Exploring mothers' experiences of perinatal care in Cyprus: Babies Born Better survey.

INTRODUCTION: A positive perinatal experience facilitates a smooth transition to motherhood and enhances the development of a strong bond between mother and newborn, contributing to maternal and societal wellbeing. Given the medicalization of childbirth in Cyprus, the examination of mothers' experiences of perinatal care becomes imperative. AIM: To investigate mothers' experiences of care during the perinatal period and to identify factors related to the provision of maternal care that contribute to the interpretation of these experiences. METHODS: The study draws on data from the European survey "Babies Born Better", an online survey utilizing a mixed-methods approach to explore women's experiences of maternity care across Europe. The study population were women who had given birth in Cyprus over a 5-year period (2013-2018). Quantitative data were analyzed using SPSS v22, while qualitative data were analyzed through inductive content analysis. FINDINGS: A total of 360 mothers participated in the study. In rating their overall experience, 24.2% stated that they had a "bad experience", 11.1% a "good experience",13.9% a "very good experience", and 13,3% a "very bad experience". The top three sub-factors of the overall experience which received positive evaluation were "Relationship with health care professionals" (33.6%), "Birth environment and care" (11.4%), and "Breastfeeding guidance" (10.8%). The qualitative analysis yielded five themes: "Relationship with health care professionals", "Breastfeeding establishment", "Childbirth rights", "Birth environment and services" and "Choice of mode of birth". CONCLUSION: Mothers in Cyprus wish to have respectful maternity care. They need maternity health care professionals to respect their dignity and ask for evidence-based information with shared decision making. Mothers in Cyprus expect to have their childbirth rights safeguarded, to have better support from HCP, and to receive humanized care. The perinatal care provided in Cyprus needs significant improvements based on mothers' needs and expectations.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium.

This corrects the article DOI: 10.1038/mp.2016.244.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium.

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10-8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

Genome-wide autozygosity is associated with lower general cognitive ability.

Inbreeding depression refers to lower fitness among offspring of genetic relatives. This reduced fitness is caused by the inheritance of two identical chromosomal segments (autozygosity) across the genome, which may expose the effects of (partially) recessive deleterious mutations. Even among outbred populations, autozygosity can occur to varying degrees due to cryptic relatedness between parents. Using dense genome-wide single-nucleotide polymorphism (SNP) data, we examined the degree to which autozygosity associated with measured cognitive ability in an unselected sample of 4854 participants of European ancestry. We used runs of homozygosity-multiple homozygous SNPs in a row-to estimate autozygous tracts across the genome. We found that increased levels of autozygosity predicted lower general cognitive ability, and estimate a drop of 0.6 s.d. among the offspring of first cousins (P=0.003-0.02 depending on the model). This effect came predominantly from long and rare autozygous tracts, which theory predicts as more likely to be deleterious than short and common tracts. Association mapping of autozygous tracts did not reveal any specific regions that were predictive beyond chance after correcting for multiple testing genome wide. The observed effect size is consistent with studies of cognitive decline among offspring of known consanguineous relationships. These findings suggest a role for multiple recessive or partially recessive alleles in general cognitive ability, and that alleles decreasing general cognitive ability have been selected against over evolutionary time.

Let's go outside: using photography to explore values and culture in mental health nursing.

Creative and imaginative approaches to mental healthcare education are known to help students explore emotions, empathy and others' experiences, as well as address ambivalence and ambiguity. Very few studies in mental health nursing education specifically utilise photography as a participatory pedagogic tool, with even fewer utilising photography to explore understandings of culture, values and diversity. Photography makes visible complex, collaborative forms of learning and previously unidentified, unarticulated ideas about culture and values. Photography as a critical pedagogic method helps develop critical, politicized understandings of culture and values. Increasing culturally diverse populations means complex and conflicting values have become a common feature in mental health nursing. In education the need to critically examine such topics necessitates creative and engaging pedagogy, and visual methods are readily acknowledged as such. Yet while many studies advocate and demonstrate the value of art-based methods in student learning, very few studies in mental health nursing specifically utilize photography as a participatory pedagogic tool, and fewer still use photography to explore understandings of culture, values and diversity. In this paper, we discuss a qualitative study where mental health nursing students used photography to create images in order to explore their own and often dominant culture and attendant values. Findings suggest that photography makes visible situated, relational and collaborative learning, and surfaces previously unidentified, unarticulated ideas about culture and values. These practices mimic important processes central to mental health nursing practice and contemporaneous understandings of diverse cultures. We argue that photography provides an important resource with which to unearth subjugated knowledge, promote critical understandings of culture and values, and thereby help address inequalities in mental health care.

