469 results on '"Laivuori, H."'
Search Results
2. The effect of low-dose aspirin on serum placental growth factor levels in a high-risk PREDO cohort
- Author
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Murtoniemi, K., Vahlberg, T., Hämäläinen, E., Kajantie, E., Pesonen, A.K., Räikkönen, K., Taipale, P., Villa, P.M., and Laivuori, H.
- Published
- 2018
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3. Prevention of gestational diabetes with a prepregnancy lifestyle intervention – findings from a randomized controlled trial
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Rönö K, Stach-Lempinen B, Eriksson JG, Pöyhönen-Alho M, Klemetti MM, Roine RP, Huvinen E, Andersson S, Laivuori H, Valkama A, Meinilä J, Kautiainen H, Tiitinen A, and Koivusalo SB
- Subjects
Preconception ,pregnancy ,obesity ,nutrition ,physical activity ,Gynecology and obstetrics ,RG1-991 - Abstract
Kristiina Rönö,1 Beata Stach-Lempinen,2 Johan Gunnar Eriksson,3,4 Maritta Pöyhönen-Alho,1 Miira Marjuska Klemetti,1,2,5 Risto Paavo Roine,6,7 Emilia Huvinen,1 Sture Andersson,8 Hannele Laivuori,6,9–11 Anita Valkama,3,4 Jelena Meinilä,3,4 Hannu Kautiainen,3,12 Aila Tiitinen,1 Saila Birgitta Koivusalo1 1Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Women’s Hospital, Helsinki, Finland; 2Department of Obstetrics and Gynecology, South Karelia Central Hospital, Lappeenranta, Finland; 3Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; 4Public Health Research Program, Folkhälsan Research Center, Helsinki, Finland; 5Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; 6Department of Health and Social Management, Research Centre for Comparative Effectiveness and Patient Safety, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland; 7Group Administration, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; 8University of Helsinki and Helsinki University Hospital, Children’s Hospital, Pediatric Research Center, Helsinki, Finland; 9Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland; 10Department of Obstetrics and Gynecology, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland; 11Department of Obstetrics and Gynecology, Tampere University Hospital, Tampere, Finland; 12Department of General Practice and Primary Health Care, University of Eastern Finland, Kuopio, Finland Purpose: Lifestyle intervention studies performed during pregnancy have shown inconsistent results in relation to prevention of gestational diabetes mellitus (GDM). Therefore, the aim of this study was to assess the effect of an intervention initiated already before pregnancy in prevention of GDM in high-risk women.Patients and methods: A randomized controlled trial was conducted in four Finnish maternity hospitals between the years 2008 and 2014. Altogether 228 high-risk women planning pregnancy were randomized to an intervention (n=116) or a control group (n=112). The risk factors were body mass index ≥30 kg/m2 (n=46), prior GDM (n=120), or both (n=62), without manifest diabetes at study inclusion. Trained study nurses provided individualized lifestyle counseling every 3 months in addition to a group session with a dietician. The control group received standard antenatal care. GDM was defined as one or more pathological glucose values in a 75 g 2-hour oral glucose tolerance test, performed between 12 and 16 weeks of gestation and if normal repeated between 24 and 28 weeks of gestation.Results: Within 12 months, 67% of the women (n=72) in the intervention group and 63% of the women (n=71) in the control group (p=0.84) became pregnant. The cumulative incidence of GDM among the women available for the final analyses was 60% (n=39/65) in the intervention group and 54% (n=34/63) in the control group (p=0.49). GDM was diagnosed already before 20 weeks of gestation in 60% (n=44/73) of the cases.Conclusion: The preconceptional lifestyle intervention applied in the present study did not reduce the incidence of GDM. Keywords: preconception, pregnancy, obesity, nutrition, physical activity
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- 2018
4. External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications (IPPIC) Network database: individual participant data meta-analysis
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Allotey, J, Whittle, R, Snell, K, Smuk, M, Townsend, R, von Dadelszen, P, Heazell, A, Magee, L, Smith, G, Sandall, J, Thilaganathan, B, Zamora, J, Riley, R, Khalil, A, Thangaratinam, S, Coomarasamy, A, Kwong, A, Savitri, A, Salvesen, K, Bhattacharya, S, Uiterwaal, C, Staff, A, Andersen, L, Olive, E, Redman, C, Sletner, L, Daskalakis, G, Macleod, M, Abdollahain, M, Ramirez, J, Masse, J, Audibert, F, Magnus, P, Jenum, A, Baschat, A, Ohkuchi, A, Mcauliffe, F, West, J, Askie, L, Mone, F, Farrar, D, Zimmerman, P, Smits, L, Riddell, C, Kingdom, J, van de Post, J, Illanes, S, Holzman, C, van Kuijk, S, Carbillon, L, Villa, P, Eskild, A, Chappell, L, Prefumo, F, Velauthar, L, Seed, P, van Oostwaard, M, Verlohren, S, Poston, L, Ferrazzi, E, Vinter, C, Nagata, C, Brown, M, Vollebregt, K, Takeda, S, Langenveld, J, Widmer, M, Saito, S, Haavaldsen, C, Carroli, G, Olsen, J, Wolf, H, Zavaleta, N, Eisensee, I, Vergani, P, Lumbiganon, P, Makrides, M, Facchinetti, F, Sequeira, E, Gibson, R, Ferrazzani, S, Frusca, T, Norman, J, Figueiro, E, Lapaire, O, Laivuori, H, Lykke, J, Conde-Agudelo, A, Galindo, A, Mbah, A, Betran, A, Herraiz, I, Trogstad, L, Steegers, E, Salim, R, Huang, T, Adank, A, Zhang, J, Meschino, W, Browne, J, Allen, R, Costa, F, Klipstein-Grobusch Browne, K, Crowther, C, Jorgensen, J, Forest, J, Rumbold, A, Mol, B, Giguere, Y, Kenny, L, Ganzevoort, W, Odibo, A, Myers, J, Yeo, S, Goffinet, F, Mccowan, L, Pajkrt, E, Teede, H, Haddad, B, Dekker, G, Kleinrouweler, E, Lecarpentier, E, Roberts, C, Groen, H, Skrastad, R, Heinonen, S, Eero, K, Anggraini, D, Souka, A, Cecatti, J, Monterio, I, Pillalis, A, Souza, R, Hawkins, L, Gabbay-Benziv, R, Crovetto, F, Figuera, F, Jorgensen, L, Dodds, J, Patel, M, Aviram, A, Papageorghiou, A, Khan, K, Allotey J., Whittle R., Snell K. I. E., Smuk M., Townsend R., von Dadelszen P., Heazell A. E. P., Magee L., Smith G. C. S., Sandall J., Thilaganathan B., Zamora J., Riley R. D., Khalil A., Thangaratinam S., Coomarasamy A., Kwong A., Savitri A. I., Salvesen K. A., Bhattacharya S., Uiterwaal C. S. P. M., Staff A. C., Andersen L. B., Olive E. L., Redman C., Sletner L., Daskalakis G., Macleod M., Abdollahain M., Ramirez J. A., Masse J., Audibert F., Magnus P. M., Jenum A. K., Baschat A., Ohkuchi A., McAuliffe F. M., West J., Askie L. M., Mone F., Farrar D., Zimmerman P. A., Smits L. J. M., Riddell C., Kingdom J. C., van de Post J., Illanes S. E., Holzman C., van Kuijk S. M. J., Carbillon L., Villa P. M., Eskild A., Chappell L., Prefumo F., Velauthar L., Seed P., van Oostwaard M., Verlohren S., Poston L., Ferrazzi E., Vinter C. A., Nagata C., Brown M., Vollebregt K. C., Takeda S., Langenveld J., Widmer M., Saito S., Haavaldsen C., Carroli G., Olsen J., Wolf H., Zavaleta N., Eisensee I., Vergani P., Lumbiganon P., Makrides M., Facchinetti F., Sequeira E., Gibson R., Ferrazzani S., Frusca T., Norman J. E., Figueiro E. A., Lapaire O., Laivuori H., Lykke J. A., Conde-Agudelo A., Galindo A., Mbah A., Betran A. P., Herraiz I., Trogstad L., Smith G. G. S., Steegers E. A. P., Salim R., Huang T., Adank A., Zhang J., Meschino W. S., Browne J. L., Allen R. E., Costa F. D. S., Klipstein-Grobusch Browne K., Crowther C. A., Jorgensen J. S., Forest J. -C., Rumbold A. R., Mol B. W., Giguere Y., Kenny L. C., Ganzevoort W., Odibo A. O., Myers J., Yeo S. A., Goffinet F., McCowan L., Pajkrt E., Teede H. J., Haddad B. G., Dekker G., Kleinrouweler E. C., LeCarpentier E., Roberts C. T., Groen H., Skrastad R. B., Heinonen S., Eero K., Anggraini D., Souka A., Cecatti J. G., Monterio I., Pillalis A., Souza R., Hawkins L. A., Gabbay-Benziv R., Crovetto F., Figuera F., Jorgensen L., Dodds J., Patel M., Aviram A., Papageorghiou A., Khan K., Allotey, J, Whittle, R, Snell, K, Smuk, M, Townsend, R, von Dadelszen, P, Heazell, A, Magee, L, Smith, G, Sandall, J, Thilaganathan, B, Zamora, J, Riley, R, Khalil, A, Thangaratinam, S, Coomarasamy, A, Kwong, A, Savitri, A, Salvesen, K, Bhattacharya, S, Uiterwaal, C, Staff, A, Andersen, L, Olive, E, Redman, C, Sletner, L, Daskalakis, G, Macleod, M, Abdollahain, M, Ramirez, J, Masse, J, Audibert, F, Magnus, P, Jenum, A, Baschat, A, Ohkuchi, A, Mcauliffe, F, West, J, Askie, L, Mone, F, Farrar, D, Zimmerman, P, Smits, L, Riddell, C, Kingdom, J, van de Post, J, Illanes, S, Holzman, C, van Kuijk, S, Carbillon, L, Villa, P, Eskild, A, Chappell, L, Prefumo, F, Velauthar, L, Seed, P, van Oostwaard, M, Verlohren, S, Poston, L, Ferrazzi, E, Vinter, C, Nagata, C, Brown, M, Vollebregt, K, Takeda, S, Langenveld, J, Widmer, M, Saito, S, Haavaldsen, C, Carroli, G, Olsen, J, Wolf, H, Zavaleta, N, Eisensee, I, Vergani, P, Lumbiganon, P, Makrides, M, Facchinetti, F, Sequeira, E, Gibson, R, Ferrazzani, S, Frusca, T, Norman, J, Figueiro, E, Lapaire, O, Laivuori, H, Lykke, J, Conde-Agudelo, A, Galindo, A, Mbah, A, Betran, A, Herraiz, I, Trogstad, L, Steegers, E, Salim, R, Huang, T, Adank, A, Zhang, J, Meschino, W, Browne, J, Allen, R, Costa, F, Klipstein-Grobusch Browne, K, Crowther, C, Jorgensen, J, Forest, J, Rumbold, A, Mol, B, Giguere, Y, Kenny, L, Ganzevoort, W, Odibo, A, Myers, J, Yeo, S, Goffinet, F, Mccowan, L, Pajkrt, E, Teede, H, Haddad, B, Dekker, G, Kleinrouweler, E, Lecarpentier, E, Roberts, C, Groen, H, Skrastad, R, Heinonen, S, Eero, K, Anggraini, D, Souka, A, Cecatti, J, Monterio, I, Pillalis, A, Souza, R, Hawkins, L, Gabbay-Benziv, R, Crovetto, F, Figuera, F, Jorgensen, L, Dodds, J, Patel, M, Aviram, A, Papageorghiou, A, Khan, K, Allotey J., Whittle R., Snell K. I. E., Smuk M., Townsend R., von Dadelszen P., Heazell A. E. P., Magee L., Smith G. C. S., Sandall J., Thilaganathan B., Zamora J., Riley R. D., Khalil A., Thangaratinam S., Coomarasamy A., Kwong A., Savitri A. I., Salvesen K. A., Bhattacharya S., Uiterwaal C. S. P. M., Staff A. C., Andersen L. B., Olive E. L., Redman C., Sletner L., Daskalakis G., Macleod M., Abdollahain M., Ramirez J. A., Masse J., Audibert F., Magnus P. M., Jenum A. K., Baschat A., Ohkuchi A., McAuliffe F. M., West J., Askie L. M., Mone F., Farrar D., Zimmerman P. A., Smits L. J. M., Riddell C., Kingdom J. C., van de Post J., Illanes S. E., Holzman C., van Kuijk S. M. J., Carbillon L., Villa P. M., Eskild A., Chappell L., Prefumo F., Velauthar L., Seed P., van Oostwaard M., Verlohren S., Poston L., Ferrazzi E., Vinter C. A., Nagata C., Brown M., Vollebregt K. C., Takeda S., Langenveld J., Widmer M., Saito S., Haavaldsen C., Carroli G., Olsen J., Wolf H., Zavaleta N., Eisensee I., Vergani P., Lumbiganon P., Makrides M., Facchinetti F., Sequeira E., Gibson R., Ferrazzani S., Frusca T., Norman J. E., Figueiro E. A., Lapaire O., Laivuori H., Lykke J. A., Conde-Agudelo A., Galindo A., Mbah A., Betran A. P., Herraiz I., Trogstad L., Smith G. G. S., Steegers E. A. P., Salim R., Huang T., Adank A., Zhang J., Meschino W. S., Browne J. L., Allen R. E., Costa F. D. S., Klipstein-Grobusch Browne K., Crowther C. A., Jorgensen J. S., Forest J. -C., Rumbold A. R., Mol B. W., Giguere Y., Kenny L. C., Ganzevoort W., Odibo A. O., Myers J., Yeo S. A., Goffinet F., McCowan L., Pajkrt E., Teede H. J., Haddad B. G., Dekker G., Kleinrouweler E. C., LeCarpentier E., Roberts C. T., Groen H., Skrastad R. B., Heinonen S., Eero K., Anggraini D., Souka A., Cecatti J. G., Monterio I., Pillalis A., Souza R., Hawkins L. A., Gabbay-Benziv R., Crovetto F., Figuera F., Jorgensen L., Dodds J., Patel M., Aviram A., Papageorghiou A., and Khan K.
