HySenS data exploitation for urban land cover analysis

This paper addresses the use of HySenS airborne hyperspectral data for environmental urban monitoring. It is known that hyperspectral data can help to characterize some of the relations between soil composition, vegetation characteristics, and natural/artificial materials in urbanized areas. During the project we collected DAIS and ROSIS data over the urban test area of Pavia, Northern Italy, though due to a late delivery of ROSIS data only DAIS data was used in this work. Here we show results referring to an accurate characterization and classification of land cover/use, using different supervised approaches, exploiting spectral as well as spatial information. We demonstrate the possibility to extract from the hyperspectral data information which is very useful for environmental characterization of urban areas

Temporal delay discounting in acutely ill and weight-recovered patients with anorexia nervosa

Background. Patients with anorexia nervosa (AN) are characterized by a very low body weight but readily give up immediate rewards (food) for long-term goals (slim figure), which might indicate an unusual level of self-control. This everyday clinical observation may be quantifiable in the framework of the anticipation-discounting dilemma. Method. Using a cross-sectional design, this study compared the capacity to delay reward in 34 patients suffering from acute AN (acAN), 33 weight-recovered AN patients (recAN) and 54 healthy controls. We also used a longitudinal study to reassess 21 acAN patients after short-term weight restoration. A validated intertemporal choice task and a hyperbolic model were used to estimate temporal discounting rates. Results. Confirming the validity of the task used, decreased delay discounting was associated with age and low selfreported impulsivity. However, no group differences in key measures of temporal discounting of monetary rewards were found. Conclusions. Increased cognitive control, which has been suggested as a key characteristic of AN, does not seem to extend the capacity to wait for delayed monetary rewards. Differences between our study and the only previous study reporting decreased delay discounting in adult AN patients may be explained by the different age range and chronicity of acute patients, but the fact that weight recovery was not associated with changes in discount rates suggests that discounting behavior is not a trait marker in AN. Future studies using paradigms with disorder-specific stimuli may help to clarify the role of delay discounting in AN

Functional neuroimaging effects of recently discovered genetic risk loci for schizophrenia and polygenic risk profile in five RDoC subdomains

Recently, 125 loci with genome-wide support for association with schizophrenia were identified. We investigated the impact of these variants and their accumulated genetic risk on brain activation in five neurocognitive domains of the Research Domain Criteria (working memory, reward processing, episodic memory, social cognition and emotion processing). In 578 healthy subjects we tested for association (i) of a polygenic risk profile score (RPS) including all single-nucleotide polymorphisms (SNPs) reaching genome-wide significance in the recent genome-wide association studies (GWAS) meta-analysis and (ii) of all independent genome-wide significant loci separately that showed sufficient distribution of all allelic groups in our sample (105 SNPs). The RPS was nominally associated with perigenual anterior cingulate and posterior cingulate/precuneus activation during episodic memory (PFWE(ROI)=0.047) and social cognition (PFWE(ROI)=0.025), respectively. Single SNP analyses revealed that rs9607782, located near EP300, was significantly associated with amygdala recruitment during emotion processing (PFWE(ROI)=1.63 × 10−4, surpassing Bonferroni correction for the number of SNPs). Importantly, this association was replicable in an independent sample (N=150; PFWE(ROI)<0.025). Other SNP effects previously associated with imaging phenotypes were nominally significant, but did not withstand correction for the number of SNPs tested. To assess whether there was true signal within our data, we repeated single SNP analyses with 105 randomly chosen non-schizophrenia-associated variants, observing fewer significant results and lower association probabilities. Applying stringent methodological procedures, we found preliminary evidence for the notion that genetic risk for schizophrenia conferred by rs9607782 may be mediated by amygdala function. We critically evaluate the potential caveats of the methodological approaches employed and offer suggestions for future studies

HySenS data exploitation for urban land cover analysis

This paper addresses the use of HySenS airborne hyperspectral data for environmental urban monitoring. It is known that hyperspectral data can help to characterize some of the relations between soil composition, vegetation characteristics, and natural/artificial materials in urbanized areas. During the project we collected DAIS and ROSIS data over the urban test area of Pavia, Northern Italy, though due to a late delivery of ROSIS data only DAIS data was used in this work. Here we show results referring to an accurate characterization and classification of land cover/use, using different supervised approaches, exploiting spectral as well as spatial information. We demonstrate the possibility to extract from the hyperspectral data information which is very useful for environmental characterization of urban areas

