Radboud Institute for Molecular Life Sciences

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies. Results for the final phase of the 1000 Genomes Project are presented including whole-genome sequencing, targeted exome sequencing, and genotyping on high-density SNP arrays for 2,504 individuals across 26 populations, providing a global reference data set to support biomedical genetics. The 1000 Genomes Project has sought to comprehensively catalogue human genetic variation across populations, providing a valuable public genomic resource. The data obtained so far have found applications ranging from association studies and fine mapping studies to the filtering of likely neutral variants in rare-disease cohorts. The authors now report on the final phase of the project, phase 3, which covers previously uncharacterized areas of human genetic diversity in terms of the populations sampled and categories of characterized variation. The sample now includes more than 2,500 individuals from 26 global populations, with low coverage whole-genome and deep exome sequencing, as well as dense microarray genotyping. They find that while most common variants are shared across populations, rarer variants are often restricted to closely related populations. The authors also demonstrate the use of the phase 3 dataset as a reference panel for imputation to improve the resolution in genetic association studies.

AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425,
\nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981,
\nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826,
\nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376,
\nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294,
\nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198,
\nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544,
\nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107,
\nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756,
\nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6,
\nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58,
\nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007,
\nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591,
\nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930,
\nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794,
\nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727,
\nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986,
\nNeelam Azad404, Tiziana Bachetti568, Jonathan M Backer28, Dong-Hun Bae1933, Jae-sung Bae677, Ok-Nam Bae409,
\nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368,
\nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884,
\nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239,
\nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997,
\nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798,
\nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909,
\nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336,
\nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419,
\nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490,
\nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401,
\nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880,
\nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913,
\nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381,
\nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112,
\nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812,
\nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287,
\nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308,
\nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901,
\nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141,
\nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374,
\nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822,
\nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480,
\nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171,
\nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789,
\nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217,
\nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24,
\nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700,
\nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983,
\nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002,
\nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318,
\nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462,
\nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884,
\nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996,
\nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628,
\nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003,
\nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434,
\nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783,
\nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514,
\nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172,
\nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113,
\nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135,
\nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702,
\nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703,
\nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308,
\nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290,
\nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105,
\nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563,
\nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936,
\nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657,
\nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254,
\nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694,
\nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781,
\nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533,
\nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829,
\nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395,
\nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566,
\nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767,
\nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301,
\nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919,
\nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576,
\nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572,
\nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940,
\nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340,
\nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254,
\nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604,
\nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182,
\nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775,
\nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,

Abstract Somatic mutations in cancer genomes are caused by multiple mutational processes, each of which generates a characteristic mutational signature 1 . Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium 2 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we characterized mutational signatures using 84,729,690 somatic mutations from 4,645 whole-genome and 19,184 exome sequences that encompass most types of cancer. We identified 49 single-base-substitution, 11 doublet-base-substitution, 4 clustered-base-substitution and 17 small insertion-and-deletion signatures. The substantial size of our dataset, compared with previous analyses 3–15 , enabled the discovery of new signatures, the separation of overlapping signatures and the decomposition of signatures into components that may represent associated—but distinct—DNA damage, repair and/or replication mechanisms. By estimating the contribution of each signature to the mutational catalogues of individual cancer genomes, we revealed associations of signatures to exogenous or endogenous exposures, as well as to defective DNA-maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes that contribute to the development of human cancer.

Abstract Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale 1–3 . Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter 4 ; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation 5,6 ; analyses timings and patterns of tumour evolution 7 ; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity 8,9 ; and evaluates a range of more-specialized features of cancer genomes 8,10–18 .

