Browsing by Subject "FALSE DISCOVERY RATE"

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  • Sung, Yun J.; Winkler, Thomas W.; de las Fuentes, Lisa; Bentley, Amy R.; Brown, Michael R.; Kraja, Aldi T.; Schwander, Karen; Ntalla, Ioanna; Guo, Xiuqing; Franceschini, Nora; Lu, Yingchang; Cheng, Ching-Yu; Sim, Xueling; Vojinovic, Dina; Marten, Jonathan; Musani, Solomon K.; Li, Changwei; Feitosa, Mary F.; Kilpelainen, Tuomas O.; Richard, Melissa A.; Noordam, Raymond; Aslibekyan, Stella; Aschard, Hugues; Bartz, Traci M.; Dorajoo, Rajkumar; Liu, Yongmei; Manning, Alisa K.; Rankinen, Tuomo; Smith, Albert Vernon; Tajuddin, Salman M.; Tayo, Bamidele O.; Warren, Helen R.; Zhao, Wei; Zhou, Yanhua; Matoba, Nana; Sofer, Tamar; Alver, Maris; Amini, Marzyeh; Boissel, Mathilde; Chai, Jin Fang; Chen, Xu; Divers, Jasmin; Gandin, Ilaria; Gao, Chuan; Giulianini, Franco; Goel, Anuj; Harris, Sarah E.; Heikkinen, Sami; Koistinen, Heikki A.; Weir, David R. (2018)
    Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined similar to 18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p <5 x 10(-8)) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p <5 x 10(-8)). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling MSRA, EBF2).
  • Avela, Henri F.; Siren, Heli (2020)
    The review concentrates on the properties of analytical and statistical ultrahigh-performance liquid chromatographic (UHPLC) - mass spectrometric (MS) methods suitable for glycero-, glycerophospho- and sphingolipids in lipidomics published between the years 2017 2019. Trends and fluctuations of conventional and nano-UHPLC methods with MS and tandem MS detection were observed in context of analysis conditions and tools used for data-analysis. Whereas general workflow characteristics are agreed upon, more details related to the chromatographic methodology (i.e. stationary and mobile phase conditions) need evidently agreements. Lipid quantitation relies upon isotope-labelled standards in targeted analyses and fully standardless algorithm-based untargeted analyses. Furthermore, a wide spectrum of setups have shown potential for the elucidation of complex and large datasets by minimizing the risks of systematic misinterpretation like false positives. This kind of evaluation was shown to have increased importance and usage for cross-validation and data-analysis. (C) 2020 Elsevier B.V. All rights reserved.
  • Scheinin, Ilari; Ferreira, Jose A.; Knuutila, Sakari; Meijer, Gerrit A.; van de Wiel, Mark A.; Ylstra, Bauke (2010)
  • Ukkola-Vuoti, L.; Torniainen-Holm, M.; Ortega-Alonso, A.; Sinha, V.; Tuulio-Henriksson, A.; Paunio, T.; Lönnqvist, J.; Suvisaari, J.; Hennah, W. (2019)
    Schizophrenia is a heterogeneous disorder characterized by a spectrum of symptoms and many different underlying causes. Thus, instead of using the broad diagnosis, intermediate phenotypes can be used to possibly decrease the underlying complexity of the disorder. Alongside the classical symptoms of delusions and hallucinations, cognitive deficits are a core feature of schizophrenia. To increase our understanding of the biological processes related to these cognitive deficits, we performed a genome-wide gene expression analysis. A battery of 14 neuropsychological tests was administered to 844 individuals from a Finnish familial schizophrenia cohort. We grouped the applied neuropsychological tests into five factors for further analysis. Cognitive endophenotypes, whole blood mRNA, genotype, and medication use data were studied from 47 individuals. Expression level of several RNA probes were significantly associated with cognitive performance. The factor representing Verbal Working Memory was associated with altered expression levels of 11 probes, of which one probe was also associated with a specific sub-measure of this factor (WMS-R Digit span backward). While, the factor Processing speed was related to one probe, which additionally associated among 55 probes with a specific sub-measure of this factor (WAIS-R Digit symbol). Two probes were associated with the measure recognition memory performance. Enrichment analysis of these differentially expressed probes highlighted immunological processes. Our findings are in line with genome-wide genetic discoveries made in schizophrenia, suggesting that immunological processes may be of biological interest for future drug design towards schizophrenia and the cognitive dysfunctions that underlie it.
