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3. Insights on EU Strategy for Building Partnerships in Mediterranean Energy Policy to Meet Decarbonization Goals

Author

Çiner, A, Naitza, S, Radwan, AE, Hamimi, Z, Lucci, F, Knight, J, Cucciniello, C, Banerjee, S, Chennaoui, H, Doronzo, DM, Candeias, C, Rodrigo-Comino, J, Kalatehjari, R, Shah, A, Gentilucci, M, Panagoulia, D, Chaminé, HI, Barbieri, M, Ergüler, Z, Di Foggia, G, Beccarello, M, Çiner, A, Naitza, S, Radwan, AE, Hamimi, Z, Lucci, F, Knight, J, Cucciniello, C, Banerjee, S, Chennaoui, H, Doronzo, DM, Candeias, C, Rodrigo-Comino, J, Kalatehjari, R, Shah, A, Gentilucci, M, Panagoulia, D, Chaminé, HI, Barbieri, M, Ergüler, Z, Di Foggia, G, and Beccarello, M

Abstract

With the approval of the REPowerEU plan, the European Union intends to build partnerships to produce mutually beneficial gains by aiming to promote renewable energy and cooperate on green technologies and innovation. In addition to the increased supply of liquefied natural gas from the United States and Canada, it is necessary to intensify the southern gas transport corridor, formalize political agreements with gas suppliers such as Egypt and Israel to increase natural gas supplies, and boost the energy dialog with Algeria. Then, it is necessary to explore the export potential of sub-Saharan African countries. The shift to an economy less dependent on fossil energy offers significant opportunities beyond the issue of security and energy supply. Indeed, the new European decarbonization goals to rapidly advance the green transition pave the way for a new perspective in geostrategic cooperation in the Mediterranean. For the Mediterranean, geostrategic cooperation could combine economic development and renewable energy production. With this paper, we aim to estimate the energy potential of Mediterranean countries for renewable energy production to engage in more sustainable energy strategies, policies, and systems. We pay particular attention to infrastructural availability and plant capacity. We, therefore, intend to investigate possible synergies to combine energy and environmental policies in line with European climate policies.

Published
2024

4. Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications

Author

Sterenborg, R.B.T.M., Steinbrenner, I., Li, Yong, Bujnis, M.N., Naito, T., Marouli, E., Galesloot, T.E., Babajide, O., Andreasen, L., Astrup, A., Åsvold, B.O., Bandinelli, S., Beekman, M., Beilby, J.P., Bork-Jensen, J., Boutin, T., Brody, J.A., Brown, S.J., Brumpton, B., Campbell, P.J., Cappola, A.R., Ceresini, G., Chaker, L., Chasman, D.I., Concas, M.P., Coutinho de Almeida, Rodrigo, Cross, S.M., Cucca, F., Deary, I.J., Kjaergaard, A.D., Echouffo Tcheugui, J.B., Ellervik, C., Eriksson, J.G., Ferrucci, L., Freudenberg, J., Fuchsberger, C., Gieger, C., Giulianini, F., Gögele, M., Graham, S.E., Grarup, N., Gunjača, I., Hansen, T., Harding, B.N., Harris, S.E., Haunsø, S., Hayward, C., Hui, J., Ittermann, T., Jukema, J.W., Kajantie, E., Kanters, J.K., Kårhus, L.L., Kiemeney, L.A.L.M., Kühnel, B., Lahti, J., Langenberg, C., Lapauw, B., Leese, G., Li, Shuo, Liewald, D.C.M., Linneberg, A., Lominchar, J.V.T., Luan, Jian'an, Martin, N.G., Matana, A., Meima, M.E., Meitinger, T., Meulenbelt, I., Mitchell, B.D., Møllehave, L.T., Mora, S., Naitza, S., Nauck, M., Netea-Maier, R.T., Noordam, R., Nursyifa, C., Okada, Y., Onano, S., Papadopoulou, A., Palmer, C.N.A., Pattaro, C., Pedersen, O., Peters, A., Pietzner, M., Polašek, O., Pramstaller, P.P., Psaty, B.M., Punda, A., Ray, D., Redmond, P., Richards, J.B., Ridker, P.M., Russ, T.C., Ryan, K.A., Olesen, M.S., Schultheiss, U.T., Selvin, E., Siddiqui, M.K., Teumer, A., Medici, M., Sterenborg, R.B.T.M., Steinbrenner, I., Li, Yong, Bujnis, M.N., Naito, T., Marouli, E., Galesloot, T.E., Babajide, O., Andreasen, L., Astrup, A., Åsvold, B.O., Bandinelli, S., Beekman, M., Beilby, J.P., Bork-Jensen, J., Boutin, T., Brody, J.A., Brown, S.J., Brumpton, B., Campbell, P.J., Cappola, A.R., Ceresini, G., Chaker, L., Chasman, D.I., Concas, M.P., Coutinho de Almeida, Rodrigo, Cross, S.M., Cucca, F., Deary, I.J., Kjaergaard, A.D., Echouffo Tcheugui, J.B., Ellervik, C., Eriksson, J.G., Ferrucci, L., Freudenberg, J., Fuchsberger, C., Gieger, C., Giulianini, F., Gögele, M., Graham, S.E., Grarup, N., Gunjača, I., Hansen, T., Harding, B.N., Harris, S.E., Haunsø, S., Hayward, C., Hui, J., Ittermann, T., Jukema, J.W., Kajantie, E., Kanters, J.K., Kårhus, L.L., Kiemeney, L.A.L.M., Kühnel, B., Lahti, J., Langenberg, C., Lapauw, B., Leese, G., Li, Shuo, Liewald, D.C.M., Linneberg, A., Lominchar, J.V.T., Luan, Jian'an, Martin, N.G., Matana, A., Meima, M.E., Meitinger, T., Meulenbelt, I., Mitchell, B.D., Møllehave, L.T., Mora, S., Naitza, S., Nauck, M., Netea-Maier, R.T., Noordam, R., Nursyifa, C., Okada, Y., Onano, S., Papadopoulou, A., Palmer, C.N.A., Pattaro, C., Pedersen, O., Peters, A., Pietzner, M., Polašek, O., Pramstaller, P.P., Psaty, B.M., Punda, A., Ray, D., Redmond, P., Richards, J.B., Ridker, P.M., Russ, T.C., Ryan, K.A., Olesen, M.S., Schultheiss, U.T., Selvin, E., Siddiqui, M.K., Teumer, A., and Medici, M.

Abstract

Contains fulltext : 304858.pdf (Publisher’s version ) (Open Access), To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.

Published
2024

12. The post-collisional late Variscan ferroan granites of southern Sardinia (Italy): Inferences for inhomogeneity of lower crust

Author

Conte A.M.[1], Cuccuru S.[2], D'Antonio M.[3, Naitza S.[5], Oggiano G.[2], Secchi F.[2, Casini L.[2], Cifelli F.[7], Conte, Aida Maria, Cuccuru, Stefano, D'Antonio, Massimo, Naitza, Stefano, Oggiano, Giacomo, Secchi, Francesco, Casini, Leonardo, Cifelli, Francesca, Conte, A. M., Cuccuru, S., D’Antonio, M., Naitza, S., Oggiano, G., Secchi, G. F., Casini, L., and Cifelli, F.

Subjects
010504 meteorology & atmospheric sciences, Crustal sources, Geochemistry, Late Variscan granites, Granite rock suites, Crustal sources, Mineral chemistry, Magnetic susceptibility, Sr Nd Pb isotopes, engineering.material, 010502 geochemistry & geophysics, 01 natural sciences, Magnetic susceptibility, Petrography, Geochemistry and Petrology, Sr-Nd-Pb isotope, Mineral chemistry, Petrology, Crustal source, Granite rock-suites, Late-Variscan granites, 0105 earth and related environmental sciences, Felsic, Late-Variscan granite, Partial melting, Geology, Crust, Sr-Nd-Pb isotopes, Batholith, Magmatism, engineering, Mafic, Granite rock-suite, Ilmenite
Abstract

The post-collisional late Variscan magmatism of Sardinia-Corsica batholith attained a peak at about 290 Ma. In southern Sardinia, in the frontal part of the Variscan orogenic wedge, this magmatism is represented by three suites of granitoids, here defined as GS1, GS2 and GS3. GS1, GS2 and GS3 are slightly peraluminous and F-bearing granitoids; GS1 and GS3 granites show in addition a ferroan character, whereas GS2 rocks range from magnesian to ferroan, from granodiorites to leucogranites. From magnetic susceptibility data, GS1 and GS2 belong to the ilmenite series, whereas GS3 is a slightly oxidized rock-suite plotting on the ilmenite/magnetite series boundary. Each rock-suite shows distinctive characters, in terms of petrography, petrochemistry, rock associations, as well as metallogenic signature of the related fluids. The distinction among rock-suite types is made on the basis of both mafic and characteristic accessory minerals. Siderophyllitic dark mica as the only mafic phase, and accessory xenotime (Y) characterize the GS1 rocks; GS2 mineral associations include biotite ± hornblende + allanite + magnetite; GS3 rocks show an association of hastingsite + annite + allanite + magnetite. Chemical variations in the studied samples suggest different magmatic evolution of independent magmas. Pb, Sr and Nd isotopic data constrain the origin of magmas to lower crustal sources. Chemical composition of rocks and dark micas meet those of liquids experimentally obtained by low degrees of partial melting of different meta-igneous deep crustal sources, felsic for GS1 rock-types and more mafic for GS3 rock-types. GS1 intrusions show granophile-type (Sn-W-Mo) metallogenic signatures, very low magnetic susceptibility, and Nd model ages (referred to the Depleted Mantle - T DM ) of 2.3 Ga, coherent with a possible derivation from an old (early Proterozoic-Neoarchean), reduced and weathered basement, tectonically buried under Variscan covers. A definite deep crustal inhomogeneity is mirrored by GS3 granites, whose compositional and isotopic features indicate a younger (Nd model age: 1.6 Ga) tonalitic amphibolite source. Overall, the peculiarities of the studied granitoids suggest further compositional differences in the deep crust between southern and northern portion of the Sardinia-Corsica Variscan transect. Late Variscan lithospheric delamination appears as the most reliable mechanism that may have determined the high thermal regime that triggered partial melting of the crust. The close field association, at 290 Ma, of tholeiitic dike swarms and ferroan granitoids, supports this inference.

Published
2017

13. Genome-wide association study of circulating interleukin 6 levels identifies novel loci

Author

Ahluwalia, T.S., Prins, B.P., Abdollahi, M., Armstrong, N.J., Aslibekyan, S., Bain, L., Jefferis, B., Baumert, J., Beekman, M., Ben-Shlomo, Y., Bis, J.C., Mitchell, B.D., Geus, E. de, Delgado, G.E., Marek, D., Eriksson, J., Kajantie, E., Kanoni, S., Kemp, J.P., Lu, C., Marioni, R.E., McLachlan, S., Milaneschi, Y., Nolte, I.M., Petrelis, A.M., Porcu, E., Sabater-Lleal, M., Naderi, E., Seppala, I., Shah, T., Singhal, G., Standl, M., Teumer, A., Thalamuthu, A., Thiering, E., Trompet, S., Ballantyne, C.M., Benjamin, E.J., Casas, J.P., Toben, C., Dedoussis, G., Deelen, J., Durda, P., Engmann, J., Feitosa, M.F., Grallert, H., Hammarstedt, A., Harris, S.E., Homuth, G., Hottenga, J.J., Jalkanen, S., Jamshidi, Y., Jawahar, M.C., Jess, T., Kivimaki, M., Kleber, M.E., Lahti, J., Liu, Y., Marques-Vidal, P., Mellstrom, D., Mooijaart, S.P., Muller-Nurasyid, M., Penninx, B., Revez, J.A., Rossing, P., Raikkonen, K., Sattar, N., Scharnagl, H., Sennblad, B., Silveira, A., St Pourcain, B., Timpson, N.J., Trollor, J., Dongen, J. van, Heemst, D. van, Visvikis-Siest, S., Vollenweider, P., Volker, U., Waldenberger, M., Willemsen, G., Zabaneh, D., Morris, R.W., Arnett, D.K., Baune, B.T., Boomsma, D.I., Chang, Y.P.C., Deary, I.J., Deloukas, P., Eriksson, J.G., Evans, D.M., Ferreira, M.A., Gaunt, T., Gudnason, V., Hamsten, A., Heinrich, J., Hingorani, A., Humphries, S.E., Jukema, J.W., Koenig, W., Kumari, M., Kutalik, Z., Lawlor, D.A., Lehtimaki, T., Marz, W., Mather, K.A., Naitza, S., Nauck, M., Ohlsson, C., Price, J.F., Raitakari, O., Rice, K., Sachdev, P.S., Slagboom, E., Sorensen, T.I.A., Spector, T., Stacey, D., Stathopoulou, M.G., Tanaka, T., Wannamethee, S.G., Whincup, P., Rotter, J.I., Dehghan, A., Boerwinkle, E., Psaty, B.M., Snieder, H., Alizadeh, B.Z., and CHARGE Inflammation Working Grp

Abstract

Interleukin 6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67428 (n(discovery)=52654 and n(replication)=14774) individuals of European ancestry. The inverse variance fixed effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on chromosome (Chr) 2q14, (P-combined=1.8x10(-11)), HLA-DRB1/DRB5 rs660895 on Chr6p21 (P-combined=1.5x10(-10)) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (P-combined=1.2x10(-122)). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology.

