Asymmetry in Volatility: A Comparison of Developed and Transition Stock Markets

ARCH modelling framework of Engle (1982) and its GARCH generalization of Bollerslev (1986) gave a huge impetus to econometric model building in the field of financial time series with time-varying variance. The main idea of the models was to describe the most typical features of capital markets like volatility clustering, excess kurtosis and fat tails. As empirical evidence shows asymmetry is also a prominent feature of stock market returns volatility. The reaction of risk if stock returns go off the long run trajectory is different in case of positive and negative market news. Thus it is indispensable to employ asymmetric models being a modification of a traditional GARCH. In the paper we used an approach of Engle and Ng (1993) to test for asymmetric effects in stock indices of developed and Central European stock markets.asymmetry, volatility, stock market, transition

The Experiences of People with Dementia and Informal Carers Related to the Closure of Social and Medical Services in Poland during the COVID-19 Pandemic-A Qualitative Study

Older people with dementia are particularly at risk of COVID-19; however, relatively little is known about the indirect impact of the pandemic on the lives of those living with, and/or caring for someone with, dementia. The aim of this study was to investigate the experiences of people with dementia and informal carers during the closure of available social and medical services in Poland during the COVID-19 pandemic. A qualitative thematic analysis of semi-structured interviews with people with dementia (n = 5) and informal carers (n = 21) was performed between June and August 2020 after the first wave of COVID-19 in Poland. Three overarching themes were identified: (1) care re-organization; (2) psychological responses; (3) emerging needs. The factor underlying all these elements was reliance on other people. Social support and engagement are vital to the ongoing health and well-being of people living with dementia and their informal carers. Services need to be strengthened to provide ongoing provision to those living with dementia to reach pre-pandemic levels, if not better. Within the post-pandemic environment, people with dementia and their informal carers need reassurance that they can rely on external institutional and social support able to meet their needs

Baseline Body Composition in Prepubertal Short Stature Children with Severe and Moderate Growth Hormone Deficiency

Objective. To compare body composition parameters in short children with severe versus moderate and no growth hormone deficiency (GHD). Design and Method. 61 children (40 boys) were studied. Height SDS, BMI Z-score, waist/height ratio (W/HtR), and body composition parameters (BIA) as fat tissue (FAT%), fat-free mass (FFM%), predicted muscle mass (PMM%), and total body water (TBW%) were evaluated. GH secretion in the overnight profile and two stimulation tests and insulin-like growth factor 1 (IGF-1) level were measured. Results. Overall, in 16 (26%) moderate (7.0 > peak GH < 10 ng/mL) and in 11 (18%) severe (GH ≤ 7.0 ng/mL) GHD was diagnosed. In children with sGHD BMI Z-score, W/HtR and FAT% were significantly higher, while FFM%, PMM%, and TBW% were significantly lower versus mGHD and versus noGHD subgroups. No significant differences between mGHD and noGHD were found. There were no differences in height SDS and IGF-1 SDS between evaluated subgroups. Night GH peak level correlated significantly with FAT%, FFM%, PMM%, and TBW%, (p<0.05) in the entire group. Conclusions. Only sGHD is associated with significant impairment of body composition. Body composition analysis may be a useful tool in distinguishing between its severe and moderate form of GHD

Identification of Recessively Inherited Genetic Variants Potentially Linked to Pancreatic Cancer Risk

Although 21 pancreatic cancer susceptibility loci have been identified in individuals of European ancestry through genome-wide association studies (GWASs), much of the heritability of pancreatic cancer risk remains unidentified. A recessive genetic model could be a powerful tool for identifying additional risk variants. To discover recessively inherited pancreatic cancer risk loci, we performed a re-analysis of the largest pancreatic cancer GWAS, the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including 8,769 cases and 7,055 controls of European ancestry. Six single nucleotide polymorphisms (SNPs) showed associations with pancreatic cancer risk according to a recessive model of inheritance. We replicated these variants in 3,212 cases and 3,470 controls collected from the PANcreatic Disease ReseArch (PANDoRA) consortium. The results of the meta-analyses confirmed that rs4626538 (7q32.2), rs7008921 (8p23.2) and rs147904962 (17q21.31) showed specific recessive effects (p&lt;10(-5)) compared with the additive effects (p&gt;10(-3)), although none of the six SNPs reached the conventional threshold for genome-wide significance (p &lt; 5x10(-8)). Additional bioinformatic analysis explored the functional annotations of the SNPs and indicated a possible relationship between rs36018702 and expression of the BCL2L11 and BUB1 genes, which are known to be involved in pancreatic biology. Our findings, while not conclusive, indicate the importance of considering non-additive genetic models when performing GWAS analysis. The SNPs associated with pancreatic cancer in this study could be used for further meta-analysis for recessive association of SNPs and pancreatic cancer risk and might be a useful addiction to improve the performance of polygenic risk scores

Genetic Polymorphisms Involved in Mitochondrial Metabolism and Pancreatic Cancer Risk

Background: The mitochondrial metabolism has been associated with pancreatic ductal adenocarcinoma (PDAC) risk. Recent evidence also suggests the involvement of the genetic variability of the mitochondrial function in several traits involved in PDAC etiology. However, a systematic investigation of the genetic variability of mitochondrial genome (mtSNP) and of all the nuclear genes involved in its functioning (n-mtSNPs) has never been reported. Methods: We conducted a two-phase association study of mtSNPs and n-mtSNPs to assess their effect on PDAC risk. We analyzed 35,297 n-mtSNPs and 101 mtSNPs in up to 55,870 individuals (12,884 PDAC cases and 42,986 controls). In addition, we also conducted a gene-based analysis on 1,588 genes involved in mitochondrial metabolism using Multi-marker Analysis of GenoMic Annotation (MAGMA) software. Results: In the discovery phase, we identified 49 n-mtSNPs and no mtSNPs associated with PDAC risk (P &lt; 0.05). In the second phase, none of the findings were replicated. In the gene-level analysis, we observed that three genes (TERT, SUGCT, and SURF1) involved in the mitochondrial metabolism showed an association below the Bonferroni-corrected threshold of statistical significance (P = 0.05/1588 - 3.1 x 10(-5)). Conclusions: Even though the mitochondrial metabolism might be involved in PDAC etiology, our results, obtained in a study with one of the largest sample sizes to date, show that neither n-mtSNPs nor mtSNPs are associated with PDAC risk