Genetic modifiers and subtypes in schizophrenia: Investigations of age at onset, severity, sex and family history

Schizophrenia is a genetically and clinically heterogeneous disorder. Genetic risk factors for the disorder may differ between the sexes or between multiply affected families compared to cases with no family history. Additionally, limited data support a genetic basis for variation in onset and severity, but specific loci have not been identified. We performed genome-wide association studies (GWAS) examining genetic influences on age at onset (AAO) and illness severity as well as specific risk by sex or family history status using up to 2762 cases and 3187 controls from the International Schizophrenia Consortium (ISC)

Polygenic risk score, parental socioeconomic status, family history of psychiatric disorders, and the risk for schizophrenia: a Danish population-based study and meta-analysis

IMPORTANCE Schizophrenia has a complex etiology influenced both by genetic and nongenetic factors but disentangling these factors is difficult. OBJECTIVE To estimate (1) how strongly the risk for schizophrenia relates to the mutual effect of the polygenic risk score, parental socioeconomic status, and family history of psychiatric disorders; (2) the fraction of cases that could be prevented if no one was exposed to these factors; (3) whether family background interacts with an individual's genetic liability so that specific subgroups are particularly risk prone; and (4) to what extent a proband's genetic makeup mediates the risk associated with familial background. DESIGN, SETTINGS, AND PARTICIPANTS We conducted a nested case-control study based onDanish population-based registers. The study consisted of 866 patients diagnosed as having schizophrenia between January 1, 1994, and December 31, 2006, and 871 matched control individuals. Genome-wide data and family psychiatric and socioeconomic background information were obtained from neonatal biobanks and national registers. Results from a separate meta-analysis (34 600 cases and 45 968 control individuals) were applied to calculate polygenic risk scores. EXPOSURES Polygenic risk scores, parental socioeconomic status, and family psychiatric history. MAIN OUTCOMES AND MEASURES Odds ratios (ORs), attributable risks, liability R2 values, and proportions mediated. RESULTS Schizophrenia was associated with the polygenic risk score (OR, 8.01; 95%CI, 4.53-14.16 for highest vs lowest decile), socioeconomic status (OR, 8.10; 95%CI, 3.24-20.3 for 6 vs no exposures), and a history of schizophrenia/psychoses (OR, 4.18; 95%CI, 2.57-6.79). The R2 values were 3.4%(95%CI, 2.1-4.6) for the polygenic risk score, 3.1%(95%CI, 1.9-4.3) for parental socioeconomic status, and 3.4%(95%CI, 2.1-4.6) for family history. Socioeconomic status and psychiatric history accounted for 45.8% (95%CI, 36.1-55.5) and 25.8% (95%CI, 21.2-30.5) of cases, respectively. There was an interaction between the polygenic risk score and family history (P = .03). A total of 17.4%(95%CI, 9.1-26.6) of the effect associated with family history of schizophrenia/psychoses was mediated through the polygenic risk score. CONCLUSIONS AND RELEVANCE Schizophrenia was associated with the polygenic risk score, family psychiatric history, and socioeconomic status. Our study demonstrated that family history of schizophrenia/psychoses is partly mediated through the individual's genetic liability

Psychometric precision in phenotype definition is a useful step in molecular genetic investigation of psychiatric disorders

Affective disorders are highly heritable, but few genetic risk variants have been consistently replicated in molecular genetic association studies. The common method of defining psychiatric phenotypes in molecular genetic research is either a summation of symptom scores or binary threshold score representing the risk of diagnosis. Psychometric latent variable methods can improve the precision of psychiatric phenotypes, especially when the data structure is not straightforward. Using data from the British 1946 birth cohort, we compared summary scores with psychometric modeling based on the General Health Questionnaire (GHQ-28) scale for affective symptoms in an association analysis of 27 candidate genes (249 single-nucleotide polymorphisms (SNPs)). The psychometric method utilized a bi-factor model that partitioned the phenotype variances into five orthogonal latent variable factors, in accordance with the multidimensional data structure of the GHQ-28 involving somatic, social, anxiety and depression domains. Results showed that, compared with the summation approach, the affective symptoms defined by the bi-factor psychometric model had a higher number of associated SNPs of larger effect sizes. These results suggest that psychometrically defined mental health phenotypes can reflect the dimensions of complex phenotypes better than summation scores, and therefore offer a useful approach in genetic association investigations