- Abstract
Objective: Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods: MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results: Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overa
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- 2022
5. Positive maternal mental health during pregnancy and mental and behavioral disorders in children:a prospective pregnancy cohort study
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Lähdepuro, A. (Anna), Lahti-Pulkkinen, M. (Marius), Pyhälä, R. (Riikka), Tuovinen, S. (Soile), Lahti, J. (Jari), Heinonen, K. (Kati), Laivuori, H. (Hannele), Villa, P. M. (Pia M.), Reynolds, R. M. (Rebecca M.), Kajantie, E. (Eero), Girchenko, P. (Polina), Räikkönen, K. (Katri), Lähdepuro, A. (Anna), Lahti-Pulkkinen, M. (Marius), Pyhälä, R. (Riikka), Tuovinen, S. (Soile), Lahti, J. (Jari), Heinonen, K. (Kati), Laivuori, H. (Hannele), Villa, P. M. (Pia M.), Reynolds, R. M. (Rebecca M.), Kajantie, E. (Eero), Girchenko, P. (Polina), and Räikkönen, K. (Katri)
- Abstract
Background: The role of positive maternal mental health during pregnancy in child mental health remains largely unknown. We investigated whether positive maternal mental health during pregnancy is associated with lower hazards of mental and behavioral disorders in children and mitigates the adverse effects of negative maternal mental health. Methods: Among 3,378 mother–child dyads of the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction study, mothers reported their positive mental health biweekly throughout pregnancy with the Positive and Negative Affect Schedule, the Spielberger State Anxiety Inventory Curiosity scale, and a visual analogue scale for social support, and negative mental health with the Center for Epidemiologic Studies Depression Scale. We extracted data on their mental and behavioral disorder diagnoses from a nationwide medical register. This register provided data on their children’s mental and behavioral disorder diagnoses as well, from birth until 8.4−12.8 (Median = 10.2, Interquartile Range 9.7−10.8) years of age. Results: A positive maternal mental health composite score during pregnancy was associated with a lower hazard of any mental and behavioral disorder among all children [Hazard Ratio (HR) = 0.79, 95% Confidence Interval (CI) 0.71 − 0.87] and among children of mothers experiencing clinically relevant depressive symptoms during pregnancy [HR = 0.80, 95%CI 0.64 − 1.00] and/or mental and behavioral disorders before or during pregnancy [HR = 0.69, 95%CI 0.55−0.86]. These associations were independent of covariates. Conclusions: Children whose mothers had more positive mental health during pregnancy were less likely to develop mental and behavioral disorders. Protective effects were seen also among children of mothers facing mental health adversities before or during pregnancy.
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- 2023
6. The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions
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Rahmioglu, N, Mortlock, S, Ghiasi, M, Moller, PL, Stefansdottir, L, Galarneau, G, Turman, C, Danning, R, Law, MH, Sapkota, Y, Christofidou, P, Skarp, S, Giri, A, Banasik, K, Krassowski, M, Lepamets, M, Marciniak, B, Noukas, M, Perro, D, Sliz, E, Sobalska-Kwapis, M, Thorleifsson, G, Topbas-Selcuki, NF, Vitonis, A, Westergaard, D, Arnadottir, R, Burgdorf, KS, Campbell, A, Cheuk, CSK, Clementi, C, Cook, J, De Vivo, I, DiVasta, A, Dorien, O, Donoghue, JF, Edwards, T, Fontanillas, P, Fung, JN, Geirsson, RT, Girling, JE, Harkki, P, Harris, HR, Healey, M, Heikinheimo, O, Holdsworth-Carson, S, Hostettler, IC, Houlden, H, Houshdaran, S, Irwin, JC, Jarvelin, M-R, Kamatani, Y, Kennedy, SH, Kepka, E, Kettunen, J, Kubo, M, Kulig, B, Kurra, V, Laivuori, H, Laufer, MR, Lindgren, CM, MacGregor, S, Mangino, M, Martin, NG, Matalliotaki, C, Matalliotakis, M, Murray, AD, Ndungu, A, Nezhat, C, Olsen, CM, Opoku-Anane, J, Padmanabhan, S, Paranjpe, M, Peters, M, Polak, G, Porteous, DJ, Rabban, J, Rexrode, KM, Romanowicz, H, Saare, M, Saavalainen, L, Schork, AJ, Sen, S, Shafrir, AL, Siewierska-Gorska, A, Slomka, M, Smith, BH, Smolarz, B, Szaflik, T, Szyllo, K, Takahashi, A, Terry, KL, Tomassetti, C, Treloar, SA, Vanhie, A, Vincent, K, Vo, KC, Werring, DJ, Zeggini, E, Zervou, M, Stefansson, K, Nyegaard, M, Uimari, O, Yurttas-Beim, P, Tung, JY, Adachi, S, Buring, JE, Ridker, PM, D'Hooghe, T, Goulielmos, GN, Hapangama, DK, Hayward, C, Horne, AW, Low, S-K, Martikainen, H, Chasman, D, Rogers, PAW, Saunders, PT, Sirota, M, Spector, T, Strapagiel, D, Whiteman, DC, Giudice, LC, Velez-Edwards, DR, Kraft, P, Salumets, A, Nyholt, DR, Magi, R, Becker, CM, Steinthorsdottir, V, Missmer, SA, Montgomery, GW, Morris, AP, Zondervan, KT, Rahmioglu, N, Mortlock, S, Ghiasi, M, Moller, PL, Stefansdottir, L, Galarneau, G, Turman, C, Danning, R, Law, MH, Sapkota, Y, Christofidou, P, Skarp, S, Giri, A, Banasik, K, Krassowski, M, Lepamets, M, Marciniak, B, Noukas, M, Perro, D, Sliz, E, Sobalska-Kwapis, M, Thorleifsson, G, Topbas-Selcuki, NF, Vitonis, A, Westergaard, D, Arnadottir, R, Burgdorf, KS, Campbell, A, Cheuk, CSK, Clementi, C, Cook, J, De Vivo, I, DiVasta, A, Dorien, O, Donoghue, JF, Edwards, T, Fontanillas, P, Fung, JN, Geirsson, RT, Girling, JE, Harkki, P, Harris, HR, Healey, M, Heikinheimo, O, Holdsworth-Carson, S, Hostettler, IC, Houlden, H, Houshdaran, S, Irwin, JC, Jarvelin, M-R, Kamatani, Y, Kennedy, SH, Kepka, E, Kettunen, J, Kubo, M, Kulig, B, Kurra, V, Laivuori, H, Laufer, MR, Lindgren, CM, MacGregor, S, Mangino, M, Martin, NG, Matalliotaki, C, Matalliotakis, M, Murray, AD, Ndungu, A, Nezhat, C, Olsen, CM, Opoku-Anane, J, Padmanabhan, S, Paranjpe, M, Peters, M, Polak, G, Porteous, DJ, Rabban, J, Rexrode, KM, Romanowicz, H, Saare, M, Saavalainen, L, Schork, AJ, Sen, S, Shafrir, AL, Siewierska-Gorska, A, Slomka, M, Smith, BH, Smolarz, B, Szaflik, T, Szyllo, K, Takahashi, A, Terry, KL, Tomassetti, C, Treloar, SA, Vanhie, A, Vincent, K, Vo, KC, Werring, DJ, Zeggini, E, Zervou, M, Stefansson, K, Nyegaard, M, Uimari, O, Yurttas-Beim, P, Tung, JY, Adachi, S, Buring, JE, Ridker, PM, D'Hooghe, T, Goulielmos, GN, Hapangama, DK, Hayward, C, Horne, AW, Low, S-K, Martikainen, H, Chasman, D, Rogers, PAW, Saunders, PT, Sirota, M, Spector, T, Strapagiel, D, Whiteman, DC, Giudice, LC, Velez-Edwards, DR, Kraft, P, Salumets, A, Nyholt, DR, Magi, R, Becker, CM, Steinthorsdottir, V, Missmer, SA, Montgomery, GW, Morris, AP, and Zondervan, KT
- Abstract
Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention.
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- 2023
7. Maternal exposure to childhood maltreatment and mental and behavioral disorders in children
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Airikka, A. (Aino), Lahti-Pulkkinen, M. (Marius), Tuovinen, S. (Soile), Heinonen, K. (Kati), Lahti, J. (Jari), Girchenko, P. (Polina), Lähdepuro, A. (Anna), Pyhälä, R. (Riikka), Czamara, D. (Darina), Villa, P. (Pia), Laivuori, H. (Hannele), Kajantie, E. (Eero), Binder, E. B. (Elisabeth B.), Räikkönen, K. (Katri), Airikka, A. (Aino), Lahti-Pulkkinen, M. (Marius), Tuovinen, S. (Soile), Heinonen, K. (Kati), Lahti, J. (Jari), Girchenko, P. (Polina), Lähdepuro, A. (Anna), Pyhälä, R. (Riikka), Czamara, D. (Darina), Villa, P. (Pia), Laivuori, H. (Hannele), Kajantie, E. (Eero), Binder, E. B. (Elisabeth B.), and Räikkönen, K. (Katri)
- Abstract
Exposure to maltreatment in childhood is associated with lifelong risk of mental and behavioral disorders. Whether the effects extend to the next generation remains unclear. We examined whether maternal exposure to childhood abuse and neglect in her own childhood were associated with mental and behavioral disorders and psychiatric symptoms in her children, and whether maternal lifetime mental and behavioral disorders or lower education level mediated or added to the effects. Mothers (n = 2252) of the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction cohort study completed the Childhood Trauma Questionnaire and reported on their education and their 7.0–12.1-year-old children’s psychiatric symptoms using the Strengths and Difficulties Questionnaire. We identified lifetime mental and behavioral disorder diagnoses for the mothers and diagnoses for their children from birth (2006–2010) until 8.4–12.8 years (12/31/2018) from Care Register for Health Care. We found that maternal exposure to childhood abuse, but not neglect, was associated with higher hazards of mental and behavioral disorders (hazard ratio 1.20, 95% confidence interval 1.06–1.37) in children. These associations were partially mediated by maternal mental and behavioral disorders and education (proportion of effect size mediated: 23.8% and 15.1%, respectively), which together with maternal exposure to childhood abuse added to the hazard of mental and behavioral disorders in children. Similar associations were found for maternal exposure to childhood abuse and neglect with psychiatric symptoms in children. To conclude, maternal exposure to childhood maltreatment is associated with mental and behavioral disorders and psychiatric symptoms in children. Our findings call for interventions to prevent intergenerational transmission.
