Citations

ABSTRACT Bipolar disorder’s (BD) clinical heterogeneity has an unresolved genetic basis. We meta-analyzed genome-wide association studies (GWAS) of 16 BD subphenotypes in 226,032 individuals from 57 cohorts (38,022 cases); 10 advanced to multivariate and multi-trait analyses. Four factors (compulsive, psychotic, dysregulated, internalizing) explained 82.8% of shared genetic variance. BD1 and BD2 loaded on distinct factors despite a high genetic correlation; 87.0% of common-factor loci were significant in neither subtype. Unipolar mania aligned with psychosis over internalizing, and was distinguishable from BD1, and rapid cycling showed heritable cross-domain liability. We identified 356 risk loci, 158 novel, including the first univariate-GWAS associations for psychosis, unipolar mania, rapid cycling and schizoaffective disorder—and 249 credible genes (89 high-confidence), 12 with approved-drug or clinical-phase annotations. Cell-type association showed a midbrain dopaminergic–GABAergic gradient along the psychotic factor. BD’s genetic architecture appears hierarchical—a general liability resolving into dimensions of course and comorbidity beyond diagnostic subtypes.

Acute kidney injury (AKI) is a commonly encountered medical problem that is associated with poor health outcomes in AKI survivors, including increased mortality and re-admission to the hospital. Despite their high-risk status, only a small fraction (< 10%) of patients receive specialized nephrologist follow-up after AKI event. To address the gap in care for AKI patients, this work proposes an artificial intelligence (AI) based fusion technique that combines patient's single-lead electrocardiograph (ECG) and demographics to predict AKI recurrence 3-7 days before onset. The ECG data is analyzed with an on-chip reservoir-computer (RC) prototyped in 28nm CMOS process to create a compressed representation for predicting AKI onset from ECG. After fusion with demographics, the proposed technique is able to predict AKI recurrence 3-7 days before onset with 75.8% accuracy when evaluated on a retrospective patient dataset collected from Mayo Clinic Enterprise.

AbstractBackgroundGastroparesis (GP) is characterized by delayed gastric emptying in the absence of mechanical obstruction.ObjectiveGenetic predisposition may play a role; however, investigation at the genome‐wide level has not been performed.MethodsWe carried out a genome‐wide association study (GWAS) meta‐analysis on (i) 478 GP patients from the National Institute of Diabetes and Digestive and Kidney Diseases Gastroparesis Clinical Research Consortium (GpCRC) compared to 9931 population‐based controls from the University of Michigan Health and Retirement Study; and (ii) 402 GP cases compared to 48,340 non‐gastroparesis controls from the Michigan Genomics Initiative. Associations for 5,811,784 high‐quality SNPs were tested on a total of 880 GP patients and 58,271 controls, using logistic mixed models adjusted for age, sex, and principal components. Gene mapping was obtained based on genomic position and expression quantitative trait loci, and a gene‐set network enrichment analysis was performed. Genetic associations with clinical data were tested in GpCRC patients. Protein expression of selected candidate genes was determined in full thickness gastric biopsies from GpCRC patients and controls.ResultsWhile no SNP associations were detected at strict significance (p ≤ 5 × 10−8), nine independent genomic loci were associated at suggestive significance (p ≤ 1 × 10−5), with the strongest signal (rs9273363, odds ratio = 1.4, p = 1 × 10−7) mapped to the human leukocyte antigen region. Computational annotation of suggestive risk loci identified 14 protein‐coding candidate genes. Gene‐set network enrichment analysis revealed pathways potentially involved in immune and motor dysregulation (pFDR ≤ 0.05). The GP risk allele rs6984536A (Peroxidasin‐Like; PXDNL) was associated with increased abdominal pain severity scores (Beta = 0.13, p = 0.03). Gastric muscularis expression of PXDNL also positively correlated with abdominal pain in GP patients (r = 0.8, p = 0.02). Dickkopf WNT Signaling Pathway Inhibitor 1 showed decreased expression in diabetic GP patients (p = 0.005 vs. controls).ConclusionWe report preliminary GWAS findings for GP, which highlight candidate genes and pathways related to immune and sensory‐motor dysregulation. Larger studies are needed to validate and expand these findings in independent datasets.

