Browsing by Subject "IMPUTATION"

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  • Pausch, Hubert; Venhoranta, Heli; Wurmser, Christine; Hakala, Kalle; Iso-Touru, Terhi; Sironen, Anu; Vingborg, Rikke K.; Lohi, Hannes; Soderquist, Lennart; Fries, Ruedi; Andersson, Magnus (2016)
    Background: Artificial insemination is widely used in many cattle breeding programs. Semen samples of breeding bulls are collected and closely examined immediately after collection at artificial insemination centers. Only ejaculates without anomalous findings are retained for artificial insemination. Although morphological aberrations of the spermatozoa are a frequent reason for discarding ejaculates, the genetic determinants underlying poor semen quality are scarcely understood. Results: A tail stump sperm defect was observed in three bulls of the Swedish Red cattle breed. The spermatozoa of affected bulls were immotile because of severely disorganized tails indicating disturbed spermatogenesis. We genotyped three affected bulls and 18 unaffected male half-sibs at 46,035 SNPs and performed homozygosity mapping to map the fertility disorder to an 8.42 Mb interval on bovine chromosome 13. The analysis of whole-genome re-sequencing data of an affected bull and 300 unaffected animals from eleven cattle breeds other than Swedish Red revealed a 1 bp deletion (Chr13: 24,301,425 bp, ss1815612719) in the eleventh exon of the armadillo repeat containing 3-encoding gene (ARMC3) that was compatible with the supposed recessive mode of inheritance. The deletion is expected to alter the reading frame and to induce premature translation termination (p.A451fs26). The mutated protein is shortened by 401 amino acids (46 %) and lacks domains that are likely essential for normal protein function. Conclusions: We report the phenotypic and genetic characterization of a sterilizing tail stump sperm defect in the Swedish Red cattle breed. Exploiting high-density genotypes and massive re-sequencing data enabled us to identify the most likely causal mutation for the fertility disorder in bovine ARMC3. Our results provide the basis for monitoring the mutated variant in the Swedish Red cattle population and for the early identification of infertile animals.
  • Bodea, Corneliu A.; Neale, Benjamin M.; Ripke, Stephan; Daly, Mark J.; Devlin, Bernie; Roeder, Kathryn; Int IBD Genetics Consortium; Palotie, A. (2016)
    One goal of human genetics is to understand the genetic basis of disease, a challenge for diseases of complex inheritance because risk alleles are few relative to the vast set of benign variants. Risk variants are often sought by association studies in which allele frequencies in case subjects are contrasted with those from population-based samples used as control subjects. In an ideal world we would know population-level allele frequencies, releasing researchers to focus on case subjects. We argue this ideal is possible, at least theoretically, and we outline a path to achieving it in reality. If such a resource were to exist, it would yield ample savings and would facilitate the effective use of data repositories by removing administrative and technical barriers. We call this concept the Universal Control Repository Network (UNICORN), a means to perform association analyses without necessitating direct access to individual-level control data. Our approach to UNICORN uses existing genetic resources and various statistical tools to analyze these data, including hierarchical clustering with spectral analysis of ancestry; and empirical Bayesian analysis along with Gaussian spatial processes to estimate ancestry-specific allele frequencies. We demonstrate our approach using tens of thousands of control subjects from studies of Crohn disease, showing how it controls false positives, provides power similar to that achieved when all control data are directly accessible, and enhances power when control data are limiting or even imperfectly matched ancestrally. These results highlight how UNICORN can enable reliable, powerful, and convenient genetic association analyses without access to the individual-level data.
  • Rivas, Manuel A.; Graham, Daniel; Sulem, Patrick; Stevens, Christine; Desch, A. Nicole; Goyette, Philippe; Gudbjartsson, Daniel; Jonsdottir, Ingileif; Thorsteinsdottir, Unnur; Degenhardt, Frauke; Mucha, Soeren; Kurki, Mitja I.; Li, Dalin; D'Amato, Mauro; Annese, Vito; Vermeire, Severine; Weersma, Rinse K.; Halfvarson, Jonas; Paavola-Sakki, Anu Liisa Paulina; Lappalainen, Anne Maarit; Lek, Monkol; Cummings, Beryl; Tukiainen, Taru; Haritunians, Talin; Halme, Leena; Koskinen, Lotta L. E.; Ananthakrishnan, Ashwin N.; Luo, Yang; Heap, Graham A.; Visschedijk, Marijn C.; MacArthur, Daniel G.; Neale, Benjamin M.; Ahmad, Tariq; Anderson, Carl A.; Brant, Steven R.; Duerr, Richard H.; Silverberg, Mark S.; Cho, Judy H.; Palotie, Aarno; Saavalainen, Paivi; Kontula, Kimmo; Farkkila, Martti; McGovern, Dermot P. B.; Franke, Andre; Stefansson, Kari; Rioux, John D.; Xavier, Ramnik J.; Daly, Mark J. (2016)
    Protein-truncating variants protective against human disease provide in vivo validation of therapeutic targets. Here we used targeted sequencing to conduct a search for protein-truncating variants conferring protection against inflammatory bowel disease exploiting knowledge of common variants associated with the same disease. Through replication genotyping and imputation we found that a predicted protein-truncating variant (rs36095412, p.R179X, genotyped in 11,148 ulcerative colitis patients and 295,446 controls, MAF = up to 0.78%) in RNF186, a single-exon ring finger E3 ligase with strong colonic expression, protects against ulcerative colitis (overall P = 6.89 x 10(-7), odds ratio = 0.30). We further demonstrate that the truncated protein exhibits reduced expression and altered subcellular localization, suggesting the protective mechanism may reside in the loss of an interaction or function via mislocalization and/or loss of an essential transmembrane domain.