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- 2023
8. Meta-analysis of genome-wide association studies of gestational duration and spontaneous preterm birth identifies new maternal risk loci
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Pasanen, A. (Anu), Karjalainen, M. K. (Minna K.), F. (FinnGen), Zhang, G. (Ge), Tiensuu, H. (Heli), Haapalainen, A. M. (Antti M.), Ojaniemi, M. (Marja), Feenstra, B. (Bjarke), Jacobsson, B. (Bo), Palotie, A. (Aarno), Laivuori, H. (Hannele), Muglia, L. J. (Louis J.), Rämet, M. (Mika), Hallman, M. (Mikko), Pasanen, A. (Anu), Karjalainen, M. K. (Minna K.), F. (FinnGen), Zhang, G. (Ge), Tiensuu, H. (Heli), Haapalainen, A. M. (Antti M.), Ojaniemi, M. (Marja), Feenstra, B. (Bjarke), Jacobsson, B. (Bo), Palotie, A. (Aarno), Laivuori, H. (Hannele), Muglia, L. J. (Louis J.), Rämet, M. (Mika), and Hallman, M. (Mikko)
- Abstract
Background: Preterm birth (<37 weeks of gestation) is a major cause of neonatal death and morbidity. Up to 40% of the variation in timing of birth results from genetic factors, mostly due to the maternal genome. Methods: We conducted a genome-wide meta-analysis of gestational duration and spontaneous preterm birth in 68,732 and 98,370 European mothers, respectively. Results: The meta-analysis detected 15 loci associated with gestational duration, and four loci associated with preterm birth. Seven of the associated loci were novel. The loci mapped to several biologically plausible genes, for example HAND2 whose expression was previously shown to decrease during gestation, associated with gestational duration, and GC (Vitamin D-binding protein), associated with preterm birth. Downstream in silico-analysis suggested regulatory roles as underlying mechanisms for the associated loci. LD score regression found birth weight measures as the most strongly correlated traits, highlighting the unique nature of spontaneous preterm birth phenotype. Tissue expression and colocalization analysis revealed reproductive tissues and immune cell types as the most relevant sites of action. Conclusions: We report novel genetic risk loci that associate with preterm birth or gestational duration, and reproduce findings from previous genome-wide association studies. Altogether, our findings provide new insight into the genetic background of preterm birth. Better characterization of the causal genetic mechanisms will be important to public health as it could suggest new strategies to treat and prevent preterm birth., Author summary Annually, more than 15 million pregnancies are affected by preterm births all over the world. There are no effective ways to prevent preterm birth, and premature babies suffer from neonatal mortality and lifelong morbidities. Genetic factors of mother and fetus explain a large proportion, approximately 30–40%, of the of the variation in gestational age at delivery. To date, there have been just a few unbiased genome-wide investigations set out to locate these genes. Better characterization of the causal genetic mechanisms could suggest new strategies to treat and prevent preterm birth. In the current study, we aimed to identify maternal genetic factors that contribute to the timing of birth by meta-analyzing genome-wide association studies from European populations. We detected 17 independent loci that were associated with gestational duration and/or the risk of preterm birth. Ten of the loci replicated associations from previous studies, and seven were novel. The replicated associations provide strong evidence for the importance of these loci in the timing of birth, although the exact genes and causal variants and pathways still require further functional analysis. The seven novel associations provide further intriguing candidates that may account for the risk of preterm birth. Bioinformatics analysis proposed the associated loci have regulatory functions predominantly in immune cell types and reproductive tissues. The analysis further highlighted the unique nature or preterm birth as a phenotype, since the only traits with strong correlations were birth weight measures that are closely linked to the studied phenotypes. Our findings complement the knowledge of the genetic factors of preterm birth.
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- 2023
9. Serum ceramides in early pregnancy as predictors of gestational diabetes
- Author
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Mustaniemi, S. (Sanna), Keikkala, E. (Elina), Kajantie, E. (Eero), Nurhonen, M. (Markku), Jylhä, A. (Antti), Morin-Papunen, L. (Laure), Öhman, H. (Hanna), Männistö, T. (Tuija), Laivuori, H. (Hannele), Eriksson, J. G. (Johan G.), Laaksonen, R. (Reijo), Vääräsmäki, M. (Marja), T. F. (The FinnGeDi Study Group), Mustaniemi, S. (Sanna), Keikkala, E. (Elina), Kajantie, E. (Eero), Nurhonen, M. (Markku), Jylhä, A. (Antti), Morin-Papunen, L. (Laure), Öhman, H. (Hanna), Männistö, T. (Tuija), Laivuori, H. (Hannele), Eriksson, J. G. (Johan G.), Laaksonen, R. (Reijo), Vääräsmäki, M. (Marja), and T. F. (The FinnGeDi Study Group)
- Abstract
Ceramides contribute to the development of type 2 diabetes but it is uncertain whether they predict gestational diabetes (GDM). In this multicentre case–control study including 1040 women with GDM and 958 non-diabetic controls, early pregnancy (mean 10.7 gestational weeks) concentrations of four ceramides—Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:0) and Cer(d18:1/24:1)—were determined by a validated mass-spectrometric method from biobanked serum samples. Traditional lipids including total cholesterol, LDL, HDL and triglycerides were measured. Logistic and linear regression and the LASSO logistic regression were used to analyse lipids and clinical risk factors in the prediction of GDM. The concentrations of four targeted ceramides and total cholesterol, LDL and triglycerides were higher and HDL was lower among women with subsequent GDM than among controls. After adjustments, Cer(d18:1/24:0), triglycerides and LDL were independent predictors of GDM, women in their highest quartile had 1.44-fold (95% CI 1.07–1.95), 2.17-fold (95% CI 1.57–3.00) and 1.63-fold (95% CI 1.19–2.24) odds for GDM when compared to their lowest quartiles, respectively. In the LASSO regression modelling ceramides did not appear to markedly improve the predictive performance for GDM alongside with clinical risk factors and triglycerides. However, their adverse alterations highlight the extent of metabolic disturbances involved in GDM.
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- 2023
10. OP0263 INFLAMMATORY RHEUMATIC DISEASES HAVE BROAD IMPACT ON REPRODUCTIVE HEALTH – A NATIONWIDE EVALUATION AND SYSTEMATIC COMPARISON ACROSS RHEUMATIC DISEASES
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Mars, N., primary, Kerola, A., additional, Eklund, K., additional, Laivuori, H., additional, Ripatti, S., additional, Palomäki, A., additional, and Registry, F., additional
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- 2023
- Full Text
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11. New insights into the genetic etiology of Alzheimer's disease and related dementias
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Bellenguez, C., Küçükali, F., Jansen, I. E., Kleineidam, L., Moreno-Grau, S., Amin, N., Naj, A. C., Campos-Martin, R., Grenier-Boley, B., Andrade, V., Holmans, P. A., Boland, A., Damotte, V., van der Lee, S. J., Costa, M. R., Kuulasmaa, T., Yang, Q., de Rojas, I., Bis, J. C., Yaqub, A., Prokic, I., Chapuis, J., Ahmad, S., Giedraitis, V., Aarsland, D., Garcia-Gonzalez, P., Abdelnour, C., Alarcón-Martín, E., Alcolea, D., Alegret, M., Alvarez, I., Álvarez, V., Armstrong, N. J., Tsolaki, A., Antúnez, C., Appollonio, I., Arcaro, M., Archetti, S., Pastor, A. A., Arosio, B., Athanasiu, L., Bailly, H., Banaj, N., Baquero, M., Barral, S., Beiser, A., Pastor, A. B., Below, J. E., Benchek, P., Benussi, L., Berr, C., Besse, C., Bessi, V., Binetti, G., Bizarro, A., Blesa, R., Boada, M., Boerwinkle, E., Borroni, B., Boschi, S., Bossù, P., Bråthen, G., Bressler, J., Bresner, C., Brodaty, H., Brookes, K. J., Brusco, L. I., Buiza-Rueda, D., Bûrger, K., Burholt, V., Bush, W. S., Calero, M., Cantwell, L. B., Chene, G., Chung, J., Cuccaro, M. L., Carracedo, Á., Cecchetti, R., Cervera-Carles, L., Charbonnier, C., Chen, H. -H., Chillotti, C., Ciccone, S., Claassen, J. A. H. R., Clark, C., Conti, E., Corma-Gómez, A., Costantini, E., Custodero, C., Daian, D., Dalmasso, M. C., Daniele, A., Dardiotis, E., Dartigues, J. -F., de Deyn, P. P., de Paiva Lopes, K., de Witte, L. D., Debette, S., Deckert, J., del Ser, T., Denning, N., Destefano, A., Dichgans, M., Diehl-Schmid, J., Diez-Fairen, M., Rossi, P. D., Djurovic, S., Duron, E., Düzel, E., Dufouil, C., Eiriksdottir, G., Engelborghs, S., Escott-Price, V., Espinosa, A., Ewers, M., Faber, K. M., Fabrizio, T., Nielsen, S. F., Fardo, D. W., Farotti, L., Fenoglio, C., Fernández-Fuertes, M., Ferrari, R., Ferreira, C. B., Ferri, E., Fin, B., Fischer, P., Fladby, T., Fließbach, K., Fongang, B., Fornage, M., Fortea, J., Foroud, T. M., Fostinelli, S., Fox, N. C., Franco-Macías, E., Bullido, M. 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P., Tárraga, L., Tesí, N., Thalamuthu, A., Thomas, T., Tosto, G., Traykov, L., Tremolizzo, L., Tybjærg-Hansen, A., Uitterlinden, A., Ullgren, A., Ulstein, I., Valero, S., Valladares, O., Broeckhoven, C. V., Vance, J., Vardarajan, B. N., van der Lugt, A., Dongen, J. V., van Rooij, J., van Swieten, J., Vandenberghe, R., Verhey, F., Vidal, J. -S., Vogelgsang, J., Vyhnalek, M., Wagner, M., Wallon, D., Wang, L. -S., Wang, R., Weinhold, L., Wiltfang, J., Windle, G., Woods, B., Yannakoulia, M., Zare, H., Zhao, Y., Zhang, X., Zhu, C., Zulaica, M., Laczo, J., Matoska, V., Serpente, M., Assogna, F., Piras, F., Ciullo, V., Shofany, J., Ferrarese, C., Andreoni, S., Sala, G., Zoia, C. P., Zompo, M. D., Benussi, A., Bastiani, P., Takalo, M., Natunen, T., Laatikainen, T., Tuomilehto, J., Antikainen, R., Strandberg, T., Lindström, J., Peltonen, M., Abraham, R., Al-Chalabi, A., Bass, N. J., Brayne, C., Brown, K. S., Collinge, J., Craig, D., Deloukas, P., Fox, N., Gerrish, A., Gill, M., Gwilliam, R., Harold, D., Hollingworth, P., Johnston, J. A., Jones, L., Lawlor, B., Livingston, G., Lovestone, S., Lupton, M., Lynch, A., Mann, D., Mcguinness, B., Mcquillin, A., O’Donovan, M. C., Owen, M. J., Passmore, P., Powell, J. F., Proitsi, P., Rossor, M., Shaw, C. E., Smith, A. D., Gurling, H., Todd, S., Mummery, C., Ryan, N., Lacidogna, G., Adarmes-Gómez, A., Mauleón, A., Pancho, A., Gailhajenet, A., Lafuente, A., Macias-García, D., Martín, E., Pelejà, E., Carrillo, F., Merlín, I. S., Garrote-Espina, L., Vargas, L., Carrion-Claro, M., Marín, M., Labrador, M., Buendia, M., Alonso, M. D., Guitart, M., Moreno, M., Ibarria, M., Periñán, M., Aguilera, N., Gómez-Garre, P., Cañabate, P., Escuela, R., Pineda-Sánchez, R., Vigo-Ortega, R., Jesús, S., Preckler, S., Rodrigo-Herrero, S., Diego, S., Vacca, A., Roveta, F., Salvadori, N., Chipi, E., Boecker, H., Laske, C., Perneczky, R., Anastasiou, C., Janowitz, D., Malik, R., Anastasiou, A., Parveen, K., López-García, S., Antonell, A., Mihova, K. Y., Belezhanska, D., Weber, H., Kochen, S., Solis, P., Medel, N., Lisso, J., Sevillano, Z., Politis, D. G., Cores, V., Cuesta, C., Ortiz, C., Bacha, J. I., Rios, M., Saenz, A., Abalos, M. S., Kohler, E., Palacio, D. L., Etchepareborda, I., Kohler, M., Novack, G., Prestia, F. A., Galeano, P., Castaño, E. M., Germani, S., Toso, C. R., Rojo, M., Ingino, C., Mangone, C., Rubinsztein, D. C., Teipel, S., Fievet, N., Deramerourt, V., Forsell, C., Thonberg, H., Bjerke, M., Roeck, E. D., Martínez-Larrad, M. 