  • Chen, Jingchun; Bacanu, S. A.; Yu, H.; Zhao, Z.; Jia, P.; Kendler, K. S.; Kranzler, H. R.; Gelernter, J.; Farrer, L.; Minica, C.; Pool, R.; Milaneschi, Y.; Boomsma, D. I.; Penninx, B. W.; Tyndale, R. F.; Ware, J. J.; Vink, J. M.; Kaprio, Jaakko; Munafo, M.; Chen, X.; Ware, J. J.; Chen, X.; Vink, J. M.; Loukola, Anu; Minica, C.; Pool, R.; Milaneschi, Y.; Mangino, M.; Menni, C.; Chen, J.; Peterson, R.; Auro, Kirsi; Lyytikäinen, Leo-Pekka; Wedenoja, Juho; Stiby, A. I.; Hemani, G.; Willemsen, G.; Hottenga, J. J.; Korhonen, Tellervo; Heliövaara, Markku; Perola, Markus; Rose, R.; Paternoster, L.; Timpson, N.; Wassenaar, C. A.; Zhu, A. Z.; Smith, G. D.; Raitakari, Olli; Lehtimäki, Terho; Kähönen, Mika; Koskinen, Seppo; Spector, T.; Penninx, B. W.; Salomaa, Veikko; Boomsma, D. I.; Tyndale, R. F.; Munafo, M.; Ware, J. J.; Chen, X.; Vink, J. M.; Minica, C.; Chen, J.; Peterson, R.; Timpson, N.; Taylor, M.; Boomsma, D. I.; Munafo, M.; Maes, H.; Riley, B.; Kendler, K. S.; Gelernter, J.; Sherva, R.; Farrer, L.; Kranzler, H. R.; Maher, B.; Vanyukov, M. (2016)
    It is well known that most schizophrenia patients smoke cigarettes. There are different hypotheses postulating the underlying mechanisms of this comorbidity. We used summary statistics from large meta-analyses of plasma cotinine concentration (COT), Fagerstrom test for nicotine dependence (FTND) and schizophrenia to examine the genetic relationship between these traits. We found that schizophrenia risk scores calculated at P-value thresholds of 5 x 10(-3) and larger predicted FTND and cigarettes smoked per day (CPD), suggesting that genes most significantly associated with schizophrenia were not associated with FTND/CPD, consistent with the self-medication hypothesis. The COT risk scores predicted schizophrenia diagnosis at P-values of 5 x 10(-3) and smaller, implying that genes most significantly associated with COT were associated with schizophrenia. These results implicated that schizophrenia and FTND/CPD/COT shared some genetic liability. Based on this shared liability, we identified multiple long non-coding RNAs and RNA binding protein genes (DA376252, BX089737, LOC101927273, LINC01029, LOC101928622, HY157071, DA902558, RBFOX1 and TINCR), protein modification genes (MANBA, UBE2D3, and RANGAP1) and energy production genes (XYLB, MTRF1 and ENOX1) that were associated with both conditions. Further analyses revealed that these shared genes were enriched in calcium signaling, long-term potentiation and neuroactive ligand-receptor interaction pathways that played a critical role in cognitive functions and neuronal plasticity.