  • Acosta, H.; Tuulari, J. J.; Kantojärvi, K.; Lewis, J. D.; Hashempour, N.; Scheinin, N. M.; Lehtola, S. J.; Fonov, V. S.; Collins, D. L.; Evans, A.; Parkkola, R.; Lahdesmaki, T.; Saunavaara, J.; Merisaari, H.; Karlsson, L.; Paunio, T.; Karlsson, H. (2021)
    Genetic variants in the oxytocin receptor (OTR) have been linked to distinct social phenotypes, psychiatric disorders and brain volume alterations in adults. However, to date, it is unknown how OTR genotype shapes prenatal brain development and whether it interacts with maternal prenatal environmental risk factors on infant brain volumes. In 105 Finnish mother-infant dyads (44 female, 11-54 days old), the association of offspring OTR genotype rs53576 and its interaction with prenatal maternal anxiety (revised Symptom Checklist 90, gestational weeks 14, 24, 34) on infant bilateral amygdalar, hippocampal and caudate volumes were probed. A sex-specific main effect of rs53576 on infant left hippocampal volumes was observed. In boys compared to girls, left hippocampal volumes were significantly larger in GG-homozygotes compared to A-allele carriers. Furthermore, genotype rs53576 and prenatal maternal anxiety significantly interacted on right hippocampal volumes irrespective of sex. Higher maternal anxiety was associated both with larger hippocampal volumes in A allele carriers than GG-homozygotes, and, though statistically weak, also with smaller right caudate volumes in GG-homozygotes than A-allele carriers. Our study results suggest that OTR genotype enhances hippocampal neurogenesis in male GG-homozygotes. Further, prenatal maternal anxiety might induce brain alterations that render GG-homozygotes compared to A-allele carriers more vulnerable to depression.
  • PRACTICAl Consortium; Law, Philip J.; Timofeeva, Maria; Fernandez-Rozadilla, Ceres; Palin, Kimmo; Hänninen, Ulrika A.; Cajuso, Tatiana; Tanskanen, Tomas; Kondelin, Johanna; Kaasinen, Eevi; Sarin, Antti-Pekka; Eriksson, Johan G.; Jousilahti, Pekka; Ripatti, Samuli; Palotie, Aarno; Renkonen-Sinisalo, Laura; Lepistö, Anna; Aaltonen, Lauri A.; Rissanen, Harri; Salomaa, Veikko; Böhm, Jan; Mecklin, Jukka-Pekka; Pukkala, Eero (2019)
    Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide, and has a strong heritable basis. We report a genome-wide association analysis of 34,627 CRC cases and 71,379 controls of European ancestry that identifies SNPs at 31 new CRC risk loci. We also identify eight independent risk SNPs at the new and previously reported European CRC loci, and a further nine CRC SNPs at loci previously only identified in Asian populations. We use in situ promoter capture Hi-C (CHi-C), gene expression, and in silico annotation methods to identify likely target genes of CRC SNPs. Whilst these new SNP associations implicate target genes that are enriched for known CRC pathways such as Wnt and BMP, they also highlight novel pathways with no prior links to colorectal tumourigenesis. These findings provide further insight into CRC susceptibility and enhance the prospects of applying genetic risk scores to personalised screening and prevention.
  • NBCS Collaborators; AOCS Grp; ABCTB Investigators; kConFab Investigators; Johnson, Nichola; Maguire, Sarah; Morra, Anna; Blomqvist, Carl; Nevanlinna, Heli (2021)
    Background Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk. Methods We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry. Results For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 x 10(-18)); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 x 10(-8)). Conclusions The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.
