To date, the primary approach to improve the transfection properties of cationic lipids has been the synthesis of new kinds of cationic amphipaths or the inclusion of noncationic helper lipids. Here, it is reported that an alternative approach can be unusually effective, namely, the combination of two cationic lipid derivatives having the same head group but tails of different chain lengths. Particularly efficient was the combination of dilauroyl (12 carbon chain) and dioleoyl (18 carbon chain) homologues of O-ethylphosphatidylcholine.This mixture transfected DNA into human umbilical artery endothelial cells (HUAEC) more than 30-fold more efficiently than either compound separately. A unique advantage of this kind of combination agent is that transfection can be optimized either in the presence or absence of serum by adjusting the component ratio.

Numerous genetic and environmental factors contribute to psychiatric disorders and other brain disorders. Common risk factors likely converge on biological pathways regulating the optimization of brain structure and function across the lifespan. Here, using structural magnetic resonance imaging and machine learning, we estimated the gap between brain age and chronological age in 36,891 individuals aged 3 to 96 years, including individuals with different brain disorders. We show that several disorders are associated with accentuated brain aging, with strongest effects in schizophrenia, multiple sclerosis and dementia, and document differential regional patterns of brain age gaps between disorders. In 16,269 healthy adult individuals, we show that brain age gap is heritable with a polygenic architecture overlapping those observed in common brain disorders. Our results identify brain age gap as a genetically modulated trait that offers a window into shared and distinct mechanisms in different brain disorders.

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Evidence suggests that microRNA-137 (miR-137) is involved in the genetic basis of schizophrenia. Risk variants within the miR-137 host gene (MIR137HG) influence structural and functional brain-imaging measures, and miR-137 itself is predicted to regulate hundreds of genes. We evaluated the influence of a MIR137HG risk variant (rs1625579) in combination with variants in miR-137-regulated genes TCF4, PTGS2, MAPK1 and MAPK3 on gray matter concentration (GMC). These genes were selected based on our previous work assessing schizophrenia risk within possible miR-137-regulated gene sets using the same cohort of subjects. A genetic risk score (GRS) was determined based on genotypes of these four schizophrenia risk-associated genes in 221 Caucasian subjects (89 schizophrenia patients and 132 controls). The effects of the rs1625579 genotype with the GRS of miR-137-regulated genes in a three-way interaction with diagnosis on GMC patterns were assessed using a multivariate analysis. We found that schizophrenia subjects homozygous for the MIR137HG risk allele show significant decreases in occipital, parietal and temporal lobe GMC with increasing miR-137-regulated GRS, whereas those carrying the protective minor allele show significant increases in GMC with GRS. No correlations of GMC and GRS were found in control subjects. Variants within or upstream of genes regulated by miR-137 in combination with the MIR137HG risk variant may influence GMC in schizophrenia-related regions in patients. Given that the genes evaluated here are involved in protein kinase A signaling, dysregulation of this pathway through alterations in miR-137 biogenesis may underlie the gray matter loss seen in the disease.

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Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalised on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine the age-related morphometric trajectories of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum early in life; the volume of the basal ganglia showed a gradual monotonic decline thereafter while the volumes of the thalamus, amygdala and the hippocampus remained largely stable (with some degree of decline in thalamus) until the sixth decade of life followed by a steep decline thereafter. The lateral ventricles showed a trajectory of continuous enlargement throughout the lifespan.Significant age-related increase in inter-individual variability was found for the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to derive risk predictions for the early identification of diverse clinical phenotypes.