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M., Pickering-Brown, S., Sussams, R., Warner, N., Bayer, A., Heuser, I., Drichel, D., Klopp, N., Mayhaus, M., Riemenschneider, M., Pinchler, S., Feulner, T., Gu, W., van den Bussche, H., Hüll, M., Frölich, L., Wichmann, H. -E., Jöckel, K. -H., O’Donovan, M., Owen, M., Bahrami, S., Bosnes, I., Selnes, P., Bergh, S., Palotie, A., Daly, M., Jacob, H., Matakidou, A., Runz, H., John, S., Plenge, R., Mccarthy, M., Hunkapiller, J., Ehm, M., Waterworth, D., Fox, C., Malarstig, A., Klinger, K., Call, K., Behrens, T., Loerch, P., Mäkelä, T., Kaprio, J., Virolainen, P., Pulkki, K., Kilpi, T., Perola, M., Partanen, J., Pitkäranta, A., Kaarteenaho, R., Vainio, S., Turpeinen, M., Serpi, R., Laitinen, T., Mäkelä, J., Kosma, V. -M., Kujala, U., Tuovila, O., Hendolin, M., Pakkanen, R., Waring, J., Riley-Gillis, B., Liu, J., Biswas, S., Diogo, D., Marshall, C., Hu, X., Gossel, M., Graham, R., Cummings, B., Ripatti, S., Schleutker, J., Arvas, M., Carpén, O., Hinttala, R., Kettunen, J., Mannermaa, A., Laukkanen, J., Julkunen, V., Remes, A., Kälviäinen, R., Peltola, J., Tienari, P., Rinne, J., Ziemann, A., Esmaeeli, S., Smaoui, N., Lehtonen, A., Eaton, S., Lahdenperä, S., van Adelsberg, J., Michon, J., Kerchner, G., Bowers, N., Teng, E., Eicher, J., Mehta, V., Gormley, P., Linden, K., Whelan, C., Xu, F., Pulford, D., Färkkilä, M., Pikkarainen, S., Jussila, A., Blomster, T., Kiviniemi, M., Voutilainen, M., Georgantas, B., Heap, G., Rahimov, F., Usiskin, K., Lu, T., Oh, D., Kalpala, K., Miller, M., Mccarthy, L., Eklund, K., Palomäki, A., Isomäki, P., Pirilä, L., Kaipiainen-Seppänen, O., Huhtakangas, J., Lertratanakul, A., Hochfeld, M., Bing, N., Gordillo, J. 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Aarsland, D, Garcia-Gonzalez, P, Abdelnour, C, Alarcón-Martín, E, Alcolea, D, Alegret, M, Alvarez, I, Álvarez, V, Armstrong, N, Tsolaki, A, Antúnez, C, Appollonio, I, Arcaro, M, Archetti, S, Pastor, A, Arosio, B, Athanasiu, L, Bailly, H, Banaj, N, Baquero, M, Barral, S, Beiser, A, Below, J, Benchek, P, Benussi, L, Berr, C, Besse, C, Bessi, V, Binetti, G, Bizarro, A, Blesa, R, Boada, M, Boerwinkle, E, Borroni, B, Boschi, S, Bossù, P, Bråthen, G, Bressler, J, Bresner, C, Brodaty, H, Brookes, K, Brusco, L, Buiza-Rueda, D, Bûrger, K, Burholt, V, Bush, W, Calero, M, Cantwell, L, Chene, G, Chung, J, Cuccaro, M, Carracedo, Á, Cecchetti, R, Cervera-Carles, L, Charbonnier, C, Chen, H, Chillotti, C, Ciccone, S, Claassen, J, Clark, C, Conti, E, Corma-Gómez, A, Costantini, E, Custodero, C, Daian, D, Dalmasso, M, Daniele, A, Dardiotis, E, Dartigues, J, de Deyn, P, de Paiva Lopes, K, de Witte, L, Debette, S, Deckert, J, Del Ser, T, Denning, N, Destefano, A, Dichgans, M, Diehl-Schmid, J, Diez-Fairen, M, Rossi, P, Djurovic, S, Duron, E, Düzel, E, Dufouil, C, Eiriksdottir, G, Engelborghs, S, Escott-Price, V, Espinosa, A, Ewers, M, Faber, K, Fabrizio, T, Nielsen, S, Fardo, D, Farotti, L, Fenoglio, C, Fernández-Fuertes, M, Ferrari, R, Ferreira, C, Ferri, E, Fin, B, Fischer, P, Fladby, T, Fließbach, K, Fongang, B, Fornage, M, Fortea, J, Foroud, T, Fostinelli, S, Fox, N, Franco-Macías, E, Bullido, M, Frank-García, A, Froelich, L, Fulton-Howard, B, Galimberti, D, García-Alberca, J, García-González, P, Garcia-Madrona, S, Garcia-Ribas, G, Ghidoni, R, Giegling, I, Giorgio, G, Goate, A, Goldhardt, O, Gomez-Fonseca, D, González-Pérez, A, Graff, C, Grande, G, Green, E, Grimmer, T, Grünblatt, E, Grunin, M, Gudnason, V, Guetta-Baranes, T, Haapasalo, A, Hadjigeorgiou, G, Haines, J, Hamilton-Nelson, K, Hampel, H, Hanon, O, Hardy, J, Hartmann, A, Hausner, L, Harwood, J, Heilmann-Heimbach, S, Helisalmi, S, Heneka, M, Hernández, I, Herrmann, M, Hoffmann, P, Holmes, C, Holstege, H, Vilas, R, Hulsman, M, Humphrey, J, Biessels, G, Jian, X, Johansson, C, Jun, G, Kastumata, Y, Kauwe, J, Kehoe, P, Kilander, L, Ståhlbom, A, Kivipelto, M, Koivisto, A, Kornhuber, J, Kosmidis, M, Kukull, W, Kuksa, P, Kunkle, B, Kuzma, A, Lage, C, Laukka, E, Launer, L, Lauria, A, Lee, C, Lehtisalo, J, Lerch, O, Lleó, A, Longstreth, W, Lopez, O, de Munain, A, Love, S, Löwemark, M, Luckcuck, L, Lunetta, K, Ma, Y, Macías, J, Macleod, C, Maier, W, Mangialasche, F, Spallazzi, M, Marquié, M, Marshall, R, Martin, E, Montes, A, Rodríguez, C, Masullo, C, Mayeux, R, Mead, S, Mecocci, P, Medina, M, Meggy, A, Mehrabian, S, Mendoza, S, Menéndez-González, M, Mir, P, Moebus, S, Mol, M, Molina-Porcel, L, Montrreal, L, Morelli, L, Moreno, F, Morgan, K, Mosley, T, Nöthen, M, Muchnik, C, Mukherjee, S, Nacmias, B, Ngandu, T, Nicolas, G, Nordestgaard, B, Olaso, R, Orellana, A, Orsini, M, Ortega, G, Padovani, A, Paolo, C, Papenberg, G, Parnetti, L, Pasquier, F, Pastor, P, Peloso, G, Pérez-Cordón, A, Pérez-Tur, J, Pericard, P, Peters, O, Pijnenburg, Y, Pineda, J, Piñol-Ripoll, G, Pisanu, C, Polak, T, Popp, J, Posthuma, D, Priller, J, Puerta, R, Quenez, O, Quintela, I, Thomassen, J, Rábano, A, Rainero, I, Rajabli, F, Ramakers, I, Real, L, Reinders, M, Reitz, C, Reyes-Dumeyer, D, Ridge, P, Riedel-Heller, S, Riederer, P, Roberto, N, Rodriguez-Rodriguez, E, Rongve, A, Allende, I, Rosende-Roca, M, Royo, J, Rubino, E, Rujescu, D, Sáez, M, Sakka, P, Saltvedt, I, Sanabria, Á, Sánchez-Arjona, M, Sanchez-Garcia, F, Juan, P, Sánchez-Valle, R, Sando, S, Sarnowski, C, Satizabal, C, Scamosci, M, Scarmeas, N, Scarpini, E, Scheltens, P, Scherbaum, N, Scherer, M, Schmid, M, Schneider, A, Schott, J, Selbæk, G, Seripa, D, Serrano, M, Sha, J, Shadrin, A, Skrobot, O, Slifer, S, Snijders, G, Soininen, H, Solfrizzi, V, Solomon, A, Song, Y, Sorbi, S, Sotolongo-Grau, O, Spalletta, G, Spottke, A, Squassina, A, Stordal, E, Tartan, J, Tárraga, L, Tesí, N, Thalamuthu, A, Thomas, T, Tosto, G, Traykov, L, Tremolizzo, L, Tybjærg-Hansen, A, Uitterlinden, A, Ullgren, A, Ulstein, I, Valero, S, Valladares, O, Broeckhoven, C, Vance, J, Vardarajan, B, van der Lugt, A, Dongen, J, van Rooij, J, van Swieten, J, Vandenberghe, R, Verhey, F, Vidal, J, Vogelgsang, J, Vyhnalek, M, Wagner, M, Wallon, D, Wang, L, Wang, R, Weinhold, L, Wiltfang, J, Windle, G, Woods, B, Yannakoulia, M, Zare, H, Zhao, Y, Zhang, X, Zhu, C, Zulaica, M, Andreoni, S, Ferrarese, C, Sala, G, Zoia, C, Farrer, L, Psaty, B, Ghanbari, M, Raj, T, Sachdev, P, Mather, K, Jessen, F, Ikram, M, de Mendonça, A, Hort, J, Tsolaki, M, Pericak-Vance, M, Amouyel, P, Williams, J, Frikke-Schmidt, R, Clarimon, J, Deleuze, J, Rossi, G, Seshadri, S, Andreassen, O, Ingelsson, M, Hiltunen, M, Sleegers, K, Schellenberg, G, van Duijn, C, Sims, R, van der Flier, W, Ruiz, A, Ramirez, A, Lambert, J, VU University medical center, Amsterdam Neuroscience - Neurodegeneration, Neurology, Human genetics, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Compulsivity, 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[0000-0002-7542-1139], Kornhuber, Johannes [0000-0002-8096-3987], Kosmidis, Mary H [0000-0001-8790-1220], Lage, Carmen [0000-0003-1703-121X], Launer, Lenore [0000-0002-3238-7612], Lee, Chien-Yueh [0000-0002-4304-974X], Lleó, Alberto [0000-0002-2568-5478], Lopez, Oscar [0000-0002-8546-8256], de Munain, Adolfo Lopez [0000-0002-9509-4032], Lunetta, Kathryn L [0000-0002-9268-810X], Ma, Yiyi [0000-0002-3609-8877], MacLeod, Catherine A [0000-0002-9314-7380], Marquié, Marta [0000-0002-0660-0950], Montes, Angel Martín [0000-0002-1694-786X], Mead, Simon [0000-0002-4326-1468], Medina, Miguel [0000-0002-7016-5340], Menéndez-González, Manuel [0000-0002-5218-0774], Mol, Merel [0000-0003-2533-2530], Morgan, Kevin [0000-0002-8217-2396], Nöthen, Markus M [0000-0002-8770-2464], Muchnik, Carolina [0000-0002-1542-3706], Nacmias, Benedetta [0000-0001-9338-9040], Nicolas, Gael [0000-0001-9391-7800], Nordestgaard, Børge G [0000-0002-1954-7220], Pasquier, Florence [0000-0001-9880-9788], Pastor, Pau [0000-0002-7493-8777], Peloso, Gina [0000-0002-5355-8636], Pérez-Cordón, Alba [0000-0002-6028-0791], Pérez-Tur, Jordi [0000-0002-9111-1712], Pericard, Pierre [0000-0001-8167-6448], Pineda, Juan A [0000-0002-3751-0296], Pisanu, Claudia [0000-0002-9151-4319], Posthuma, Danielle [0000-0001-7582-2365], Puerta, Raquel [0000-0002-1191-5893], Quenez, Olivier [0000-0002-8273-8505], Thomassen, Jesper Qvist [0000-0003-3484-9531], Real, Luis M [0000-0003-4932-7429], Reinders, Marcel JT [0000-0002-1148-1562], Reitz, Christiane [0000-0001-8757-7889], Riedel-Heller, Steffi [0000-0003-4321-6090], Rodriguez-Rodriguez, Eloy [0000-0001-7742-677X], Rongve, Arvid [0000-0002-0476-4134], Sáez, María Eugenia [0000-0001-9299-2534], Saltvedt, Ingvild [0000-0002-7897-9808], Juan, Pascual Sánchez [0000-0002-6081-8037], Sarnowski, Chloé [0000-0002-6090-7099], Satizabal, Claudia L [0000-0002-1115-4430], Schott, Jonathan M [0000-0003-2059-024X], Selbæk, Geir [0000-0001-6511-8219], Shadrin, Alexey A 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Sachdev, Perminder [0000-0002-9595-3220], Mather, Karen [0000-0003-4143-8941], Ikram, M Arfan [0000-0003-0372-8585], Tsolaki, Magda [0000-0002-2072-8010], Pericak-Vance, Margaret A [0000-0001-7283-8804], Amouyel, Philippe [0000-0001-9088-234X], Williams, Julie [0000-0002-4069-0259], Frikke-Schmidt, Ruth [0000-0003-4084-5027], Seshadri, Sudha [0000-0001-6135-2622], Andreassen, Ole A [0000-0002-4461-3568], Sleegers, Kristel [0000-0002-0283-2332], van Duijn, Cornelia M [0000-0002-2374-9204], Sims, Rebecca [0000-0002-3885-1199], van der Flier, Wiesje M [0000-0001-8766-6224], Ramirez, Alfredo [0000-0003-4991-763X], Lambert, Jean-Charles [0000-0003-0829-7817], Apollo - University of Cambridge Repository, Complex Trait Genetics, Clinical sciences, Neuroprotection & Neuromodulation, Pathologic Biochemistry and Physiology, Clinical Biology, Epidemiology, Internal Medicine, Psychiatrie & Neuropsychologie, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, MUMC+: MA Med Staf Spec Psychiatrie (9), UAM. Departamento de Biología Molecular, University of Helsinki, Department of Neurosciences, HUS Internal Medicine and Rehabilitation, Timo Strandberg / Principal Investigator, Department of Medicine, Clinicum, HUS Neurocenter, Neurologian yksikkö, Centre of Excellence in Complex Disease Genetics, HUS Abdominal Center, Institut Pasteur, Institut National de la Santé et de la Recherche Médicale (France), European Commission, LabEx DISTALZ, Pérez-Tur, Jordi, University Children’s Hospital Basel (Suiza), INSERM (Francia), Lille Métropole Communauté Urbaine, Government of France (Francia), EADB, GR@ACE, DEGESCO, EADI, GERAD, Demgene, FinnGen, ADGC, CHARGE, Holmans, Peter A. [0000-0003-0870-9412], van der Lee, Sven J. [0000-0003-1606-8643], Costa, Marcos R. [0000-0002-4928-2163], Bis, Joshua C. [0000-0002-3409-1110], Brookes, Keeley J. [0000-0003-2427-2513], Bush, William S. [0000-0002-9729-6519], de Witte, Lot D. [0000-0002-7235-9958], del Ser, Teodoro [0000-0001-9806-7083], Fox, Nick C. [0000-0002-6660-657X], Bullido, María J. [0000-0002-6477-1117], Goate, Alison M. [0000-0002-0576-2472], Herrmann, Martin J. [0000-0001-9970-2122], Jun, Gyungah R. [0000-0002-3230-8697], Kehoe, Patrick G. [0000-0002-7542-1139], Kosmidis, Mary H. [0000-0001-8790-1220], Lunetta, Kathryn L. [0000-0002-9268-810X], MacLeod, Catherine A. [0000-0002-9314-7380], Nöthen, Markus M. [0000-0002-8770-2464], Nordestgaard, Børge G. [0000-0002-1954-7220], Pineda, Juan A. [0000-0002-3751-0296], Real, Luis M. [0000-0003-4932-7429], Reinders, Marcel J. T. [0000-0002-1148-1562], Satizabal, Claudia L. [0000-0002-1115-4430], Schott, Jonathan M. [0000-0003-2059-024X], Shadrin, Alexey A. [0000-0002-7467-250X], Farrer, Lindsay A. [0000-0001-5533-4225], Psaty, Bruce M. [0000-0002-7278-2190], Ikram, M. Arfan [0000-0003-0372-8585], Pericak-Vance, Margaret A. [0000-0001-7283-8804], Andreassen, Ole A. [0000-0002-4461-3568], van Duijn, Cornelia M. [0000-0002-2374-9204], van der Flier, Wiesje M. [0000-0001-8766-6224], and Molecular Neuroscience and Ageing Research (MOLAR)