  • Flannick, Jason; Fuchsberger, Christian; Mahajan, Anubha; Teslovich, Tanya M.; Agarwala, Vineeta; Gaulton, Kyle J.; Caulkins, Lizz; Koesterer, Ryan; Ma, Clement; Moutsianas, Loukas; McCarthy, Davis J.; Rivas, Manuel A.; Perry, John R. B.; Sim, Xueling; Blackwell, Thomas W.; Robertson, Neil R.; Rayner, N. William; Cingolani, Pablo; Locke, Adam E.; Tajes, Juan Fernandez; Highland, Heather M.; Dupuis, Josee; Chines, Peter S.; Lindgren, Cecilia M.; Hartl, Christopher; Jackson, Anne U.; Chen, Han; Huyghe, Jeroen R.; De Bunt, Martijn Van; Pearson, Richard D.; Kumar, Ashish; Muller-Nurasyid, Martina; Grarup, Niels; Stringham, Heather M.; Gamazon, Eric R.; Lee, Jaehoon; Chen, Yuhui; Scott, Robert A.; Below, Jennifer E.; Chen, Peng; Huang, Jinyan; Go, Min Jin; Stitzel, Michael L.; Pasko, Dorota; Parker, Stephen C. J.; Varga, Tibor V.; Green, Todd; Beer, Nicola L.; Day-Williams, Aaron G.; Ferreira, Teresa; Fingerlin, Tasha; Horikoshi, Momoko; Hu, Cheng; Huh, Iksoo; Ikram, Mohammad Kamran; Kim, Bong-Jo; Kim, Yongkang; Kim, Young Jin; Kwon, Min-Seok; Lee, Juyoung; Lee, Selyeong; Lin, Keng-Han; Maxwell, Taylor J.; Nagai, Yoshihiko; Wang, Xu; Welch, Ryan P.; Yoon, Joon; Zhang, Weihua; Barzilai, Nir; Voight, Benjamin F.; Han, Bok-Ghee; Jenkinson, Christopher P.; Kuulasmaa, Teemu; Kuusisto, Johanna; Manning, Alisa; Ng, Maggie C. Y.; Palmer, Nicholette D.; Balkau, Beverley; Stancakova, Alena; Abboud, Hanna E.; Boeing, Heiner; Giedraitis, Vilmantas; Prabhakaran, Dorairaj; Gottesman, Omri; Scott, James; Carey, Jason; Kwan, Phoenix; Grant, George; Smith, Joshua D.; Neale, Benjamin M.; Purcell, Shaun; Butterworth, Adam S.; Howson, Joanna M. M.; Lee, Heung Man; Lu, Yingchang; Kwak, Soo-Heon; Zhao, Wei; Danesh, John; Lam, Vincent K. L.; Park, Kyong Soo; Saleheen, Danish; So, Wing Yee; Tam, Claudia H. T.; Afzal, Uzma; Aguilar, David; Arya, Rector; Aung, Tin; Chan, Edmund; Navarro, Carmen; Cheng, Ching-Yu; Palli, Domenico; Correa, Adolfo; Curran, Joanne E.; Rybin, Dennis; Farook, Vidya S.; Fowler, Sharon P.; Freedman, Barry I.; Griswold, Michael; Hale, Daniel Esten; Hicks, Pamela J.; Khor, Chiea-Chuen; Kumar, Satish; Lehne, Benjamin; Thuillier, Dorothee; Lim, Wei Yen; Liu, Jianjun; Loh, Marie; Musani, Solomon K.; Puppala, Sobha; Scott, William R.; Yengo, Loic; Tan, Sian-Tsung; Taylor, Herman A.; Thameem, Farook; Wilson, Gregory; Wong, Tien Yin; Njolstad, Pal Rasmus; Levy, Jonathan C.; Mangino, Massimo; Bonnycastle, Lori L.; Schwarzmayr, Thomas; Fadista, Joao; Surdulescu, Gabriela L.; Herder, Christian; Groves, Christopher J.; Wieland, Thomas; Bork-Jensen, Jette; Brandslund, Ivan; Christensen, Cramer; Koistinen, Heikki A.; Doney, Alex S. F.; Kinnunen, Leena; Esko, Tonu; Farmer, Andrew J.; Hakaste, Liisa; Hodgkiss, Dylan; Kravic, Jasmina; Lyssenko, Valeriya; Hollensted, Mette; Jorgensen, Marit E.; Jorgensen, Torben; Ladenvall, Claes; Justesen, Johanne Marie; Karajamaki, Annemari; Kriebel, Jennifer; Rathmann, Wolfgang; Lannfelt, Lars; Lauritzen, Torsten; Narisu, Narisu; Linneberg, Allan; Melander, Olle; Milani, Lili; Neville, Matt; Orho-Melander, Marju; Qi, Lu; Qi, Qibin; Roden, Michael; Rolandsson, Olov; Swift, Amy; Rosengren, Anders H.; Stirrups, Kathleen; Wood, Andrew R.; Mihailov, Evelin; Blancher, Christine; Carneiro, Mauricio O.; Maguire, Jared; Poplin, Ryan; Shakir, Khalid; Fennell, Timothy; DePristo, Mark; De Angelis, Martin Hrabe; Deloukas, Panos; Gjesing, Anette P.; Jun, Goo; Nilsson, Peter M.; Murphy, Jacquelyn; Onofrio, Robert; Thorand, Barbara; Hansen, Torben; Meisinger, Christa; Hu, Frank B.; Isomaa, Bo; Karpe, Fredrik; Liang, Liming; Peters, Annette; Huth, Cornelia; O'Rahilly, Stephen P.; Palmer, Colin N. A.; Pedersen, Oluf; Rauramaa, Rainer; Tuomilehto, Jaakko; Salomaa, Veikko; Watanabe, Richard M.; Syvanen, Ann-Christine; Bergman, Richard N.; Bharadwaj, Dwaipayan; Bottinger, Erwin P.; Cho, Yoon Shin; Chandak, Giriraj R.; Chan, Juliana Cn; Chia, Kee Seng; Daly, Mark J.; Ebrahim, Shah B.; Langenberg, Claudia; Elliott, Paul; Jablonski, Kathleen A.; Lehman, Donna M.; Jia, Weiping; Ma, Ronald Cw; Pollin, Toni I.; Sandhu, Manjinder; Tandon, Nikhil; Froguel, Philippe; Barroso, Ines; Teo, Yik Ying; Zeggini, Eleftheria; Loos, Ruth J. F.; Small, Kerrin S.; Ried, Janina S.; DeFronzo, Ralph A.; Grallert, Harald; Glaser, Benjamin; Metspalu, Andres; Wareham, Nicholas J.; Walker, Mark; Banks, Eric; Gieger, Christian; Ingelsson, Erik; Im, Hae Kyung; Illig, Thomas; Franks, Paul W.; Buck, Gemma; Trakalo, Joseph; Buck, David; Prokopenko, Inga; Magi, Reedik; Lind, Lars; Farjoun, Yossi; Owen, Katharine R.; Gloyn, Anna L.; Strauch, Konstantin; Tuomi, Tiinamaija; Kooner, Jaspal Singh; Lee, Jong-Young; Park, Taesung; Donnelly, Peter; Morris, Andrew D.; Hattersley, Andrew T.; Bowden, Donald W.; Collins, Francis S.; Atzmon, Gil; Chambers, John C.; Spector, Timothy D.; Laakso, Markku; Strom, Tim M.; Bell, Graeme I.; Blangero, John; Duggirala, Ravindranath; Tai, EShyong; McVean, Gilean; Hanis, Craig L.; Wilson, James G.; Seielstad, Mark; Frayling, Timothy M.; Meigs, James B.; Cox, Nancy J.; Sladek, Rob; Lander, Eric S.; Gabriel, Stacey; Mohlke, Karen L.; Meitinger, Thomas; Groop, Leif; Abecasis, Goncalo; Scott, Laura J.; Morris, Andrew P.; Kang, Hyun Min; Altshuler, David; Burtt, Noel P.; Florez, Jose C.; Boehnke, Michael; McCarthy, Mark I. (2017)