BACKGROUND: Invasive fungal diseases (IFDs) remain important causes of morbidity and mortality. The consensus definitions of the Infectious Diseases Group of the European Organization for Research and Treatment of Cancer and the Mycoses Study Group have been of immense value to researchers who conduct clinical trials of antifungals, assess diagnostic tests, and undertake epidemiologic studies. However, their utility has not extended beyond patients with cancer or recipients of stem cell or solid organ transplants. With newer diagnostic techniques available, it was clear that an update of these definitions was essential. METHODS: To achieve this, 10 working groups looked closely at imaging, laboratory diagnosis, and special populations at risk of IFD. A final version of the manuscript was agreed upon after the groups' findings were presented at a scientific symposium and after a 3-month period for public comment. There were several rounds of discussion before a final version of the manuscript was approved. RESULTS: There is no change in the classifications of "proven," "probable," and "possible" IFD, although the definition of "probable" has been expanded and the scope of the category "possible" has been diminished. The category of proven IFD can apply to any patient, regardless of whether the patient is immunocompromised. The probable and possible categories are proposed for immunocompromised patients only, except for endemic mycoses. CONCLUSIONS: These updated definitions of IFDs should prove applicable in clinical, diagnostic, and epidemiologic research of a broader range of patients at high-risk.

The general view that only adaptive immunity can build immunological memory has recently been challenged. In organisms lacking adaptive immunity, as well as in mammals, the innate immune system can mount resistance to reinfection, a phenomenon termed "trained immunity" or "innate immune memory." Trained immunity is orchestrated by epigenetic reprogramming, broadly defined as sustained changes in gene expression and cell physiology that do not involve permanent genetic changes such as mutations and recombination, which are essential for adaptive immunity. The discovery of trained immunity may open the door for novel vaccine approaches, new therapeutic strategies for the treatment of immune deficiency states, and modulation of exaggerated inflammation in autoinflammatory diseases.

Making devices with graphene necessarily involves making contacts with metals. We use density functional theory to study how graphene is doped by adsorption on metal substrates and find that weak bonding on Al, Ag, Cu, Au, and Pt, while preserving its unique electronic structure, can still shift the Fermi level with respect to the conical point by approximately 0.5 eV. At equilibrium separations, the crossover from p-type to n-type doping occurs for a metal work function of approximately 5.4 eV, a value much larger than the graphene work function of 4.5 eV. The numerical results for the Fermi level shift in graphene are described very well by a simple analytical model which characterizes the metal solely in terms of its work function, greatly extending their applicability.

BACKGROUND: Patients with acute myeloid leukemia (AML) and a FLT3 mutation have poor outcomes. We conducted a phase 3 trial to determine whether the addition of midostaurin - an oral multitargeted kinase inhibitor that is active in patients with a FLT3 mutation - to standard chemotherapy would prolong overall survival in this population. METHODS: We screened 3277 patients, 18 to 59 years of age, who had newly diagnosed AML for FLT3 mutations. Patients were randomly assigned to receive standard chemotherapy (induction therapy with daunorubicin and cytarabine and consolidation therapy with high-dose cytarabine) plus either midostaurin or placebo; those who were in remission after consolidation therapy entered a maintenance phase in which they received either midostaurin or placebo. Randomization was stratified according to subtype of FLT3 mutation: point mutation in the tyrosine kinase domain (TKD) or internal tandem duplication (ITD) mutation with either a high ratio (>0.7) or a low ratio (0.05 to 0.7) of mutant to wild-type alleles (ITD [high] and ITD [low], respectively). Allogeneic transplantation was allowed. The primary end point was overall survival. RESULTS: A total of 717 patients underwent randomization; 360 were assigned to the midostaurin group, and 357 to the placebo group. The FLT3 subtype was ITD (high) in 214 patients, ITD (low) in 341 patients, and TKD in 162 patients. The treatment groups were well balanced with respect to age, race, FLT3 subtype, cytogenetic risk, and blood counts but not with respect to sex (51.7% in the midostaurin group vs. 59.4% in the placebo group were women, P=0.04). Overall survival was significantly longer in the midostaurin group than in the placebo group (hazard ratio for death, 0.78; one-sided P=0.009), as was event-free survival (hazard ratio for event or death, 0.78; one-sided P=0.002). In both the primary analysis and an analysis in which data for patients who underwent transplantation were censored, the benefit of midostaurin was consistent across all FLT3 subtypes. The rate of severe adverse events was similar in the two groups. CONCLUSIONS: The addition of the multitargeted kinase inhibitor midostaurin to standard chemotherapy significantly prolonged overall and event-free survival among patients with AML and a FLT3 mutation. (Funded by the National Cancer Institute and Novartis; ClinicalTrials.gov number, NCT00651261 .).