  • Pajula, Juha; Kauppi, Jukka-Pekka; Tohka, Jussi (2012)
  • Sutela, Suvi; Niemi, Karoliina; Edesi, Jaanika; Laakso, Tapio; Saranpää, Pekka; Vuosku, Jaana; Makela, Riina; Tiimonen, Heidi; Chiang, Vincent L.; Koskimäki, Janne; Suorsa, Marja; Julkunen-Tiitto, Riitta; Haggman, Hely (2009)
  • 23andMe Res Team (2018)
    Phenome-wide association studies (PheWAS) have been proposed as a possible aid in drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we select 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease indications. We interrogate these SNPs by PheWAS in four large cohorts with extensive health information (23andMe, UK Biobank, FINRISK, CHOP) for association with 1683 binary endpoints in up to 697,815 individuals and conduct meta-analyses for 145 mapped disease endpoints. Our analyses replicate 75% of known GWAS associations (P<0.05) and identify nine study-wide significant novel associations (of 71 with FDR <0.1). We describe associations that may predict ADEs, e.g., acne, high cholesterol, gout, and gallstones with rs738409 (p.I148M) in PNPLA3 and asthma with rs1990760 (p.T946A) in IFIH1. Our results demonstrate PheWAS as a powerful addition to the toolkit for drug discovery.
  • Marques, Elsa; Peltola, Tomi; Kaski, Samuel; Klefstrom, Juha (2018)
    In metazoans, epithelial architecture provides a context that dynamically modulates most if not all epithelial cell responses to intrinsic and extrinsic signals, including growth or survival signalling and transforming oncogene action. Three-dimensional ( 3D) epithelial culture systems provide tractable models to interrogate the function of human genetic determinants in establishment of context-dependency. We performed an arrayed genetic shRNA screen in mammary epithelial 3D cultures to identify new determinants of epithelial architecture, finding that the key phenotype impacting shRNAs altered not only the data population average but even more noticeably the population distribution. The broad distributions were attributable to sporadic gene silencing actions by shRNA in unselected populations. We employed Maximum Mean Discrepancy concept to capture similar population distribution patterns and demonstrate here the feasibility of the test in identifying an impact of shRNA in populations of 3D structures. Integration of the clustered morphometric data with protein-protein interactions data enabled hypothesis generation of novel biological pathways underlying similar 3D phenotype alterations. The results present a new strategy for 3D phenotype-driven pathway analysis, which is expected to accelerate discovery of context-dependent gene functions in epithelial biology and tumorigenesis.
  • Asare, Kennedy Opoku; Terhorst, Yannik; Vega, Julio; Peltonen, Ella; Lagerspetz, Eemil; Ferreira, Denzil (2021)
    Background: Depression is a prevalent mental health challenge. Current depression assessment methods using self-reported and clinician-administered questionnaires have limitations. Instrumenting smartphones to passively and continuously collect moment-by-moment data sets to quantify human behaviors has the potential to augment current depression assessment methods for early diagnosis, scalable, and longitudinal monitoring of depression. Objective: The objective of this study was to investigate the feasibility of predicting depression with human behaviors quantified from smartphone data sets, and to identify behaviors that can influence depression. Methods: Smartphone data sets and self-reported 8-item Patient Health Questionnaire (PHQ-8) depression assessments were collected from 629 participants in an exploratory longitudinal study over an average of 22.1 days (SD 17.90; range 8-86). We quantified 22 regularity, entropy, and SD behavioral markers from the smartphone data. We explored the relationship between the behavioral features and depression using correlation and bivariate linear mixed models (LMMs). We leveraged 5 supervised machine learning (ML) algorithms with hyperparameter optimization, nested cross-validation, and imbalanced data handling to predict depression. Finally, with the permutation importance method, we identified influential behavioral markers in predicting depression. Results: Of the 629 participants from at least 56 countries, 69 (10.97%) were females, 546 (86.8%) were males, and 14 (2.2%) were nonbinary. Participants' age distribution is as follows: 73/629 (11.6%) were aged between 18 and 24, 204/629 (32.4%) were aged between 25 and 34, 156/629 (24.8%) were aged between 35 and 44, 166/629 (26.4%) were aged between 45 and 64, and 30/629 (4.8%) were aged 65 years and over. Of the 1374 PHQ-8 assessments, 1143 (83.19%) responses were nondepressed scores (PHQ-8 score = 10), as identified based on PHQ-8 cut-off. A significant positive Pearson correlation was found between screen status-normalized entropy and depression (r=0.14, P Conclusions: Our findings demonstrate that behavioral markers indicative of depression can be unobtrusively identified from smartphone sensors' data. Traditional assessment of depression can be augmented with behavioral markers from smartphones for depression diagnosis and monitoring.