    To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to 82 K Europeans via the exome chip, and similar to 90% of low-frequency non-coding variants in similar to 44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
  • Hermes, Gerben D. A.; Eckermann, Henrik A.; de Vos, Willem M.; de Weerth, Carolina (2020)
    Entry to center-based childcare (CC) at three months of life can be an important challenge for infants as it includes major stressors such as long maternal separations and frequently changing caregivers. Stress and the new environment may in turn alter the composition of the gut microbiota with possible implications for future health outcomes. As part of an ongoing longitudinal study, we investigated whether CC, as compared to being cared for by the parents at home, alters the composition of the gut microbiota, while accounting for known covariates of the infant gut microbiota. Stool samples of infants who entered CC (n=49) and control infants (n=49) were obtained before and four weeks after CC entrance. Using Redundancy analysis, Random Forests and Bayesian linear models we found that infant gut microbiota was not affected in a uniform way by entry to CC. In line with the literature, breastfeeding, birth mode, age, and the presence of siblings were shown to significantly impact the microbial composition.
  • Torvik, Fartein Ask; Flato, Martin; McAdams, Tom A.; Colman, Ian; Silventoinen, Karri; Stoltenberg, Camilla (2021)
    Purpose: On average, boys have lower academic achievement than girls. We investigated whether the timing of puberty is associated with academic achievement, and whether later puberty among boys contributes to the sex difference in academic achievement. Method: Examination scores at age 16 were studied among 13,477 British twins participating in the population-based Twins Early Development Study. A pubertal development scale, a height based proxy of growth spurt, and age at menarche were used as indicators of puberty. Associations between puberty, sex, and academic achievement were estimated in phenotypic mediation models and biometric twin models. Results: Earlier puberty was associated with higher academic achievement both in boys and girls. The exception was early age at menarche in girls, which associated with lower academic achievement. More than half of the sex differences in academic achievement could be linked to sex differences in pubertal development, but part of this association appeared to be rooted in prepubertal differences. The biometric twin modelling indicated that the association between puberty and academic achievement was due to shared genetic risk factors. Genetic influences on pubertal development accounted for 7%-8% of the phenotypic variation in academic achievement. Conclusions: Pubertal maturation relates to the examination scores of boys and of girls. This can give genes related to pubertal maturation an influence on outcomes in education and beyond. Sex differences in pubertal maturation can explain parts of the sex difference in academic achievement. Grading students when they are immature may not accurately measure their academic potential. (c) 2021 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved. This is an open access article under the CC BY license (
  • Luoma, Ville; Vastaranta, Mikko; Eyvindson, Kyle; Kankare, Ville; Saarinen, Ninni; Holopainen, Markus; Hyyppa, Juha (Springer International Publishing AG, 2017)
    Lecture Notes in Geoinformation and Cartography
    Currently the forest sector in Finland is looking towards the next generation's forest resource information systems. Information used in forest planning is currently collected by using an area-based approach (ABA) where airborne laser scanning (ALS) data are used to generalize field-measured inventory attributes over an entire inventory area. Inventories are typically updated at 10-year interval. Thus, one of the key challenges is the age of the inventory information and the cost-benefit trade-off between using the old data and obtaining new data. Prediction of future forest resource information is possible through growth modelling. In this paper, the error sources related to ALS-based forest inventory and the growth models applied in forest planning to update the forest resource information were examined. The error sources included (i) forest inventory, (ii) generation of theoretical stem distribution, and (iii) growth modelling. Error sources (ii) and (iii) stem from the calculations used for forest planning, and were combined in the investigations. Our research area, Evo, is located in southern Finland. In all, 34 forest sample plots (300 m(2)) have been measured twice tree-by-tree. First measurements have been carried out in 2007 and the second measurements in 2014 which leads to 7 year updating period. Respectively, ALS-based forest inventory data were available for 2007. The results showed that prediction of theoretical stem distribution and forest growth modelling affected only slightly to the quality of the predicted stem volume in short-term information update when compared to forest inventory error.