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tau Proteins/genetics ,Alzheimer`s disease Donders Center for Medical Neuroscience [Radboudumc 1] ,Neurologi ,MED/03 - GENETICA MEDICA ,45/43 ,Medizin ,Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13] ,genetics [Alzheimer Disease] ,Genome-Wide Association Study ,Humans ,tau Proteins ,Alzheimer Disease ,Cognitive Dysfunction ,VARIANTS ,pathology [Alzheimer Disease] ,Tau Proteins ,Settore BIO/13 - Biologia Applicata ,Cognitive Dysfunction/psychology ,692/699/375/365/1283 ,IMPUTATION ,article ,1184 Genetics, developmental biology, physiology ,Biología y Biomedicina / Biología ,AMYLOID-BETA ,Settore MED/26 - NEUROLOGIA ,Neurology ,psychology [Cognitive Dysfunction] ,Medical Genetics ,Human ,Neuroscience(all) ,631/208/205/2138 ,All institutes and research themes of the Radboud University Medical Center ,SDG 3 - Good Health and Well-being ,ddc:570 ,Genetics ,Genetic Predisposition to Disease ,GENOME-WIDE ASSOCIATION ,METAANALYSIS ,Medicinsk genetik ,MED/26 - NEUROLOGIA ,Alzheimer Disease/genetics ,neurology ,tau Protein ,NECROSIS-FACTOR-ALPHA ,RISK LOCI ,genetics [tau Proteins] ,PREDICTION MODELS ,Human medicine ,GENERATION ,RESPONSES - Abstract
25 páginas, 6 figuras, 2 tablas, Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele., This work was funded by a grant (EADB) from the EU Joint Programme – Neurodegenerative Disease Research. INSERM UMR1167 is also funded by the INSERM, Institut Pasteur de Lille, Lille Métropole Communauté Urbaine and French government’s LABEX DISTALZ program (development of innovative strategies for a transdisciplinary approach to AD). Full consortium acknowledgements and funding are in the Supplementary Not
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- 2022
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12. The effect of dietary counselling on food intakes in pregnant women at risk for gestational diabetes: a secondary analysis of a randomised controlled trial RADIEL
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Valkama, A., Koivusalo, S., Lindstrom, J., Meinila, J., Kautiainen, H., Stach-Lempinen, B., Rono, K., Klemetti, M., Poyhonen-Alho, M., Tiitinen, A., Huvinen, E., Laivuori, H., Andersson, S., Roine, R., and Eriksson, J.G.
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Risk factors ,Patient outcomes ,Health aspects ,Gestational diabetes -- Risk factors ,Nutrition counseling -- Patient outcomes ,Food habits -- Health aspects ,Pregnant women -- Health aspects - Abstract
INTRODUCTION Gestational diabetes mellitus (GDM) is defined as glucose intolerance with its first detection during pregnancy. (1) Factors associated with GDM risk are pre-pregnancy overweight, previous GDM and a family [...], BACKGROUND/OBJECTIVES: The prevalence of gestational diabetes mellitus (GDM) is increasing worldwide. GDM may be prevented by improving the diets of pregnant women. The objective of this study was to evaluate the effect of dietary counselling on the diets of pregnant women at GDM risk. SUBJECTS/METHODS: This study was a secondary analysis of a randomised controlled trial the Finnish gestational diabetes prevention study (RADIEL) in which pre-pregnant and pregnant women with previous GDM or BMI [greater than or equal to] 30 kg/[m.sup.2] were allocated into two groups, namely the control and the intervention groups. The control group received standard antenatal dietary counselling according to the Finnish Nutrition Recommendations. The intervention group participated in one individual dietary counselling session and one group dietary counselling session in addition to the standard counselling. This study included women who were recruited during pregnancy. To assess changes in food intake, food-intake questionnaires were collected during the first and the second trimester of pregnancy. Bootstrap type analysis of covariance was used, and 242 participants were included in the final analysis to study changes in food intake. RESULTS: The intakes of low-fat cheese (baseline adjusted mean 0.09 times/day; 95% confidence interval (CI) 0.07, 0.24; P = 0.040) and fish (baseline adjusted mean 0.28 times per week; 95% CI 0.08, 0.49; P = 0.011) showed a significant increase in the intervention group compared with the control group. CONCLUSIONS: This study showed that dietary counselling in early pregnancy can lead to modest dietary improvements in pregnant women at GDM risk. European Journal of Clinical Nutrition (2016) 70, 912-917; doi:10.1038/ejcn.2015.205; published online 16 December 2015
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- 2016
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13. External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications (IPPIC) Network database: individual participant data meta-analysis
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Allotey, J., Whittle, R., Snell, K. I. E., Smuk, M., Townsend, R., von Dadelszen, P., Heazell, A. E. P., Magee, L., Smith, G. C. S., Sandall, J., Thilaganathan, B., Zamora, J., Riley, R. D., Khalil, A., Thangaratinam, S., Coomarasamy, A., Kwong, A., Savitri, A. I., Salvesen, K. A., Bhattacharya, S., Uiterwaal, C. S. P. M., Staff, A. C., Andersen, L. B., Olive, E. L., Redman, C., Sletner, L., Daskalakis, G., Macleod, M., Abdollahain, M., Ramirez, J. A., Masse, J., Audibert, F., Magnus, P. M., Jenum, A. K., Baschat, A., Ohkuchi, A., Mcauliffe, F. M., West, J., Askie, L. M., Mone, F., Farrar, D., Zimmerman, P. A., Smits, L. J. M., Riddell, C., Kingdom, J. C., van de Post, J., Illanes, S. E., Holzman, C., van Kuijk, S. M. J., Carbillon, L., Villa, P. M., Eskild, A., Chappell, L., Prefumo, F., Velauthar, L., Seed, P., van Oostwaard, M., Verlohren, S., Poston, L., Ferrazzi, E., Vinter, C. A., Nagata, C., Brown, M., Vollebregt, K. C., Takeda, S., Langenveld, J., Widmer, M., Saito, S., Haavaldsen, C., Carroli, G., Olsen, J., Wolf, H., Zavaleta, N., Eisensee, I., Vergani, P., Lumbiganon, P., Makrides, M., Facchinetti, F., Sequeira, E., Gibson, R., Ferrazzani, S., Frusca, T., Norman, J. E., Figueiro, E. A., Lapaire, O., Laivuori, H., Lykke, J. A., Conde-Agudelo, A., Galindo, A., Mbah, A., Betran, A. P., Herraiz, I., Trogstad, L., Smith, G. G. S., Steegers, E. A. P., Salim, R., Huang, T., Adank, A., Zhang, J., Meschino, W. S., Browne, J. L., Allen, R. E., Costa, F. D. S., Klipstein-Grobusch Browne, K., Crowther, C. A., Jorgensen, J. S., Forest, J. -C., Rumbold, A. R., Mol, B. W., Giguere, Y., Kenny, L. C., Ganzevoort, W., Odibo, A. O., Myers, J., Yeo, S. A., Goffinet, F., Mccowan, L., Pajkrt, E., Teede, H. J., Haddad, B. G., Dekker, G., Kleinrouweler, E. C., Lecarpentier, E., Roberts, C. T., Groen, H., Skrastad, R. B., Heinonen, S., Eero, K., Anggraini, D., Souka, A., Cecatti, J. G., Monterio, I., Pillalis, A., Souza, R., Hawkins, L. A., Gabbay-Benziv, R., Crovetto, F., Figuera, F., Jorgensen, L., Dodds, J., Patel, M., Aviram, A., Papageorghiou, A., Khan, K., Clinicum, HUS Gynecology and Obstetrics, Department of Obstetrics and Gynecology, HUS Children and Adolescents, Lastentautien yksikkö, Children's Hospital, Allotey, J, Whittle, R, Snell, K, Smuk, M, Townsend, R, von Dadelszen, P, Heazell, A, Magee, L, Smith, G, Sandall, J, Thilaganathan, B, Zamora, J, Riley, R, Khalil, A, Thangaratinam, S, Coomarasamy, A, Kwong, A, Savitri, A, Salvesen, K, Bhattacharya, S, Uiterwaal, C, Staff, A, Andersen, L, Olive, E, Redman, C, Sletner, L, Daskalakis, G, Macleod, M, Abdollahain, M, Ramirez, J, Masse, J, Audibert, F, Magnus, P, Jenum, A, Baschat, A, Ohkuchi, A, Mcauliffe, F, West, J, Askie, L, Mone, F, Farrar, D, Zimmerman, P, Smits, L, Riddell, C, Kingdom, J, van de Post, J, Illanes, S, Holzman, C, van Kuijk, S, Carbillon, L, Villa, P, Eskild, A, Chappell, L, Prefumo, F, Velauthar, L, Seed, P, van Oostwaard, M, Verlohren, S, Poston, L, Ferrazzi, E, Vinter, C, Nagata, C, Brown, M, Vollebregt, K, Takeda, S, Langenveld, J, Widmer, M, Saito, S, Haavaldsen, C, Carroli, G, Olsen, J, Wolf, H, Zavaleta, N, Eisensee, I, Vergani, P, Lumbiganon, P, Makrides, M, Facchinetti, F, Sequeira, E, Gibson, R, Ferrazzani, S, Frusca, T, Norman, J, Figueiro, E, Lapaire, O, Laivuori, H, Lykke, J, Conde-Agudelo, A, Galindo, A, Mbah, A, Betran, A, Herraiz, I, Trogstad, L, Steegers, E, Salim, R, Huang, T, Adank, A, Zhang, J, Meschino, W, Browne, J, Allen, R, Costa, F, Klipstein-Grobusch Browne, K, Crowther, C, Jorgensen, J, Forest, J, Rumbold, A, Mol, B, Giguere, Y, Kenny, L, Ganzevoort, W, Odibo, A, Myers, J, Yeo, S, Goffinet, F, Mccowan, L, Pajkrt, E, Teede, H, Haddad, B, Dekker, G, Kleinrouweler, E, Lecarpentier, E, Roberts, C, Groen, H, Skrastad, R, Heinonen, S, Eero, K, Anggraini, D, Souka, A, Cecatti, J, Monterio, I, Pillalis, A, Souza, R, Hawkins, L, Gabbay-Benziv, R, Crovetto, F, Figuera, F, Jorgensen, L, Dodds, J, Patel, M, Aviram, A, Papageorghiou, A, Khan, K, Tampere University, Obstetrics and Gynaecology, APH - Quality of Care, Amsterdam Reproduction & Development (AR&D), APH - Personalized Medicine, APH - Digital Health, and Obstetrics and gynaecology
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Calibration (statistics) ,Perinatal Death ,Overfitting ,Cohort Studies ,Fetal Development ,0302 clinical medicine ,Discriminative model ,3123 Gynaecology and paediatrics ,Models ,Pregnancy ,GROWTH RESTRICTION ,Statistics ,Medicine ,Prenatal ,030212 general & internal medicine ,Ultrasonography ,RISK ,030219 obstetrics & reproductive medicine ,PRETERM ,Radiological and Ultrasound Technology ,LOW-DOSE ASPIRIN ,DIAGNOSIS TRIPOD ,Obstetrics and Gynecology ,General Medicine ,Statistical ,Stillbirth ,Prognosis ,Pregnancy Complication ,external validation ,individual participant data ,intrauterine death ,prediction model ,stillbirth ,Female ,Humans ,Infant, Newborn ,Models, Statistical ,Pregnancy Complications ,Regression Analysis ,Risk Assessment ,Ultrasonography, Prenatal ,3. Good health ,PREECLAMPSIA ,Meta-analysis ,Human ,Cohort study ,Prognosi ,MEDLINE ,Regression Analysi ,WEEKS GESTATION ,03 medical and health sciences ,VELOCIMETRY ,Radiology, Nuclear Medicine and imaging ,RECURRENCE ,business.industry ,Infant ,Newborn ,R1 ,HYPERTENSIVE DISORDERS ,Reproductive Medicine ,Sample size determination ,Cohort Studie ,RG ,business ,RA ,Predictive modelling - Abstract
Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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- 2022
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14. First trimester hyperglycosylated human chorionic gonadotrophin in serum – A marker of early-onset preeclampsia
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Keikkala, E., Vuorela, P., Laivuori, H., Romppanen, J., Heinonen, S., and Stenman, U.-H.