Epigenetic reprogramming of myeloid cells, also known as trained immunity, confers nonspecific protection from secondary infections. Using histone modification profiles of human monocytes trained with the Candida albicans cell wall constituent β-glucan, together with a genome-wide transcriptome, we identified the induced expression of genes involved in glucose metabolism. Trained monocytes display high glucose consumption, high lactate production, and a high ratio of nicotinamide adenine dinucleotide (NAD(+)) to its reduced form (NADH), reflecting a shift in metabolism with an increase in glycolysis dependent on the activation of mammalian target of rapamycin (mTOR) through a dectin-1-Akt-HIF-1α (hypoxia-inducible factor-1α) pathway. Inhibition of Akt, mTOR, or HIF-1α blocked monocyte induction of trained immunity, whereas the adenosine monophosphate-activated protein kinase activator metformin inhibited the innate immune response to fungal infection. Mice with a myeloid cell-specific defect in HIF-1α were unable to mount trained immunity against bacterial sepsis. Our results indicate that induction of aerobic glycolysis through an Akt-mTOR-HIF-1α pathway represents the metabolic basis of trained immunity.

IMPORTANCE: Systematic reviews and meta-analyses of individual participant data (IPD) aim to collect, check, and reanalyze individual-level data from all studies addressing a particular research question and are therefore considered a gold standard approach to evidence synthesis. They are likely to be used with increasing frequency as current initiatives to share clinical trial data gain momentum and may be particularly important in reviewing controversial therapeutic areas. OBJECTIVE: To develop PRISMA-IPD as a stand-alone extension to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement, tailored to the specific requirements of reporting systematic reviews and meta-analyses of IPD. Although developed primarily for reviews of randomized trials, many items will apply in other contexts, including reviews of diagnosis and prognosis. DESIGN: Development of PRISMA-IPD followed the EQUATOR Network framework guidance and used the existing standard PRISMA Statement as a starting point to draft additional relevant material. A web-based survey informed discussion at an international workshop that included researchers, clinicians, methodologists experienced in conducting systematic reviews and meta-analyses of IPD, and journal editors. The statement was drafted and iterative refinements were made by the project, advisory, and development groups. The PRISMA-IPD Development Group reached agreement on the PRISMA-IPD checklist and flow diagram by consensus. FINDINGS: Compared with standard PRISMA, the PRISMA-IPD checklist includes 3 new items that address (1) methods of checking the integrity of the IPD (such as pattern of randomization, data consistency, baseline imbalance, and missing data), (2) reporting any important issues that emerge, and (3) exploring variation (such as whether certain types of individual benefit more from the intervention than others). A further additional item was created by reorganization of standard PRISMA items relating to interpreting results. Wording was modified in 23 items to reflect the IPD approach. CONCLUSIONS AND RELEVANCE: PRISMA-IPD provides guidelines for reporting systematic reviews and meta-analyses of IPD.

