Approximately 30% of older adults exhibit the neuropathological features of Alzheimer's disease without signs of cognitive impairment. Yet, little is known about the genetic factors that allow these potentially resilient individuals to remain cognitively unimpaired in the face of substantial neuropathology. We performed a large, genome-wide association study (GWAS) of two previously validated metrics of cognitive resilience quantified using a latent variable modelling approach and representing better-than-predicted cognitive performance for a given level of neuropathology. Data were harmonized across 5108 participants from a clinical trial of Alzheimer's disease and three longitudinal cohort studies of cognitive ageing. All analyses were run across all participants and repeated restricting the sample to individuals with unimpaired cognition to identify variants at the earliest stages of disease. As expected, all resilience metrics were genetically correlated with cognitive performance and education attainment traits (P-values < 2.5 × 10-20), and we observed novel correlations with neuropsychiatric conditions (P-values < 7.9 × 10-4). Notably, neither resilience metric was genetically correlated with clinical Alzheimer's disease (P-values > 0.42) nor associated with APOE (P-values > 0.13). In single variant analyses, we observed a genome-wide significant locus among participants with unimpaired cognition on chromosome 18 upstream of ATP8B1 (index single nucleotide polymorphism rs2571244, minor allele frequency = 0.08, P = 2.3 × 10-8). The top variant at this locus (rs2571244) was significantly associated with methylation in prefrontal cortex tissue at multiple CpG sites, including one just upstream of ATPB81 (cg19596477; P = 2 × 10-13). Overall, this comprehensive genetic analysis of resilience implicates a putative role of vascular risk, metabolism, and mental health in protection from the cognitive consequences of neuropathology, while also providing evidence for a novel resilience gene along the bile acid metabolism pathway. Furthermore, the genetic architecture of resilience appears to be distinct from that of clinical Alzheimer's disease, suggesting that a shift in focus to molecular contributors to resilience may identify novel pathways for therapeutic targets.

Takayasu arteritis is a rare inflammatory disease of large arteries. We performed a genetic study in Takayasu arteritis comprising 6,670 individuals (1,226 affected individuals) from five different populations. We discovered HLA risk factors and four non-HLA susceptibility loci in VPS8, SVEP1, CFL2, and chr13q21 and reinforced IL12B, PTK2B, and chr21q22 as robust susceptibility loci shared across ancestries. Functional analysis proposed plausible underlying disease mechanisms and pinpointed ETS2 as a potential causal gene for chr21q22 association. We also identified >60 candidate loci with suggestive association (p < 5 × 10-5) and devised a genetic risk score for Takayasu arteritis. Takayasu arteritis was compared to hundreds of other traits, revealing the closest genetic relatedness to inflammatory bowel disease. Epigenetic patterns within risk loci suggest roles for monocytes and B cells in Takayasu arteritis. This work enhances understanding of the genetic basis and pathophysiology of Takayasu arteritis and provides clues for potential new therapeutic targets.

