Shared genetic contribution to ischemic stroke and Alzheimer's disease

Objective Increasing evidence suggests epidemiological and pathological links between Alzheimer's disease (AD) and ischemic stroke (IS). We investigated the evidence that shared genetic factors underpin the two diseases. Methods Using genome-wide association study (GWAS) data from METASTROKE + (15,916 IS cases and 68,826 controls) and the International Genomics of Alzheimer's Project (IGAP; 17,008 AD cases and 37,154 controls), we evaluated known associations with AD and IS. On the subset of data for which we could obtain compatible genotype-level data (4,610 IS cases, 1,281 AD cases, and 14,320 controls), we estimated the genome-wide genetic correlation (rG) between AD and IS, and the three subtypes (cardioembolic, small vessel, and large vessel), using genome-wide single-nucleotide polymorphism (SNP) data. We then performed a meta-analysis and pathway analysis in the combined AD and small vessel stroke data sets to identify the SNPs and molecular pathways through which disease risk may be conferred. Results We found evidence of a shared genetic contribution between AD and small vessel stroke (rG [standard error] = 0.37 [0.17]; p = 0.011). Conversely, there was no evidence to support shared genetic factors in AD and IS overall or with the other stroke subtypes. Of the known GWAS associations with IS or AD, none reached significance for association with the other trait (or stroke subtypes). A meta-analysis of AD IGAP and METASTROKE + small vessel stroke GWAS data highlighted a region (ATP5H/KCTD2/ICT1) associated with both diseases (p = 1.8 × 10-8). A pathway analysis identified four associated pathways involving cholesterol transport and immune response. Interpretation Our findings indicate shared genetic susceptibility to AD and small vessel stroke and highlight potential causal pathways and loci. Ann Neurol 2016;79:739-74

Evaluation of bioelectrical impedance analysis in critically Ill patients: results of a multicenter prospective study

BACKGROUND: In critically ill patients, muscle loss is associated with adverse outcomes. Raw bioelectrical impedance analysis (BIA) parameters (eg, phase angle [PA] and impedance ratio [IR]) have received attention as potential markers of muscularity, nutrition status, and clinical outcomes. Our objective was to test whether PA and IR could be used to assess low muscularity and predict clinical outcomes. METHODS: Patients (≥18 years) having an abdominal computed tomography (CT) scan and admitted to intensive care underwent multifrequency BIA within 72 hours of scan. CT scans were landmarked at the third lumbar vertebra and analyzed for skeletal muscle cross-sectional area (CSA). CSA ≤170 cm(2) for males and ≤110 cm(2) for females defined low muscularity. The relationship between PA (and IR) and CT muscle CSA was evaluated using multivariate regression and included adjustments for age, sex, body mass index, Charlson Comorbidity Index, and admission type. PA and IR were also evaluated for predicting discharge status using dual-energy X-ray absorptiometry-derived cut-points for low fat-free mass index. RESULTS: Of 171 potentially eligible patients, 71 had BIA and CT scans within 72 hours. Area under the receiver operating characteristic (c-index) curve to predict CT-defined low muscularity was 0.67 (P ≤ .05) for both PA and IR. With covariates added to logistic regression models, PA and IR c-indexes were 0.78 and 0.76 (P < .05), respectively. Low PA and high IR predicted time to live ICU discharge. CONCLUSION: Our study highlights the potential utility of PA and IR as markers to identify patients with low muscularity who may benefit from early and rigorous intervention

Urinary Retinol Binding Protein Is a Marker of the Extent of Interstitial Kidney Fibrosis

<div><p>Currently, a non-invasive method to estimate the degree of interstitial fibrosis (IF) in chronic kidney disease is not available in routine. The aim of our study was to evaluate the diagnostic performance of the measurement of urinary low molecular weight (LMW) protein concentrations as a method to determine the extent of IF. The urines specimen from 162 consecutive patients who underwent renal biopsy were used in the analysis. Numerical quantification software based on the colorimetric analysis of fibrous areas was used to assess the percentage IF. Total proteinuria, albuminuria, and the urinary levels of retinol binding protein (RBP), alpha1-microglobulin (α1MG), beta 2-microglobulin (β2MG), transferrin, and IgG immunoglobulins were measured. There was a significant correlation between the degree of IF and the RBP/creatinine (creat) ratio (R2: 0.11, p<0.0001). IF was associated to a lesser extent with urinary β2MG and α1MG; however, there was no association with total proteinuria or high molecular weight (HMW) proteinuria. The correlation between IF and RBP/creat remained significant after adjustment to the estimated glomerular filtration rate, age, body mass index, α1MG, and β2MG. The specificity of the test for diagnosing a fibrosis score of >25% of the parenchyma was 95% when using a threshold of 20 mg/g creat. In conclusion, RBP appears to be a quantitative and non-invasive marker for the independent prediction of the extent of kidney IF. Because methods for the measurement of urinary RBP are available in most clinical chemistry departments, RBP measurement is appealing for implementation in the routine care of patients with chronic kidney disease.</p></div

Expression patterns of proteinuria.

<p><b>A</b>, <b>B</b>. Best-fit slope of the linear regression between RBP and β2MG (A) and RBP and Alb (B). <b>C</b>, <b>D</b>, <b>E</b>. Histogram showing Alb (A), RBP (B), and IgG (C) values according to the type of kidney disease. Protein concentrations are expressed as the mean ± sem. **p<0.01, ***p<0.001 compared to glomerular disease using Student's T test; the Mann-Whitney test was used for the glomerular vs. comparison with non-specific lesions. Glom: glomerular diseases; Tub-Int: tubular and/or interstitial diseases; Vasc: vascular diseases; Non-spe: non-specific.</p

Correlation between the estimated glomerular filtration rate and extent of interstitial fibrosis.

<p><b>A</b>. Best-fit slope of the linear regression between eGFR and extent of fibrosis. <b>B</b>, <b>C</b>, <b>D</b>. Best-fit slope of the linear regression between eGFR and extent of fibrosis in glomerular disease (B), tubular disease (C), and vascular disease (D). <b>E</b>. Histogram of the distribution of the extent of interstitial fibrosis according to the type of kidney disease. The percentages of interstitial fibrosis are expressed as the mean ± sem. *p<0.05 compared to glomerular disease, using Student's T test; the Mann-Whitney test was used for the glomerular vs. non specific lesions comparison. Glom: glomerular diseases; Tub-Int: tubular and/or interstitial diseases; Vasc: vascular diseases; Non-spe: non-specific.</p

Summary of correlative data.

<p>Summary of correlative data.</p

Correlation between proteinuria and the extent of interstitial fibrosis.

<p><b>A</b>, <b>B</b>. Best-fit slope of the linear regression between RBP (A) and Alb (B) and extent of fibrosis extent.</p

Baseline characteristics of the study cohort (n = 162).

<p>Continuous variables are expressed as the mean ± sem; categorical variables are expressed as n (%).</p><p>Hyperlipidemia: total cholesterol >200 mg/dl and/orTriglycerides >200 mg/dl, and/or LDL cholesterol>130 mg/dl.</p><p>Cancer: Multiple myemoma ( = 13), Urogenital ( = 7), Breast ( = 2), Lung ( = 1).</p><p>Non specific: no diagnosis, moderate interstitial fibrosis and/or glomerulosclerosis.</p