  • Fung, Pak L.; Zaidan, Martha A.; Timonen, Hilkka; Niemi, Jarkko V.; Kousa, Anu; Kuula, Joel; Luoma, Krista; Tarkoma, Sasu; Petäjä, Tuukka; Kulmala, Markku; Hussein, Tareq (2021)
    Air quality prediction with black-box (BB) modelling is gaining widespread interest in research and industry. This type of data-driven models work generally better in terms of accuracy but are limited to capture physical, chemical and meteorological processes and therefore accountability for interpretation. In this paper, we evaluated different white-box (WB) and BB methods that estimate atmospheric black carbon (BC) concentration by a suite of observations from the same measurement site. This study involves data in the period of 1st January 2017–31st December 2018 from two measurement sites, from a street canyon site in Mäkelänkatu and from an urban background site in Kumpula, in Helsinki, Finland. At the street canyon site, WB models performed (R² = 0.81–0.87) in a similar way as the BB models did (R² = 0.86–0.87). The overall performance of the BC concentration estimation methods at the urban background site was much worse probably because of a combination of smaller dynamic variability in the BC values and longer data gaps. However, the difference in WB (R²= 0.44–0.60) and BB models (R² = 0.41–0.64) was not significant. Furthermore, the WB models are closer to physics-based models, and it is easier to spot the relative importance of the predictor variable and determine if the model output makes sense. This feature outweighs slightly higher performance of some individual BB models, and inherently the WB models are a better choice due to their transparency in the model architecture. Among all the WB models, IAP and LASSO are recommended due to its flexibility and its efficiency, respectively. Our findings also ascertain the importance of temporal properties in statistical modelling. In the future, the developed BC estimation model could serve as a virtual sensor and complement the current air quality monitoring.
  • Benner, Christian; Spencer, Chris C. A.; Havulinna, Aki S.; Salomaa, Veikko; Ripatti, Samuli; Pirinen, Matti (2016)
    Motivation: The goal of fine-mapping in genomic regions associated with complex diseases and traits is to identify causal variants that point to molecular mechanisms behind the associations. Recent fine-mapping methods using summary data from genome-wide association studies rely on exhaustive search through all possible causal configurations, which is computationally expensive. Results: We introduce FINEMAP, a software package to efficiently explore a set of the most important causal configurations of the region via a shotgun stochastic search algorithm. We show that FINEMAP produces accurate results in a fraction of processing time of existing approaches and is therefore a promising tool for analyzing growing amounts of data produced in genome-wide association studies and emerging sequencing projects.
  • Ahlström, Sirkku; Bergman, Paula; Jokela, Ritva; Ottensmann, Linda; Ahola-Olli, Ari; Pirinen, Matti; Olkkola, Klaus T.; Kaunisto, Mari A.; Kalso, Eija (2021)
    Background: Rocuronium, a common neuromuscular blocking agent, is mainly excreted unchanged in urine (10-25%) and bile ( 70%). Age, sex, liver blood flow, smoking, medical conditions, and ethnic background can affect its pharmacological actions. However, reasons for the wide variation in rocuronium requirements are mostly unknown. We hypothesised that pharmacogenetic factors might explain part of the variation. Methods: One thousand women undergoing surgery for breast cancer were studied. Anaesthesia was maintained with propofol (50-100 mg kg(-1) min(-1)) and remifentanil (0.05-0.25 mg kg(-1) min(-1)). Neuromuscular block was maintained with rocuronium to keep the train-of-four ratio at 0-10%. DNA was extracted from peripheral blood and genotyped with a next-generation genotyping array. The genome-wide association study (GWAS) was conducted using an additive linear regression model with PLINK software. The FINEMAP tool and data from the Genotype-Tissue Expression project v8 were utilised to study the locus further. Results: The final patient population comprised 918 individuals. Of the clinical variables tested, age, BMI, ASA physical status, and total dose of propofol correlated significantly (all P Conclusions: Genetic variation in the gene SLCO1A2, encoding OATP1A2, an uptake transporter, accounted for 4% of the variability in rocuronium consumption. The underlying mechanism remains unknown.
