Crohn’s disease (CD) and ulcerative colitis (UC), the two common forms of inflammatory bowel disease (IBD), affect over 2.5 million people of European ancestry with rising prevalence in other populations1. Genome-wide association studies (GWAS) and subsequent meta-analyses of CD and UC2,3 as separate phenotypes implicated previously unsuspected mechanisms, such as autophagy4, in pathogenesis and showed that some IBD loci are shared with other inflammatory diseases5. Here we expand knowledge of relevant pathways by undertaking a meta-analysis of CD and UC genome-wide association scans, with validation of significant findings in more than 75,000 cases and controls. We identify 71 new associations, for a total of 163 IBD loci that meet genome-wide significance thresholds. Most loci contribute to both phenotypes, and both directional and balancing selection effects are evident. Many IBD loci are also implicated in other immune-mediated disorders, most notably with ankylosing spondylitis and psoriasis. We also observe striking overlap between susceptibility loci for IBD and mycobacterial infection. Gene co-expression network analysis emphasizes this relationship, with pathways shared between host responses to mycobacteria and those predisposing to IBD.

Brain age is a metric that quantifies the degree of aging of a brain based on whole-brain anatomical characteristics. While associations between individual human brain regions and environmental or genetic factors have been investigated, how brain age is associated with those factors remains unclear. We investigated these associations using UK Biobank data. We first trained a statistical model for obtaining relative brain age (RBA), a metric describing a subject's brain age relative to peers, based on whole-brain anatomical measurements, from training set subjects (n = 5,193). We then applied this model to evaluation set subjects (n = 12,115) and tested the association of RBA with tobacco smoking, alcohol consumption, and genetic variants. We found that daily or almost daily consumption of tobacco and alcohol were both significantly associated with increased RBA (P < 0.001). We also found SNPs significantly associated with RBA (p-value < 5E-8). The SNP most significantly associated with RBA is located in MApt gene. our results suggest that both environmental and genetic factors are associated with structural brain aging.

previous studies of the association between parity and long-term cognitive changes have primarily focused on women and have shown conflicting results. We investigated this association by analyzing data collected on 303,196 subjects from the UK Biobank. We found that in both females and males, having offspring was associated with a faster response time and fewer mistakes made in the visual memory task. Subjects with two or three children had the largest differences relative to those who were childless, with greater effects observed in men. We further analyzed the association between parity and relative brain age (n = 13,584), a brain image-based biomarker indicating how old one's brain structure appears relative to peers. We found that in both sexes, subjects with two or three offspring had significantly reduced brain age compared to those without offspring, corroborating our cognitive function results. Our findings suggest that lifestyle factors accompanying having offspring, rather than the physical process of pregnancy experienced only by females, contribute to these associations and underscore the importance of studying such factors, particularly in the context of sex. Pregnancy involves dramatic hormonal and physiological changes. In part due to these large changes, the effect of pregnancy on cognitive and cardiovascular health has been studied 1,2. Declined cognitive function was observed during pregnancy 1,2. Researchers have also hypothesized that hormonal changes, which occur both during and after pregnancy, drive the association between parity (number of offspring) and cognitive function in later life. Multiple studies have investigated this association in females, though different conclusions have been found. Some studies found that parity was associated with better episodic memory and had a protective effect against Alzheimer's disease (AD) 3,4. Contrarily, parity has been associated with poor word recall score, Mini Mental State Exam score, and AD neural pathology 5,6. A recent study of approximately 10,000 male and female subjects found an association between the number of offspring and cognitive function in later life in both sexes, including memory and executive function, and suggested that socioeconomic status largely accounted for the association 7. In addition to the association between cognitive function and parity, the association between brain structural change and parity has been studied previously. Hoekzema et al. reported that the volume of certain gray matter regions was reduced during pregnancy and the reductions did not recover for at least 2 years post partum 2 , while others reported that the gray matter restoration process was evident within the first few months postpartum 8,9. Most studies on the association between brain structure and parity had a relatively small sample size (n < 100) and less than three years of postpartum follow-up 2,8,9. To date, it is still unclear if there are any long-term effects of parity on brain structure in the mid-to-old age population. We therefore so...

Summary Inflammatory bowel disease (IBD) is characterized by dysregulated intestinal immune homeostasis and cytokine secretion. Multiple loci are associated with IBD, but a functional explanation is missing for most. Here we found that pattern-recognition receptor (PRR)-induced cytokine secretion was diminished in human monocyte-derived dendritic cells (MDDC) from rs7282490 ICOSLG GG risk-carriers. Homotypic interactions between the co-stimulatory molecule ICOS and the ICOS ligand on MDDCs amplified nucleotide-binding oligomerization domain 2 (NOD2)-initiated cytokine secretion. This amplification required arginine residues in the ICOSL cytoplasmic tail that recruited the adaptor protein RACK1 and the kinases PKC and JNK leading to PKC, MAPK and NFκB activation. MDDC from rs7282490 GG risk-carriers had reduced ICOSL expression and PRR-initiated signaling and this loss-of-function ICOSLG risk allele associated with an ileal Crohn’s disease phenotype, similar to polymorphisms in NOD2. Taken together, ICOSL amplifies PRR-initiated outcomes, which may contribute to immune homeostasis.

Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.