  • Kallio, Aleksi; Vuokko, Niko; Ojala, Markus; Haiminen, Niina; Mannila, Heikki (2011)
  • Raivisto, Teija; Heikkinen, AnnaMaria; Kovanen, Leena; Ruokonen, Hellevi; Kettunen, Kaisa; Tervahartiala, Taina; Haukka, Jari; Sorsa, Timo (2018)
    Background. Dental caries is the most common infection in the world and is influenced by genetic and environmental factors. Environmental factors are largely known, but the role of genetic factors is quite unknown. The aim was to investigate the genetic background of caries in Finnish adolescents. Materials and Methods. This study was carried out at the Kotka Health Center in Eastern Finland. 94 participants aged 15-17 years gave approval for the saliva and DNA analyses. However, one was excluded in DNA analysis; thus, the overall number of participants in analysis was 93. Caries status was recorded clinically and from bite-wing X-rays to all 94 participants. Genomic DNA was extracted by genomic QIAamp (R) DNA Blood Mini Kit and genotyped for polymorphisms. The results were analyzed using additive and logistic regression models. Results. No significant associations between caries and the genes studied were found. However, SNPs in DDX39B and MPO showed association tendencies but were not statistically significant after false discovery rate (FDR) analysis. SNPs in VDR, LTA, and MMP3 were not statistically significant with initial caries lesions after FDR analysis. Conclusion. The present study could not demonstrate statistically significant associations between caries and the genes studied. Further studies with larger populations are needed.
  • Jamshidi, Maral; Fagerholm, Rainer; Khan, Sofia; Aittomaki, Kristiina; Czene, Kamila; Darabi, Hatef; Li, Jingmei; Andrulis, Irene L.; Chang-Claude, Jenny; Devilee, Peter; Fasching, Peter A.; Michailidou, Kyriaki; Bolla, Manjeet K.; Dennis, Joe; Wang, Qin; Guo, Qi; Rhenius, Valerie; Cornelissen, Sten; Rudolph, Anja; Knight, Julia A.; Loehberg, Christian R.; Burwinkel, Barbara; Marme, Frederik; Hopper, John L.; Southey, Melissa C.; Bojesen, Stig E.; Flyger, Henrik; Brenner, Hermann; Holleczek, Bernd; Margolin, Sara; Mannermaa, Arto; Kosma, Veli-Matti; Van Dyck, Laurien; Nevelsteen, Ines; Couch, Fergus J.; Olson, Janet E.; Giles, Graham G.; McLean, Catriona; Haiman, Christopher A.; Henderson, Brian E.; Winqvist, Robert; Pylkas, Katri; Tollenaar, Rob A. E. M.; Garcia-Closas, Montserrat; Figueroa, Jonine; Hooning, Maartje J.; Martens, John W. M.; Cox, Angela; Cross, Simon S.; Simard, Jacques; Dunning, Alison M.; Easton, Douglas F.; Pharoah, Paul D. P.; Hall, Per; Blomqvist, Carl; Schmidt, Marjanka K.; Nevanlinna, Heli; kConFab Investigators (2015)
    In breast cancer, constitutive activation of NF-kappa B has been reported, however, the impact of genetic variation of the pathway on patient prognosis has been little studied. Furthermore, a combination of genetic variants, rather than single polymorphisms, may affect disease prognosis. Here, in an extensive dataset (n = 30,431) from the Breast Cancer Association Consortium, we investigated the association of 917 SNPs in 75 genes in the NF-kappa B pathway with breast cancer prognosis. We explored SNP-SNP interactions on survival using the likelihood-ratio test comparing multivariate Cox' regression models of SNP pairs without and with an interaction term. We found two interacting pairs associating with prognosis: patients simultaneously homozygous for the rare alleles of rs5996080 and rs7973914 had worse survival (HRinteraction 6.98, 95% CI= 3.3-14.4, P=1.42E-07), and patients carrying at least one rare allele for rs17243893 and rs57890595 had better survival (HRinteraction 0.51, 95% CI= 0.3-0.6, P = 2.19E-05). Based on in silico functional analyses and literature, we speculate that the rs5996080 and rs7973914 loci may affect the BAFFR and TNFR1/TNFR3 receptors and breast cancer survival, possibly by disturbing both the canonical and non-canonical NF-kappa B pathways or their dynamics, whereas, rs17243893-rs57890595 interaction on survival may be mediated through TRAF2-TRAIL-R4 interplay. These results warrant further validation and functional analyses.
