12 research outputs found
Not All Income is the Same to Everyone: Cognitive Ability and the House Money Effect in Public Goods Games
No full textThe provision of public goods often suffers from a social dilemma generating too little contributions. Yet, it remains an open question how positive contributions materialise. Existing studies suggest that individuals' decisions on how much to contribute depend on cognitive skills. Furthermore, mental accounting research indicates that the source of income matters for economic decision making. I show experimentally that subjects' contributions in a one-shot linear public goods game depend on an interplay of the two factors. While a house money effect exists for subjects with low cognitive skills there is no such effect for those with high cognitive skills. My findings have important implications for taxation, redistribution, and voting behaviour, as well as past and future experiments
A Brief Guide for the Creation of Author-specific Citation Metrics and Publication Data Using the Thomson Reuters Web of Science and Scopus Databases
No full textThe objective of this guide is twofold. First, it shall enable interested readers to understand and reproduce the process of collecting author-specific citation metrics and publication data from the Thomson Reuters Web of Science and Scopus databases that is adopted in Andreoli-Versbach and Mueller-Langer (2013). Second, it presents the problems faced during the data collection process and the refined method of data collection we adopt to address related concerns. Thereby, it may serve interested readers as a guideline to accurately and efficiently retrieve citation metrics and publication information from Thomson Reuters Web of Science and Scopus in similar endeavors
Evidence for genetic contribution to the increased risk of type 2 diabetes in schizophrenia
No full textThe epidemiologic link between schizophrenia (SCZ) and type 2 diabetes (T2D) remains poorly understood. Here, we investigate the presence and extent of a shared genetic background between SCZ and T2D using genome-wide approaches. We performed a genome-wide association study (GWAS) and polygenic risk score analysis in a Greek sample collection (GOMAP) comprising three patient groups: SCZ only (n = 924), T2D only (n = 822), comorbid SCZ and T2D (n = 505); samples from two separate Greek cohorts were used as population-based controls (n = 1,125). We used genome-wide summary statistics from two large-scale GWAS of SCZ and T2D from the PGC and DIAGRAM consortia, respectively, to perform genetic overlap analyses, including a regional colocalisation test. We show for the first time that patients with comorbid SCZ and T2D have a higher genetic predisposition to both disorders compared to controls. We identify five genomic regions with evidence of colocalising SCZ and T2D signals, three of which contain known loci for both diseases. We also observe a significant excess of shared association signals between SCZ and T2D at nine out of ten investigated p value thresholds. Finally, we identify 29 genes associated with both T2D and SCZ, several of which have been implicated in biological processes relevant to these disorders. Together our results demonstrate that the observed comorbidity between SCZ and T2D is at least in part due to shared genetic mechanisms. © 2018, The Author(s)
Evidence for genetic contribution to the increased risk of type 2 diabetes in schizophrenia
No full textThe epidemiologic link between schizophrenia (SCZ) and type 2 diabetes (T2D) remains poorly understood. Here, we investigate the presence and extent of a shared genetic background between SCZ and T2D using genome-wide approaches. We performed a genome-wide association study (GWAS) and polygenic risk score analysis in a Greek sample collection (GOMAP) comprising three patient groups: SCZ only (n = 924), T2D only (n = 822), comorbid SCZ and T2D (n = 505); samples from two separate Greek cohorts were used as population-based controls (n = 1,125). We used genome-wide summary statistics from two large-scale GWAS of SCZ and T2D from the PGC and DIAGRAM consortia, respectively, to perform genetic overlap analyses, including a regional colocalisation test. We show for the first time that patients with comorbid SCZ and T2D have a higher genetic predisposition to both disorders compared to controls. We identify five genomic regions with evidence of colocalising SCZ and T2D signals, three of which contain known loci for both diseases. We also observe a significant excess of shared association signals between SCZ and T2D at nine out of ten investigated p value thresholds. Finally, we identify 29 genes associated with both T2D and SCZ, several of which have been implicated in biological processes relevant to these disorders. Together our results demonstrate that the observed comorbidity between SCZ and T2D is at least in part due to shared genetic mechanisms. © 2018, The Author(s)
Combination therapy as a potential risk factor for the development of type 2 diabetes in patients with schizophrenia: The GOMAP study