Published
2021

14. Genome-Wide Association Study of Circulating Interleukin 6 Levels Identifies Novel Loci

Author

Ahluwalia, TS, Prins, BP, Abdollahi, M, Armstrong, NJ, Aslibekyan, S, Bain, L, Jefferis, B, Baumert, J, Beekman, M, Ben-Shlomo, Y, Bis, JC, Mitchell, BD, de Geus, E, Delgado, GE, Marek, D, Eriksson, J, Kajantie, E, Kanoni, S, Kemp, JP, Lu, C, Marioni, RE, McLachlan, S, Milaneschi, Y, Nolte, IM, Petrelis, AM, Porcu, E, Sabater-Lleal, M, Naderi, E, Seppälä, I, Shah, T, Singhal, G, Standl, M, Teumer, A, Thalamuthu, A, Thiering, E, Trompet, S, Ballantyne, CM, Benjamin, EJ, Casas, JP, Toben, C, Dedoussis, G, Deelen, J, Durda, P, Engmann, J, Feitosa, MF, Grallert, H, Hammarstedt, A, Harris, SE, Homuth, G, Hottenga, J-J, Jalkanen, S, Jamshidi, Y, Jawahar, MC, Jess, T, Kivimaki, M, Kleber, ME, Lahti, J, Liu, Y, Marques-Vidal, P, Mellström, D, Mooijaart, SP, Müller-Nurasyid, M, Penninx, B, Revez, JA, Rossing, P, Räikkönen, K, Sattar, N, Scharnagl, H, Sennblad, B, Silveira, A, Pourcain, BS, Timpson, NJ, Trollor, J, CHARGE Inflammation Working Group, van Dongen, J, Van Heemst, D, Visvikis-Siest, S, Vollenweider, P, Völker, U, Waldenberger, M, Willemsen, G, Zabaneh, D, Morris, RW, Arnett, DK, Baune, BT, Boomsma, DI, Chang, Y-PC, Deary, IJ, Deloukas, P, Eriksson, JG, Evans, DM, Ferreira, MA, Gaunt, T, Gudnason, V, Hamsten, A, Heinrich, J, Hingorani, A, Humphries, SE, Jukema, JW, Koeing, W, Kumari, M, Kutalik, Z, Lawlor, DA, Lehtimäki, T, März, W, Mather, K, Naitza, S, Nauck, M, Ohlsson, C, Price, JF, Raitakari, O, Rice, K, Sachdev, PS, Slagboom, E, Sørensen, TIA, Spector, T, Stacey, D, Stathopoulou, MG, Tanaka, T, Wannamethee, SG, Whincup, P, Rotter, JI, Dehghan, A, Boerwinkle, E, Psaty, BM, Snieder, H, and Alizadeh, BZ

Abstract

Interleukin-6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery, and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67 428 (ndiscovery = 52 654 and nreplication = 14 774) individuals of European ancestry. The inverse variance fixed-effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on Chromosome (Chr) 2q14, (pcombined = 1.8 × 10-11), HLA-DRB1/DRB5 rs660895 on Chr6p21 (pcombined = 1.5 × 10-10) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (pcombined = 1.2 × 10-122). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology.

Published
2021

16. GWAS of thyroid stimulating hormone highlights pleiotropic effects and inverse association with thyroid cancer

Author

Zhou, W. (Wei), Brumpton, B. (Ben), Kabil, O. (Omer), Gudmundsson, J. (Julius), Thorleifsson, G. (Gudmar), Weinstock, J. (Josh), Zawistowski, M. (Matthew), Nielsen, J.B. (Jonas B.), Chaker, L. (Layal), Medici, M. (Marco), Teumer, A. (Alexander), Naitza, S. (Silvia), Sanna, S. (Serena), Schultheiss, U.T. (Ulla T.), Cappola, A.R. (Anne), Karjalainen, J. (Juha), Kurki, M. (Mitja), Oneka, M. (Morgan), Taylor, P.N. (Peter N.), Fritsche, L.G. (Lars), Graham, S.E. (Sarah E.), Wolford, B.N. (Brooke N.), Overton, W. (William), Rasheed, H. (Humaira), Haug, E.B. (Eirin B.), Gabrielsen, M.E. (Maiken Elvestad), Skogholt, A.H. (Anne Heidi), Surakka, I. (Ida), Davey Smith, G. (George), Pandit, A. (Anita), Roychowdhury, T. (Tanmoy), Hornsby, W.E. (Whitney E.), Jonasson, J.G. (Jon G.), Senter, L. (Leigha), Liyanarachchi, S. (Sandya), Ringel, M.D. (Matthew D.), Xu, L. (Li), Kiemeney, L.A. (Lambertus A.), He, H. (Hao), Netea-Maier, R.T. (Romana), Mayordomo, J.I. (José), Plantinga, T.S. (Theo S.), Hrafnkelsson, J. (Jon), Hjartarson, H. (Hannes), Sturgis, E.M. (Erich M.), Palotie, A. (Aarno), Daly, M.J. (Mark), Citterio, C.E. (Cintia E.), Arvan, P. (Peter), Brummett, C.M. (Chad M.), Boehnke, M. (Michael), La Chapelle, A. (Albert) de, Stefansson, K. (Kari), Hveem, K. (Kristian), Willer, C.J. (Cristen), Asvold, B.O. (Bjorn O.), Zhou, W. (Wei), Brumpton, B. (Ben), Kabil, O. (Omer), Gudmundsson, J. (Julius), Thorleifsson, G. (Gudmar), Weinstock, J. (Josh), Zawistowski, M. (Matthew), Nielsen, J.B. (Jonas B.), Chaker, L. (Layal), Medici, M. (Marco), Teumer, A. (Alexander), Naitza, S. (Silvia), Sanna, S. (Serena), Schultheiss, U.T. (Ulla T.), Cappola, A.R. (Anne), Karjalainen, J. (Juha), Kurki, M. (Mitja), Oneka, M. (Morgan), Taylor, P.N. (Peter N.), Fritsche, L.G. (Lars), Graham, S.E. (Sarah E.), Wolford, B.N. (Brooke N.), Overton, W. (William), Rasheed, H. (Humaira), Haug, E.B. (Eirin B.), Gabrielsen, M.E. (Maiken Elvestad), Skogholt, A.H. (Anne Heidi), Surakka, I. (Ida), Davey Smith, G. (George), Pandit, A. (Anita), Roychowdhury, T. (Tanmoy), Hornsby, W.E. (Whitney E.), Jonasson, J.G. (Jon G.), Senter, L. (Leigha), Liyanarachchi, S. (Sandya), Ringel, M.D. (Matthew D.), Xu, L. (Li), Kiemeney, L.A. (Lambertus A.), He, H. (Hao), Netea-Maier, R.T. (Romana), Mayordomo, J.I. (José), Plantinga, T.S. (Theo S.), Hrafnkelsson, J. (Jon), Hjartarson, H. (Hannes), Sturgis, E.M. (Erich M.), Palotie, A. (Aarno), Daly, M.J. (Mark), Citterio, C.E. (Cintia E.), Arvan, P. (Peter), Brummett, C.M. (Chad M.), Boehnke, M. (Michael), La Chapelle, A. (Albert) de, Stefansson, K. (Kari), Hveem, K. (Kristian), Willer, C.J. (Cristen), and Asvold, B.O. (Bjorn O.)

Abstract

Thyroid stimulating hormone (TSH) is critical for normal development and metabolism. To better understand the genetic contribution to TSH levels, we conduct a GWAS meta-analysis at 22.4 million genetic markers in up to 119,715 individuals and identify 74 genome-wide significant loci for TSH, of which 28 are previously unreported. Functional experiments show that the thyroglobulin protein-altering variants P118L and G67S impact thyroglobulin secretion. Phenome-wide association analysis in the UK Biobank demonstrates the pleiotropic effects of TSH-associated variants and a polygenic score for higher TSH levels is associated with a reduced risk of thyroid cancer in the UK Biobank and three other independent studies. Two-sample Mendelian randomization using TSH index variants as instrumental variables suggests a protective effect of higher TSH levels (indicating lower thyroid function) on risk of thyroid cancer and goiter. Our findings highlight the pleiotropic effects of TSH-associated variants on thyroid function and growth of malignant and benign thyroid tumors.

Published
2020
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17. Long-lasting mantle-derived activity and evolution in the late-Variscan Sàrrabus igneous complex (SE Sardinia, Italy)

Author

Conte, A. M., Cuccuru, S., D'Antonio, M., Naitza, S., Oggiano, G., Secchi, F. (2018), Società Geologica Italiana, Conte, A. M., Cuccuru, S., D’Antonio, M., Naitza, S., Oggiano, G., and Secchi, F.

Subjects
Igneous massif, Sardina-Corsica, Magma differentiation, syn-plutonic mafic dikes, variable stress field, batholith
Abstract

The Sàrrabus igneous massif (400 km2), belongs to the Sardinia-Corsica batholith and is a late-Variscan post-collisional intrusive complex occurring in the frontal part of the orogenic wedge. It is mostly made up of Bt-granodiorites and Bt-monzogranites predating late leucogranites. This complex experienced the contribution of several mafic mantle-derived pulses for about 20 Ma. Mafic intrusions are dominated by Hb-gabbroic rocks cropping out for 10 km along the southern coastline, as stretched and dismembered dikes arranged on a general WNW/ESE trend. They were emplaced as forced intrusions -mostly hosted into Bt-granodiorite- surrounded by discontinuous shells of foliated quartz-diorite/tonalite grading to Hb-granodiorite. Mechanical interaction between different terms of a gabbro/tonalitic association is represented by lobate plagioclase xenocrysts and quartz-diorite fragments in gabbroic rocks. Variations in plastic rheological interaction are testified by gabbroic/quartz-diorite interdigitations or by large (up to 4 m) cuspate fragments of mafic dikes into Hbgranodiorites lobes. Mafic magmas experienced (polybaric?) low-pressure crystal/liquid fractionation at depth, as documented by decametric angular fragments of stratified olivine-two pyroxene-bearing gabbroic rocks. Progressive water saturation of mafic magmas is commonly documented by ortho- and clinopyroxene relic cores rimmed by diffuse amphibole growth. A possible plagioclase + amphibole fractionation path (

Published
2018

18. Evaluating the controls on the origin of tourmaline-bearing rocks in peraluminous and metaluminous systems: examples from Late-Variscan magmatism of Sardinia (Italy)

Author

Andreozzi, G. B., Bosi, F., Conte, A. M., Cuccuru, S., and Naitza, S.

Subjects
tourmaline, magmatic system, Sardinia
Abstract

In magmatic systems, intensive and compositional parameters are commonly invoked to account for tourmaline saturation in the melt. To model the frequent occurrence of tourmaline-bearing rocks associated with peraluminous intrusions, a large emphasis is typically given to Al2O3 saturation index of magmas (ASI> 1.2). However, a major role played by partial melting processes of B-bearing protoliths has been recently proposed to control the B saturation of anatectic melts. In Sardinia, a B-bearing rock series is documented by tourmaline occurrence in the late-crystallization stages of Late-Variscan intrusives related to the older magmatic peak (305-300 Ma). Conversely, intrusives related to the younger magmatic peak (290-280 Ma) are almost made up of F-bearing granites and lack in tourmaline. The controls on the origin of tourmaline were investigated by comparing mineral assemblages from Mandrolisai (central Sardinia) and Arbus (SW Sardinia) igneous massifs, both emplaced at shallow depths in the frontal zone of a nappe edifice. Mandrolisai igneous massif results as a single pulse of a granodioritic metaluminous magma, while Arbus is a composite pluton made of several pulses reaching a peraluminous character in leucogranitic rock-units (ASI < 1.16). Arbus magmas belong to a true ilmenite series while the Mandrolisai straddles the ilmenite/magnetite field series. In Mandrolisai, tourmaline occurs in layered aplite/pegmatite dikes and in thin tourmalinite veins in roof pendants of metamorphic rocks, close to the western contacts of the intrusion. In Arbus, tourmaline occurs in pegmatitic layers, in granophyric dykes and within metamorphic country rock. The inclusive crystal-chemical study of tourmaline samples from pegmatites of both plutons highlights a comparable evolution from shorlitic to foititic composition; in addition, crystals from tourmalinite veins of Mandrolisai and dispersed within the country rock of Arbus show a dravitic composition, mostly related to magma-country rock interaction. The main differences regard the Mg-richest and Al-poorest composition of Mandrolisai tourmaline, which reflect a different composition of granodioritic magma, more magnesian and less aluminous (ASI = 0.93-0.95) The whole data sets of the two plutons allow the reconstruction of the same crystallization path: T = 650-400 °C, P

Published
2019

19. Application of in-situ gamma-ray spectrometry to mapping intrusive complexes: examples from Sàrrabus igneous massif (SE Sardinia, Italy)

Author

Cuccuru, S., Conte, A. M., Naitza, S., Oggiano, G., Secchi, F., and Puccini, A.