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- 2013
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15. Obstetric and perinatal risks after the use of donor sperm : A systematic review and meta-analysis
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Pohjonen, E. M., Söderström-Anttila, V., Bergh, C., Loft, A., Magnusson, Pinborg, A., Oldereid, N. B., Petzold, M., Romundstad, L. B., Laivuori, H., Clinicum, HUS Gynecology and Obstetrics, Genomics of Neurological and Neuropsychiatric Disorders, Institute for Molecular Medicine Finland, University of Helsinki, Helsinki Institute of Life Science HiLIFE, Tampere University, Department of Gynaecology and Obstetrics, and Clinical Medicine
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endocrine system ,SINGLE WOMEN ,Donor sperm ,OFFSPRING HEALTH ,PARTNER SPERM ,urogenital system ,INTRAUTERINE INSEMINATION ,ARTIFICIAL-INSEMINATION ,Perinatal outcome ,Preeclampsia ,Hypertensive disorders of pregnancy ,HYPERTENSIVE DISORDERS ,3123 Gynaecology and paediatrics ,ADVANCED MATERNAL AGE ,Donor insemination ,ADVERSE PREGNANCY OUTCOMES ,reproductive and urinary physiology ,ASSISTED-REPRODUCTIVE-TECHNOLOGIES - Abstract
Donor sperm is widely used in infertility treatments. The purpose of the study was to investigate, whether use of donor sperm in intrauterine insemination (IUI) or in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) treatments affect maternal and perinatal risks compared with spontaneously conceived pregnancies or use of partner sperm in IUI, IVF or ICSI. We provide a systematic review and meta-analyses on the most clinically relevant obstetric and perinatal outcomes after use of donor sperm compared with partner sperm: hypertensive disorders of pregnancy, preeclampsia, low birth weight, and preterm birth. Our meta-analyses showed an increased risk for preeclampsia (pooled adjusted odds ratio (aOR) 1.77, 95% CI 1.26–2.48) and hypertensive disorders of pregnancy (pooled aOR 1.55, 95%, CI 1.20–2.00) in pregnancies resulting from IUI with donor sperm compared with IUI with partner sperm. No increased risk was seen for low birth weight or preterm birth after the use of donor sperm in IUI compared with the use of partner sperm in IUI. Subgroup analysis for singletons only did not change these results. The meta-analysis on low birth weight showed a lower risk after in IVF with donor sperm compared with IVF with partner sperm (pooled aOR 0.89, 95% CI 0.83–0.94). For hypertensive disorders of pregnancy, preeclampsia and preterm birth, no difference was found between IVF with donor sperm vs. partner sperm. Patients need to be informed about the moderately increased risk of hypertensive disorders of pregnancy and preeclampsia in pregnancies after IUI with donor sperm. publishedVersion
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- 2022
16. Genome-wide copy number variant and high-throughput transcriptomics analyses of placental tissues underscore persisting child susceptibility in at-risk pregnancies cleared in standard genetic testing
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Czamara, D. (Darina), Cruceanu, C. (Cristiana), Lahti-Pulkkinen, M. (Marius), Dieckmann, L. (Linda), Ködel, M. (Maik), Sauer, S. (Susann), Rex-Haffner, M. (Monika), Sammallahti, S. (Sara), Kajantie, E. (Eero), Laivuori, H. (Hannele), Lahti, J. (Jari), Räikkönen, K. (Katri), Binder, E. B. (Elisabeth B.), Czamara, D. (Darina), Cruceanu, C. (Cristiana), Lahti-Pulkkinen, M. (Marius), Dieckmann, L. (Linda), Ködel, M. (Maik), Sauer, S. (Susann), Rex-Haffner, M. (Monika), Sammallahti, S. (Sara), Kajantie, E. (Eero), Laivuori, H. (Hannele), Lahti, J. (Jari), Räikkönen, K. (Katri), and Binder, E. B. (Elisabeth B.)
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Several studies have shown that children from pregnancies with estimated first-trimester risk based on fetal nuchal translucency thickness and abnormal maternal serum pregnancy protein and hormone levels maintain a higher likelihood of adverse outcomes, even if initial testing for known genetic conditions is negative. We used the Finnish InTraUterine cohort (ITU), which is a comprehensively characterized perinatal cohort consisting of 943 mothers and their babies followed throughout pregnancy and 18 months postnatally, including mothers shortlisted for prenatal genetic testing but cleared for major aneuploidies (cases: n = 544, 57.7%) and control pregnancies (n = 399, 42.3%). Using genome-wide genotyping and RNA sequencing of first-trimester and term placental tissue, combined with medical information from registry data and maternal self-report data, we investigated potential negative medical outcomes and genetic susceptibility to disease and their correlates in placenta gene expression. Case mothers did not present with higher levels of depression, perceived stress, or anxiety during pregnancy. Case children were significantly diagnosed more often with congenital malformations of the circulatory system (4.12 (95% CI [1.22–13.93]) higher hazard) and presented with significantly more copy number duplications as compared to controls (burden analysis, based on all copy number variants (CNVs) with at most 10% frequency, 823 called duplications in 297 cases versus 626 called duplications in 277 controls, p = 0.01). Fifteen genes showed differential gene expression (FDR < 0.1) in association with congenital malformations in first-trimester but not term placenta. These were significantly enriched for genes associated with placental dysfunction. In spite of normal routine follow-up prenatal testing results in early pregnancy, case children presented with an increased likelihood of negative outcomes, which should prompt vigilance in follow-up during pregnancy and
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- 2022
17. Maternal early-pregnancy body mass index-associated metabolomic component and mental and behavioral disorders in children
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Girchenko, P. (Polina), Lahti-Pulkkinen, M. (Marius), Lipsanen, J. (Jari), Heinonen, K. (Kati), Lahti, J. (Jari), Rantalainen, V. (Ville), Hämäläinen, E. (Esa), Laivuori, H. (Hannele), Villa, P. M. (Pia M.), Kajantie, E. (Eero), Räikkönen, K. (Katri), Girchenko, P. (Polina), Lahti-Pulkkinen, M. (Marius), Lipsanen, J. (Jari), Heinonen, K. (Kati), Lahti, J. (Jari), Rantalainen, V. (Ville), Hämäläinen, E. (Esa), Laivuori, H. (Hannele), Villa, P. M. (Pia M.), Kajantie, E. (Eero), and Räikkönen, K. (Katri)
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Maternal pre-pregnancy obesity and/or higher body mass index (BMI) have been associated with neurodevelopmental and mental health adversities in children. While maternal metabolomic perturbations during pregnancy may underpin these associations, the existing evidence is limited to studying individual metabolites, not capturing metabolic variation specific to maternal BMI, and not accounting for the correlated nature of the metabolomic measures. By using multivariate supervised analytical methods, we first identified maternal early-pregnancy BMI-associated metabolomic component during pregnancy. We then examined whether this component was associated with mental and behavioral disorders in children, improved the prediction of the child outcomes over maternal BMI, and what proportion of the effect of maternal BMI on the child outcomes this component mediated. Early-pregnancy BMI of 425 mothers participating in the PREDO study was extracted from the national Medical Birth Register. During pregnancy, mothers donated up to three blood samples, from which a targeted panel of 68 metabolites were measured. Mental and behavioral disorders in children followed-up from birth until 8.4–12.8 years came from the Care Register for Health Care. Of the 68 metabolites averaged across the three sampling points, 43 associated significantly with maternal early-pregnancy BMI yielding a maternal early-pregnancy BMI-associated metabolomic component (total variance explained, 55.4%; predictive ability, 52.0%). This metabolomic component was significantly associated with higher hazard of any mental and behavioral disorder [HR 1.45, 95%CI(1.15, 1.84)] and relative risk of having a higher number of co-morbid disorders [RR 1.43, 95%CI(1.12, 1.69)] in children. It improved the goodness-of-model-fit over maternal BMI by 37.7–65.6%, and hence the predictive significance of the model, and mediated 60.8–75.8% of the effect of maternal BMI on the child outcomes. Maternal BMI-related metabolom
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- 2022
18. Increased risk of preeclampsia in women with a genetic predisposition to elevated blood pressure
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Kivioja, A. (Anna), Toivonen, E. (Elli), Tyrmi, J. (Jaakko), Ruotsalainen, S. (Sanni), Ripatti, S. (Samuli), Huhtala, H. (Heini), Jääskeläinen, T. (Tiina), Heinonen, S. (Seppo), Kajantie, E. (Eero), Kere, J. (Juha), Kivinen, K. (Katja), Pouta, A. (Anneli), Saarela, T. (Tanja), Laivuori, H. (Hannele), Kivioja, A. (Anna), Toivonen, E. (Elli), Tyrmi, J. (Jaakko), Ruotsalainen, S. (Sanni), Ripatti, S. (Samuli), Huhtala, H. (Heini), Jääskeläinen, T. (Tiina), Heinonen, S. (Seppo), Kajantie, E. (Eero), Kere, J. (Juha), Kivinen, K. (Katja), Pouta, A. (Anneli), Saarela, T. (Tanja), and Laivuori, H. (Hannele)
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Background: Preeclampsia causes significant maternal and perinatal morbidity. Genetic factors seem to affect the onset of the disease. We aimed to investigate whether the polygenic risk score for blood pressure (BP; BP-PRS) is associated with preeclampsia, its subtypes, and BP values during pregnancy. Methods: The analyses were performed in the FINNPEC study (Finnish Genetics of Pre-Eclampsia Consortium) cohort of 1514 preeclamptic and 983 control women. In a case-control setting, the data were divided into percentiles to compare women with high BP-PRS (HBP-PRS; >95th percentile) or low BP-PRS (≤5th percentile) to others. Furthermore, to evaluate the effect of BP-PRS on BP, we studied 3 cohorts: women with preeclampsia, hypertensive controls, and normotensive controls. Results: BP values were higher in women with HBP-PRS throughout the pregnancy. Preeclampsia was more common in women with HBP-PRS compared with others (71.8% and 60.1%, respectively; P=0.009), and women with low BP-PRS presented with preeclampsia less frequently than others (44.8% and 61.5%, respectively; P<0.001). HBP-PRS was associated with an increased risk for preeclampsia (odds ratio, 1.7 [95% CI, 1.1–2.5]). Furthermore, women with HBP-PRS presented with recurrent preeclampsia and preeclampsia with severe features more often. Conclusions: Our results suggest that HBP-PRS is associated with an increased risk of preeclampsia, recurrent preeclampsia, and preeclampsia with severe features. Furthermore, women with HBP-PRS present higher BP values during pregnancy. The results strengthen the evidence pointing toward the role of genetic variants associated with BP regulation in the etiology of preeclampsia, especially its more severe forms.
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- 2022
19. Associations of low sex hormone-binding globulin and androgen excess in early pregnancy with fasting and post-prandial hyperglycaemia, gestational diabetes, and its severity
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Mustaniemi, S. (Sanna), Morin-Papunen, L. (Laure), Keikkala, E. (Elina), Öhman, H. (Hanna), Surcel, H.-M. (Heljä-Marja), Kaaja, R. (Risto), Gissler, M. (Mika), Eriksson, J. G. (Johan G.), Laivuori, H. (Hannele), Kajantie, E. (Eero), Vääräsmäki, M. (Marja), Mustaniemi, S. (Sanna), Morin-Papunen, L. (Laure), Keikkala, E. (Elina), Öhman, H. (Hanna), Surcel, H.-M. (Heljä-Marja), Kaaja, R. (Risto), Gissler, M. (Mika), Eriksson, J. G. (Johan G.), Laivuori, H. (Hannele), Kajantie, E. (Eero), and Vääräsmäki, M. (Marja)
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Aims: We studied whether androgen excess and low sex hormone-binding globulin (SHBG) measured in early pregnancy are independently associated with fasting and post-prandial hyperglycaemia, gestational diabetes (GDM), and its severity. Materias and Methods: This nationwide case–control study included 1045 women with GDM and 963 non-diabetic pregnant controls. We measured testosterone (T) and SHBG from biobanked serum samples (mean 10.7 gestational weeks) and calculated the free androgen index (FAI). We first studied their associations with GDM and secondly with the type of hyperglycaemia (fasting, 1 and 2 h glucose concentrations during the oral glucose tolerance test), early-onset GDM (<20 gestational weeks) and the need for anti-diabetic medication. Results: After adjustments for gestational weeks at sampling, pre-pregnancy BMI, and age, women with GDM had 3.7% (95% CI 0.1%–7.3%) lower SHBG levels, 3.1% (95% CI 0.1%–6.2%) higher T levels, and 4.6% (95% CI 1.9%–7.3%) higher FAI levels than controls. SHBG was inversely associated with fasting glucose, whereas higher FAI and T were associated with higher post-prandial glucose concentrations. Women with early-onset GDM had 6.7% (95% CI 0.7%–12.7%) lower SHBG levels and women who needed insulin for fasting hyperglycaemia 8.7% (95% CI 1.8%–14.8%) lower SHBG levels than other women with GDM. Conclusions: Lower SHBG levels were associated especially with early-onset GDM, higher fasting glucose and insulin treatment, whereas androgen excess was associated with higher post-prandial glucose values. Thus, a low SHBG level may reflect the degree of existing insulin resistance, while androgen excess might impair post-prandial insulin secretion.