GWAS-based pathway analysis differentiates between fluid and crystallized intelligence.

Cognitive abilities vary among people. About 40-50% of this variability is due to general intelligence (g), which reflects the positive correlation among individuals' scores on diverse cognitive ability tests. g is positively correlated with many life outcomes, such as education, occupational status and health, motivating the investigation of its underlying biology. In psychometric research, a distinction is made between general fluid intelligence (gF) - the ability to reason in novel situations - and general crystallized intelligence (gC) - the ability to apply acquired knowledge. This distinction is supported by developmental and cognitive neuroscience studies. Classical epidemiological studies and recent genome-wide association studies (GWASs) have established that these cognitive traits have a large genetic component. However, no robust genetic associations have been published thus far due largely to the known polygenic nature of these traits and insufficient sample sizes. Here, using two GWAS datasets, in which the polygenicity of gF and gC traits was previously confirmed, a gene- and pathway-based approach was undertaken with the aim of characterizing and differentiating their genetic architecture. Pathway analysis, using genes selected on the basis of relaxed criteria, revealed notable differences between these two traits. gF appeared to be characterized by genes affecting the quantity and quality of neurons and therefore neuronal efficiency, whereas long-term depression (LTD) seemed to underlie gC. Thus, this study supports the gF-gC distinction at the genetic level and identifies functional annotations and pathways worthy of further investigation.

Human cognitive ability is influenced by genetic variation in components of postsynaptic signalling complexes assembled by NMDA receptors and MAGUK proteins.

Differences in general cognitive ability (intelligence) account for approximately half of the variation in any large battery of cognitive tests and are predictive of important life events including health. Genome-wide analyses of common single-nucleotide polymorphisms indicate that they jointly tag between a quarter and a half of the variance in intelligence. However, no single polymorphism has been reliably associated with variation in intelligence. It remains possible that these many small effects might be aggregated in networks of functionally linked genes. Here, we tested a network of 1461 genes in the postsynaptic density and associated complexes for an enriched association with intelligence. These were ascertained in 3511 individuals (the Cognitive Ageing Genetics in England and Scotland (CAGES) consortium) phenotyped for general cognitive ability, fluid cognitive ability, crystallised cognitive ability, memory and speed of processing. By analysing the results of a genome wide association study (GWAS) using Gene Set Enrichment Analysis, a significant enrichment was found for fluid cognitive ability for the proteins found in the complexes of N-methyl-D-aspartate receptor complex; P=0.002. Replication was sought in two additional cohorts (N=670 and 2062). A meta-analytic P-value of 0.003 was found when these were combined with the CAGES consortium. The results suggest that genetic variation in the macromolecular machines formed by membrane-associated guanylate kinase (MAGUK) scaffold proteins and their interaction partners contributes to variation in intelligence.

Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the Cognitive Genomics consorTium (COGENT).

It has long been recognized that generalized deficits in cognitive ability represent a core component of schizophrenia (SCZ), evident before full illness onset and independent of medication. The possibility of genetic overlap between risk for SCZ and cognitive phenotypes has been suggested by the presence of cognitive deficits in first-degree relatives of patients with SCZ; however, until recently, molecular genetic approaches to test this overlap have been lacking. Within the last few years, large-scale genome-wide association studies (GWAS) of SCZ have demonstrated that a substantial proportion of the heritability of the disorder is explained by a polygenic component consisting of many common single-nucleotide polymorphisms (SNPs) of extremely small effect. Similar results have been reported in GWAS of general cognitive ability. The primary aim of the present study is to provide the first molecular genetic test of the classic endophenotype hypothesis, which states that alleles associated with reduced cognitive ability should also serve to increase risk for SCZ. We tested the endophenotype hypothesis by applying polygenic SNP scores derived from a large-scale cognitive GWAS meta-analysis (~5000 individuals from nine nonclinical cohorts comprising the Cognitive Genomics consorTium (COGENT)) to four SCZ case-control cohorts. As predicted, cases had significantly lower cognitive polygenic scores compared to controls. In parallel, polygenic risk scores for SCZ were associated with lower general cognitive ability. In addition, using our large cognitive meta-analytic data set, we identified nominally significant cognitive associations for several SNPs that have previously been robustly associated with SCZ susceptibility. Results provide molecular confirmation of the genetic overlap between SCZ and general cognitive ability, and may provide additional insight into pathophysiology of the disorder.