Subjects
gamma ray spectrometry, Sarrabus igneous massif, Sardinia
Abstract

The in-situ gamma ray spectrometry is a sound and proven technique to map radioelements variations of rocks. Recently this technique has been satisfactorily used in geological surveys of the Variscan basement and late-Variscan plutons belonging to the northern part of the Sardinia batholith, dominated by coalescing intrusions of peraluminous monzogranites, which are hardly distinguishable each other in the field. In addition, at the scale of the entire Sardinia batholith, good contact exposures between intrusive units are often obliterated by the occurrence of colluvium covers and by regolith. This leads to frequent mapping issues, as the geological definition of single intrusive units when common field indicators (e. g. magmatic flow, unconformities and chilled margins), usually used to constrain the anatomy of plutons, are not applicable or conclusive. The Sàrrabus igneous massif (400 km2) is a multi-pulse, composite intrusive complex recording a complicated history marked by coalescing intrusions dominated by granodiorites, monzogranites and leucogranites. A continuous contribution of mantle pulses is documented by several mafic episodes -predating or coeval to-, granodiorites. Mantle-derived pulses were followed by diffuse diking, which resulted in several generations of mainly NNW mafic dike swarms. Peraluminous character is only recognized for garnet-bearing two mica granites occurring as minor intrusions and NE trending acidic dikes. In this scenario, some unsolved issues mainly regard the discrimination within different rock-units of similar composition and geological style.The geo-statistical processing of 100 in-situ measurements of 40K, 232Th and 238 U abundances by mean of a gamma-ray spectrometer -equipped with a 1-liter NaI (Tl) scintillator generated three radionuclides maps, which mirror seven intrusive units improving the previous geological reconstruction. Indeed, the combined geological-petrographical and radiological mapping, allows to better constrain the anatomy and the emplacement sequence of the several intrusions in Sàrrabus massif. In detail, from older to younger, main intrusive units are: Burcèi Unit (gabbrotonalites) > Monte Cresia Unit (granodiorites grading to monzogranites) > Cala Regina Unit (granodiorites with mafic septa and monzosyenites) > Monte Maria Unit (peraluminous leucogranites) > Bruncu Nicola Bove Unit (monzogranites grading to leucogranites) > San Priamo Unit (leucogranites) > Monte Sette Fratelli Unit (monzogranites grading to leucogranites). In this way, an early southward growth model for the Sàrrabus igneous massif can be envisaged for granodioritic intrusions; it seems to be controlled by mixing of different crustal melts and mantle batches, along an E-W crustal shear zone. Overall, the surveys performed in the Sàrrabus igneous massif has confirmed as the portable gamma-ray spectrometer is a useful tool to improve field surveys when conventional geological discrimination techniques are not conclusive.

Published
2019

20. Emplacement of the huge Zn-Pb-Ag vein system of Montevecchio, Arburese (SW Sardinia): geological, mineralogical, geothermometric and isotopic inputs towards a new metallogenic model

Author

Moroni, M., Naitza, S., Lattanzi, P., Ruggieri, G., Aquino, A., Caruso, S., and Ferrari, E.

Subjects
Metallogenic model, Sardinia, Arburese, Montevecchio, Zn-Pb-Ag vein system
Abstract

Geological, mineralogical, geothermometric and isotopic inputs towards a new metallogenic model for the emplacement of the huge Zn-Pb-Ag vein system of Montevecchio, Arburese (SW Sardinia).

Published
2018
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21. Architecture, emplacement mode of late-Variscan plutons and their relationships with post-collisional phases: examples from Sàrrabus igneous massif (SE Sardinia, Italy)

Author

Conte, A. M., Naitza, S., Oggiano, G., Secchi, F., Cuccuru, S., Casini, L., and Puccini, A.

Subjects
Igneous massif, Sardina-Corsica, batholith
Abstract

Sardinia is a southern transect of the Variscan Belt intruded by many post-collisional coalescent igneous complexes forming the Sardinia-Corsica batholith. The Sardinian portion of this batholith grew during two main magmatic peaks, clustered at about 305 Ma (Old Magmatic Peak, OMP) and at 285 Ma (Young Magmatic Peak, YMP); plutons intruding different parts of the Variscan basement show different geological styles in terms of emplacement style and mantle/crust contribution. The Sàrrabus igneous massif (400 km2) is a multi-pulse, composite intrusive complex, occurring in the frontal part of the orogenic wedge in SE Sardinia. It records a complex evolutive history, consisting of several intrusive sequences. The coalescing intrusion are roughly elongated WNW, with sharp sub-vertical contacts. Schematically, the Sàrrabus igneous massif consists of a southern part dominated by granodioritic up to monzogranitic rocks related to the OMP, and a northern part made up of leucogranitic rocks referred to the YMP. A continuous contribution of mantle pulses is documented mostly in the OMP. Early mantle-derived products are gabbrotonalites exposed close to the northern contacts with the host basement; these mafic intrusives occur as a homogeneous sills or masses dismembered by YMP leucogranites. A further mafic pulse consists of disrupted sub-vertical, syn-plutonic, gabbroic dikes associated with quartz-diorites, which are well exposed along the southern Sàrrabus coastline. These dismembered dykes, scattered within the granodiorite with a general WNW trend. The mafic activity evolved towards diffuse diking (mainly spessartites), which resulted in several NNW trending dike swarms that crosscut the OMP intrusives with cool, sharp contact. Spessartites are the latest episodes referable to the OMP; they are frequently associated to metaluminous and garnet-bearing peraluminous felsic dikes and stocks.A subsequent generation of olivine plagioclase -phyric mafic dikes with tholeiitic signature crosscut the YMP.The resulting scenario suggests a northward growth of Sàrrabus igneous massif, accompanied by (1) bimodal character of this magmatism; (2) increasing contribution of crustal melts and a progressive decrease of mantle/crust interactions; (3) progressive shallower emplacement conditions. The late NS trending dyke swarm, which emplaced in dilational jogs accounts for a NS ?1 stress field affecting the entire southern Sardinia lithosphere during Permian time. Conversely, the emplacement of the OMS intrusions and the related dismembered mafic bodies and dykes were controlled by a possible WNW transtensional kinematics. On a larger scale, this variability of stress field, joined to crustal inhomogeneity, could account for different mechanisms of magma ascent and decompression melting that result in different rock associations and petrological signatures.

Published
2018
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22. Il campo filoniano a Ni-Co del Distretto Arburese (Sardegna SW): caratterizzazione geo-giacimentologica e mineralogico-geochimica di una risorsa di interesse strategico

Author

Moroni, M., Naitza, S., Ferrari, E., Magnani, L., Oggiano, G., and Secchi, F.

Subjects
Sardegna, campo filoniano, Distretto Arburese, geo-giacimentologia
Abstract

La caratterizzazione geo-giacimentologica e mineralogico-geochimica di una risorsa di interesse strategico per il campo filoniano a Ni-Co del Distretto Arburese (Sardegna SW).

Published
2018

23. The Ni-Co-As-Ag-Bi-rich hydrothermal vein ores of the Arburese district (SW Sardinia, Italy): mineralogical and geochemical characterization of possible sources for critical metals

Author

Moroni, M., Naitza, S., Magnani, L., Ferrari, E., Oggiano, G., and Secchi, F.

Subjects
Arburese district, critical metals, ores, Sardinia, hydrothermal vein
Abstract

Mineralogical and geochemical characterization of possible sources for critical metals in the Ni-Co-As-Ag-Bi-rich hydrothermal vein ores of the Arburese district (SW Sardinia, Italy)

Published
2018
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25. Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation

Author

Teumer, A. (Alexander), Chaker, L. (Layal), Groeneweg, S. (Stefan), Li, Y. (Yong), Di Munno, C. (Celia), Barbieri, C. (Caterina), Schultheiss, U.T. (Ulla T.), Traglia, M. (Michela), Ahluwalia, T.S. (Tarunveer Singh), Akiyama, M. (Masato), Appel, E.V.R. (Emil Vincent R.), Arking, D.E. (Dan), Arnold, A.M. (Alice), Astrup, A. (Arne), Beekman, M. (Marian), Beilby, J.P. (John), Bekaert, S. (Sofie), Boerwinkle, E. (Eric), Brown, S.J. (Stephen), Buyzere, M. (Marc) de, Campbell, P.J. (Purdey J.), Ceresini, G. (Graziano), Cerqueira, C. (Charlotte), Cucca, F. (Francesco), Deary, I.J. (Ian), Deelen, J. (Joris), Eckardt, K.-U. (Kai-Uwe), Ekici, A.B. (Arif B.), Hagen, K. (Knut), Ferrrucci, L. (Luigi), Fiers, T. (Tom), Fiorillo, E. (Edoardo), Ford, I. (Ian), Fox, C.S. (Caroline), Fuchsberger, C. (Christian), Galesloot, T.E. (Tessel), Gieger, C. (Christian), Gögele, M. (Martin), Grandi, A. (Alessandro) de, Grarup, N. (Niels), Greiser, K.H. (Karin Halina), Haljas, K. (Kadri), Hansen, T. (Torben), Harris, S.E. (Sarah), Heemst, D. (Diana) van, Heijer, M. (Martin) den, Hicks, A.A. (Andrew A.), Hollander, W. (Wouter) den, Homuth, G. (Georg), Hui, J. (Jennie), Ikram, M.A. (Arfan), Ittermann, T. (Till), Jensen, R.A. (Richard A.), Jing, J. (Jiaojiao), Jukema, J.W. (Jan Wouter), Kajantie, E. (Eero), Kamatani, Y. (Yoichiro), Kasbohm, E. (Elisa), Kaufman, J.-M. (Jean-Marc), Kiemeney, L.A. (Lambertus A.), Kloppenburg, M. (Margreet), Kronenberg, F. (Florian), Kubo, M. (Michiaki), Lahti, J. (Jari), Lapauw, B. (Bruno), Li, S. (Shuo), Liewald, D.C.M. (David C. M.), Alizadeh, B.Z. (Behrooz), Boezen, H.M. (Marike), Franke, L. (Lude), van der Harst, P. (Pim), Navis, G. (Gerjan), Rots, M.G. (M.), Snieder, H. (Harold), Swertz, M.A. (Morris A.), Wijmenga, C. (Cisca), Lim, E.M. (Ee Mun), Linneberg, A. (Allan), Marina, M. (Michela), Mascalzoni, D. (Deborah), Matsuda, K. (Koichi), Medenwald, D. (Daniel), Meisinger, C. (Christa), Meulenbelt, I. (Ingrid), Meyer, T. (Thorsten), Meyer zu Schwabedissen, H.E. (Henriette E.), Mikolajczyk, R. (Rafael), Moed, H. (Heleen), Netea-Maier, R.T. (Romana), Nolte, I.M. (Ilja), Okada, Y. (Yukinori), Pala, M. (Mauro), Penninx, B.W.J.H., Pedersen, O. (Oluf), Petersmann, A. (Astrid), Porcu, E. (Eleonora), Postmus, D. (Douwe), Pramstaller, P.P. (Peter Paul), Psaty, B.M. (Bruce), Ramos, Y.F.M. (Yolande F. M.), Rawal, R. (Rajesh), Redmond, P. (Paul), Richards, J.B. (Brent), Rietzschel, E.R. (Ernst), Rivadeneira Ramirez, F. (Fernando), Roef, G.L. (Greet), Rotter, J.I. (Jerome I.), Sala, C. (Cinzia), Schlessinger, D. (David), Selvin, E. (Elizabeth), Slagboom, P.E. (Eline), Soranzo, N. (Nicole), Sørensen, T.I.A. (Thorkild), Spector, T.D. (Timothy), Starr, J.M. (John), Stott, D.J. (David. J.), Taes, Y.E. (Youri), Taliun, D. (Daniel), Tanaka, T. (Toshiko), Thuesen, L. (Leif), Tiller, D. (Daniel), Toniolo, D. (Daniela), Uitterlinden, A.G. (Andre G.), Visser, W.E. (Edward), Walsh, J.P. (John P.), Wilson, S.G. (Scott), Wolffenbuttel, B.H.R. (Bruce), Yang, Q. (Qiong Fang), Zheng, H.-F. (Hou-Feng), Cappola, A.R. (Anne), Peeters, R.P. (Robin), Naitza, S. (Silvia), Völzke, H. (Henry), Sanna, S. (Serena), Köttgen, A. (Anna), Visser, T.J. (Theo), Medici, M. (Marco), Teumer, A. (Alexander), Chaker, L. (Layal), Groeneweg, S. (Stefan), Li, Y. (Yong), Di Munno, C. (Celia), Barbieri, C. (Caterina), Schultheiss, U.T. (Ulla T.), Traglia, M. (Michela), Ahluwalia, T.S. (Tarunveer Singh), Akiyama, M. (Masato), Appel, E.V.R. (Emil Vincent R.), Arking, D.E. (Dan), Arnold, A.M. (Alice), Astrup, A. (Arne), Beekman, M. (Marian), Beilby, J.P. (John), Bekaert, S. (Sofie), Boerwinkle, E. (Eric), Brown, S.J. (Stephen), Buyzere, M. (Marc) de, Campbell, P.J. (Purdey J.), Ceresini, G. (Graziano), Cerqueira, C. (Charlotte), Cucca, F. (Francesco), Deary, I.J. (Ian), Deelen, J. (Joris), Eckardt, K.-U. (Kai-Uwe), Ekici, A.B. (Arif B.), Hagen, K. (Knut), Ferrrucci, L. (Luigi), Fiers, T. (Tom), Fiorillo, E. (Edoardo), Ford, I. (Ian), Fox, C.S. (Caroline), Fuchsberger, C. (Christian), Galesloot, T.E. (Tessel), Gieger, C. (Christian), Gögele, M. (Martin), Grandi, A. (Alessandro) de, Grarup, N. (Niels), Greiser, K.H. (Karin Halina), Haljas, K. (Kadri), Hansen, T. (Torben), Harris, S.E. (Sarah), Heemst, D. (Diana) van, Heijer, M. (Martin) den, Hicks, A.A. (Andrew A.), Hollander, W. (Wouter) den, Homuth, G. (Georg), Hui, J. (Jennie), Ikram, M.A. (Arfan), Ittermann, T. (Till), Jensen, R.A. (Richard A.), Jing, J. (Jiaojiao), Jukema, J.W. (Jan Wouter), Kajantie, E. (Eero), Kamatani, Y. (Yoichiro), Kasbohm, E. (Elisa), Kaufman, J.-M. (Jean-Marc), Kiemeney, L.A. (Lambertus A.), Kloppenburg, M. (Margreet), Kronenberg, F. (Florian), Kubo, M. (Michiaki), Lahti, J. (Jari), Lapauw, B. (Bruno), Li, S. (Shuo), Liewald, D.C.M. (David C. M.), Alizadeh, B.Z. (Behrooz), Boezen, H.M. (Marike), Franke, L. (Lude), van der Harst, P. (Pim), Navis, G. (Gerjan), Rots, M.G. (M.), Snieder, H. (Harold), Swertz, M.A. (Morris A.), Wijmenga, C. (Cisca), Lim, E.M. (Ee Mun), Linneberg, A. (Allan), Marina, M. (Michela), Mascalzoni, D. (Deborah), Matsuda, K. (Koichi), Medenwald, D. (Daniel), Meisinger, C. (Christa), Meulenbelt, I. (Ingrid), Meyer, T. (Thorsten), Meyer zu Schwabedissen, H.E. (Henriette E.), Mikolajczyk, R. (Rafael), Moed, H. (Heleen), Netea-Maier, R.T. (Romana), Nolte, I.M. (Ilja), Okada, Y. (Yukinori), Pala, M. (Mauro), Penninx, B.W.J.H., Pedersen, O. (Oluf), Petersmann, A. (Astrid), Porcu, E. (Eleonora), Postmus, D. (Douwe), Pramstaller, P.P. (Peter Paul), Psaty, B.M. (Bruce), Ramos, Y.F.M. (Yolande F. M.), Rawal, R. (Rajesh), Redmond, P. (Paul), Richards, J.B. (Brent), Rietzschel, E.R. (Ernst), Rivadeneira Ramirez, F. (Fernando), Roef, G.L. (Greet), Rotter, J.I. (Jerome I.), Sala, C. (Cinzia), Schlessinger, D. (David), Selvin, E. (Elizabeth), Slagboom, P.E. (Eline), Soranzo, N. (Nicole), Sørensen, T.I.A. (Thorkild), Spector, T.D. (Timothy), Starr, J.M. (John), Stott, D.J. (David. J.), Taes, Y.E. (Youri), Taliun, D. (Daniel), Tanaka, T. (Toshiko), Thuesen, L. (Leif), Tiller, D. (Daniel), Toniolo, D. (Daniela), Uitterlinden, A.G. (Andre G.), Visser, W.E. (Edward), Walsh, J.P. (John P.), Wilson, S.G. (Scott), Wolffenbuttel, B.H.R. (Bruce), Yang, Q. (Qiong Fang), Zheng, H.-F. (Hou-Feng), Cappola, A.R. (Anne), Peeters, R.P. (Robin), Naitza, S. (Silvia), Völzke, H. (Henry), Sanna, S. (Serena), Köttgen, A. (Anna), Visser, T.J. (Theo), and Medici, M. (Marco)