  • Tanskanen, Tomas; van den Berg, Linda; Valimaki, Niko; Aavikko, Mervi; Ness-Jensen, Eivind; Hveem, Kristian; Wettergren, Yvonne; Lindskog, Elinor Bexe; Tonisson, Neeme; Metspalu, Andres; Silander, Kaisa; Orlando, Giulia; Law, Philip J.; Tuupanen, Sari; Gylfe, Alexandra E.; Hanninen, Ulrika A.; Cajuso, Tatiana; Kondelin, Johanna; Sarin, Antti-Pekka; Pukkala, Eero; Jousilahti, Pekka; Salomaa, Veikko; Ripatti, Samuli; Palotie, Aarno; Jarvinen, Heikki; Renkonen-Sinisalo, Laura; Lepisto, Anna; Bohm, Jan; Mecklin, Jukka-Pekka; Al-Tassan, Nada A.; Palles, Claire; Martin, Lynn; Barclay, Ella; Tenesa, Albert; Farrington, Susan M.; Timofeeva, Maria N.; Meyer, Brian F.; Wakil, Salma M.; Campbell, Harry; Smith, Christopher G.; Idziaszczyk, Shelley; Maughan, Tim S.; Kaplan, Richard; Kerr, Rachel; Kerr, David; Buchanan, Daniel D.; Win, Aung K.; Hopper, John; Jenkins, Mark A.; Newcomb, Polly A.; Gallinger, Steve; Conti, David; Schumacher, Fredrick R.; Casey, Graham; Cheadle, Jeremy P.; Dunlop, Malcolm G.; Tomlinson, Ian P.; Houlston, Richard S.; Palin, Kimmo; Aaltonen, Lauri A. (2018)
    Genome-wide association studies have been successful in elucidating the genetic basis of colorectal cancer (CRC), but there remains unexplained variability in genetic risk. To identify new risk variants and to confirm reported associations, we conducted a genome-wide association study in 1,701 CRC cases and 14,082 cancer-free controls from the Finnish population. A total of 9,068,015 genetic variants were imputed and tested, and 30 promising variants were studied in additional 11,647 cases and 12,356 controls of European ancestry. The previously reported association between the single-nucleotide polymorphism (SNP) rs992157 (2q35) and CRC was independently replicated (p=2.08 x 10(-4); OR, 1.14; 95% CI, 1.06-1.23), and it was genome-wide significant in combined analysis (p=1.50 x 10(-9); OR, 1.12; 95% CI, 1.08-1.16). Variants at 2q35, 6p21.2, 8q23.3, 8q24.21, 10q22.3, 10q24.2, 11q13.4, 11q23.1, 14q22.2, 15q13.3, 18q21.1, 20p12.3 and 20q13.33 were associated with CRC in the Finnish population (false discovery rate
  • Justice, Anne E.; Winkler, Thomas W.; Feitosa, Mary F.; Graff, Misa; Fisher, Virginia A.; Young, Kristin; Barata, Llilda; Deng, Xuan; Czajkowski, Jacek; Hadley, David; Ngwa, Julius S.; Ahluwalia, Tarunveer S.; Chu, Audrey Y.; Heard-Costa, Nancy L.; Lim, Elise; Perez, Jeremiah; Eicher, John D.; Kutalik, Zoltan; Xue, Luting; Mahajan, Anubha; Renstrom, Frida; Wu, Joseph; Qi, Qibin; Ahmad, Shafqat; Alfred, Tamuno; Amin, Najaf; Bielak, Lawrence F.; Bonnefond, Amelie; Bragg, Jennifer; Cadby, Gemma; Chittani, Martina; Coggeshall, Scott; Corre, Tanguy; Direk, Nese; Eriksson, Joel; Fischer, Krista; Gorski, Mathias; Harder, Marie Neergaard; Horikoshi, Momoko; Huang, Tao; Huffman, Jennifer E.; Jackson, Anne U.; Justesen, Johanne Marie; Kanoni, Stavroula; Kinnunen, Leena; Kleber, Marcus E.; Komulainen, Pirjo; Kumari, Meena; Lim, Unhee; Luan, Jian'an; Lyytikainen, Leo-Pekka; Mangino, Massimo; Manichaikul, Ani; Marten, Jonathan; Middelberg, Rita P. S.; Mueller-Nurasyid, Martina; Navarro, Pau; Perusse, Louis; Pervjakova, Natalia; Sarti, Cinzia; Smith, Albert Vernon; Smith, Jennifer A.; Stancakova, Alena; Strawbridge, Rona J.; Stringham, Heather M.; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W.; van der Most, Peter J.; Van Vliet-Ostaptchouk, Jana V.; Vedantam, Sailaja L.; Verweij, Niek; Vink, Jacqueline M.; Vitart, Veronique; Wu, Ying; Yengo, Loic; Zhang, Weihua; Zhao, Jing Hua; Zimmermann, Martina E.; Zubair, Niha; Abecasis, Goncalo R.; Adair, Linda S.; Afaq, Saima; Afzal, Uzma; Bakker, Stephan J. L.; Bartz, Traci M.; Beilby, John; Bergman, Richard N.; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boerwinkle, Eric; Bonnycastle, Lori L.; Bottinger, Erwin; Braga, Daniele; Buckley, Brendan M.; Buyske, Steve; Campbell, Harry; Chambers, John