Displaying publications 21 - 26 of 26 in total

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  1. Kalman JL, Yoshida T, Andlauer TFM, Schulte EC, Adorjan K, Alda M, et al.
    Eur Arch Psychiatry Clin Neurosci, 2022 Dec;272(8):1611-1620.
    PMID: 35146571 DOI: 10.1007/s00406-021-01366-5
    Personality traits influence risk for suicidal behavior. We examined phenotype- and genotype-level associations between the Big Five personality traits and suicidal ideation and attempt in major depressive, bipolar and schizoaffective disorder, and schizophrenia patients (N = 3012) using fixed- and random-effects inverse variance-weighted meta-analyses. Suicidal ideations were more likely to be reported by patients with higher neuroticism and lower extraversion phenotypic scores, but showed no significant association with polygenic load for these personality traits. Our findings provide new insights into the association between personality and suicidal behavior across mental illnesses and suggest that the genetic component of personality traits is unlikely to have strong causal effects on suicidal behavior.
  2. Sekiguchi F, Tsurusaki Y, Okamoto N, Teik KW, Mizuno S, Suzumura H, et al.
    J Hum Genet, 2019 Dec;64(12):1173-1186.
    PMID: 31530938 DOI: 10.1038/s10038-019-0667-4
    Coffin-Siris syndrome (CSS, MIM#135900) is a congenital disorder characterized by coarse facial features, intellectual disability, and hypoplasia of the fifth digit and nails. Pathogenic variants for CSS have been found in genes encoding proteins in the BAF (BRG1-associated factor) chromatin-remodeling complex. To date, more than 150 CSS patients with pathogenic variants in nine BAF-related genes have been reported. We previously reported 71 patients of whom 39 had pathogenic variants. Since then, we have recruited an additional 182 CSS-suspected patients. We performed comprehensive genetic analysis on these 182 patients and on the previously unresolved 32 patients, targeting pathogenic single nucleotide variants, short insertions/deletions and copy number variations (CNVs). We confirmed 78 pathogenic variations in 78 patients. Pathogenic variations in ARID1B, SMARCB1, SMARCA4, ARID1A, SOX11, SMARCE1, and PHF6 were identified in 48, 8, 7, 6, 4, 1, and 1 patients, respectively. In addition, we found three CNVs including SMARCA2. Of particular note, we found a partial deletion of SMARCB1 in one CSS patient and we thoroughly investigated the resulting abnormal transcripts.
  3. Amare AT, Schubert KO, Hou L, Clark SR, Papiol S, Cearns M, et al.
    Mol Psychiatry, 2021 Jun;26(6):2457-2470.
    PMID: 32203155 DOI: 10.1038/s41380-020-0689-5
    Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.
  4. Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah YW, et al.
    Sci Data, 2020 07 09;7(1):225.
    PMID: 32647314 DOI: 10.1038/s41597-020-0534-3
    The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
  5. Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah YW, et al.
    Sci Data, 2021 Feb 25;8(1):72.
    PMID: 33633116 DOI: 10.1038/s41597-021-00851-9
  6. Pereda J, Niimi G, Kaul JM, Mishra S, Pangtey B, Peri D, et al.
    Surg Radiol Anat, 2009 Sep;31 Suppl 1:49-93.
    PMID: 27392491 DOI: 10.1007/BF03371485
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