  • Federico, Antonio; Serra, Angela; Ha, My Kieu; Kohonen, Pekka; Choi, Jang-Sik; Liampa, Irene; Nymark, Penny; Sanabria, Natasha; Cattelani, Luca; Fratello, Michele; Kinaret, Pia Anneli Sofia; Jagiello, Karolina; Puzyn, Tomasz; Melagraki, Georgia; Gulumian, Mary; Afantitis, Antreas; Sarimveis, Haralambos; Yoon, Tae-Hyun; Grafström, Roland; Greco, Dario (2020)
    Preprocessing of transcriptomics data plays a pivotal role in the development of toxicogenomics-driven tools for chemical toxicity assessment. The generation and exploitation of large volumes of molecular profiles, following an appropriate experimental design, allows the employment of toxicogenomics (TGx) approaches for a thorough characterisation of the mechanism of action (MOA) of different compounds. To date, a plethora of data preprocessing methodologies have been suggested. However, in most cases, building the optimal analytical workflow is not straightforward. A careful selection of the right tools must be carried out, since it will affect the downstream analyses and modelling approaches. Transcriptomics data preprocessing spans across multiple steps such as quality check, filtering, normalization, batch effect detection and correction. Currently, there is a lack of standard guidelines for data preprocessing in the TGx field. Defining the optimal tools and procedures to be employed in the transcriptomics data preprocessing will lead to the generation of homogeneous and unbiased data, allowing the development of more reliable, robust and accurate predictive models. In this review, we outline methods for the preprocessing of three main transcriptomic technologies including microarray, bulk RNA-Sequencing (RNA-Seq), and single cell RNA-Sequencing (scRNA-Seq). Moreover, we discuss the most common methods for the identification of differentially expressed genes and to perform a functional enrichment analysis. This review is the second part of a three-article series on Transcriptomics in Toxicogenomics.
  • Villarreal, Sanna; Linnavuo, Matti; Sepponen, Raimo; Vuori, Outi; Bonato, Mario; Jokinen, Hanna; Hietanen, Marja (2021)
    Objective: Patients with unilateral stroke commonly show hemispatial neglect or milder contralesional visuoattentive deficits, but spatially non-lateralized visuoattentive deficits have also been reported. The aim of the present study was to compare spatially lateralized (i.e., contralesional) and non-lateralized (i.e., general) visuoattentive deficits in left and right hemisphere stroke patients. Method: Participants included 40 patients with chronic unilateral stroke in either the left hemisphere (LH group, n = 20) or the right hemisphere (RH group, n = 20) and 20 healthy controls. To assess the contralesional deficits, we used a traditional paper-and-pencil cancellation task (the Bells Test) and a Lateralized Targets Computer Task. To assess the non-lateralized deficits, we developed a novel large-screen (173 x 277 cm) computer method, the Ball Rain task, with moving visual stimuli and fast-paced requirements for selective attention. Results: There were no contralesional visuoattentive deficits according to the cancellation task. However, in the Lateralized Targets Computer Task, RH patients missed significantly more left-sided than right-sided targets in bilateral trials. This omission distribution differed significantly from those of the controls and LH patients. In the assessment of non-lateralized attention, RH and LH patients missed significantly more Ball Rain targets than controls in both the left and right hemifields. Conclusions: Computer-based assessment sensitively reveals various aspects of visuoattentive deficits in unilateral stroke. Patients with either right or left hemisphere stroke demonstrate non-lateralized visual inattention. In right hemisphere stroke, these symptoms can be accompanied by subtle contralesional visuoattentive deficits that have remained unnoticed in cancellation task.