👤 Julie K O'Reilly

Physical inactivity post-stroke increases risk of recurrent stroke. Adaptive physical activity (PA) interventions are recommended, and alternative designs, such as sequential multiple assignment randomized trials (SMARTs) can be used. This SMART investigates the feasibility of a mobile health (mHealth) PA intervention post-stroke. People post-stroke are randomized to 12-week online exercise (EX) or lifestyle PA (LPA). Six-week daily step count data are used to classify participants as responders or nonresponses. Nonresponders are re-randomized to switch or augment their mHealth intervention, responders continue unchanged. Primary outcomes include recruitment, retention and adherence rates. Secondary outcomes include PA, sedentary behavior, fatigue, quality of life, psychological distress, and activities of daily living. General linear models estimate trends regarding first-stage interventions, nonresponse strategies, and adaptive interventions are examined using weighted and replicated regressions. Fifty participants are included. Recruitment, retention, and adherence rates are 85%, 84%, and 82%. Positive trends are seen for nonresponse strategies, switching interventions, on step count, fatigue, and quality of life. Starting with EX and switching to LPA show potential benefits for fatigue, quality of life and return to normal living. Potential benefits of these interventions are preliminary and require validation in a full-scale trial. This SMART offers novel evidence supporting the design of adaptive mHealth PA interventions post-stroke, confirming the feasibility of a definitive SMART. Show less

Coronary artery disease (CAD) is a complex, heterogeneous disease with distinct etiological mechanisms. These different etiologies may give rise to multiple subtypes of CAD that could benefit from alternative preventions and treatments. However, so far, there have been no systematic efforts to predict CAD subtypes using clinical and genetic factors. Here, we trained and applied statistical models incorporating clinical and genetic factors to predict CAD subtypes in 26 036 patients with CAD in the UK Biobank. We performed external validation of the UK Biobank models in the US-based All of Us cohort (8598 patients with CAD). Subtypes were defined as high versus normal LDL (low-density lipoprotein) levels, high versus normal Lpa (lipoprotein A) levels, ST-segment-elevation myocardial infarction versus non-ST-segment-elevation myocardial infarction, occlusive versus nonocclusive CAD, and stable versus unstable CAD. Clinical predictors included levels of ApoA, ApoB, HDL (high-density lipoprotein), triglycerides, and CRP (C-reactive protein). Genetic predictors were genome-wide and pathway-based polygenic risk scores (PRSs). Results showed that both clinical-only and genetic-only models can predict CAD subtypes, while combining clinical and genetic factors leads to greater predictive accuracy. Pathway-based PRSs had higher discriminatory power than genome-wide PRSs for the Lpa and LDL subtypes and provided insights into their etiologies. The 10-pathway PRS most predictive of the LDL subtype involved cholesterol metabolism. Pathway PRS models had poor generalizability to the All of Us cohort. In summary, we present the first systematic demonstration that CAD subtypes can be distinguished by clinical and genomic risk factors, which could have important implications for stratified cardiovascular medicine. Show less

Chemically modified small interfering RNAs (siRNAs) are a promising drug class that silences disease-causing genes via mRNA degradation. Both siRNA-specific features (e.g. sequence, modification pattern, and structure) and target mRNA-specific factors contribute to observed efficacy. Systematically defining the relative contributions of siRNA sequence, structure, and modification pattern versus the native context of the target mRNA is necessary to inform design considerations and facilitate the widespread application of this therapeutic platform. To address this, we synthesized a panel of ∼1260 differentially modified siRNAs and evaluated their silencing efficiency against therapeutically relevant mRNAs (APP, BACE1, MAPT, and SNCA) using both reporter-based and native expression assays. Our results demonstrate that the siRNA modification pattern (e.g. level of 2'-O-methyl content) significantly impacts efficacy, while structural features (e.g. symmetric versus asymmetric configurations) do not. Furthermore, we observed substantial differences in the number of effective siRNAs identified per target. These target-specific differences in hit rates are largely mitigated when efficacy is tested in the context of a reporter assay, confirming that native mRNA-specific features influence siRNA performance. Key target-specific factors, including exon usage, polyadenylation site selection, and ribosomal occupancy, partially explained efficacy variability. These insights led to a proposed framework of parameters for optimizing therapeutic siRNA design. Show less

Systemic sclerosis (SSc) is an autoimmune connective tissue disease with a triad of features that include vascular abnormalities, inflammation and skin and lung fibrosis. At the core of the disease is the activation of myofibroblasts from quiescent fibroblasts and this can be modified by various cytokines. IL-41 is a recently described cytokine that was initially characterised as an adipokine as it was highly expressed in adipocytes and adipose tissue. However, it has recently been identified as being widely expressed and has immunomodulatory functions. This study examined the circulating levels of IL-41 and its expression in skin biopsies. We demonstrated significantly reduced levels of IL-41 in diffuse SSc that was also mirrored in the skin of SSc patients. AMPK has been proposed as a downstream target of IL-41, so we also measure mammalian target of rapamycin in skin and found that this is elevated in SSc patients. We speculate that IL-41 maybe an antifibrotic cytokine and its reduction may facilitate the activation of fibroblasts. Show less