Abstract

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves’ disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets.

Published
2018
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26. Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation

Author

Teumer, A, Chaker, Layal, Groeneweg, Stefan, Li, Yi, Di Munno, Celia, Barbieri, C, Schultheiss, UT, Traglia, M, Ahluwalia, TS, Akiyama, M, Appel, EVR, Arking, DE, Arnold, A, Astrup, A, Beekman, M, Beilby, JP, Bekaert, S, Boerwinkle, E, Brown, SJ, de Buyzere, M, Campbell, PJ, Ceresini, G, Cerqueira, C, Cucca, F, Deary, IJ, Deelen, J, Eckardt, KU, Ekici, AB, Eriksson, JG, Ferrrucci, L, Fiers, T, Fiorillo, E, Ford, I, Fox, CS, Fuchsberger, C, Galesloot, TE, Gieger, C, Gogele, M, De Grandi, A, Grarup, N, Greiser, KH, Haljas, K, Hansen, T, Harris, SE, van Heemst, D, Heijer, M, Hicks, AA, den Hollander, W, Homuth, G, Hui, JN, Ikram, Arfan, Ittermann, T, Jensen, RA, Jing, J, Jukema, JW, Kajalltie, E, Kamatani, Y, Kasbohm, E, Kaufman, JM, Kiemeney, LA, Kloppenburg, M, Kronenberg, F, Kubo, M, Lahti, J, Lapauw, B, Li, S, Liewald, DCM, Lim, EM, Linneberg, A, Marina, M, Mascalzoni, D, Matsuda, K, Medenwald, D, Meisinger, C, Meulenbelt, I, Meyer, T, zu Schwabedissen, HEM, Mikolajczyk, R, Moed, M, Netea-Maier, RT, Nolte, IM, Okadah, Y, Pala, M, Pattaro, C, Pedersen, O, Petersmann, A, Porcu, E, Postmus, I, Pramstaller, PP, Psaty, BM, Ramos, YFM, Rawal, R, Redmond, P, Richards, JB, Rietzschel, ER, Rivadeneira, Fernando, Roef, G, Rotter, JI, Sala, CF, Schlessinger, D, Selvin, E, Slagboom, PE (Eline), Soranzo, N, Sorensen, TIA, Spector, TD, Starr, JM, Stott, DJ, Taes, Y, Taliun, D, Tanaka, T, Thuesen, B, Tiller, D, Toniolo, D, Uitterlinden, André, Visser, Edward, Walsh, JP, Wilson, SG, Wolffenbuttel, BHR, Yang, Q, Zheng, HF, Cappola, A, Peeters, Robin, Naitza, S, Volzke, H, Sanna, S, Kottgen, A, Visser, Theo, Medici, Marco, Teumer, A, Chaker, Layal, Groeneweg, Stefan, Li, Yi, Di Munno, Celia, Barbieri, C, Schultheiss, UT, Traglia, M, Ahluwalia, TS, Akiyama, M, Appel, EVR, Arking, DE, Arnold, A, Astrup, A, Beekman, M, Beilby, JP, Bekaert, S, Boerwinkle, E, Brown, SJ, de Buyzere, M, Campbell, PJ, Ceresini, G, Cerqueira, C, Cucca, F, Deary, IJ, Deelen, J, Eckardt, KU, Ekici, AB, Eriksson, JG, Ferrrucci, L, Fiers, T, Fiorillo, E, Ford, I, Fox, CS, Fuchsberger, C, Galesloot, TE, Gieger, C, Gogele, M, De Grandi, A, Grarup, N, Greiser, KH, Haljas, K, Hansen, T, Harris, SE, van Heemst, D, Heijer, M, Hicks, AA, den Hollander, W, Homuth, G, Hui, JN, Ikram, Arfan, Ittermann, T, Jensen, RA, Jing, J, Jukema, JW, Kajalltie, E, Kamatani, Y, Kasbohm, E, Kaufman, JM, Kiemeney, LA, Kloppenburg, M, Kronenberg, F, Kubo, M, Lahti, J, Lapauw, B, Li, S, Liewald, DCM, Lim, EM, Linneberg, A, Marina, M, Mascalzoni, D, Matsuda, K, Medenwald, D, Meisinger, C, Meulenbelt, I, Meyer, T, zu Schwabedissen, HEM, Mikolajczyk, R, Moed, M, Netea-Maier, RT, Nolte, IM, Okadah, Y, Pala, M, Pattaro, C, Pedersen, O, Petersmann, A, Porcu, E, Postmus, I, Pramstaller, PP, Psaty, BM, Ramos, YFM, Rawal, R, Redmond, P, Richards, JB, Rietzschel, ER, Rivadeneira, Fernando, Roef, G, Rotter, JI, Sala, CF, Schlessinger, D, Selvin, E, Slagboom, PE (Eline), Soranzo, N, Sorensen, TIA, Spector, TD, Starr, JM, Stott, DJ, Taes, Y, Taliun, D, Tanaka, T, Thuesen, B, Tiller, D, Toniolo, D, Uitterlinden, André, Visser, Edward, Walsh, JP, Wilson, SG, Wolffenbuttel, BHR, Yang, Q, Zheng, HF, Cappola, A, Peeters, Robin, Naitza, S, Volzke, H, Sanna, S, Kottgen, A, Visser, Theo, and Medici, Marco

Published
2018

28. Pleiotropy among common genetic loci identified for cardiometabolic disorders and C-reactive protein

Author

Ligthart, S, De Vries, PS, Uitterlinden, AG, Hofman, A, Franco, OH, Chasman, DI, Dehghan, A, Dupuis, J, Barbalic, M, Bis, JC, Eiriksdottir, G, Lu, C, Pellikka, N, Wallaschofski, H, Kettunen, J, Henneman, P, Baumert, J, Strachan, DP, Fuchsberger, C, Vitart, V, Wilson, JF, Paré, G, Naitza, S, Rudock, ME, Surakka, I, De Geus, EJC, Alizadeh, BZ, Guralnik, JMD, Shuldiner, A, Tanaka, T, Zee, RYL, Schnabel, RB, Nambi, V, Kavousi, M, Ripatti, S, Nauck, M, Smith, NL, Smith, AV, Sundvall, J, Scheet, P, Liu, Y, Ruokonen, A, Rose, LM, Larson, MG, Hoogeveen, RC, Freimer, NB, Teumer, A, Tracy, RP, Launer, LJ, Buring, JE, Yamamoto, JF, Folsom, AR, Sijbrands, EJG, Pankow, J, Elliott, P, Keaney, JF, Sun, W, Sarin, AP, Fontes, JD, Badola, S, Astor, BC, Pouta, A, Werda, K, Greiser, KH, Kuss, O, Schwabedissen, HEMZ, Thiery, J, Jamshidi, Y, Nolte, IM, Soranzo, N, Spector, TD, Völzke, H, Parker, AN, Aspelund, T, Bates, D, Young, L, Tsui, K, Siscovick, DS, Guo, X, Rotter, JI, Uda, M, Schlessinger, D, Rudan, I, Hicks, AA, Penninx, BW, Thorand, B, Gieger, C, Coresh, J, Willemsen, G, Harris, TB, Järvelin, MR, Rice, K, Radke, D, Salomaa, V, Van Dijk, KW, Boerwinkle, E, Vasan, RS, Ferrucci, L, and Gibson, QD

Abstract

© 2015 Ligthart et al. Pleiotropic genetic variants have independent effects on different phenotypes. C-reactive protein (CRP) is associated with several cardiometabolic phenotypes. Shared genetic backgrounds may partially underlie these associations. We conducted a genome-wide analysis to identify the shared genetic background of inflammation and cardiometabolic phenotypes using published genome-wide association studies (GWAS). We also evaluated whether the pleiotropic effects of such loci were biological or mediated in nature. First, we examined whether 283 common variants identified for 10 cardiometabolic phenotypes in GWAS are associated with CRP level. Second, we tested whether 18 variants identified for serum CRP are associated with 10 cardiometabolic phenotypes. We used a Bonferroni corrected p-value of 1.1×10-04 (0.05/463) as a threshold of significance. We evaluated the independent pleiotropic effect on both phenotypes using individual level data from the Women Genome Health Study. Evaluating the genetic overlap between inflammation and cardiometabolic phenotypes, we found 13 pleiotropic regions. Additional analyses showed that 6 regions (APOC1, HNF1A, IL6R, PPP1R3B, HNF4A and IL1F10) appeared to have a pleiotropic effect on CRP independent of the effects on the cardiometabolic phenotypes. These included loci where individuals carrying the risk allele for CRP encounter higher lipid levels and risk of type 2 diabetes. In addition, 5 regions (GCKR, PABPC4, BCL7B, FTO and TMEM18) had an effect on CRP largely mediated through the cardiometabolic phenotypes. In conclusion, our results show genetic pleiotropy among inflammation and cardiometabolic phenotypes. In addition to reverse causation, our data suggests that pleiotropic genetic variants partially underlie the association between CRP and cardiometabolic phenotypes.