The effect of organelle discovery upon sub-cellular protein localisation.

Prediction of protein sub-cellular localisation by employing quantitative mass spectrometry experiments is an expanding field. Several methods have led to the assignment of proteins to specific subcellular localisations by partial separation of organelles across a fractionation scheme coupled with computational analysis. Methods developed to analyse organelle data have largely employed supervised machine learning algorithms to map unannotated abundance profiles to known protein-organelle associations. Such approaches are likely to make association errors if organelle-related groupings present in experimental output are not included in data used to create a protein-organelle classifier. Currently, there is no automated way to detect organelle-specific clusters within such datasets. In order to address the above issues we adapted a phenotype discovery algorithm, originally created to filter image-based output for RNAi screens, to identify putative subcellular groupings in organelle proteomics experiments. We were able to mine datasets to a deeper level and extract interesting phenotype clusters for more comprehensive evaluation in an unbiased fashion upon application of this approach. Organelle-related protein clusters were identified beyond those sufficiently annotated for use as training data. Furthermore, we propose avenues for the incorporation of observations made into general practice for the classification of protein-organelle membership from quantitative MS experiments. BIOLOGICAL SIGNIFICANCE: Protein sub-cellular localisation plays an important role in molecular interactions, signalling and transport mechanisms. The prediction of protein localisation by quantitative mass-spectrometry (MS) proteomics is a growing field and an important endeavour in improving protein annotation. Several such approaches use gradient-based separation of cellular organelle content to measure relative protein abundance across distinct gradient fractions. The distribution profiles are commonly mapped in silico to known protein-organelle associations via supervised machine learning algorithms, to create classifiers that associate unannotated proteins to specific organelles. These strategies are prone to error, however, if organelle-related groupings present in experimental output are not represented, for example owing to the lack of existing annotation, when creating the protein-organelle mapping. Here, the application of a phenotype discovery approach to LOPIT gradient-based MS data identifies candidate organelle phenotypes for further evaluation in an unbiased fashion. Software implementation and usage guidelines are provided for application to wider protein-organelle association experiments. In the wider context, semi-supervised organelle discovery is discussed as a paradigm with which to generate new protein annotations from MS-based organelle proteomics experiments.

Genome-wide association studies establish that human intelligence is highly heritable and polygenic.

General intelligence is an important human quantitative trait that accounts for much of the variation in diverse cognitive abilities. Individual differences in intelligence are strongly associated with many important life outcomes, including educational and occupational attainments, income, health and lifespan. Data from twin and family studies are consistent with a high heritability of intelligence, but this inference has been controversial. We conducted a genome-wide analysis of 3511 unrelated adults with data on 549,692 single nucleotide polymorphisms (SNPs) and detailed phenotypes on cognitive traits. We estimate that 40% of the variation in crystallized-type intelligence and 51% of the variation in fluid-type intelligence between individuals is accounted for by linkage disequilibrium between genotyped common SNP markers and unknown causal variants. These estimates provide lower bounds for the narrow-sense heritability of the traits. We partitioned genetic variation on individual chromosomes and found that, on average, longer chromosomes explain more variation. Finally, using just SNP data we predicted ∼1% of the variance of crystallized and fluid cognitive phenotypes in an independent sample (P=0.009 and 0.028, respectively). Our results unequivocally confirm that a substantial proportion of individual differences in human intelligence is due to genetic variation, and are consistent with many genes of small effects underlying the additive genetic influences on intelligence.

Association study of energy homeostasis genes and antipsychotic-induced weight gain in patients with schizophrenia.