Progressive vision loss and neurocognitive impairment are early and frequent presentations in CLN3 disease. This highlights neurodevelopmental functioning as critical to the disease, but limits the neuropsychological test repertoire. We evaluated the convergent validity of the Vineland Adaptive Behavior Scales as a potential outcome measure. In a prospective observational study of 22 individuals (female:male 11:11; 6-20 years-old) with a molecular diagnosis of CLN3, we used generalized linear models and Spearman correlations to quantify the relationship of the adaptive behavior composite (ABC) standard score with established outcomes of verbal IQ (VIQ) and disease severity (Unified Batten Disease Rating Scale, UBDRS) scores. We analyzed ABC changes in 1-year follow-up data in a subset of the same cohort (n = 17). The ABC and VIQ, both standard scores, exhibited a strong positive correlation in cross-sectional data (r = 0.81). ABC and UBDRS scores were strongly and positively correlated in cross-sectional data (r Show less

High-fat diet (HFD)-induced obesity impairs macrophage-to-feces reverse cholesterol transport (RCT). It is hypothesized that dietary supplementation with the polyunsaturated fatty acids conjugated linoleic acid (CLA) or alpha linolenic acid (ALA) would prevent HFD-impaired RCT by modulating hepatic protein pathways. ApoE3L.CETP mice are fed a HFD supplemented ± CLA or ALA for 12 weeks and in vivo macrophage-to-feces RCT is determined. Hepatic cholesterol transporters and the hepatic proteome are assessed by immunoblotting and mass spectrometry, respectively. Mice fed HFD alone, but not ALA-HFD or CLA-HFD, exhibit increased systemic cholesterol levels, increased ALA and CLA exert distinct mechanistic advantages on cholesterol homeostasis and RCT in obesity. Show less

Autophagosome formation depends on a carefully orchestrated interplay between membrane-associated protein complexes. Initiation of macroautophagy/autophagy is mediated by the ULK1 (unc-51 like autophagy activating kinase 1) protein kinase complex and the autophagy-specific class III phosphatidylinositol 3-kinase complex I (PtdIns3K-C1). The latter contains PIK3C3/VPS34, PIK3R4/VPS15, BECN1/Beclin 1 and ATG14 and phosphorylates phosphatidylinositol to generate phosphatidylinositol 3-phosphate (PtdIns3P). Here, we show that PIK3C3, BECN1 and ATG14 contain functional LIR motifs and interact with the Atg8-family proteins with a preference for GABARAP and GABARAPL1. High resolution crystal structures of the functional LIR motifs of these core components of PtdIns3K-C1were obtained. Variation in hydrophobic pocket 2 (HP2) may explain the specificity for the GABARAP family. Mutation of the LIR motif in ATG14 did not prevent formation of the PtdIns3K-C1 complex, but blocked colocalization with MAP1LC3B/LC3B and impaired mitophagy. The ULK-mediated phosphorylation of S29 in ATG14 was strongly dependent on a functional LIR motif in ATG14. GABARAP-preferring LIR motifs in PIK3C3, BECN1 and ATG14 may, via coincidence detection, contribute to scaffolding of PtdIns3K-C1 on membranes for efficient autophagosome formation. Show less

Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify germline single-nucleotide polymorphisms (SNPs) that contribute to variations in individual responses to chemotherapy, we carried out a multi-phase genome-wide association study (GWAS) in 1,244 women diagnosed with serous EOC who were treated with the same first-line chemotherapy, carboplatin and paclitaxel. We identified two SNPs (rs7874043 and rs72700653) in TTC39B (best P=7x10-5, HR=1.90, for rs7874043) associated with progression-free survival (PFS). Functional analyses show that both SNPs lie in a putative regulatory element (PRE) that physically interacts with the promoters of PSIP1, CCDC171 and an alternative promoter of TTC39B. The C allele of rs7874043 is associated with poor PFS and showed increased binding of the Sp1 transcription factor, which is critical for chromatin interactions with PSIP1. Silencing of PSIP1 significantly impaired DNA damage-induced Rad51 nuclear foci and reduced cell viability in ovarian cancer lines. PSIP1 (PC4 and SFRS1 Interacting Protein 1) is known to protect cells from stress-induced apoptosis, and high expression is associated with poor PFS in EOC patients. We therefore suggest that the minor allele of rs7874043 confers poor PFS by increasing PSIP1 expression. Show less

Colorectal cancer is one of the most common cancers worldwide with almost 700,000 deaths every year. Detection of colorectal cancer at an early stage significantly improves patient survival. Cancer-specific autoantibodies found in sera of cancer patients can be used for pre-symptomatic detection of the disease. In this study we assess the zinc finger proteins ZNF346, ZNF638, ZNF700 and ZNF768 as capture antigens for the detection of autoantibodies in colorectal cancer. Sera from 96 patients with colorectal cancer and 35 control patients with no evidence of cancer on colonoscopy were analysed for the presence of ZNF-specific autoantibodies using an indirect ELISA. Autoantibodies to individual ZNF proteins were detected in 10-20% of colorectal cancer patients and in 0-5.7% of controls. A panel of all four ZNF proteins resulted in an assay specificity of 91.4% and sensitivity of 41.7% for the detection of cancer patients in a cohort of non-cancer controls and colorectal cancer patients. Clinicopathological and survival analysis revealed that ZNF autoantibodies were independent of disease stage and did not correlate with disease outcome. Since ZNF autoantibodies were shared between patients and corresponding ZNF proteins showed similarities in their zinc finger motifs, we performed an in silico epitope sequence analysis. Zinc finger proteins ZNF700 and ZNF768 showed the highest sequence similarity with a bl2seq score of 262 (E-value 1E-81) and their classical C2H2 ZNF motifs were identified as potential epitopes contributing to their elevated immunogenic potential. Our findings show an enhanced and specific immunogenicity to zinc finger proteins, thereby providing a multiplexed autoantibody assay for minimally invasive detection of colorectal cancer. Show less

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants. Show less

Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P = 10(-190)). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function. Show less