Given that substantial genetic components have been shown in ischemic stroke, intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH), heritability may be higher in early-onset than late-onset individuals with these conditions. Although genome-wide association studies (GWASs) have identified various genes and loci significantly associated with ischemic stroke, ICH, or intracranial aneurysm mainly in European ancestry populations, genetic variants that contribute to susceptibility to these disorders remain to be identified definitively. We performed exome-wide association studies (EWASs) to identify genetic variants that confer susceptibility to ischemic stroke, ICH, or SAH in early-onset subjects with these conditions. A total of 6,649 individuals aged ≤65 years were examined. For the EWAS of ischemic or hemorrhagic stroke, 6,224 individuals (450 subjects with ischemic stroke, 5,774 controls) or 6,179 individuals (261 subjects with ICH, 176 subjects with SAH, 5,742 controls), respectively, were examined. EWASs were performed with the use of Illumina Human Exome-12 v1.2 DNA Analysis BeadChip or Infinium Exome-24 v1.0 BeadChip. To compensate for multiple comparisons of allele frequencies with ischemic stroke, ICH, or SAH, we applied a false discovery rate (FDR) of <0.05 for statistical significance of association. The association of allele frequencies of 31,245 single nucleotide polymorphisms (SNPs) that passed quality control to ischemic stroke was examined with Fisher's exact test, and 31 SNPs were significantly (FDR <0.05) associated with ischemic stroke. The association of allele frequencies of 31,253 or 30,970 SNPs to ICH or SAH, respectively, was examined with Fisher's exact test, and six or two SNPs were significantly associated with ICH or SAH, respectively. Multivariable logistic regression analysis with adjustment for age, sex, and the prevalence of hypertension and diabetes mellitus revealed that 12 SNPs were significantly [P<0.0004 (0.05/124)] related to ischemic stroke. Similar analysis with adjustment for age, sex, and the prevalence of hypertension revealed that six or two SNPs were significantly [P<0.0016 (0.05/32)] related to ICH or SAH, respectively. After examination of linkage disequilibrium of identified SNPs and results of previous GWASs, we identified HHIPL2, CTNNA3, LOC643770, UTP20, and TRIB3 as susceptibility loci for ischemic stroke, DNTTIP2 and FAM205A as susceptibility loci for ICH, and FAM160A1 and OR52E4 as such loci for SAH. Therefore, to the best of our knowledge, we have newly identified nine genes that confer susceptibility to early-onset ischemic stroke, ICH, or SAH. Determination of genotypes for the SNPs in these genes may prove informative for assessment of the genetic risk for ischemic stroke, ICH, or SAH in Japanese.

AIMS/HYPOTHESIS: Our study aimed to integrate maternal metabolic and genetic data related to insulin sensitivity during pregnancy to provide novel insights into mechanisms underlying pregnancy-induced insulin resistance. METHODS: Fasting and 1 h serum samples were collected from women in the Hyperglycemia and Adverse Pregnancy Outcome study who underwent an OGTT at ∼28 weeks' gestation. We obtained targeted and non-targeted metabolomics and genome-wide association data from 1600 and 4528 mothers, respectively, in four ancestry groups (Northern European, Afro-Caribbean, Mexican American and Thai); 1412 of the women had both metabolomics and genome-wide association data. Insulin sensitivity was calculated using a modified insulin sensitivity index that included fasting and 1 h glucose and C-peptide levels after a 75 g glucose load. RESULTS: Per-metabolite and network analyses across the four ancestries identified numerous metabolites associated with maternal insulin sensitivity before and 1 h after a glucose load, ranging from amino acids and carbohydrates to fatty acids and lipids. Genome-wide association analyses identified 12 genetic variants in the glucokinase regulatory protein gene locus that were significantly associated with maternal insulin sensitivity, including a common functional missense mutation, rs1260326 (β = -0.2004, p = 4.67 × 10-12 in a meta-analysis across the four ancestries). This SNP was also significantly associated with multiple fasting and 1 h metabolites during pregnancy, including fasting and 1 h triacylglycerols and 2-hydroxybutyrate and 1 h lactate, 2-ketoleucine/ketoisoleucine and palmitoleic acid. Mediation analysis suggested that 1 h palmitoleic acid contributes, in part, to the association of rs1260326 with maternal insulin sensitivity, explaining 13.7% (95% CI 4.0%, 23.3%) of the total effect. CONCLUSIONS/INTERPRETATION: The present study demonstrates commonalities between metabolites and genetic variants associated with insulin sensitivity in the gravid and non-gravid states and provides insights into mechanisms underlying pregnancy-induced insulin resistance. Graphical abstract.