Published
2015

30. Pleiotropy among common genetic loci identified for cardiometabolic disorders and C-reactive protein

Author

Ligthart, S. (Symen), Vries, P.S. (Paul) de, Uitterlinden, A.G. (André), Hofman, A. (Albert), Franco, O.H. (Oscar), Chasman, D.I. (Daniel), Dehghan, A. (Abbas), Dupuis, J. (Josée), Barbalic, M. (maja), Bis, J.C. (Joshua), Eiriksdottir, G. (Gudny), Lu, C. (Chen), Pellikka, N. (Niina), Wallaschofski, H. (Henri), Kettunen, J. (Johannes), Henneman, P. (Peter), Baumert, J. (Jens), Strachan, D.P. (David), Fuchsberger, C. (Christian), Vitart, V. (Veronique), Wilson, J.F. (James F), Paré, G. (Guillaume), Naitza, S. (Silvia), Rudock, M.E. (Megan), Surakka, I. (Ida), Geus, E.J.C. (Eco) de, Alizadeh, B.Z. (Behrooz), Guralnik, J.M. (Jack), Shuldiner, A.R. (Alan), Tanaka, T. (Toshiko), Zee, R.Y.L. (Robert), Schnabel, R.B. (Renate), Nambi, V. (Vijay), Kavousi, M. (Maryam), Ripatti, S. (Samuli), Nauck, M. (Matthias), Smith, N.L. (Nicholas L.), Smith, A.V. (Albert Vernon), Sundvall, J. (Jouko), Scheet, P. (Paul), Liu, Y. (YongMei), Ruokonen, A. (Aimo), Rose, L.M. (Lynda), Larson, M.G. (Martin), Hoogeveen, R.C. (Ron), Freimer, N.B. (Nelson), Teumer, A. (Alexander), Tracy, R.P. (Russell), Launer, L.J. (Lenore), Buring, J.E. (Julie), Yamamoto, J.F. (Jennifer), Folsom, A.R. (Aaron), Sijbrands, E.J.G. (Eric), Pankow, J.S. (James), Elliott, P. (Paul), Keaney, J.F. (John), Sun, W. (Wei), Sarin, A.-P., Fontes, M. (Michel), Badola, S. (Sunita), Astor, B.C. (Brad), Pouta, A. (Anneli), Werda, K. (Karl), Greiser, K.H. (Karin Halina), Kuss, O. (Oliver), Schwabedissen, H.E.M.Z. (Henriette E. Meyer Zu), Thiery, J. (Joachim), Jamshidi, Y. (Yalda), Nolte, I.M. (Ilja M.), Soranzo, N. (Nicole), Spector, T.D. (Timothy), Völzke, H. (Henry), Parker, A.N. (Alex), Aspelund, T. (Thor), Bates, D. (David), Young, L. (Lauren), Tsui, K. (Kim), Siscovick, D.S. (David), Guo, X. (Xiuqing), Rotter, J.I. (Jerome I.), Uda, M. (Manuela), Schlessinger, D., Rudan, I. (Igor), Hicks, A.A. (Andrew), Penninx, B.W.J.H. (Brenda), Thorand, B. (Barbara), Gieger, C. (Christian), Coresh, J. (Josef), Willemsen, G.A.H.M. (Gonneke), Harris, T.B. (Tamara), Jarvelin, M.-R. (Marjo-Riitta), Rice, K.M. (Kenneth), Radke, D. (Dörte), Salomaa, V. (Veikko), Willems van Dijk, J.A.P. (Ko), Boerwinkle, E.A. (Eric), Vasan, R.S. (Ramachandran Srini), Ferrucci, L. (Luigi), Gibson, Q. (Quince), Bandinelli, S. (Stefania), Snieder, H. (Harold), Boomsma, D.I. (Dorret), Xiao, X. (Xiangjun), Campbell, H. (Harry), Hayward, C. (Caroline), Pramstaller, P.P. (Peter Paul), Duijn, C.M. (Cornelia) van, Peltonen, L. (Leena Johanna), Psaty, B.M. (Bruce), Gudnason, V. (Vilmundur), Ridker, P.M. (Paul), Homuth, G. (Georg), Koenig, W. (Wolfgang), Ballantyne, C. (Christie), Witteman, J.C.M. (Jacqueline), Benjamin, E.J. (Emelia), Perola, M. (Markus), Chasman., D.I. (Daniel I.), Ligthart, S. (Symen), Vries, P.S. (Paul) de, Uitterlinden, A.G. (André), Hofman, A. (Albert), Franco, O.H. (Oscar), Chasman, D.I. (Daniel), Dehghan, A. (Abbas), Dupuis, J. (Josée), Barbalic, M. (maja), Bis, J.C. (Joshua), Eiriksdottir, G. (Gudny), Lu, C. (Chen), Pellikka, N. (Niina), Wallaschofski, H. (Henri), Kettunen, J. (Johannes), Henneman, P. (Peter), Baumert, J. (Jens), Strachan, D.P. (David), Fuchsberger, C. (Christian), Vitart, V. (Veronique), Wilson, J.F. (James F), Paré, G. (Guillaume), Naitza, S. (Silvia), Rudock, M.E. (Megan), Surakka, I. (Ida), Geus, E.J.C. (Eco) de, Alizadeh, B.Z. (Behrooz), Guralnik, J.M. (Jack), Shuldiner, A.R. (Alan), Tanaka, T. (Toshiko), Zee, R.Y.L. (Robert), Schnabel, R.B. (Renate), Nambi, V. (Vijay), Kavousi, M. (Maryam), Ripatti, S. (Samuli), Nauck, M. (Matthias), Smith, N.L. (Nicholas L.), Smith, A.V. (Albert Vernon), Sundvall, J. (Jouko), Scheet, P. (Paul), Liu, Y. (YongMei), Ruokonen, A. (Aimo), Rose, L.M. (Lynda), Larson, M.G. (Martin), Hoogeveen, R.C. (Ron), Freimer, N.B. (Nelson), Teumer, A. (Alexander), Tracy, R.P. (Russell), Launer, L.J. (Lenore), Buring, J.E. (Julie), Yamamoto, J.F. (Jennifer), Folsom, A.R. (Aaron), Sijbrands, E.J.G. (Eric), Pankow, J.S. (James), Elliott, P. (Paul), Keaney, J.F. (John), Sun, W. (Wei), Sarin, A.-P., Fontes, M. (Michel), Badola, S. (Sunita), Astor, B.C. (Brad), Pouta, A. (Anneli), Werda, K. (Karl), Greiser, K.H. (Karin Halina), Kuss, O. (Oliver), Schwabedissen, H.E.M.Z. (Henriette E. Meyer Zu), Thiery, J. (Joachim), Jamshidi, Y. (Yalda), Nolte, I.M. (Ilja M.), Soranzo, N. (Nicole), Spector, T.D. (Timothy), Völzke, H. (Henry), Parker, A.N. (Alex), Aspelund, T. (Thor), Bates, D. (David), Young, L. (Lauren), Tsui, K. (Kim), Siscovick, D.S. (David), Guo, X. (Xiuqing), Rotter, J.I. (Jerome I.), Uda, M. (Manuela), Schlessinger, D., Rudan, I. (Igor), Hicks, A.A. (Andrew), Penninx, B.W.J.H. (Brenda), Thorand, B. (Barbara), Gieger, C. (Christian), Coresh, J. (Josef), Willemsen, G.A.H.M. (Gonneke), Harris, T.B. (Tamara), Jarvelin, M.-R. (Marjo-Riitta), Rice, K.M. (Kenneth), Radke, D. (Dörte), Salomaa, V. (Veikko), Willems van Dijk, J.A.P. (Ko), Boerwinkle, E.A. (Eric), Vasan, R.S. (Ramachandran Srini), Ferrucci, L. (Luigi), Gibson, Q. (Quince), Bandinelli, S. (Stefania), Snieder, H. (Harold), Boomsma, D.I. (Dorret), Xiao, X. (Xiangjun), Campbell, H. (Harry), Hayward, C. (Caroline), Pramstaller, P.P. (Peter Paul), Duijn, C.M. (Cornelia) van, Peltonen, L. (Leena Johanna), Psaty, B.M. (Bruce), Gudnason, V. (Vilmundur), Ridker, P.M. (Paul), Homuth, G. (Georg), Koenig, W. (Wolfgang), Ballantyne, C. (Christie), Witteman, J.C.M. (Jacqueline), Benjamin, E.J. (Emelia), Perola, M. (Markus), and Chasman., D.I. (Daniel I.)

Abstract

Pleiotropic genetic variants have independent effects on different phenotypes. C-reactive protein (CRP) is associated with several cardiometabolic phenotypes. Shared genetic backgrounds may partially underlie these associations. We conducted a genome-wide analysis to identify the shared genetic background of inflammation and cardiometabolic phenotypes using published genome-wide association studies (GWAS). We also evaluated whether the pleiotropic effects of such loci were biological or mediated in nature. First, we examined whether 283 common variants identified for 10 cardiometabolic phenotypes in GWAS are associated with CRP level. Second, we tested whether 18 variants identified for serum CRP are associated with 10 cardiometabolic phenotypes. We used a Bonferroni corrected p-value of 1.1×10-04 (0.05/463) as a threshold of significance. We evaluated the independent pleiotropic effect on both phenotypes using individual level data from the Women Genome Health Study. Evaluating the genetic overlap between inflammation and cardiometabolic phenotypes, we found 13 pleiotropic regions. Additional analyses showed that 6 regions (APOC1, HNF1A, IL6R, PPP1R3B, HNF4A and IL1F10) appeared to have a pleiotropic effect on CRP independent of the effects on the cardiometabolic phenotypes. These included loci where individuals carrying the risk allele for CRP encounter higher lipid levels and risk of type 2 diabetes. In addition, 5 regions (GCKR, PABPC4, BCL7B, FTO and TMEM18) had an effect on CRP largely mediated through the cardiometabolic phenotypes. In conclusion, our results show genetic pleiotropy among inflammation and cardiometabolic phenotypes. In addition to reverse causation, our data suggests that pleiotropic genetic variants partially underlie the association between CRP and cardiometabolic phenotypes.

Published
2015
Full Text
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31. Whole-genome sequence-based analysis of thyroid function.

Author

Taylor, PN, Porcu, E, Chew, S, Campbell, PJ, Traglia, M, Brown, SJ, Mullin, BH, Shihab, HA, Min, J, Walter, K, Memari, Y, Huang, J, Barnes, MR, Beilby, JP, Charoen, P, Danecek, P, Dudbridge, F, Forgetta, V, Greenwood, C, Grundberg, E, Johnson, AD, Hui, J, Lim, EM, McCarthy, S, Muddyman, D, Panicker, V, Perry, JRB, Bell, JT, Yuan, W, Relton, C, Gaunt, T, Schlessinger, D, Abecasis, G, Cucca, F, Surdulescu, GL, Woltersdorf, W, Zeggini, E, Zheng, H-F, Toniolo, D, Dayan, CM, Naitza, S, Walsh, JP, Spector, T, Davey Smith, G, Durbin, R, Richards, JB, Sanna, S, Soranzo, N, Timpson, NJ, Wilson, SG, UK0K Consortium, Taylor, PN, Porcu, E, Chew, S, Campbell, PJ, Traglia, M, Brown, SJ, Mullin, BH, Shihab, HA, Min, J, Walter, K, Memari, Y, Huang, J, Barnes, MR, Beilby, JP, Charoen, P, Danecek, P, Dudbridge, F, Forgetta, V, Greenwood, C, Grundberg, E, Johnson, AD, Hui, J, Lim, EM, McCarthy, S, Muddyman, D, Panicker, V, Perry, JRB, Bell, JT, Yuan, W, Relton, C, Gaunt, T, Schlessinger, D, Abecasis, G, Cucca, F, Surdulescu, GL, Woltersdorf, W, Zeggini, E, Zheng, H-F, Toniolo, D, Dayan, CM, Naitza, S, Walsh, JP, Spector, T, Davey Smith, G, Durbin, R, Richards, JB, Sanna, S, Soranzo, N, Timpson, NJ, Wilson, SG, and UK0K Consortium

Abstract

Normal thyroid function is essential for health, but its genetic architecture remains poorly understood. Here, for the heritable thyroid traits thyrotropin (TSH) and free thyroxine (FT4), we analyse whole-genome sequence data from the UK10K project (N=2,287). Using additional whole-genome sequence and deeply imputed data sets, we report meta-analysis results for common variants (MAF≥1%) associated with TSH and FT4 (N=16,335). For TSH, we identify a novel variant in SYN2 (MAF=23.5%, P=6.15 × 10(-9)) and a new independent variant in PDE8B (MAF=10.4%, P=5.94 × 10(-14)). For FT4, we report a low-frequency variant near B4GALT6/SLC25A52 (MAF=3.2%, P=1.27 × 10(-9)) tagging a rare TTR variant (MAF=0.4%, P=2.14 × 10(-11)). All common variants explain ≥20% of the variance in TSH and FT4. Analysis of rare variants (MAF<1%) using sequence kernel association testing reveals a novel association with FT4 in NRG1. Our results demonstrate that increased coverage in whole-genome sequence association studies identifies novel variants associated with thyroid function.