No full textBackground: Schizophrenia (SCZ) is associated with increased risk of type 2 diabetes (T2D). The potential diabetogenic effect of concomitant application of psychotropic treatment classes in patients with SCZ has not yet been evaluated. The overarching goal of the Genetic Overlap between Metabolic and Psychiatric disease (GOMAP) study is to assess the effect of pharmacological, anthropometric, lifestyle and clinical measurements, helping elucidate the mechanisms underlying the aetiology of T2D. Methods: The GOMAP case-control study (Genetic Overlap between Metabolic and Psychiatric disease) includes hospitalized patients with SCZ, some of whom have T2D. We enrolled 1653 patients with SCZ; 611 with T2D and 1042 patients without T2D. This is the first study of SCZ and T2D comorbidity at this scale in the Greek population. We retrieved detailed information on first- and second-generation antipsychotics (FGA, SGA), antidepressants and mood stabilizers, applied as monotherapy, 2-drug combination, or as 3- or more drug combination. We assessed the effects of psychotropic medication, body mass index, duration of schizophrenia, number of hospitalizations and physical activity on risk of T2D. Using logistic regression, we calculated crude and adjusted odds ratios (OR) to identify associations between demographic factors and the psychiatric medications. Results: Patients with SCZ on a combination of at least three different classes of psychiatric drugs had a higher risk of T2D [OR 1.81 (95% CI 1.22-2.69); p=0.003] compared to FGA alone therapy, after adjustment for age, BMI, sex, duration of SCZ and number of hospitalizations. We did not find evidence for an association of SGA use or the combination of drugs belonging to two different classes of psychiatric medications with increased risk of T2D [1.27 (0.84-1.93), p=0.259 and 0.98 (0.71-1.35), p=0.885, respectively] compared to FGA use. Conclusions: We find an increased risk of T2D in patients with SCZ who take a combination of at least three different psychotropic medication classes compared to patients whose medication consists only of one or two classes of drugs. © 2018 The Author(s)
Evaluating the glucose raising effect of established loci via a genetic risk score
No full textRecent genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) associated with glucose levels. We tested the hypothesis here whether the cumulative effect of glucose raising SNPs, assessed via a score, is associated with glucose levels. A total of 1,434 participants of Greek descent from the THISEAS study and 1,160 participants form the GOMAP study were included in this analysis. We developed a genetic risk score (GRS), based on the known glucose-raising loci, in order to investigate the cumulative effect of known glucose loci on glucose levels. In the THISEAS study, the GRS score was significantly associated with increased glucose levels (mmol/L) (β ± SE: 0.024 ± 0.004, P = 8.27e-07). The effect of the genetic risk score was also significant in the GOMAP study (β ± SE: 0.011 ± 0.005, P = 0.031). In the meta-analysis of the two studies both scores were significantly associated with higher glucose levels GRS: β ± SE: 0.019 ± 0.003, P = 1.41e-09. Also, variants at the SLC30A8, PROX1, MTNR1B, ADRA2A, G6PC2, LPIN3 loci indicated nominal evidence for association with glucose levels (p < 0.05). We replicate associations of the established glucose raising variants in the Greek population and confirm directional consistency of effects (binomial sign test p = 6.96e-05). We also demonstrate that the cumulative effect of the established glucose loci yielded a significant association with increasing glucose levels. © 2017 Marouli et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Genome-wide analyses using UK Biobank data provide insights into the genetic architecture of osteoarthritis
No full textOsteoarthritis is a common complex disease imposing a large public-health burden. Here, we performed a genome-wide association study for osteoarthritis, using data across 16.5 million variants from the UK Biobank resource. After performing replication and meta-analysis in up to 30,727 cases and 297,191 controls, we identified nine new osteoarthritis loci, in all of which the most likely causal variant was noncoding. For three loci, we detected association with biologically relevant radiographic endophenotypes, and in five signals we identified genes that were differentially expressed in degraded compared with intact articular cartilage from patients with osteoarthritis. We established causal effects on osteoarthritis for higher body mass index but not for triglyceride levels or genetic predisposition to type 2 diabetes. © 2018 The Author(s)
Author Correction: High- or low-dose preoperative ipilimumab plus nivolumab in stage III urothelial cancer: the phase 1B NABUCCO trial (Nature Medicine, (2023), 29, 3, (588-592), 10.1038/s41591-022-02199-y)
No full textCorrection to: Nature Medicine. Published online 2 February 2023. In the version of this article initially published, the first name of Antoine G. van der Heijden was misspelled as “Toine” and has now been corrected in the HTML and PDF versions of the article
Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps
No full textWe expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency <5%, 14 with estimated allelic odds ratio >2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence). © 2018, The Author(s), under exclusive licence to Springer Nature America, Inc
