GWAS for executive function and processing speed suggests involvement of the CADM2 gene

To identify common variants contributing to normal variation in two specific domains of cognitive functioning, we conducted a genome-wide association study (GWAS) of executive functioning and information processing speed in non-demented older adults from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. Neuropsychological testing was available for 5429-32 070 subjects of European ancestry aged 45 years or older, free of dementia and clinical stroke at the time of cognitive testing from 20 cohorts in the discovery phase. We analyzed performance on the Trail Making Test parts A and B, the Letter Digit Substitution Test (LDST), the Digit Symbol Substitution Task (DSST), semantic and phonemic fluency tests, and the Stroop Color and Word Test. Replication was sought in 1311-21860 subjects from 20 independent cohorts. A significant association was observed in the discovery cohorts for the single-nucleotide polymorphism (SNP) rs17518584 (discovery P-value=3.12 × 10(-8)) and in the joint discovery and replication meta-analysis (P-value=3.28 × 10(-9) after adjustment for age, gender and education) in an intron of the gene cell adhesion molecule 2 (CADM2) for performance on the LDST/DSST. Rs17518584 is located about 170 kb upstream of the transcription start site of the major transcript for the CADM2 gene, but is within an intron of a variant transcript that includes an alternative first exon. The variant is associated with expression of CADM2 in the cingulate cortex (P-value=4 × 10(-4)). The protein encoded by CADM2 is involved in glutamate signaling (P-value=7.22 × 10(-15)), gamma-aminobutyric acid (GABA) transport (P-value=1.36 × 10(-11)) and neuron cell-cell adhesion (P-value=1.48 × 10(-13)). Our findings suggest that genetic variation in the CADM2 gene is associated with individual differences in information processing speed.Molecular Psychiatry advance online publication, 14 April 2015; doi:10.1038/mp.2015.37

SPIN (Version 3. 83): A Fortran program for modeling one-dimensional rotating-disk/stagnation-flow chemical vapor deposition reactors

In rotating-disk reactor a heated substrate spins (at typical speeds of 1000 rpm or more) in an enclosure through which the reactants flow. The rotating disk geometry has the important property that in certain operating regimes{sup 1} the species and temperature gradients normal to the disk are equal everywhere on the disk. Thus, such a configuration has great potential for highly uniform chemical vapor deposition (CVD),{sup 2--5} and indeed commercial rotating-disk CVD reactors are now available. In certain operating regimes, the equations describing the complex three-dimensional spiral fluid motion can be solved by a separation-of-variables transformation{sup 5,6} that reduces the equations to a system of ordinary differential equations. Strictly speaking, the transformation is only valid for an unconfined infinite-radius disk and buoyancy-free flow. Furthermore, only some boundary conditions are consistent with the transformation (e.g., temperature, gas-phase composition, and approach velocity all specified to be independent of radius at some distances above the disk). Fortunately, however, the transformed equations will provide a very good practical approximation to the flow in a finite-radius reactor over a large fraction of the disk (up to {approximately}90% of the disk radius) when the reactor operating parameters are properly chosen, i.e, high rotation rates. In the limit of zero rotation rate, the rotating disk flow reduces to a stagnation-point flow, for which a similar separation-of-variables transformation is also available. Such flow configurations ( pedestal reactors'') also find use in CVD reactors. In this report we describe a model formulation and mathematical analysis of rotating-disk and stagnation-point CVD reactors. Then we apply the analysis to a compute code called SPIN and describe its implementation and use. 31 refs., 4 figs

Plasma biomarkers of depressive symptoms in older adults

The pathophysiology of negative affect states in older adults is complex, and a host of central nervous system and peripheral systemic mechanisms may play primary or contributing roles. We conducted an unbiased analysis of 146 plasma analytes in a multiplex biochemical biomarker study in relation to number of depressive symptoms endorsed by 566 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) at their baseline and 1-year assessments. Analytes that were most highly associated with depressive symptoms included hepatocyte growth factor, insulin polypeptides, pregnancy-associated plasma protein-A and vascular endothelial growth factor. Separate regression models assessed contributions of past history of psychiatric illness, antidepressant or other psychotropic medicine, apolipoprotein E genotype, body mass index, serum glucose and cerebrospinal fluid (CSF) τ and amyloid levels, and none of these values significantly attenuated the main effects of the candidate analyte levels for depressive symptoms score. Ensemble machine learning with Random Forests found good accuracy (∼80%) in classifying groups with and without depressive symptoms. These data begin to identify biochemical biomarkers of depressive symptoms in older adults that may be useful in investigations of pathophysiological mechanisms of depression in aging and neurodegenerative dementias and as targets of novel treatment approaches