Published
2015

33. Microbial Diversity of Bacteria Involved in Biomineralization Processes in Mine-Impacted Freshwaters

Author

Flavia Tasso, Nicola Rigonat, Salvatore Vacca, Patrizia Paganin, Anna Rosa Sprocati, Chiara Alisi, Pier Andrea Marras, Stefano Naitza, Dario Fancello, Maria Rita Montereali, Daniela Medas, Elisabetta Dore, Giovanni De Giudici, Paganin, P., Alisi, C., Dore, E., Fancello, D., Marras, P. A., Medas, D., Montereali, M. R., Naitza, S., Rigonat, N., Sprocati, A. R., Tasso, F., Vacca, S., and De Giudici, G.

Subjects
Microbiology (medical), Pollutant, next generation sequencing, biology, Chemistry, Microorganism, Desulfovibrionaceae, biology.organism_classification, biomineralization, Microbiology, QR1-502, Bioremediation, bioremediation, Environmental chemistry, microbial diversity, sulfate-reducing bacteria, Desulfosporosinus, mine waters, Sulfate-reducing bacteria, Zn sulfide precipitates, heavy metals, Bacteria, Original Research, Biomineralization
Abstract

In order to increase the knowledge about geo-bio interactions in extreme metal-polluted mine waters, we combined microbiological, mineralogical, and geochemical analyses to study the indigenous sulfate-reducing bacteria (SRB) involved in the heavy metal (HM) biomineralization processes occurring in Iglesiente and Arburese districts (SW Sardinia, Italy). Anaerobic cultures from sediments of two different mining-affected streams of this regional framework were enriched and analyzed by 16S rRNA next-generation sequencing (NGS) technique, showing sequences closely related to SRB classified in taxa typical of environments with high concentrations of metals (Desulfovibrionaceae, Desulfosporosinus). Nevertheless, the most abundant genera found in our samples did not belong to the traditional SRB groups (i.e., Rahnella, Acinetobacter). The bio-precipitation process mediated by these selected cultures was assessed by anaerobic batch tests performed with polluted river water showing a dramatic (more than 97%) Zn decrease. Scanning electron microscopy (SEM) analysis revealed the occurrence of Zn sulfide with tubular morphology, suggesting a bacteria-mediated bio-precipitation. The inocula represent two distinct communities of microorganisms, each adapted to peculiar environmental conditions. However, both the communities were able to use pollutants in their metabolism and tolerating HMs by detoxification mechanisms. The Zn precipitation mediated by the different enriched cultures suggests that SRB inocula selected in this study have great potentialities for the development of biotechnological techniques to reduce contaminant dispersion and for metal recovery.

Published
2021

34. Whole-genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles.

Author

Huffman JE, Nicholas J, Hahn J, Heath AS, Raffield LM, Yanek LR, Brody JA, Thibord F, Almasy L, Bartz TM, Bielak LF, Bowler RP, Carrasquilla GD, Chasman DI, Chen MH, Emmert DB, Ghanbari M, Haessler J, Hottenga JJ, Kleber ME, Le NQ, Lee J, Lewis JP, Li-Gao R, Luan J, Malmberg AL, Mangino M, Marioni R, Martinez-Perez A, Pankratz N, Polasek O, Richmond A, Rodriguez BAT, Rotter JI, Steri M, Suchon P, Trompet S, Weiss S, Zare M, Auer PL, Cho M, Christofidou P, Davies G, de Geus EJ, Deleuze JF, Delgado GE, Ekunwe L, Faraday N, Gogele M, Greinacher A, Gao H, Howard TE, Joshi PK, Kilpeläinen TO, Lahti J, Linneberg A, Naitza S, Noordam R, Vergés FP, Rich SS, Rosendaal FR, Rudan I, Ryan KA, Souto JCC, van Rooij FJA, Wang H, Zhao W, Becker L, Beswick A, Brown MR, Cade B, Campbell H, Cho K, Crapo J, Curran J, de Maat MPM, Doyle MF, Elliott P, Floyd JS, Fuchsberger C, Grarup N, Guo X, Harris S, Hou L, Kolcic I, Kooperberg C, Menni C, Nauck M, O'Connell JR, Orru V, Psaty BM, Räikkönen K, Smith JA, Soria JM, Stott D, van Hylckama Vlieg A, Watkins H, Willemsen G, Wilson PW, Ben-Shlomo Y, Blangero J, Boomsma D, Cox SR, Dehghan A, Eriksson JG, Fiorillo E, Fornage M, Hansen T, Hayward C, Ikram MA, Jukema JW, Kardia S, Lange L, Maerz W, Mathias R, Mitchell BD, Mook-Kanamori DO, Morange PE, Pedersen O, Pramstaller PP, Redline S, Reiner AP, Ridker PM, Silverman EK, Spector TD, Volker U, Wareham N, Wilson J, Yao J, Tregouet DA, Johnson AD, Wolberg AS, de Vries PS, Sabater-Lleal M, Morrison A, and Smith NL

Abstract

Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI's Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10 percentage points higher in African populations. Three signals (SERPINA1, ZFP36L2, and TLR10) contain predicted deleterious missense variants. Two loci, SOCS3 and HPN, each harbor two conditionally distinct, non-coding variants. The gene region encoding the fibrinogen protein chain subunits (FGG;FGB;FGA), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common in African ancestry populations but extremely rare in Europeans (MAFAFR=0.180; MAFEUR=0.008). Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation., (Copyright © 2024 American Society of Hematology.)

Published
2024
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35. Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications.

Author

Sterenborg RBTM, Steinbrenner I, Li Y, Bujnis MN, Naito T, Marouli E, Galesloot TE, Babajide O, Andreasen L, Astrup A, Åsvold BO, Bandinelli S, Beekman M, Beilby JP, Bork-Jensen J, Boutin T, Brody JA, Brown SJ, Brumpton B, Campbell PJ, Cappola AR, Ceresini G, Chaker L, Chasman DI, Concas MP, Coutinho de Almeida R, Cross SM, Cucca F, Deary IJ, Kjaergaard AD, Echouffo Tcheugui JB, Ellervik C, Eriksson JG, Ferrucci L, Freudenberg J, Fuchsberger C, Gieger C, Giulianini F, Gögele M, Graham SE, Grarup N, Gunjača I, Hansen T, Harding BN, Harris SE, Haunsø S, Hayward C, Hui J, Ittermann T, Jukema JW, Kajantie E, Kanters JK, Kårhus LL, Kiemeney LALM, Kloppenburg M, Kühnel B, Lahti J, Langenberg C, Lapauw B, Leese G, Li S, Liewald DCM, Linneberg A, Lominchar JVT, Luan J, Martin NG, Matana A, Meima ME, Meitinger T, Meulenbelt I, Mitchell BD, Møllehave LT, Mora S, Naitza S, Nauck M, Netea-Maier RT, Noordam R, Nursyifa C, Okada Y, Onano S, Papadopoulou A, Palmer CNA, Pattaro C, Pedersen O, Peters A, Pietzner M, Polašek O, Pramstaller PP, Psaty BM, Punda A, Ray D, Redmond P, Richards JB, Ridker PM, Russ TC, Ryan KA, Olesen MS, Schultheiss UT, Selvin E, Siddiqui MK, Sidore C, Slagboom PE, Sørensen TIA, Soto-Pedre E, Spector TD, Spedicati B, Srinivasan S, Starr JM, Stott DJ, Tanaka T, Torlak V, Trompet S, Tuhkanen J, Uitterlinden AG, van den Akker EB, van den Eynde T, van der Klauw MM, van Heemst D, Verroken C, Visser WE, Vojinovic D, Völzke H, Waldenberger M, Walsh JP, Wareham NJ, Weiss S, Willer CJ, Wilson SG, Wolffenbuttel BHR, Wouters HJCM, Wright MJ, Yang Q, Zemunik T, Zhou W, Zhu G, Zöllner S, Smit JWA, Peeters RP, Köttgen A, Teumer A, and Medici M

Subjects
Humans, Genome-Wide Association Study, Triiodothyronine metabolism, Thyrotropin metabolism, Thyroid Gland metabolism, Thyroxine metabolism
Abstract

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases., (© 2024. The Author(s).)

Published
2024
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36. Whole genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles.

Author

Huffman JE, Nicolas J, Hahn J, Heath AS, Raffield LM, Yanek LR, Brody JA, Thibord F, Almasy L, Bartz TM, Bielak LF, Bowler RP, Carrasquilla GD, Chasman DI, Chen MH, Emmert DB, Ghanbari M, Haessle J, Hottenga JJ, Kleber ME, Le NQ, Lee J, Lewis JP, Li-Gao R, Luan J, Malmberg A, Mangino M, Marioni RE, Martinez-Perez A, Pankratz N, Polasek O, Richmond A, Rodriguez BA, Rotter JI, Steri M, Suchon P, Trompet S, Weiss S, Zare M, Auer P, Cho MH, Christofidou P, Davies G, de Geus E, Deleuze JF, Delgado GE, Ekunwe L, Faraday N, Gögele M, Greinacher A, He G, Howard T, Joshi PK, Kilpeläinen TO, Lahti J, Linneberg A, Naitza S, Noordam R, Paüls-Vergés F, Rich SS, Rosendaal FR, Rudan I, Ryan KA, Souto JC, van Rooij FJ, Wang H, Zhao W, Becker LC, Beswick A, Brown MR, Cade BE, Campbell H, Cho K, Crapo JD, Curran JE, de Maat MP, Doyle M, Elliott P, Floyd JS, Fuchsberger C, Grarup N, Guo X, Harris SE, Hou L, Kolcic I, Kooperberg C, Menni C, Nauck M, O'Connell JR, Orrù V, Psaty BM, Räikkönen K, Smith JA, Soria JM, Stott DJ, van Hylckama Vlieg A, Watkins H, Willemsen G, Wilson P, Ben-Shlomo Y, Blangero J, Boomsma D, Cox SR, Dehghan A, Eriksson JG, Fiorillo E, Fornage M, Hansen T, Hayward C, Ikram MA, Jukema JW, Kardia SL, Lange LA, März W, Mathias RA, Mitchell BD, Mook-Kanamori DO, Morange PE, Pedersen O, Pramstaller PP, Redline S, Reiner A, Ridker PM, Silverman EK, Spector TD, Völker U, Wareham N, Wilson JF, Yao J, Trégouët DA, Johnson AD, Wolberg AS, de Vries PS, Sabater-Lleal M, Morrison AC, and Smith NL

Abstract

Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI's Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10% higher in African populations. Three ( SERPINA1, ZFP36L2 , and TLR10) signals contain predicted deleterious missense variants. Two loci, SOCS3 and HPN , each harbor two conditionally distinct, non-coding variants. The gene region encoding the protein chain subunits ( FGG;FGB;FGA ), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common (MAF=0.180) in African reference panels but extremely rare (MAF=0.008) in Europeans. Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation., Key Points: Largest and most diverse genetic study of plasma fibrinogen identifies 54 regions (18 novel), housing 69 conditionally distinct variants (20 novel).Sufficient power achieved to identify signal driven by African population variant.Links to (1) liver enzyme, blood cell and lipid genetic signals, (2) liver regulatory elements, and (3) thrombotic and inflammatory disease.

Published
2023
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37. Author Correction: GWAS of thyroid stimulating hormone highlights the pleiotropic effects and inverse association with thyroid cancer.

Author

Zhou W, Brumpton B, Kabil O, Gudmundsson J, Thorleifsson G, Weinstock J, Zawistowski M, Nielsen JB, Chaker L, Medici M, Teumer A, Naitza S, Sanna S, Schultheiss UT, Cappola A, Karjalainen J, Kurki M, Oneka M, Taylor P, Fritsche LG, Graham SE, Wolford BN, Overton W, Rasheed H, Haug EB, Gabrielsen ME, Skogholt AH, Surakka I, Davey Smith G, Pandit A, Roychowdhury T, Hornsby WE, Jonasson JG, Senter L, Liyanarachchi S, Ringel MD, Xu L, Kiemeney LA, He H, Netea-Maier RT, Mayordomo JI, Plantinga TS, Hrafnkelsson J, Hjartarson H, Sturgis EM, Palotie A, Daly M, Citterio CE, Arvan P, Brummett CM, Boehnke M, de la Chapelle A, Stefansson K, Hveem K, Willer CJ, and Åsvold BO

Published
2021
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38. Microbial Diversity of Bacteria Involved in Biomineralization Processes in Mine-Impacted Freshwaters.