The possibility of using shape mixtures of randomly oriented spheroids for modeling desert dust aerosol light scattering is discussed. For reducing calculation time, look‐up tables were simulated for quadrature coefficients employed in the numerical integration of spheroid optical properties over size and shape. The calculations were done for 25 bins of the spheroid axis ratio ranging from ∼0.3 (flattened spheroids) to ∼3.0 (elongated spheroids) and for 41 narrow size bins covering the size parameter range from ∼0.012 to ∼625. The look‐up tables were arranged into a software package, which allows fast, accurate, and flexible modeling of scattering by randomly oriented spheroids with different size and shape distributions. In order to evaluate spheroid model and explore the possibility of aerosol shape identification, the software tool has been integrated into inversion algorithms for retrieving detailed aerosol properties from laboratory or remote sensing polarimetric measurements of light scattering. The application of this retrieval technique to laboratory measurements by Volten et al. (2001) has shown that spheroids can closely reproduce mineral dust light scattering matrices. The spheroid model was utilized for retrievals of aerosol properties from atmospheric radiation measured by AERONET ground‐based Sun/sky‐radiometers. It is shown that mixtures of spheroids allow rather accurate fitting of measured spectral and angular dependencies of observed intensity and polarization. Moreover, it is shown that for aerosol mixtures with a significant fraction of coarse‐mode particles (radii ≥ ∼1 μm), the nonsphericity of aerosol particles can be detected as part of AERONET retrievals. The retrieval results indicate that nonspherical particles with aspect ratios ∼1.5 and higher dominate in desert dust plumes, while in the case of background maritime aerosol spherical particles are dominant. Finally, the potential of using AERONET derived spheroid mixtures for modeling the effects of aerosol particle nonsphericity in other remote sensing techniques is discussed. For example, the variability of lidar measurements (extinction to backscattering ratio and signal depolarization ratio) is illustrated and analyzed. Also, some potentially important differences in the sensitivity of angular light scattering to parameters of nonspherical versus spherical aerosols are revealed and discussed.

Adaptive features of innate immunity, recently described as "trained immunity," have been documented in plants, invertebrate animals, and mice, but not yet in humans. Here we show that bacille Calmette-Guérin (BCG) vaccination in healthy volunteers led not only to a four- to sevenfold increase in the production of IFN-γ, but also to a twofold enhanced release of monocyte-derived cytokines, such as TNF and IL-1β, in response to unrelated bacterial and fungal pathogens. The enhanced function of circulating monocytes persisted for at least 3 mo after vaccination and was accompanied by increased expression of activation markers such as CD11b and Toll-like receptor 4. These training effects were induced through the NOD2 receptor and mediated by increased histone 3 lysine 4 trimethylation. In experimental studies, BCG vaccination induced T- and B-lymphocyte-independent protection of severe combined immunodeficiency SCID mice from disseminated candidiasis (100% survival in BCG-vaccinated mice vs. 30% in control mice). In conclusion, BCG induces trained immunity and nonspecific protection from infections through epigenetic reprogramming of innate immune cells.

Monocyte differentiation into macrophages represents a cornerstone process for host defense. Concomitantly, immunological imprinting of either tolerance or trained immunity determines the functional fate of macrophages and susceptibility to secondary infections. We characterized the transcriptomes and epigenomes in four primary cell types: monocytes and in vitro-differentiated naïve, tolerized, and trained macrophages. Inflammatory and metabolic pathways were modulated in macrophages, including decreased inflammasome activation, and we identified pathways functionally implicated in trained immunity. β-glucan training elicits an exclusive epigenetic signature, revealing a complex network of enhancers and promoters. Analysis of transcription factor motifs in deoxyribonuclease I hypersensitive sites at cell-type-specific epigenetic loci unveiled differentiation and treatment-specific repertoires. Altogether, we provide a resource to understand the epigenetic changes that underlie innate immunity in humans.

Magnesium (Mg(2+)) is an essential ion to the human body, playing an instrumental role in supporting and sustaining health and life. As the second most abundant intracellular cation after potassium, it is involved in over 600 enzymatic reactions including energy metabolism and protein synthesis. Although Mg(2+) availability has been proven to be disturbed during several clinical situations, serum Mg(2+) values are not generally determined in patients. This review aims to provide an overview of the function of Mg(2+) in human health and disease. In short, Mg(2+) plays an important physiological role particularly in the brain, heart, and skeletal muscles. Moreover, Mg(2+) supplementation has been shown to be beneficial in treatment of, among others, preeclampsia, migraine, depression, coronary artery disease, and asthma. Over the last decade, several hereditary forms of hypomagnesemia have been deciphered, including mutations in transient receptor potential melastatin type 6 (TRPM6), claudin 16, and cyclin M2 (CNNM2). Recently, mutations in Mg(2+) transporter 1 (MagT1) were linked to T-cell deficiency underlining the important role of Mg(2+) in cell viability. Moreover, hypomagnesemia can be the consequence of the use of certain types of drugs, such as diuretics, epidermal growth factor receptor inhibitors, calcineurin inhibitors, and proton pump inhibitors. This review provides an extensive and comprehensive overview of Mg(2+) research over the last few decades, focusing on the regulation of Mg(2+) homeostasis in the intestine, kidney, and bone and disturbances which may result in hypomagnesemia.