INTRODUCTION: Marked inter-individual variation has been observed with respect to the risk of weight gain and related metabolic disturbances during antipsychotic treatment, which in part could be explained by heritability. Such adverse effects have been proposed to occur through drug-induced mechanisms involving both the central nervous system and different peripheral tissues. METHODS: We genotyped tagSNPs in several genes ( ADIPOQ, PRKAA1, PRKAA2, PRKAB1, PRKAG1, PRKAG2, PRKAG3, FTO and FABP3) that regulate lipid and energy homeostasis for their possible association to antipsychotic-induced weight gain. RESULTS: In a sample of 160 patients of German origin with schizophrenia who had been monitored with respect to body weight, we found marked association between antipsychotic-related changes in BMI and 6 markers in the adiponectin gene ( ADIPOQ). DISCUSSION: These findings support previous observations (in patients' serum) that adiponectin is involved in antipsychotic-mediated metabolic adverse effects.

Interacting haplotypes at the NPAS3 locus alter risk of schizophrenia and bipolar disorder.

The neuronal PAS domain 3 (NPAS3) gene encodes a neuronal transcription factor that is implicated in psychiatric disorders by the identification of a human chromosomal translocation associated with schizophrenia and a mouse knockout model with behavioural and hippocampal neurogenesis defects. To determine its contribution to the risk of psychiatric illness in the general population, we genotyped 70 single-nucleotide polymorphisms across the NPAS3 gene in 368 individuals with bipolar disorder, 386 individuals with schizophrenia and 455 controls. Modestly significant single-marker and global and individual haplotypes were identified in four discrete regions of the gene. The presence of both risk and protective haplotypes at each of these four regions indicated locus and allelic heterogeneity within NPAS3 and suggested a model whereby interactions between variants across the gene might contribute to susceptibility to illness. This was supported by predicting the most likely haplotype for each individual at each associated region and then calculating an NPAS3-mediated 'net genetic load' value. This value differed significantly from controls for both bipolar disorder (P=0.0000010) and schizophrenia (P=0.0000012). Logistic regression analysis also confirmed the combinatorial action of the four associated regions on disease risk. In addition, sensitivity/specificity plots showed that the extremes of the genetic loading distribution possess the greatest predictive power-a feature suggesting multiplicative allele interaction. These data add to recent evidence that the combinatorial analysis of a number of relatively small effect size haplotypes may have significant power to predict an individual's risk of a complex genetic disorder such as psychiatric illness.

Association analysis of the chromosome 4p15-p16 candidate region for bipolar disorder and schizophrenia.

Several independent linkage studies have identified chromosome 4p15-p16 as a putative region of susceptibility for bipolar disorder (BP), schizophrenia (SCZ) and related phenotypes. Previously, we identified two subregions (B and D) of the 4p15-p16 region that are shared by three of four 4p-linked families examined. Here, we describe a large-scale association analysis of regions B and D (3.8 and 4.5 Mb, respectively). We selected 408 haplotype-tagging single nucleotide polymorphisms (SNPs) on a block-by-block basis from the International HapMap project and tested them in 368 BP, 386 SCZ and 458 control individuals. Nominal significance thresholds were determined using principal component analysis as implemented in the program SNPSpD. In region B, overlapping SNPs and haplotypes met the region-wide threshold (P

Association of Neuregulin 1 with schizophrenia and bipolar disorder in a second cohort from the Scottish population.

Neuregulin 1 (NRG1) is a strong candidate for involvement in the aetiology of schizophrenia. A haplotype, initially identified as showing association in the Icelandic and Scottish populations, has shown a consistent effect size in multiple European populations. Additionally, NRG1 has been implicated in susceptibility to bipolar disorder. In this first study to select markers systematically on the basis of linkage disequilibrium across the entire NRG1 gene, we used haplotype-tagging single-nucleotide polymorphisms to identify single markers and haplotypes associated with schizophrenia and bipolar disorder in an independently ascertained Scottish population. Haplotypes in two regions met an experiment-wide significance threshold of P=0.0016 (Nyholt's SpD) and were permuted to correct for multiple testing. Region A overlaps with the Icelandic haplotype and shows nominal association with schizophrenia (P=0.00032), bipolar disorder (P=0.0011), and the combined case group (P=0.0017). This region includes the 5' exon of the NRG1 GGF2 isoform and overlaps the expressed sequence tag (EST) cluster Hs.97362. However, no haplotype in Region A remains significant after permutation analysis (P>0.05). Region B contains a haplotype associated with both schizophrenia (P=0.00014), and the combined case group (P=0.000062), although it does not meet Nyholt's threshold in bipolar disorder alone (P=0.0022). This haplotype remained significant after permutation analysis in both the schizophrenia and combined case groups (P=0.024 and P=0.016, respectively). It spans a approximately 136 kb region that includes the coding sequence of the sensory and motor neuron derived factor (SMDF) isoform and 3' exons of all other known NRG1 isoforms. Our study identifies a new of NRG1 region involved in schizophrenia and bipolar disorder in the Scottish population.

