Widespread sex differences in gene expression and splicing in the adult human brain

There is strong evidence to show that men and women differ in terms of neurodevelopment, neurochemistry and susceptibility to neurodegenerative and neuropsychiatric disease. The molecular basis of these differences remains unclear. Progress in this field has been hampered by the lack of genome-wide information on sex differences in gene expression and in particular splicing in the human brain. Here we address this issue by using post-mortem adult human brain and spinal cord samples originating from 137 neuropathologically confirmed control individuals to study whole-genome gene expression and splicing in 12 CNS regions. We show that sex differences in gene expression and splicing are widespread in adult human brain, being detectable in all major brain regions and involving 2.5% of all expressed genes. We give examples of genes where sex-biased expression is both disease-relevant and likely to have functional consequences, and provide evidence suggesting that sex biases in expression may reflect sex-biased gene regulatory structures

Incidence of Schizophrenia and Other Psychoses in England, 1950–2009: A Systematic Review and Meta-Analyses

Background We conducted a systematic review of incidence rates in England over a sixty-year period to determine the extent to which rates varied along accepted (age, sex) and less-accepted epidemiological gradients (ethnicity, migration and place of birth and upbringing, time). Objectives To determine variation in incidence of several psychotic disorders as above. Data Sources Published and grey literature searches (MEDLINE, PSycINFO, EMBASE, CINAHL, ASSIA, HMIC), and identification of unpublished data through bibliographic searches and author communication. Study Eligibility Criteria Published 1950–2009; conducted wholly or partially in England; original data on incidence of non-organic adult-onset psychosis or one or more factor(s) pertaining to incidence. Participants People, 16–64 years, with first -onset psychosis, including non-affective psychoses, schizophrenia, bipolar disorder, psychotic depression and substance-induced psychosis. Study Appraisal and Synthesis Methods Title, abstract and full-text review by two independent raters to identify suitable citations. Data were extracted to a standardized extraction form. Descriptive appraisals of variation in rates, including tables and forest plots, and where suitable, random-effects meta-analyses and meta-regressions to test specific hypotheses; rate heterogeneity was assessed by the I2-statistic. Results 83 citations met inclusion. Pooled incidence of all psychoses (N = 9) was 31.7 per 100,000 person-years (95%CI: 24.6–40.9), 23.2 (95%CI: 18.3–29.5) for non-affective psychoses (N = 8), 15.2 (95%CI: 11.9–19.5) for schizophrenia (N = 15) and 12.4 (95%CI: 9.0–17.1) for affective psychoses (N = 7). This masked rate heterogeneity (I2: 0.54–0.97), possibly explained by socio-environmental factors; our review confirmed (via meta-regression) the typical age-sex interaction in psychosis risk, including secondary peak onset in women after 45 years. Rates of most disorders were elevated in several ethnic minority groups compared with the white (British) population. For example, for schizophrenia: black Caribbean (pooled RR: 5.6; 95%CI: 3.4–9.2; N = 5), black African (pooled RR: 4.7; 95%CI: 3.3–6.8; N = 5) and South Asian groups in England (pooled RR: 2.4; 95%CI: 1.3–4.5; N = 3). We found no evidence to support an overall change in the incidence of psychotic disorder over time, though diagnostic shifts (away from schizophrenia) were reported. Limitations Incidence studies were predominantly cross-sectional, limiting causal inference. Heterogeneity, while evidencing important variation, suggested pooled estimates require interpretation alongside our descriptive systematic results. Conclusions and Implications of Key Findings Incidence of psychotic disorders varied markedly by age, sex, place and migration status/ethnicity. Stable incidence over time, together with a robust socio-environmental epidemiology, provides a platform for developing prediction models for health service planning