We have developed an automatable procedure for reconstructing the tree of life with branch lengths comparable across all three domains. The tree has its basis in a concatenation of 31 orthologs occurring in 191 species with sequenced genomes. It revealed interdomain discrepancies in taxonomic classification. Systematic detection and subsequent exclusion of products of horizontal gene transfer increased phylogenetic resolution, allowing us to confirm accepted relationships and resolve disputed and preliminary classifications. For example, we place the phylum Acidobacteria as a sister group of delta-Proteobacteria, support a Gram-positive origin of Bacteria, and suggest a thermophilic last universal common ancestor.

The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7×) or exomes (high read depth, 80×) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results. Low read depth sequencing of whole genomes and high read depth exomes of nearly 10,000 extensively phenotyped individuals are combined to help characterize novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with lipid-related traits; in addition to describing population structure and providing functional annotation of rare and low-frequency variants the authors use the data to estimate the benefits of sequencing for association studies. This paper, combining data and initial findings from the different arms of the UK10K project, describes insights from low-read-depth sequencing of whole genomes or high-read-depth exome sequencing of nearly 10,000 individuals sampled from a range of disease collections, as well as participants from healthy population based cohorts. The authors characterize novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with lipid-related traits. In addition to describing population structure and providing functional annotation of rare and low frequency variants, they use the data to estimate the benefits of sequencing for association studies.

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.

Abstract Cancer develops through a process of somatic evolution 1,2 . Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes 3 . Here, by whole-genome sequencing analysis of 2,658 cancers as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) 4 , we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection.

We describe a set of algorithms that allow to simulate dihydrofolate reductase (DHFR, a common benchmark) with the AMBER all-atom force field at 160 nanoseconds/day on a single Intel Core i7 5960X CPU (no graphics processing unit (GPU), 23,786 atoms, particle mesh Ewald (PME), 8.0 Å cutoff, correct atom masses, reproducible trajectory, CPU with 3.6 GHz, no turbo boost, 8 AVX registers). The new features include a mixed multiple time-step algorithm (reaching 5 fs), a tuned version of LINCS to constrain bond angles, the fusion of pair list creation and force calculation, pressure coupling with a "densostat," and exploitation of new CPU instruction sets like AVX2. The impact of Intel's new transactional memory, atomic instructions, and sloppy pair lists is also analyzed. The algorithms map well to GPUs and can automatically handle most Protein Data Bank (PDB) files including ligands. An implementation is available as part of the YASARA molecular modeling and simulation program from www.YASARA.org.

Ancient polyploidization events have shaped diverse eukaryotic genomes 1 , including two rounds of whole-genome duplication at the base of the vertebrate radiation 2 . While polyploidy is rare in amniotes, presumably owing to constraints on sex chromosome dosage Polyploidy provides raw material for evolutionary diversification because gene duplicates To explore the origins and consequences of tetraploidy in the African clawed frog, we sequenced the Xenopus laevis genome and compared it to the related diploid X. tropicalis genome. We characterize the allotetraploid origin of X. laevis by partitioning its genome into two homoeologous subgenomes, marked by distinct families of 'fossil' transposable elements. On the basis of the activity of these elements and the age of hundreds of unitary pseudogenes, we estimate that the two diploid progenitor species diverged around 34 million years ago (Ma) and combined to form an allotetraploid around 17-18 Ma. More than 56% of all genes were retained in two homoeologous copies. Protein function, gene expression, and the amount of conserved flanking sequence all correlate with retention rates. The subgenomes have evolved asymmetrically, with one chromosome set more often preserving the ancestral state and the other experiencing more gene loss, deletion, rearrangement, and reduced gene expression.