BACKGROUND: A substantial number of patients diagnosed with multiple sclerosis (MS) suffer from depression in addition to physical symptoms and disability. Recent evidence suggests a stronger relationship may exist between MS and depression than previously thought, in which a diagnosis of depression may be prodromic to the development of MS. METHODS: A genome-wide association study (GWAS) was performed to identify genetic variants associated with the development of depression in a cohort of MS patients. The control group (n = 1180) was composed of MS patients with no diagnoses of depression as determined by ICD-9 and ICD-10 billing codes present in the electronic health record (EHR). Separate analyses were performed for three different case groups: 1) MS patients having a depression diagnosis at any time (n = 182), 2) MS patients having a depression diagnosis one year pre-MS diagnosis (n = 27), and 3) MS patients having a depression diagnosis one year post-MS diagnosis (n = 130). Logistic regression analyses were also performed to test for associations between the development of depression and an APOE tagging variant, as APOE was previously linked to depressive affect in MS. An additional logistic regression analysis tested for associations between depression in MS patients and SNPs associated with depression in the general population. Pathway enrichment analyses were also conducted to identify pathways that link the two diseases. RESULTS: GWAS identified no novel associations between variants and a diagnosis of depression relative to a diagnosis of MS. One variant, rs1432639, associated with depression in the general population, was significantly associated with the development of depression post-MS diagnosis. The APOE-related SNPs were not associated with depression in this study population. An IGF1 pathway approached statistical significance in patients diagnosed with depression prior to a diagnosis of MS. CONCLUSION: rs1432639 and the IGF1 pathway provide evidence for a genetic link between MS and depression that warrants further research.

Recent population-based1-4 and clinical studies5 have identified a range of factors associated with human gut microbiome variation. Murine quantitative trait loci6, human twin studies7 and microbiome genome-wide association studies1,3,8-12 have provided evidence for genetic contributions to microbiome composition. Despite this, there is still poor overlap in genetic association across human studies. Using appropriate taxon-specific models, along with support from independent cohorts, we show an association between human host genotype and gut microbiome variation. We also suggest that interpretation of applied analyses using genetic associations is complicated by the probable overlap between genetic contributions and heritable components of host environment. Using faecal 16S ribosomal RNA gene sequences and host genotype data from the Flemish Gut Flora Project (n = 2,223) and two German cohorts (FoCus, n = 950; PopGen, n = 717), we identify genetic associations involving multiple microbial traits. Two of these associations achieved a study-level threshold of P = 1.57 × 10-10; an association between Ruminococcus and rs150018970 near RAPGEF1 on chromosome 9, and between Coprococcus and rs561177583 within LINC01787 on chromosome 1. Exploratory analyses were undertaken using 11 other genome-wide associations with strong evidence for association (P < 2.5 × 10-8) and a previously reported signal of association between rs4988235 (MCM6/LCT) and Bifidobacterium. Across these 14 single-nucleotide polymorphisms there was evidence of signal overlap with other genome-wide association studies, including those for age at menarche and cardiometabolic traits. Mendelian randomization analysis was able to estimate associations between microbial traits and disease (including Bifidobacterium and body composition); however, in the absence of clear microbiome-driven effects, caution is needed in interpretation. Overall, this work marks a growing catalogue of genetic associations that will provide insight into the contribution of host genotype to gut microbiome. Despite this, the uncertain origin of association signals will likely complicate future work looking to dissect function or use associations for causal inference analysis.

Identification of genetic variants associated with glucocorticoids (GC) sensitivity of leukaemia cells may provide insight into potential drug targets and tailored therapy. In the present study, within 72 leukaemic cell lines derived from Japanese patients with B-cell precursor acute lymphoblastic leukaemia (ALL), we conducted genome-wide genotyping of single nucleotide polymorphisms (SNP) and attempted to identify genetic variants associated with GC sensitivity and NR3C1 (GC receptor) gene expression. IC50 measures for prednisolone (Pred) and dexamethasone (Dex) were available using an alamarBlue cell viability assay. IC50 values of Pred showed the strongest association with rs904419 (P = 4.34 × 10-8 ), located between the FRMD4B and MITF genes. The median IC50 values of prednisolone for cell lines with rs904419 AA (n = 13), AG (n = 31) and GG (n = 28) genotypes were 0.089, 0.139 and 297 µmol/L, respectively. For dexamethasone sensitivity, suggestive association was observed for SNP rs2306888 (P = 1.43 × 10-6 ), a synonymous SNP of the TGFBR3 gene. For NR3C1 gene expression, suggestive association was observed for SNP rs11982167 (P = 6.44 × 10-8 ), located in the PLEKHA8 gene. These genetic variants may affect GC sensitivity of ALL cells and may give rise to opportunities in personalized medicine for effective and safe chemotherapy in ALL patients.