Author

Paganin P, Alisi C, Dore E, Fancello D, Marras PA, Medas D, Montereali MR, Naitza S, Rigonat N, Sprocati AR, Tasso F, Vacca S, and De Giudici G

Abstract

In order to increase the knowledge about geo-bio interactions in extreme metal-polluted mine waters, we combined microbiological, mineralogical, and geochemical analyses to study the indigenous sulfate-reducing bacteria (SRB) involved in the heavy metal (HM) biomineralization processes occurring in Iglesiente and Arburese districts (SW Sardinia, Italy). Anaerobic cultures from sediments of two different mining-affected streams of this regional framework were enriched and analyzed by 16S rRNA next-generation sequencing (NGS) technique, showing sequences closely related to SRB classified in taxa typical of environments with high concentrations of metals ( Desulfovibrionaceae , Desulfosporosinus ). Nevertheless, the most abundant genera found in our samples did not belong to the traditional SRB groups (i.e., Rahnella , Acinetobacter ). The bio-precipitation process mediated by these selected cultures was assessed by anaerobic batch tests performed with polluted river water showing a dramatic (more than 97%) Zn decrease. Scanning electron microscopy (SEM) analysis revealed the occurrence of Zn sulfide with tubular morphology, suggesting a bacteria-mediated bio-precipitation. The inocula represent two distinct communities of microorganisms, each adapted to peculiar environmental conditions. However, both the communities were able to use pollutants in their metabolism and tolerating HMs by detoxification mechanisms. The Zn precipitation mediated by the different enriched cultures suggests that SRB inocula selected in this study have great potentialities for the development of biotechnological techniques to reduce contaminant dispersion and for metal recovery., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Paganin, Alisi, Dore, Fancello, Marras, Medas, Montereali, Naitza, Rigonat, Sprocati, Tasso, Vacca and De Giudici.)

Published
2021
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39. Genome-wide association study of circulating interleukin 6 levels identifies novel loci.

Author

Ahluwalia TS, Prins BP, Abdollahi M, Armstrong NJ, Aslibekyan S, Bain L, Jefferis B, Baumert J, Beekman M, Ben-Shlomo Y, Bis JC, Mitchell BD, de Geus E, Delgado GE, Marek D, Eriksson J, Kajantie E, Kanoni S, Kemp JP, Lu C, Marioni RE, McLachlan S, Milaneschi Y, Nolte IM, Petrelis AM, Porcu E, Sabater-Lleal M, Naderi E, Seppälä I, Shah T, Singhal G, Standl M, Teumer A, Thalamuthu A, Thiering E, Trompet S, Ballantyne CM, Benjamin EJ, Casas JP, Toben C, Dedoussis G, Deelen J, Durda P, Engmann J, Feitosa MF, Grallert H, Hammarstedt A, Harris SE, Homuth G, Hottenga JJ, Jalkanen S, Jamshidi Y, Jawahar MC, Jess T, Kivimaki M, Kleber ME, Lahti J, Liu Y, Marques-Vidal P, Mellström D, Mooijaart SP, Müller-Nurasyid M, Penninx B, Revez JA, Rossing P, Räikkönen K, Sattar N, Scharnagl H, Sennblad B, Silveira A, Pourcain BS, Timpson NJ, Trollor J, van Dongen J, Van Heemst D, Visvikis-Siest S, Vollenweider P, Völker U, Waldenberger M, Willemsen G, Zabaneh D, Morris RW, Arnett DK, Baune BT, Boomsma DI, Chang YC, Deary IJ, Deloukas P, Eriksson JG, Evans DM, Ferreira MA, Gaunt T, Gudnason V, Hamsten A, Heinrich J, Hingorani A, Humphries SE, Jukema JW, Koenig W, Kumari M, Kutalik Z, Lawlor DA, Lehtimäki T, März W, Mather KA, Naitza S, Nauck M, Ohlsson C, Price JF, Raitakari O, Rice K, Sachdev PS, Slagboom E, Sørensen TIA, Spector T, Stacey D, Stathopoulou MG, Tanaka T, Wannamethee SG, Whincup P, Rotter JI, Dehghan A, Boerwinkle E, Psaty BM, Snieder H, and Alizadeh BZ

Subjects
Cohort Studies, Gene Expression Regulation, Genetic Loci, Genetic Predisposition to Disease, Humans, Interleukin-6 blood, Polymorphism, Single Nucleotide, White People genetics, Genome-Wide Association Study, HLA-DRB1 Chains genetics, Interleukin 1 Receptor Antagonist Protein genetics, Interleukin-1 genetics, Interleukin-6 genetics, Receptors, Interleukin-6 genetics
Abstract

Interleukin 6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67 428 (ndiscovery = 52 654 and nreplication = 14 774) individuals of European ancestry. The inverse variance fixed effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on chromosome (Chr) 2q14, (Pcombined = 1.8 × 10-11), HLA-DRB1/DRB5 rs660895 on Chr6p21 (Pcombined = 1.5 × 10-10) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (Pcombined = 1.2 × 10-122). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology., (© The Author(s) 2021. Published by Oxford University Press.)

Published
2021
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40. GWAS of thyroid stimulating hormone highlights pleiotropic effects and inverse association with thyroid cancer.

Author

Zhou W, Brumpton B, Kabil O, Gudmundsson J, Thorleifsson G, Weinstock J, Zawistowski M, Nielsen JB, Chaker L, Medici M, Teumer A, Naitza S, Sanna S, Schultheiss UT, Cappola A, Karjalainen J, Kurki M, Oneka M, Taylor P, Fritsche LG, Graham SE, Wolford BN, Overton W, Rasheed H, Haug EB, Gabrielsen ME, Skogholt AH, Surakka I, Davey Smith G, Pandit A, Roychowdhury T, Hornsby WE, Jonasson JG, Senter L, Liyanarachchi S, Ringel MD, Xu L, Kiemeney LA, He H, Netea-Maier RT, Mayordomo JI, Plantinga TS, Hrafnkelsson J, Hjartarson H, Sturgis EM, Palotie A, Daly M, Citterio CE, Arvan P, Brummett CM, Boehnke M, de la Chapelle A, Stefansson K, Hveem K, Willer CJ, and Åsvold BO

Subjects
Genetic Loci, Genetic Predisposition to Disease, Goiter genetics, Humans, Mendelian Randomization Analysis, Multifactorial Inheritance genetics, Mutation, Missense genetics, Phenotype, Physical Chromosome Mapping, Prevalence, Risk Factors, Thyroglobulin genetics, Thyroid Neoplasms epidemiology, Genetic Pleiotropy, Genome-Wide Association Study, Thyroid Neoplasms genetics, Thyrotropin genetics
Abstract

Thyroid stimulating hormone (TSH) is critical for normal development and metabolism. To better understand the genetic contribution to TSH levels, we conduct a GWAS meta-analysis at 22.4 million genetic markers in up to 119,715 individuals and identify 74 genome-wide significant loci for TSH, of which 28 are previously unreported. Functional experiments show that the thyroglobulin protein-altering variants P118L and G67S impact thyroglobulin secretion. Phenome-wide association analysis in the UK Biobank demonstrates the pleiotropic effects of TSH-associated variants and a polygenic score for higher TSH levels is associated with a reduced risk of thyroid cancer in the UK Biobank and three other independent studies. Two-sample Mendelian randomization using TSH index variants as instrumental variables suggests a protective effect of higher TSH levels (indicating lower thyroid function) on risk of thyroid cancer and goiter. Our findings highlight the pleiotropic effects of TSH-associated variants on thyroid function and growth of malignant and benign thyroid tumors.

Published
2020
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41. Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation.

Author

Teumer A, Chaker L, Groeneweg S, Li Y, Di Munno C, Barbieri C, Schultheiss UT, Traglia M, Ahluwalia TS, Akiyama M, Appel EVR, Arking DE, Arnold A, Astrup A, Beekman M, Beilby JP, Bekaert S, Boerwinkle E, Brown SJ, De Buyzere M, Campbell PJ, Ceresini G, Cerqueira C, Cucca F, Deary IJ, Deelen J, Eckardt KU, Ekici AB, Eriksson JG, Ferrrucci L, Fiers T, Fiorillo E, Ford I, Fox CS, Fuchsberger C, Galesloot TE, Gieger C, Gögele M, De Grandi A, Grarup N, Greiser KH, Haljas K, Hansen T, Harris SE, van Heemst D, den Heijer M, Hicks AA, den Hollander W, Homuth G, Hui J, Ikram MA, Ittermann T, Jensen RA, Jing J, Jukema JW, Kajantie E, Kamatani Y, Kasbohm E, Kaufman JM, Kiemeney LA, Kloppenburg M, Kronenberg F, Kubo M, Lahti J, Lapauw B, Li S, Liewald DCM, Lim EM, Linneberg A, Marina M, Mascalzoni D, Matsuda K, Medenwald D, Meisinger C, Meulenbelt I, De Meyer T, Meyer Zu Schwabedissen HE, Mikolajczyk R, Moed M, Netea-Maier RT, Nolte IM, Okada Y, Pala M, Pattaro C, Pedersen O, Petersmann A, Porcu E, Postmus I, Pramstaller PP, Psaty BM, Ramos YFM, Rawal R, Redmond P, Richards JB, Rietzschel ER, Rivadeneira F, Roef G, Rotter JI, Sala CF, Schlessinger D, Selvin E, Slagboom PE, Soranzo N, Sørensen TIA, Spector TD, Starr JM, Stott DJ, Taes Y, Taliun D, Tanaka T, Thuesen B, Tiller D, Toniolo D, Uitterlinden AG, Visser WE, Walsh JP, Wilson SG, Wolffenbuttel BHR, Yang Q, Zheng HF, Cappola A, Peeters RP, Naitza S, Völzke H, Sanna S, Köttgen A, Visser TJ, and Medici M

Subjects
2-Aminoadipate Transaminase genetics, Animals, Biological Transport, COS Cells, Chlorocebus aethiops, Genome-Wide Association Study, Humans, Hyperthyroidism genetics, Hyperthyroidism physiopathology, Hypothyroidism genetics, Hypothyroidism physiopathology, Polymorphism, Single Nucleotide, Risk Factors, Sodium-Phosphate Cotransporter Proteins, Type I genetics, Thyroid Gland metabolism, Thyroid Gland physiopathology, Thyroid Hormones metabolism, White People, 2-Aminoadipate Transaminase metabolism, Gene Expression Regulation genetics, Sodium-Phosphate Cotransporter Proteins, Type I metabolism, Thyroid Hormones genetics, Thyrotropin metabolism
Abstract

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets.

Published
2018
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42. 52 Genetic Loci Influencing Myocardial Mass.

Author

van der Harst P, van Setten J, Verweij N, Vogler G, Franke L, Maurano MT, Wang X, Mateo Leach I, Eijgelsheim M, Sotoodehnia N, Hayward C, Sorice R, Meirelles O, Lyytikäinen LP, Polašek O, Tanaka T, Arking DE, Ulivi S, Trompet S, Müller-Nurasyid M, Smith AV, Dörr M, Kerr KF, Magnani JW, Del Greco M F, Zhang W, Nolte IM, Silva CT, Padmanabhan S, Tragante V, Esko T, Abecasis GR, Adriaens ME, Andersen K, Barnett P, Bis JC, Bodmer R, Buckley BM, Campbell H, Cannon MV, Chakravarti A, Chen LY, Delitala A, Devereux RB, Doevendans PA, Dominiczak AF, Ferrucci L, Ford I, Gieger C, Harris TB, Haugen E, Heinig M, Hernandez DG, Hillege HL, Hirschhorn JN, Hofman A, Hubner N, Hwang SJ, Iorio A, Kähönen M, Kellis M, Kolcic I, Kooner IK, Kooner JS, Kors JA, Lakatta EG, Lage K, Launer LJ, Levy D, Lundby A, Macfarlane PW, May D, Meitinger T, Metspalu A, Nappo S, Naitza S, Neph S, Nord AS, Nutile T, Okin PM, Olsen JV, Oostra BA, Penninger JM, Pennacchio LA, Pers TH, Perz S, Peters A, Pinto YM, Pfeufer A, Pilia MG, Pramstaller PP, Prins BP, Raitakari OT, Raychaudhuri S, Rice KM, Rossin EJ, Rotter JI, Schafer S, Schlessinger D, Schmidt CO, Sehmi J, Silljé HHW, Sinagra G, Sinner MF, Slowikowski K, Soliman EZ, Spector TD, Spiering W, Stamatoyannopoulos JA, Stolk RP, Strauch K, Tan ST, Tarasov KV, Trinh B, Uitterlinden AG, van den Boogaard M, van Duijn CM, van Gilst WH, Viikari JS, Visscher PM, Vitart V, Völker U, Waldenberger M, Weichenberger CX, Westra HJ, Wijmenga C, Wolffenbuttel BH, Yang J, Bezzina CR, Munroe PB, Snieder H, Wright AF, Rudan I, Boyer LA, Asselbergs FW, van Veldhuisen DJ, Stricker BH, Psaty BM, Ciullo M, Sanna S, Lehtimäki T, Wilson JF, Bandinelli S, Alonso A, Gasparini P, Jukema JW, Kääb S, Gudnason V, Felix SB, Heckbert SR, de Boer RA, Newton-Cheh C, Hicks AA, Chambers JC, Jamshidi Y, Visel A, Christoffels VM, Isaacs A, Samani NJ, and de Bakker PIW