Broad-spectrum therapeutics in non-small cell lung cancer (NSCLC) are in demand. Most human solid tumors express proteoglycans modified with distinct oncofetal chondroitin sulfate (CS) chains that can be detected and targeted with recombinant VAR2CSA (rVAR2) proteins and rVAR2-derived therapeutics. Here, we investigated expression and targetability of oncofetal CS expression in human NSCLC. High oncofetal CS expression is associated with shorter disease-free survival and poor overall survival of clinically annotated stage I and II NSCLC patients (n = 493). Oncofetal CS qualifies as an independent prognosticator of NSCLC in males and smokers, and high oncofetal CS levels are more prevalent in EGFR/KRAS wild-type cases, as compared to mutation cases. NSCLC cell lines express oncofetal CS-modified proteoglycans that can be specifically detected and targeted by rVAR2 proteins in a CSA-dependent manner. Importantly, a novel VAR2-drug conjugate (VDC-MMAE) efficiently eliminates NSCLC cells in vitro and in vivo. In summary, oncofetal CS is a prognostic biomarker and an actionable glycosaminoglycan target in NSCLC.

Objective Haemorrhoidal disease (HEM) affects a large and silently suffering fraction of the population but its aetiology, including suspected genetic predisposition, is poorly understood. We report the first genome-wide association study (GWAS) meta-analysis to identify genetic risk factors for HEM to date. Design We conducted a GWAS meta-analysis of 218 920 patients with HEM and 725 213 controls of European ancestry. Using GWAS summary statistics, we performed multiple genetic correlation analyses between HEM and other traits as well as calculated HEM polygenic risk scores (PRS) and evaluated their translational potential in independent datasets. Using functional annotation of GWAS results, we identified HEM candidate genes, which differential expression and coexpression in HEM tissues were evaluated employing RNA-seq analyses. The localisation of expressed proteins at selected loci was investigated by immunohistochemistry. Results We demonstrate modest heritability and genetic correlation of HEM with several other diseases from the GI, neuroaffective and cardiovascular domains. HEM PRS validated in 180 435 individuals from independent datasets allowed the identification of those at risk and correlated with younger age of onset and recurrent surgery. We identified 102 independent HEM risk loci harbouring genes whose expression is enriched in blood vessels and GI tissues, and in pathways associated with smooth muscles, epithelial and endothelial development and morphogenesis. Network transcriptomic analyses highlighted HEM gene coexpression modules that are relevant to the development and integrity of the musculoskeletal and epidermal systems, and the organisation of the extracellular matrix. Conclusion HEM has a genetic component that predisposes to smooth muscle, epithelial and connective tissue dysfunction.

Abstract Eating disorders and substance use disorders frequently co‐occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [ r g ], twin‐based = 0.23‐0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome‐wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance‐use‐related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism‐based genetic correlations between eating disorder‐ and substance‐use‐related phenotypes. Significant positive genetic associations emerged between AUD and AN ( r g = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN ( r g = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating ( r g = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating ( r gs = −0.19 to −0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co‐varying for major depressive disorder loci. The patterns of association between eating disorder‐ and substance‐use‐related phenotypes highlights the potentially complex and substance‐specific relationships among these behaviors.

Genome-wide association studies have identified >50 common variants associated with kidney function, but these variants do not fully explain the variation in eGFR. We performed a two-stage meta-analysis of associations between genotypes from the Illumina exome array and eGFR on the basis of serum creatinine (eGFRcrea) among participants of European ancestry from the CKDGen Consortium ( n Stage1 : 111,666; n Stage2 : 48,343). In single-variant analyses, we identified single nucleotide polymorphisms at seven new loci associated with eGFRcrea ( PPM1J , EDEM3, ACP1, SPEG, EYA4, CYP1A1 , and ATXN2L ; P Stage1 <3.7×10 −7 ), of which most were common and annotated as nonsynonymous variants. Gene-based analysis identified associations of functional rare variants in three genes with eGFRcrea, including a novel association with the SOS Ras/Rho guanine nucleotide exchange factor 2 gene, SOS2 ( P =5.4×10 −8 by sequence kernel association test). Experimental follow-up in zebrafish embryos revealed changes in glomerular gene expression and renal tubule morphology in the embryonic kidney of acp1- and sos2 -knockdowns. These developmental abnormalities associated with altered blood clearance rate and heightened prevalence of edema. This study expands the number of loci associated with kidney function and identifies novel genes with potential roles in kidney formation.

Genetic College Many genomic elements in humans are associated with behavior, including educational attainment. In a genome-wide association study including more than 100,000 samples, Rietveld et al. (p. 1467 , published online 30 May; see the Perspective by Flint and Munafò ) looked for genes related to educational attainment in Caucasians. Small genetic effects at three loci appeared to impact educational attainment.