Cytogenetic and genetic evidence supports a role for the kainate-type glutamate receptor gene, GRIK4, in schizophrenia and bipolar disorder.

In the search for the biological causes of schizophrenia and bipolar disorder, glutamate neurotransmission has emerged as one of a number of candidate processes and pathways where underlying gene deficits may be present. The analysis of chromosomal rearrangements in individuals diagnosed with neuropsychiatric disorders is an established route to candidate gene identification in both Mendelian and complex disorders. Here we describe a set of genes disrupted by, or proximal to, chromosomal breakpoints (2p12, 2q31.3, 2q21.2, 11q23.3 and 11q24.2) in a patient where chronic schizophrenia coexists with mild learning disability (US: mental retardation). Of these disrupted genes, the most promising candidate is a member of the kainate-type ionotropic glutamate receptor family, GRIK4 (KA1). A subsequent systematic case-control association study on GRIK4 assessed its contribution to psychiatric illness in the karyotypically normal population. This identified two discrete regions of disease risk within the GRIK4 locus: three single single nucleotide polymorphism (SNP) markers with a corresponding underlying haplotype associated with susceptibility to schizophrenia (P=0.0005, odds ratio (OR) of 1.453, 95% CI 1.182-1.787) and two single SNP markers and a haplotype associated with a protective effect against bipolar disorder (P=0.0002, OR of 0.624, 95% CI 0.485-0.802). After permutation analysis to correct for multiple testing, schizophrenia and bipolar disorder haplotypes remained significant (P=0.0430, s.e. 0.0064 and P=0.0190, s.e. 0.0043, respectively). We propose that these convergent cytogenetic and genetic findings provide molecular evidence for common aetiologies for different psychiatric conditions and further support the 'glutamate hypothesis' of psychotic illness.

Association analysis of the chromosome 4p-located G protein-coupled receptor 78 (GPR78) gene in bipolar affective disorder and schizophrenia.

The orphan G protein-coupled receptor 78 (GPR78) gene lies within a region of chromosome 4p where we have previously shown linkage to bipolar affective disorder (BPAD) in a large Scottish family. GPR78 was screened for single-nucleotide polymorphisms (SNPs) and a linkage disequilibrium map was constructed. Six tagging SNPs were selected and tested for association on a sample of 377 BPAD, 392 schizophrenia (SCZ) and 470 control individuals. Using standard chi(2) statistics and a backwards logistic regression approach to adjust for the effect of sex, SNP rs1282, located approximately 3 kb upstream of the coding region, was identified as a potentially important variant in SCZ (chi(2) P=0.044; LRT P=0.065). When the analysis was restricted to females, the strength of association increased to an uncorrected allele P-value of 0.015 (odds ratios (OR)=1.688, 95% confidence intervals (CI): 1.104-2.581) and uncorrected genotype P-value of 0.015 (OR=5.991, 95% CI: 1.545-23.232). Under the recessive model, the genotype P-value improved further to 0.005 (OR=5.618, 95% CI: 1.460-21.617) and remained significant after correcting for multiple testing (P=0.017). No single-marker association was detected in the SCZ males, in the BPAD individuals or with any other SNP. Haplotype analysis of the case-control samples revealed several global and individual haplotypes, with P-values <0.05, all but one of which contained SNP rs1282. After correcting for multiple testing, two haplotypes remained significant in both the female BPAD individuals (P=0.038 and 0.032) and in the full sample of affected female individuals (P=0.044 and 0.033). Our results provide preliminary evidence for the involvement of GPR78 in susceptibility to BPAD and SCZ in the Scottish population.