C.; Collins, Francis S.; Curran, Joanne E.; de Borst, Gert J.; de Craen, Anton J. M.; de Geus, Eco J. C.; Dedoussis, George; Delgado, Graciela E.; den Ruijter, Hester M.; Eiriksdottir, Gudny; Eriksson, Anna L.; Esko, Tonu; Faul, Jessica D.; Ford, Ian; Forrester, Terrence; Gertow, Karl; Gigante, Bruna; Glorioso, Nicola; Gong, Jian; Grallert, Harald; Grammer, Tanja B.; Grarup, Niels; Haitjema, Saskia; Hallmans, Goran; Hamsten, Anders; Hansen, Torben; Harris, Tamara B.; Hartman, Catharina A.; Hassinen, Maija; Hastie, Nicholas D.; Heath, Andrew C.; Hernandez, Dena; Hindorff, Lucia; Hocking, Lynne J.; Hollensted, Mette; Holmen, Oddgeir L.; Homuth, Georg; Hottenga, Jouke Jan; Huang, Jie; Hung, Joseph; Hutri-Kahonen, Nina; Ingelsson, Erik; James, Alan L.; Jansson, John-Olov; Jarvelin, Marjo-Riitta; Jhun, Min A.; Jorgensen, Marit E.; Juonala, Markus; Kahonen, Mika; Karlsson, Magnus; Koistinen, Heikki A.; Kolcic, Ivana; Kolovou, Genovefa; Kooperberg, Charles; Kramer, Bernhard K.; Kuusisto, Johanna; Kvaloy, Kirsti; Lakka, Timo A.; Langenberg, Claudia; Launer, Lenore J.; Leander, Karin; Lee, Nanette R.; Lind, Lars; Lindgren, Cecilia M.; Linneberg, Allan; Lobbens, Stephane; Loh, Marie; Lorentzon, Mattias; Luben, Robert; Lubke, Gitta; Ludolph-Donislawski, Anja; Lupoli, Sara; Madden, Pamela A. F.; Mannikko, Reija; Marques-Vidal, Pedro; Martin, Nicholas G.; McKenzie, Colin A.; McKnight, Barbara; Mellstrom, Dan; Menni, Cristina; Montgomery, Grant W.; Musk, A. W. (Bill); Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M.; Oldehinkel, Albertine J.; Olden, Matthias; Ong, Ken K.; Padmanabhan, Sandosh; Peyser, Patricia A.; Pisinger, Charlotta; Porteous, David J.; Raitakari, Olli T.; Rankinen, Tuomo; Rao, D. C.; Rasmussen-Torvik, Laura J.; Rawal, Rajesh; Rice, Treva; Ridker, Paul M.; Rose, Lynda M.; Bien, Stephanie A.; Rudan, Igor; Sanna, Serena; Sarzynski, Mark A.; Sattar, Naveed; Savonen, Kai; Schlessinger, David; Scholtens, Salome; Schurmann, Claudia; Scott, Robert A.; Sennblad, Bengt; Siemelink, Marten A.; Silbernagel, Gunther; Slagboom, P. Eline; Snieder, Harold; Staessen, Jan A.; Stott, David J.; Swertz, Morris A.; Swift, Amy J.; Taylor, Kent D.; Tayo, Bamidele O.; Thorand, Barbara; Thuillier, Dorothee; Tuomilehto, Jaakko; Uitterlinden, Andre G.; Vandenput, Liesbeth; Vohl, Marie-Claude; Volzke, Henry; Vonk, Judith M.; Waeber, Gerard; Waldenberger, Melanie; Westendorp, R. G. J.; Wild, Sarah; Willemsen, Gonneke; Wolffenbuttel, Bruce H. R.; Wong, Andrew; Wright, Alan F.; Zhao, Wei; Zillikens, M. Carola; Baldassarre, Damiano; Balkau, Beverley; Bandinelli, Stefania; Boger, Carsten A.; Boomsma, Dorret I.; Bouchard, Claude; Bruinenberg, Marcel; Chasman, Daniel I.; Chen, Yii-Der Ida; Chines, Peter S.; Cooper, Richard S.; Cucca, Francesco; Cusi, Daniele; de Faire, Ulf; Ferrucci, Luigi; Franks, Paul W.; Froguel, Philippe; Gordon-Larsen, Penny; Grabe, Hans-Jorgen; Gudnason, Vilmundur; Haiman, Christopher A.; Hayward, Caroline; Hveem, Kristian; Johnson, Andrew D.; Jukema, Wouter; Kardia, Sharon L. R.; Kivimaki, Mika; Kooner, Jaspal S.; Kuh, Diana; Laakso, Markku; Lehtimaki, Terho; Le Marchand, Loic; Marz, Winfried; McCarthy, Mark I.; Metspalu, Andres; Morris, Andrew P.; Ohlsson, Claes; Palmer, Lyle J.; Pasterkamp, Gerard; Pedersen, Oluf; Peters, Annette; Peters, Ulrike; Polasek, Ozren; Psaty, Bruce M.; Qi, Lu; Rauramaa, Rainer; Smith, Blair H.; Sorensen, Thorkild I. A.; Strauch, Konstantin; Tiemeier, Henning; Tremoli, Elena; Van der Harst, Pim; Vestergaard, Henrik; Vollenweider, Peter; Wareham, Nicholas J.; Weir, David R.; Whitfield, John B.; Wilson, James F.; Tyrrell, Jessica; Frayling, Timothy M.; Barroso, Ines; Boehnke, Michael; Deloukas, Panagiotis; Fox, Caroline S.; Hirschhorn, Joel N.; Hunter, David J.; Spector, Tim D.; Strachan, David P.; van Duijn, Cornelia M.; Heid, Iris M.; Mohlke, Karen L.; Marchini, Jonathan; Loos, Ruth J. F.; Kilpelainen, Tuomas O.; Liu, Ching-Ti; Borecki, Ingrid B.; North, Kari E.; Cupples, L. Adrienne (2017)
    Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.
  • Ali, Mehreen; Khan, Suleiman A.; Wennerberg, Krister; Aittokallio, Tero (2018)
    Motivation: Proteomics profiling is increasingly being used for molecular stratification of cancer patients and cell-line panels. However, systematic assessment of the predictive power of large-scale proteomic technologies across various drug classes and cancer types is currently lacking. To that end, we carried out the first pan-cancer, multi-omics comparative analysis of the relative performance of two proteomic technologies, targeted reverse phase protein array (RPPA) and global mass spectrometry (MS), in terms of their accuracy for predicting the sensitivity of cancer cells to both cytotoxic chemotherapeutics and molecularly targeted anticancer compounds. Results: Our results in two cell-line panels demonstrate how MS profiling improves drug response predictions beyond that of the RPPA or the other omics profiles when used alone. However, frequent missing MS data values complicate its use in predictive modeling and required additional filtering, such as focusing on completely measured or known oncoproteins, to obtain maximal predictive performance. Rather strikingly, the two proteomics profiles provided complementary predictive signal both for the cytotoxic and targeted compounds. Further, information about the cellular-abundance of primary target proteins was found critical for predicting the response of targeted compounds, although the non-target features also contributed significantly to the predictive power. The clinical relevance of the selected protein markers was confirmed in cancer patient data. These results provide novel insights into the relative performance and optimal use of the widely applied proteomic technologies, MS and RPPA, which should prove useful in translational applications, such as defining the best combination of omics technologies and marker panels for understanding and predicting drug sensitivities in cancer patients.
  • Gaal, Emilia Ilona; Salo, Perttu; Kristiansson, Kati; Rehnstrom, Karola; Kettunen, Johannes; Sarin, Antti-Pekka; Niemela, Mika; Jula, Antti; Raitakari, Olli T.; Lehtimaki, Terho; Eriksson, Johan G.; Widen, Elisabeth; Guenel, Murat; Kurki, Mitja; Fraunberg, Mikael von Und Zu; Jaaskelainen, Juha E.; Hernesniemi, Juha; Jarvelin, Marjo-Riitta; Pouta, Anneli; Newton-Cheh, Christopher; Salomaa, Veikko; Palotie, Aarno; Perola, Markus; ICBP-GWAS (2012)
  • UK10K Consortium (2019)
    Cranial growth and development is a complex process which affects the closely related traits of head circumference (HC) and intracranial volume (ICV). The underlying genetic influences shaping these traits during the transition from childhood to adulthood are little understood, but might include both age-specific genetic factors and low-frequency genetic variation. Here, we model the developmental genetic architecture of HC, showing this is genetically stable and correlated with genetic determinants of ICV. Investigating up to 46,000 children and adults of European descent, we identify association with final HC and/or final ICV + HC at 9 novel common and low-frequency loci, illustrating that genetic variation from a wide allele frequency spectrum contributes to cranial growth. The largest effects are reported for low-frequency variants within TP53, with 0.5 cm wider heads in increaser-allele carriers versus non-carriers during mid-childhood, suggesting a previously unrecognized role of TP53 transcripts in human cranial development.
  • Vastaranta, Mikko; Saarinen, Ninni; Kankare, Ville; Holopainen, Markus; Kaartinen, Harri; Hyyppa, Juha; Hyyppa, Hannu (2014)
  • 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.