Rupture of an intracranial aneurysm leads to subarachnoid hemorrhage, a severe type of stroke. To discover new risk loci and the genetic architecture of intracranial aneurysms, we performed a cross-ancestry, genome-wide association study in 10,754 cases and 306,882 controls of European and East Asian ancestry. We discovered 17 risk loci, 11 of which are new. We reveal a polygenic architecture and explain over half of the disease heritability. We show a high genetic correlation between ruptured and unruptured intracranial aneurysms. We also find a suggestive role for endothelial cells by using gene mapping and heritability enrichment. Drug-target enrichment shows pleiotropy between intracranial aneurysms and antiepileptic and sex hormone drugs, providing insights into intracranial aneurysm pathophysiology. Finally, genetic risks for smoking and high blood pressure, the two main clinical risk factors, play important roles in intracranial aneurysm risk, and drive most of the genetic correlation between intracranial aneurysms and other cerebrovascular traits.

INTRODUCTION: Anorectal malformations (ARM) are rare congenital malformations, resulting from disturbed hindgut development. A genetic etiology has been suggested, but evidence for the involvement of specific genes is scarce. We evaluated the contribution of rare and low-frequency coding variants in ARM etiology, assuming a multifactorial model. METHODS: We analyzed 568 Caucasian ARM patients and 1,860 population-based controls using the Illumina HumanExome Beadchip array, which contains >240,000 rare and low-frequency coding variants. GenomeStudio clustering and calling was followed by re-calling of 'no-calls' using zCall for patients and controls simultaneously. Single variant and gene-based analyses were performed to identify statistically significant associations, applying Bonferroni correction. Following an extra quality control step, candidate variants were selected for validation using Sanger sequencing. RESULTS: When we applied a MAF of ≥1.0%, no variants or genes showed statistically significant associations with ARM. Using a MAF cut-off at 0.4%, 13 variants initially reached statistical significance, but had to be discarded upon further inspection: ten variants represented calling errors of the software, while the minor alleles of the remaining three variants were not confirmed by Sanger sequencing. CONCLUSION: Our results show that rare and low-frequency coding variants with large effect sizes, present on the exome chip do not contribute to ARM etiology.

In modern drug development, genotype information becomes more frequently collected in randomized controlled trials (RCTs) for individualized risk prediction and personalized medicine development. Finding single nucleotide polymorphisms (SNPs) that are predictive of differential treatment efficacy, measured by a clinical outcome, is fundamentally different and more challenging than the traditional association test for a quantitative trait. With the objective to confidently identify and infer genetic subgroups with enhanced treatment efficacy from a large RCT for an eye disease, age-related macular degeneration (AMD), where the clinical endpoint is binary (progressed or not), we propose a novel SNP-testing procedure for binary clinical outcomes. Specifically, we formulate four contrasts to simultaneously assess all possible genetic effects on a logic-respecting efficacy measure, the relative risk (between treatment and control). Our method controls both within- and across-SNP multiplicity rigorously. We then use real genotype data to perform chromosome-wide simulations to evaluate our method performance and to provide practical recommendations. Finally, we apply the proposed method to perform a genome-wide SNP testing for the AMD trial and successfully identify multiple gene regions with genetic subgroups exhibiting enhanced efficacy in terms of decreasing the AMD progression rate.