may help facilitate future mechanistic and biomarker discovery studies in AD.

Three Brothers With Autism Carry a Stop-Gain Mutation in the HPA-Axis Gene NR3C2.

Whole exome sequencing and copy-number variant analysis was performed on a family with three brothers diagnosed with autism. Each of the siblings shares an alteration in the nuclear receptor subfamily 3 group C member 2 (NR3C2) gene that is predicted to result in a stop-gain mutation (p.Q919X) in the mineralocorticoid receptor (MR) protein. This variant was maternally inherited and provides further evidence for a connection between the NR3C2 and autism. Interestingly, the NR3C2 gene encodes the MR protein, a steroid hormone-regulated transcription factor that acts in the hypothalamic-pituitary-adrenal axis and has been connected to stress and anxiety, both of which are features often seen in individuals with autism. Autism Res 2020, 13: 523-531. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Given the complexity of the genetics underlying autism, each gene contributes to risk in a relatively small number of individuals, typically less than 1% of all autism cases. Whole exome sequencing of three brothers with autism identified a rare variant in the nuclear receptor subfamily 3 group C member 2 gene that is predicted to strongly interfere with its normal function. This gene encodes the mineralocorticoid receptor protein, which plays a role in how the body responds to stress and anxiety, features that are often elevated in people diagnosed with autism. This study adds further support to the relevance of this gene as a risk factor for autism.

Tagging SNP association study of the IL-1beta gene (IL1B) and childhood-onset mood disorders.

Given substantial evidence for IL-1beta involvement in the etiology of depression, the IL1B gene is a strong candidate for involvement in susceptibility to depressive disorders. However, association studies investigating this, to date, have been limited to just two polymorphisms (rs1143627[-31T/C] and rs16944[-511C/T]) that constitute only a fraction of the genetic variation that is actually present across this gene in the population. Here, in a family-based association study of childhood-onset mood disorders (COMD), characterized by onset of depression before the age of 15, we have used a gene-wide approach, employing a panel of five tagging SNPs spanning the entire gene. Based on TDT analyses of both individual alleles and haplotypes, in a study sample of 646 families (with 782 affected children), none of the SNPs, including those implicated in transcriptional regulation of the gene, showed evidence for association with COMD. This is the largest and most comprehensive study of IL1B in relation to mood disorders that has been carried out, to date. The results do not support the involvement of IL1B as a major factor in genetic risk for early-onset mood disorders.

G72/G30 (DAOA) and juvenile-onset mood disorders.

The chromosome 13q region has been linked to bipolar disorder in a number of genome scans as well as focused linkage studies. Previously we identified linkage to the 13q32 region in a genome scan of 146 affected sibling pair families from Hungary with juvenile-onset mood disorders. Within this region are the overlapping genes G72/G30, with G72 now officially named as D-amino-acid oxidase activator (DAOA). This locus has been associated with panic disorder, schizophrenia, and bipolar disorder. In this study, we tested for association to 11 markers in these genes and mood disorders in a sample of 646 nuclear families identified with a proband with onset of a mood disorder before 14.9 years of age. We identified evidence for association to three markers within the gene (rs2391191, rs3918341, rs1935062), two of which had been associated with bipolar disorder in previous studies. When corrected for the number of markers tested, the results were no longer significant, however the prior evidence for association of this gene in multiple studies points to this gene as a potential contributor to juvenile-onset mood disorders.

Genome scan in sibling pairs with juvenile-onset mood disorders: Evidence for linkage to 13q and Xq.

Mood disorders (bipolar and depressive disorders) in children and adolescents are associated with significant morbidity and mortality. Twin and family studies, for the most part, indicate higher familiality and heritability for mood disorders that onset in childhood/adolescence than those that onset in adulthood. To identify the genetic contribution to mood disorders that onset in childhood/adolescence, we performed a genome scan on 146 nuclear families from Hungary containing an affected proband and affected siblings. In total, the pedigrees contained 303 affected children: 146 probands, 137 siblings with a first episode of mood disorder before 14.9 years of age, and 20 siblings with onset of their first episode after 14.9 years of age but before the age of 18. The results of the genome scan using 405 microsatellite markers did not provide evidence for linkage at the recommended genome wide significance level for any novel loci. However, markers on two chromosomes, 13q and Xq, provided evidence for linkage in regions previously identified as linked to bipolar disorder in multiple studies. For the marker on chromosome 13q the peak non-parametric multipoint LOD score was at the marker D13S779 (LOD = 1.5, P = 0.004). On chromosome Xq, evidence for linkage was observed across a large region spanning two regions previously linked to bipolar disorder; Xq24 to Xq28, with a peak at marker TTTA062 (LOD 2.10, P = 0.0009) in Xq28. Results for these regions exceed the recommended P-value for a replication study of P < 0.01 and thus provide evidence for these two loci as contributing to mood disorders with juvenile onset.