Subjects
Animals, Humans, Cardiomegaly genetics, Genetic Loci, Genome-Wide Association Study
Abstract

Background: Myocardial mass is a key determinant of cardiac muscle function and hypertrophy. Myocardial depolarization leading to cardiac muscle contraction is reflected by the amplitude and duration of the QRS complex on the electrocardiogram (ECG). Abnormal QRS amplitude or duration reflect changes in myocardial mass and conduction, and are associated with increased risk of heart failure and death., Objectives: This meta-analysis sought to gain insights into the genetic determinants of myocardial mass., Methods: We carried out a genome-wide association meta-analysis of 4 QRS traits in up to 73,518 individuals of European ancestry, followed by extensive biological and functional assessment., Results: We identified 52 genomic loci, of which 32 are novel, that are reliably associated with 1 or more QRS phenotypes at p < 1 × 10(-8). These loci are enriched in regions of open chromatin, histone modifications, and transcription factor binding, suggesting that they represent regions of the genome that are actively transcribed in the human heart. Pathway analyses provided evidence that these loci play a role in cardiac hypertrophy. We further highlighted 67 candidate genes at the identified loci that are preferentially expressed in cardiac tissue and associated with cardiac abnormalities in Drosophila melanogaster and Mus musculus. We validated the regulatory function of a novel variant in the SCN5A/SCN10A locus in vitro and in vivo., Conclusions: Taken together, our findings provide new insights into genes and biological pathways controlling myocardial mass and may help identify novel therapeutic targets., (Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Published
2016
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43. Genome sequencing elucidates Sardinian genetic architecture and augments association analyses for lipid and blood inflammatory markers.

Author

Sidore C, Busonero F, Maschio A, Porcu E, Naitza S, Zoledziewska M, Mulas A, Pistis G, Steri M, Danjou F, Kwong A, Ortega Del Vecchyo VD, Chiang CWK, Bragg-Gresham J, Pitzalis M, Nagaraja R, Tarrier B, Brennan C, Uzzau S, Fuchsberger C, Atzeni R, Reinier F, Berutti R, Huang J, Timpson NJ, Toniolo D, Gasparini P, Malerba G, Dedoussis G, Zeggini E, Soranzo N, Jones C, Lyons R, Angius A, Kang HM, Novembre J, Sanna S, Schlessinger D, Cucca F, and Abecasis GR

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Female, Founder Effect, Gene Frequency, Genetics, Population, Genotype, Geography, Haplotypes, Humans, Inflammation Mediators blood, Italy, Male, Middle Aged, Polymorphism, Single Nucleotide, Young Adult, Biomarkers blood, Genetic Variation, Genome, Human genetics, Genome-Wide Association Study methods, Lipids blood, Sequence Analysis, DNA methods
Abstract

We report ∼17.6 million genetic variants from whole-genome sequencing of 2,120 Sardinians; 22% are absent from previous sequencing-based compilations and are enriched for predicted functional consequences. Furthermore, ∼76,000 variants common in our sample (frequency >5%) are rare elsewhere (<0.5% in the 1000 Genomes Project). We assessed the impact of these variants on circulating lipid levels and five inflammatory biomarkers. We observe 14 signals, including 2 major new loci, for lipid levels and 19 signals, including 2 new loci, for inflammatory markers. The new associations would have been missed in analyses based on 1000 Genomes Project data, underlining the advantages of large-scale sequencing in this founder population.

Published
2015
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44. The association of thyroid peroxidase antibody risk loci with susceptibility to and phenotype of Graves' disease.

Author

Kuś A, Szymański K, Peeters RP, Miśkiewicz P, Porcu E, Pistis G, Sanna S, Naitza S, Płoski R, Medici M, and Bednarczuk T

Subjects
Adult, Female, Genetic Predisposition to Disease genetics, Genome-Wide Association Study, Graves Disease immunology, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide genetics, Autoantibodies genetics, Autoantigens immunology, Graves Disease genetics, Iodide Peroxidase immunology, Iron-Binding Proteins immunology
Abstract

Background: Despite great progress, the genetic basis of Graves' disease (GD) remains poorly understood. Recently, a population-based genomewide association study (GWAS) identified five novel loci (ATXN2/SH2B3, MAGI3, BACH2, TPO and KALRN) as significantly associated with the presence of thyroid peroxidase autoantibodies (TPOAbs), whereas several other loci showed suggestive association., Methods: In this study, we investigated 16 single nucleotide polymorphisms (SNPs) associated with TPOAbs for the association with susceptibility to and phenotype of GD in a cohort of 647 patients with GD and 769 controls from a Polish Caucasian population., Results: SNPs within/near HCP5 (rs3094228, P = 1·6 × 10(-12) , OR = 1·88), MAGI3 (rs1230666, P = 1·9 × 10(-5) , OR = 1·51) and ATXN2/SH2B3 (rs653178, P = 0·0015, OR = 1·28) loci were significantly associated with susceptibility to GD. Allele frequencies differed significantly in subgroups of patients with GD stratified by age of GD onset for HCP5 (P = 0·0014, OR = 1·50) and showed a suggestive difference for MAGI3 (P = 0·0035, OR = 1·50) SNPs. Although rs11675434 located near TPO showed no association with GD susceptibility, it was significantly associated with the presence of clinically evident Graves' ophthalmopathy (GO, P = 5·2 × 10(-5) , OR = 1·64), and this effect was independent from smoking status, age of GD onset and gender., Conclusions: This is the first study showing an association of the ATXN2/SH2B3 locus with susceptibility to GD. Furthermore, we observed a novel significant association within the HLA region at a SNP located near HCP5 and confirmed the association of the MAGI3 locus with GD susceptibility. HCP5 and MAGI3 SNPs were further correlated with age of GD onset. Finally, we identified TPO as a new susceptibility locus for GO., (© 2014 John Wiley & Sons Ltd.)

Published
2015
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45. Erratum: Whole-genome sequence-based analysis of thyroid function.

Author

Taylor PN, Porcu E, Chew S, Campbell PJ, Traglia M, Brown SJ, Mullin BH, Shihab HA, Min J, Walter K, Memari Y, Huang J, Barnes MR, Beilby JP, Charoen P, Danecek P, Dudbridge F, Forgetta V, Greenwood C, Grundberg E, Johnson AD, Hui J, Lim EM, McCarthy S, Muddyman D, Panicker V, Perry JR, Bell JT, Yuan W, Relton C, Gaunt T, Schlessinger D, Abecasis G, Cucca F, Surdulescu GL, Woltersdorf W, Zeggini E, Zheng HF, Toniolo D, Dayan CM, Naitza S, Walsh JP, Spector T, Smith GD, Durbin R, Richards JB, Sanna S, Soranzo N, Timpson NJ, and Wilson SG

Published
2015
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46. Whole-genome sequence-based analysis of thyroid function.

Author

Taylor PN, Porcu E, Chew S, Campbell PJ, Traglia M, Brown SJ, Mullin BH, Shihab HA, Min J, Walter K, Memari Y, Huang J, Barnes MR, Beilby JP, Charoen P, Danecek P, Dudbridge F, Forgetta V, Greenwood C, Grundberg E, Johnson AD, Hui J, Lim EM, McCarthy S, Muddyman D, Panicker V, Perry JR, Bell JT, Yuan W, Relton C, Gaunt T, Schlessinger D, Abecasis G, Cucca F, Surdulescu GL, Woltersdorf W, Zeggini E, Zheng HF, Toniolo D, Dayan CM, Naitza S, Walsh JP, Spector T, Davey Smith G, Durbin R, Richards JB, Sanna S, Soranzo N, Timpson NJ, and Wilson SG

Subjects
3',5'-Cyclic-AMP Phosphodiesterases genetics, 3',5'-Cyclic-AMP Phosphodiesterases metabolism, Cohort Studies, DNA Methylation genetics, Genetic Association Studies, Genomics methods, Humans, Synapsins genetics, Thyroid Gland metabolism, Thyrotropin genetics, Thyroxine genetics, United Kingdom, Synapsins metabolism, Thyroid Gland physiology, Thyrotropin metabolism, Thyroxine metabolism
Abstract

Normal thyroid function is essential for health, but its genetic architecture remains poorly understood. Here, for the heritable thyroid traits thyrotropin (TSH) and free thyroxine (FT4), we analyse whole-genome sequence data from the UK10K project (N=2,287). Using additional whole-genome sequence and deeply imputed data sets, we report meta-analysis results for common variants (MAF≥1%) associated with TSH and FT4 (N=16,335). For TSH, we identify a novel variant in SYN2 (MAF=23.5%, P=6.15 × 10(-9)) and a new independent variant in PDE8B (MAF=10.4%, P=5.94 × 10(-14)). For FT4, we report a low-frequency variant near B4GALT6/SLC25A52 (MAF=3.2%, P=1.27 × 10(-9)) tagging a rare TTR variant (MAF=0.4%, P=2.14 × 10(-11)). All common variants explain ≥20% of the variance in TSH and FT4. Analysis of rare variants (MAF<1%) using sequence kernel association testing reveals a novel association with FT4 in NRG1. Our results demonstrate that increased coverage in whole-genome sequence association studies identifies novel variants associated with thyroid function.

Published
2015
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47. No evidence for genome-wide interactions on plasma fibrinogen by smoking, alcohol consumption and body mass index: results from meta-analyses of 80,607 subjects.

Author

Baumert J, Huang J, McKnight B, Sabater-Lleal M, Steri M, Chu AY, Trompet S, Lopez LM, Fornage M, Teumer A, Tang W, Rudnicka AR, Mälarstig A, Hottenga JJ, Kavousi M, Lahti J, Tanaka T, Hayward C, Huffman JE, Morange PE, Rose LM, Basu S, Rumley A, Stott DJ, Buckley BM, de Craen AJ, Sanna S, Masala M, Biffar R, Homuth G, Silveira A, Sennblad B, Goel A, Watkins H, Müller-Nurasyid M, Rückerl R, Taylor K, Chen MH, de Geus EJ, Hofman A, Witteman JC, de Maat MP, Palotie A, Davies G, Siscovick DS, Kolcic I, Wild SH, Song J, McArdle WL, Ford I, Sattar N, Schlessinger D, Grotevendt A, Franzosi MG, Illig T, Waldenberger M, Lumley T, Tofler GH, Willemsen G, Uitterlinden AG, Rivadeneira F, Räikkönen K, Chasman DI, Folsom AR, Lowe GD, Westendorp RG, Slagboom PE, Cucca F, Wallaschofski H, Strawbridge RJ, Seedorf U, Koenig W, Bis JC, Mukamal KJ, van Dongen J, Widen E, Franco OH, Starr JM, Liu K, Ferrucci L, Polasek O, Wilson JF, Oudot-Mellakh T, Campbell H, Navarro P, Bandinelli S, Eriksson J, Boomsma DI, Dehghan A, Clarke R, Hamsten A, Boerwinkle E, Jukema JW, Naitza S, Ridker PM, Völzke H, Deary IJ, Reiner AP, Trégouët DA, O'Donnell CJ, Strachan DP, Peters A, and Smith NL

Subjects
Gene-Environment Interaction, Humans, Alcohol Drinking genetics, Body Mass Index, Fibrinogen metabolism, Genomics methods, Smoking genetics
Abstract

Plasma fibrinogen is an acute phase protein playing an important role in the blood coagulation cascade having strong associations with smoking, alcohol consumption and body mass index (BMI). Genome-wide association studies (GWAS) have identified a variety of gene regions associated with elevated plasma fibrinogen concentrations. However, little is yet known about how associations between environmental factors and fibrinogen might be modified by genetic variation. Therefore, we conducted large-scale meta-analyses of genome-wide interaction studies to identify possible interactions of genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentration. The present study included 80,607 subjects of European ancestry from 22 studies. Genome-wide interaction analyses were performed separately in each study for about 2.6 million single nucleotide polymorphisms (SNPs) across the 22 autosomal chromosomes. For each SNP and risk factor, we performed a linear regression under an additive genetic model including an interaction term between SNP and risk factor. Interaction estimates were meta-analysed using a fixed-effects model. No genome-wide significant interaction with smoking status, alcohol consumption or BMI was observed in the meta-analyses. The most suggestive interaction was found for smoking and rs10519203, located in the LOC123688 region on chromosome 15, with a p value of 6.2 × 10(-8). This large genome-wide interaction study including 80,607 participants found no strong evidence of interaction between genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentrations. Further studies are needed to yield deeper insight in the interplay between environmental factors and gene variants on the regulation of fibrinogen concentrations.

Published
2014
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