Identifying the genetic variants that increase the risk of type 2 diabetes (T2D) in humans has been a formidable challenge. Adopting a genome-wide association strategy, we genotyped 1161 Finnish T2D cases and 1174 Finnish normal glucose-tolerant (NGT) controls with >315,000 single-nucleotide polymorphisms (SNPs) and imputed genotypes for an additional >2 million autosomal SNPs. We carried out association analysis with these SNPs to identify genetic variants that predispose to T2D, compared our T2D association results with the results of two similar studies, and genotyped 80 SNPs in an additional 1215 Finnish T2D cases and 1258 Finnish NGT controls. We identify T2D-associated variants in an intergenic region of chromosome 11p12, contribute to the identification of T2D-associated variants near the genes IGF2BP2 and CDKAL1 and the region of CDKN2A and CDKN2B, and confirm that variants near TCF7L2, SLC30A8, HHEX, FTO, PPARG, and KCNJ11 are associated with T2D risk. This brings the number of T2D loci now confidently identified to at least 10.

Major depressive disorder (MDD), one of the most frequently encountered forms of mental illness and a leading cause of disability worldwide1, poses a major challenge to genetic analysis. To date no robustly replicated genetic loci have been identified 2, despite analysis of more than 9,000 cases3. Using low coverage genome sequence of 5,303 Chinese women with recurrent MDD selected to reduce phenotypic heterogeneity, and 5,337 controls screened to exclude MDD, we identified and replicated two genome-wide significant loci contributing to risk of MDD on chromosome 10: one near the SIRT1 gene (P-value = 2.53×10−10) the other in an intron of the LHPP gene (P = 6.45×10−12). Analysis of 4,509 cases with a severe subtype of MDD, melancholia, yielded an increased genetic signal at the SIRT1 locus. We attribute our success to the recruitment of relatively homogeneous cases with severe illness.

Trace amounts of explosives on solid surfaces were detected by mass spectrometry at ambient conditions with a new technique termed dielectric barrier discharge ionization (DBDI). By the needle-plate discharge mode, a plasma discharge with energetic electrons was generated, which could launch the desorption and ionization of the explosives from solid surfaces. Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), 2,4,6-trinitrotoluene (TNT), and pentaerythritol tetranitrate (PETN) were desorbed directly from the explosives-contaminated surface by DBDI, forming the typical anions of [TNT](-), [TNT - H](-), [RDX + NO(2)](-), [PETN + ONO(2)](-), and [RDX + ONO(2)](-). The ions were transferred into the MS instrument for analysis in the negative ion mode. The detection limit of present method was 10 pg for TNT (m/z 197, S/N 8 : 1), 0.1 ng for RDX (m/z 284, S/N 10 : 1), and 1 ng for PETN (m/z 260, S/N 12 : 1). The present method allowed the detection of trace explosives on various matrices, including paper, cloth, chemical fiber, glass, paints, and soil. A relative standard deviation of 5.57% was achieved by depositing 100 pg of TNT on these matrices. The analysis of A-5, a mixture of RDX and additives, has been carried out and the results were consistent with the reference values. The DBDI-MS method represents a simple and rapid way for the detection of explosives with high sensitivity and specificity, which is especially useful when they are present in trace amounts on ordinary environmental surfaces.

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We had developed pulsed direct current electrospray ionization mass spectrometry (pulsed-dc-ESI-MS) for systematically profiling and determining components in small volume sample. Pulsed-dc-ESI utilized constant high voltage to induce the generation of single polarity pulsed electrospray remotely. This method had significantly boosted the sample economy, so as to obtain several minutes MS signal duration from merely picoliter volume sample. The elongated MS signal duration enable us to collect abundant MS(2) information on interested components in a small volume sample for systematical analysis. This method had been successfully applied for single cell metabolomics analysis. We had obtained 2-D profile of metabolites (including exact mass and MS(2) data) from single plant and mammalian cell, concerning 1034 components and 656 components for Allium cepa and HeLa cells, respectively. Further identification had found 162 compounds and 28 different modification groups of 141 saccharides in a single Allium cepa cell, indicating pulsed-dc-ESI a powerful tool for small volume sample systematical analysis.

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Data processing for three dimensional mass spectrometry (3D-MS) imaging was investigated, starting with a consideration of the challenges in its practical implementation using a series of sections of a tissue volume. The technical issues related to data reduction, 2D imaging data alignment, 3D visualization, and statistical data analysis were identified. Software solutions for these tasks were developed using functions in MATLAB. Peak detection and peak alignment were applied to reduce the data size, while retaining the mass accuracy. The main morphologic features of tissue sections were extracted using a classification method for data alignment. Data insertion was performed to construct a 3D data set with spectral information that can be used for generating 3D views and for data analysis. The imaging data previously obtained for a mouse brain using desorption electrospray ionization mass spectrometry (DESI-MS) imaging have been used to test and demonstrate the new methodology.