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- 2022
20. Increased oral care needs and third molar symptoms in women with gestational diabetes mellitus:a finnish gestational diabetes case–control study
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Pukkila, J. (Jenni), Mustaniemi, S. (Sanna), Lingaiah, S. (Shilpa), Lappalainen, O.-P. (Olli-Pekka), Kajantie, E. (Eero), Pouta, A. (Anneli), Kaaja, R. (Risto), Eriksson, J. G. (Johan G.), Laivuori, H. (Hannele), Gissler, M. (Mika), Vääräsmäki, M. (Marja), Keikkala, E. (Elina), Pukkila, J. (Jenni), Mustaniemi, S. (Sanna), Lingaiah, S. (Shilpa), Lappalainen, O.-P. (Olli-Pekka), Kajantie, E. (Eero), Pouta, A. (Anneli), Kaaja, R. (Risto), Eriksson, J. G. (Johan G.), Laivuori, H. (Hannele), Gissler, M. (Mika), Vääräsmäki, M. (Marja), and Keikkala, E. (Elina)
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(1) Hyperglycemia and oral pathology accelerate each other in diabetes. We evaluated whether gestational diabetes mellitus (GDM) is associated with self-reported increased oral health care needs and oral symptoms, including third molar symptoms, during pregnancy. (2) Pregnant women with (n = 1030) and without GDM (n = 935) were recruited in this multicenter Finnish Gestational Diabetes study in 2009–2012. Of the women with GDM, 196 (19.0%) receiving pharmacological treatment, 797 (77.0%) receiving diet treatment and 233 (23.0%) with recurrent GDM were analyzed separately. Oral health was assessed using structured questionnaires and analyzed by multivariable logistic regression adjusted for background risk factors. (3) Women with GDM were more likely to report a higher need for oral care than controls (31.1% vs. 24.5%; odds ratio (OR) 1.39; 95% confidence interval (CI) 1.14–1.69), particularly women with recurrent GDM (38.1% vs. 24.5%; OR 1.90; 95% CI 1.40–2.58). Women with pharmacologically treated GDM (46.9%) more often had third molar symptoms than controls (36.1%; OR 1.57; 95% CI 1.15–2.15) than women with diet-treated GDM (38.0%; OR 1.47; 95% CI 1.07–2.02). (4) GDM is associated with perceived oral care needs. Third molar symptoms were associated with pharmacologically treated GDM.
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- 2022
21. Optimized detection of homologous recombination deficiency improves the prediction of clinical outcomes in cancer
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Perez-Villatoro, F. (Fernando), Oikkonen, J. (Jaana), Casado, J. (Julia), Chernenko, A. (Anastasiya), Gulhan, D. C. (Doga C.), Tumiati, M. (Manuela), Li, Y. (Yilin), Lavikka, K. (Kari), Hietanen, S. (Sakari), Hynninen, J. (Johanna), Haltia, U.-M. (Ulla-Maija), Tyrmi, J. S. (Jaakko S.), Laivuori, H. (Hannele), Konstantinopoulos, P. A. (Panagiotis A.), Hautaniemi, S. (Sampsa), Kauppi, L. (Liisa), Färkkilä, A. (Anniina), Perez-Villatoro, F. (Fernando), Oikkonen, J. (Jaana), Casado, J. (Julia), Chernenko, A. (Anastasiya), Gulhan, D. C. (Doga C.), Tumiati, M. (Manuela), Li, Y. (Yilin), Lavikka, K. (Kari), Hietanen, S. (Sakari), Hynninen, J. (Johanna), Haltia, U.-M. (Ulla-Maija), Tyrmi, J. S. (Jaakko S.), Laivuori, H. (Hannele), Konstantinopoulos, P. A. (Panagiotis A.), Hautaniemi, S. (Sampsa), Kauppi, L. (Liisa), and Färkkilä, A. (Anniina)
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Homologous recombination DNA-repair deficiency (HRD) is a common driver of genomic instability and confers a therapeutic vulnerability in cancer. The accurate detection of somatic allelic imbalances (AIs) has been limited by methods focused on BRCA1/2 mutations and using mixtures of cancer types. Using pan-cancer data, we revealed distinct patterns of AIs in high-grade serous ovarian cancer (HGSC). We used machine learning and statistics to generate improved criteria to identify HRD in HGSC (ovaHRDscar). ovaHRDscar significantly predicted clinical outcomes in three independent patient cohorts with higher precision than previous methods. Characterization of 98 spatiotemporally distinct metastatic samples revealed low intra-patient variation and indicated the primary tumor as the preferred site for clinical sampling in HGSC. Further, our approach improved the prediction of clinical outcomes in triple-negative breast cancer (tnbcHRDscar), validated in two independent patient cohorts. In conclusion, our tumor-specific, systematic approach has the potential to improve patient selection for HR-targeted therapies.
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- 2022
22. Leveraging Northern European population history:novel low-frequency variants for polycystic ovary syndrome
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Tyrmi, J. S. (Jaakko S.), Arffman, R. K. (Riikka K.), Pujol-Gualdo, N. (Natàlia), Kurra, V. (Venla), Morin-Papunen, L. (Laure), Sliz, E. (Eeva), FinnGen Consortium, Estonian Biobank Research Team, Piltonen, T. T. (Terhi T.), Laisk, T. (Triin), Kettunen, J. (Johannes), Laivuori, H. (Hannele), Tyrmi, J. S. (Jaakko S.), Arffman, R. K. (Riikka K.), Pujol-Gualdo, N. (Natàlia), Kurra, V. (Venla), Morin-Papunen, L. (Laure), Sliz, E. (Eeva), FinnGen Consortium, Estonian Biobank Research Team, Piltonen, T. T. (Terhi T.), Laisk, T. (Triin), Kettunen, J. (Johannes), and Laivuori, H. (Hannele)
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Study question: Can we identify novel variants associated with polycystic ovary syndrome (PCOS) by leveraging the unique population history of Northern Europe? Summary answer: We identified three novel genome-wide significant associations with PCOS, with two putative independent causal variants in the checkpoint kinase 2 (CHEK2) gene and a third in myosin X (MYO10). What is known already: PCOS is a common, complex disorder with unknown aetiology. While previous genome-wide association studies (GWAS) have mapped several loci associated with PCOS, the analysis of populations with unique population history and genetic makeup has the potential to uncover new low-frequency variants with larger effects. Study design, size, duration: A population-based case–control GWAS was carried out. Participants/materials, setting, methods: We identified PCOS cases from national registers by ICD codes (ICD-10 E28.2, ICD-9 256.4, or ICD-8 256.90), and all remaining women were considered controls. We then conducted a three-stage case–control GWAS: in the discovery phase, we had a total of 797 cases and 140 558 controls from the FinnGen study. For validation, we used an independent dataset from the Estonian Biobank, including 2812 cases and 89 230 controls. Finally, we performed a joint meta-analysis of 3609 cases and 229 788 controls from both cohorts. Additionally, we reran the association analyses including BMI as a covariate, with 2169 cases and 160 321 controls from both cohorts. Main results and the role of chance: Two out of the three novel genome-wide significant variants associating with PCOS, rs145598156 (P = 3.6×10−8, odds ratio (OR) = 3.01 [2.02–4.50] minor allele frequency (MAF) = 0.005) and rs182075939 (P = 1.9×10−16, OR = 1.69 [1.49–1.91], MAF = 0.04), were found to be enriched in the Finnish and Estonian populations and are tightly linked to a deletion c.1100delC (r2 = 0.95) and a missense I157T (r2 = 0.83) in CHEK2. The third novel association is a common variant
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- 2022
23. Cohort profile:InTraUterine sampling in early pregnancy (ITU), a prospective pregnancy cohort study in Finland:study design and baseline characteristics
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Kvist, T. (Tuomas), Sammallahti, S. (Sara), Lahti-Pulkkinen, M. (Marius), Cruceanu, C. (Cristiana), Czamara, D. (Darina), Dieckmann, L. (Linda), Tontsch, A. (Alina), Röh, S. (Simone), Rex-Haffner, M. (Monika), Wolford, E. (Eiina), Reynolds, R. (Rebecca), Eriksson, J. (Johan), Suomalainen-König, S. (Sanna), Laivuori, H. (Hannele), Kajantie, E. (Eero), Lahdensuo, E. (Eija), Binder, E. (Elisabeth), Räikkönen, K. (Katri), Kvist, T. (Tuomas), Sammallahti, S. (Sara), Lahti-Pulkkinen, M. (Marius), Cruceanu, C. (Cristiana), Czamara, D. (Darina), Dieckmann, L. (Linda), Tontsch, A. (Alina), Röh, S. (Simone), Rex-Haffner, M. (Monika), Wolford, E. (Eiina), Reynolds, R. (Rebecca), Eriksson, J. (Johan), Suomalainen-König, S. (Sanna), Laivuori, H. (Hannele), Kajantie, E. (Eero), Lahdensuo, E. (Eija), Binder, E. (Elisabeth), and Räikkönen, K. (Katri)
- Abstract
Purpose: The InTraUterine sampling in early pregnancy (ITU) is a prospective pregnancy cohort study. The overarching aim of ITU is to unravel genomic, epigenomic, transcriptomic, endocrine, inflammatory and metabolic maternal-placental-fetal mechanisms involved in the programming of health and disease after exposure to prenatal environmental adversity, such as maternal malnutrition, cardiometabolic disorders, infections, medical interventions, mental disorders and psychosocial stress. This paper describes the study protocol, design and baseline characteristics of the cohort. Participants: We included 944 pregnant Finnish women, their partners and children born alive between April 2012 and December 2017. The women were recruited through the national, voluntary trisomy 21 screening between 9+0 and 21+6 gestational weeks. Of the participating women, 543 were screen positive and underwent fetal chromosomal testing. Test result of these women suggested no fetal chromosomal abnormality. Further, we recruited 401 women who were screen negative and who did not undergo fetal chromosomal testing. Findings to date: We have collected chorionic villi and amniotic fluid from the screen-positive women; blood, urine, buccal swabs and diurnal salivary samples from all women; blood and buccal swabs from all partners; and placenta, cord blood and buccal swabs from all newborns for analyses of the genome, epigenome, transcriptome, and endocrine, inflammatory and metabolic markers. These data are coupled with comprehensive phenotypes, including questions on demographic characteristics, health and well-being of the women and their partners during pregnancy and of the women and their children at the child’s age of 1.7 and 3 years. Data also come from patient records and nationwide registers covering health, lifestyle and medication data. Future plans: Multiple layers of ITU data allow integrative data analyses, which translate to biomarker identification and allow risk stratifica
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- 2022
24. Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes
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Pervjakova, N. (Natalia), Moen, G.-H. (Gunn-Helen), Borges, M.-C. (Maria-Carolina), Ferreira, T. (Teresa), Cook, J. P. (James P.), Allard, C. (Catherine), Beaumont, R. N. (Robin N.), Canouil, M. (Mickael), Hatem, G. (Gad), Heiskala, A. (Anni), Joensuu, A. (Anni), Karhunen, V. (Ville), Kwak, S. H. (Soo Heon), Lin, F. T. (Frederick T. J.), Liu, J. (Jun), Rifas-Shiman, S. (Sheryl), Tam, C. H. (Claudia H.), Tam, W. H. (Wing Hung), Thorleifsson, G. (Gudmar), Andrew, T. (Toby), Auvinen, J. (Juha), Bhowmik, B. (Bishwajit), Bonnefond, A. (Amelie), Delahaye, F. (Fabien), Demirkan, A. (Ayse), Froguel, P. (Philippe), Haller-Kikkatalo, K. (Kadri), Hardardottir, H. (Hildur), Hummel, S. (Sandra), Hussain, A. (Akhtar), Kajantie, E. (Eero), Keikkala, E. (Elina), Khamis, A. (Amna), Lahti, J. (Jari), Lekva, T. (Tove), Mustaniemi, S. (Sanna), Sommer, C. (Christine), Tagoma, A. (Aili), Tzala, E. (Evangelia), Uibo, R. (Raivo), Vääräsmäki, M. (Marja), Villa, P. M. (Pia M.), Birkeland, K. I. (Kare, I), Bouchard, L. (Luigi), Duijn, C. M. (Cornelia M.), Finer, S. (Sarah), Groop, L. (Leif), Hamalainen, E. (Esa), Hayes, G. M. (Geoffrey M.), Hitman, G. A. (Graham A.), Jang, H. C. (Hak C.), Järvelin, M.-R. (Marjo-Riitta), Jenum, A. K. (Anne Karen), Laivuori, H. (Hannele), Ma, R. C. (Ronald C.), Melander, O. (Olle), Oken, E. (Emily), Park, K. S. (Kyong Soo), Perron, P. (Patrice), Prasad, R. B. (Rashmi B.), Qvigstad, E. (Elisabeth), Sebert, S. (Sylvain), Stefansson, K. (Kari), Steinthorsdottir, V. (Valgerdur), Tuomi, T. (Tiinamaija), Hivert, M.-F. (Marie-France), Franks, P. W. (Paul W.), McCarthy, M. I. (Mark, I), Lindgren, C. M. (Cecilia M.), Freathy, R. M. (Rachel M.), Lawlor, D. A. (Deborah A.), Morris, A. P. (Andrew P.), Magi, R. (Reedik), Pervjakova, N. (Natalia), Moen, G.-H. (Gunn-Helen), Borges, M.-C. (Maria-Carolina), Ferreira, T. (Teresa), Cook, J. P. (James P.), Allard, C. (Catherine), Beaumont, R. N. (Robin N.), Canouil, M. (Mickael), Hatem, G. (Gad), Heiskala, A. (Anni), Joensuu, A. (Anni), Karhunen, V. (Ville), Kwak, S. H. (Soo Heon), Lin, F. T. (Frederick T. J.), Liu, J. (Jun), Rifas-Shiman, S. (Sheryl), Tam, C. H. (Claudia H.), Tam, W. H. (Wing Hung), Thorleifsson, G. (Gudmar), Andrew, T. (Toby), Auvinen, J. (Juha), Bhowmik, B. (Bishwajit), Bonnefond, A. (Amelie), Delahaye, F. (Fabien), Demirkan, A. (Ayse), Froguel, P. (Philippe), Haller-Kikkatalo, K. (Kadri), Hardardottir, H. (Hildur), Hummel, S. (Sandra), Hussain, A. (Akhtar), Kajantie, E. (Eero), Keikkala, E. (Elina), Khamis, A. (Amna), Lahti, J. (Jari), Lekva, T. (Tove), Mustaniemi, S. (Sanna), Sommer, C. (Christine), Tagoma, A. (Aili), Tzala, E. (Evangelia), Uibo, R. (Raivo), Vääräsmäki, M. (Marja), Villa, P. M. (Pia M.), Birkeland, K. I. (Kare, I), Bouchard, L. (Luigi), Duijn, C. M. (Cornelia M.), Finer, S. (Sarah), Groop, L. (Leif), Hamalainen, E. (Esa), Hayes, G. M. (Geoffrey M.), Hitman, G. A. (Graham A.), Jang, H. C. (Hak C.), Järvelin, M.-R. (Marjo-Riitta), Jenum, A. K. (Anne Karen), Laivuori, H. (Hannele), Ma, R. C. (Ronald C.), Melander, O. (Olle), Oken, E. (Emily), Park, K. S. (Kyong Soo), Perron, P. (Patrice), Prasad, R. B. (Rashmi B.), Qvigstad, E. (Elisabeth), Sebert, S. (Sylvain), Stefansson, K. (Kari), Steinthorsdottir, V. (Valgerdur), Tuomi, T. (Tiinamaija), Hivert, M.-F. (Marie-France), Franks, P. W. (Paul W.), McCarthy, M. I. (Mark, I), Lindgren, C. M. (Cecilia M.), Freathy, R. M. (Rachel M.), Lawlor, D. A. (Deborah A.), Morris, A. P. (Andrew P.), and Magi, R. (Reedik)
- Abstract
Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 x 10-8) with GDM, mapping to/near MTNR1B (P = 4.3 x 10-54), TCF7L2 (P = 4.0 x 10-16), CDKAL1 (P = 1.6 x 10-14), CDKN2A-CDKN2B (P = 4.1 x 10-9) and HKDC1 (P = 2.9 x 10-8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.
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- 2022
25. Maternal postpartum depressive symptoms partially mediate the association between preterm birth and mental and behavioral disorders in children
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Girchenko, P. (Polina), Robinson, R. (Rachel), Rantalainen, V. J. (Ville Juhani), Lahti-Pulkkinen, M. (Marius), Heinonen-Tuomaala, K. (Kati), Lemola, S. (Sakari), Wolke, D. (Dieter), Schnitzlein, D. (Daniel), Hämäläinen, E. (Esa), Laivuori, H. (Hannele), Villa, P. M. (Pia M.), Kajantie, E. (Eero), Räikkönen, K. (Katri), Girchenko, P. (Polina), Robinson, R. (Rachel), Rantalainen, V. J. (Ville Juhani), Lahti-Pulkkinen, M. (Marius), Heinonen-Tuomaala, K. (Kati), Lemola, S. (Sakari), Wolke, D. (Dieter), Schnitzlein, D. (Daniel), Hämäläinen, E. (Esa), Laivuori, H. (Hannele), Villa, P. M. (Pia M.), Kajantie, E. (Eero), and Räikkönen, K. (Katri)
- Abstract
Preterm birth has been linked with postpartum depressive (PPD) disorders and high symptom levels, but evidence remains conflicting and limited in quality. It remains unclear whether PPD symptoms of mothers with preterm babies were already elevated before childbirth, and whether PPD symptoms mediate/aggravate the effect of preterm birth on child mental disorders. We examined whether preterm birth associated with maternal PPD symptoms, depressive symptoms trajectories from antenatal to postpartum stage, and whether PPD symptoms mediated/aggravated associations between preterm birth and child mental disorders. Mothers of preterm (n = 125) and term-born (n = 3033) children of the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction study reported depressive symptoms four times within 8 weeks before and twice within 12 months after childbirth. Child mental and behavioral disorder diagnoses until age 8.4–12.8 years came from medical register. Preterm birth associated with higher PPD symptoms (mean difference = 0.19 SD, 95% CI 0.01, 0.37, p = 0.04), and higher odds (odds ratio = 2.23, 95% CI 1.22, 4.09, p = 0.009) of the mother to belong to a group that had consistently high depressive symptoms levels trajectory from antenatal to postpartum stage. PPD symptoms partially mediated and aggravated the association between preterm birth and child mental disorders. Preterm birth, maternal PPD symptoms and child mental disorders are associated, calling for timely prevention interventions.
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- 2022
26. Reliability of a novel approach for reference-based cell type estimation in human placental DNA methylation studies
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Dieckmann, L. (Linda), Cruceanu, C. (Cristiana), Lahti-Pulkkinen, M. (Marius), Lahti, J. (Jari), Kvist, T. (Tuomas), Laivuori, H. (Hannele), Sammallahti, S. (Sara), Villa, P. M. (Pia M.), Suomalainen-König, S. (Sanna), Rancourt, R. C. (Rebecca C.), Plagemann, A. (Andreas), Henrich, W. (Wolfgang), Eriksson, J. G. (Johan G.), Kajantie, E. (Eero), Entringer, S. (Sonja), Braun, T. (Thorsten), Räikkönen, K. (Katri), Binder, E. B. (Elisabeth B.), Czamara, D. (Darina), Dieckmann, L. (Linda), Cruceanu, C. (Cristiana), Lahti-Pulkkinen, M. (Marius), Lahti, J. (Jari), Kvist, T. (Tuomas), Laivuori, H. (Hannele), Sammallahti, S. (Sara), Villa, P. M. (Pia M.), Suomalainen-König, S. (Sanna), Rancourt, R. C. (Rebecca C.), Plagemann, A. (Andreas), Henrich, W. (Wolfgang), Eriksson, J. G. (Johan G.), Kajantie, E. (Eero), Entringer, S. (Sonja), Braun, T. (Thorsten), Räikkönen, K. (Katri), Binder, E. B. (Elisabeth B.), and Czamara, D. (Darina)
- Abstract
The placenta is a central organ during early development, influencing trajectories of health and disease. DNA methylation (DNAm) studies of human placenta improve our understanding of how its function relates to disease risk. However, DNAm studies can be biased by cell type heterogeneity, so it is essential to control for this in order to reduce confounding and increase precision. Computational cell type deconvolution approaches have proven to be very useful for this purpose. For human placenta, however, an assessment of the performance of these estimation methods is still lacking. Here, we examine the performance of a newly available reference-based cell type estimation approach and compare it to an often-used reference-free cell type estimation approach, namely RefFreeEWAS, in placental genome-wide DNAm samples taken at birth and from chorionic villus biopsies early in pregnancy using three independent studies comprising over 1000 samples. We found both reference-free and reference-based estimated cell type proportions to have predictive value for DNAm, however, reference-based cell type estimation outperformed reference-free estimation for the majority of data sets. Reference-based cell type estimations mirror previous histological knowledge on changes in cell type proportions through gestation. Further, CpGs whose variation in DNAm was largely explained by reference-based estimated cell type proportions were in the proximity of genes that are highly tissue-specific for placenta. This was not the case for reference-free estimated cell type proportions. We provide a list of these CpGs as a resource to help researchers to interpret results of existing studies and improve future DNAm studies of human placenta.
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- 2022
27. Characteristics of preeclampsia in donor cell gestations
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Ervaala, A. (Attina), Laivuori, H. (Hannele), Gissler, M. (Mika), Kere, J. (Juha), Kivinen, K. (Katja), Pouta, A. (Anneli), Kajantie, E. (Eero), Heinonen, S. (Seppo), Wedenoja, S. (Satu), Ervaala, A. (Attina), Laivuori, H. (Hannele), Gissler, M. (Mika), Kere, J. (Juha), Kivinen, K. (Katja), Pouta, A. (Anneli), Kajantie, E. (Eero), Heinonen, S. (Seppo), and Wedenoja, S. (Satu)
- Abstract
Pregnancies conceived through donor oocytes or sperm show increased risk for preeclampsia. We studied this issue in a preeclampsia case-control cohort (n = 2778), and found overrepresentation of donor cell gestations among women with preeclampsia (14/1627, 0.86%; OR 1.81; 95% CI: 1.07–3.08; P = 0.025) compared to the population data. Moreover, we observed excess of male births from donor cell pregnancies (male-to-female ratio 2.5 vs. 0.97; OR 2.57; 95% CI 1.02–6.36; P = 0.043). Maternal age (36.7 vs. 30.2; P < 0.0001) and preterm deliveries (64% vs. 38%; P = 0.046) distinguished donor cell gestations from other pregnancies with preeclampsia. These results support foreign fetal antigens as modulators of preeclampsia.
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- 2022
28. Quantitative urine proteomics in pregnant women for the identification of predictive biomarkers for preeclampsia
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Joenväärä, S. (Sakari), Holm, M. (Matilda), Saraswat, M. (Mayank), Agarwal, R. (Rahul), Tohmola, T. (Tiialotta), Kajantie, E. (Eero), Räikkönen, K. (Katri), Laivuori, H. (Hannele), Villa, P. M. (Pia M.), Hämäläinen, E. (Esa), Renkonen, R. (Risto), Joenväärä, S. (Sakari), Holm, M. (Matilda), Saraswat, M. (Mayank), Agarwal, R. (Rahul), Tohmola, T. (Tiialotta), Kajantie, E. (Eero), Räikkönen, K. (Katri), Laivuori, H. (Hannele), Villa, P. M. (Pia M.), Hämäläinen, E. (Esa), and Renkonen, R. (Risto)
- Abstract
Background: Preeclampsia (PE) is a life-threatening disease characterized by elevated blood pressure and proteinuria. Predictive biomarkers of PE are needed, especially those predicting PE in early pregnancy. The aim of this pilot study was to identify urine proteins that could be candidates for new non-invasive markers for PE. Methods: Urine samples at three time points of pregnancy (12–14, 18–20 and 26–28 weeks of gestation) were prospectively collected from high-risk women who subsequently developed PE (n = 7), high-risk women who did not develop PE (n = 6), and women without known risk factors for PE (n = 4). The samples were analyzed using mass spectrometry and we subsequently quantified 361 proteins used for further analysis. Rigorous statistical analysis with multiple methods was performed to identify biomarker candidates. Results: Of the clinical risk factors analyzed, pre-pregnancy body mass index (BMIBP) was found to be the most important predictor of PE. We identified multiple proteins that correlated with BMIBP and could improve the prediction of PE in combination with BMIBP. Other statistical analyses identified six proteins that each could differentiate women who subsequently developed PE from those who did not at all three time points. Conclusions: We identified multiple urine proteins that could be used to predict PE in combination with BMIBP. We also identified six proteins that are strong candidates for predicting PE already in early pregnancy.
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- 2022
29. Obstetric and perinatal risks after the use of donor sperm:A systematic review and meta-analysis
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Pohjonen, E. M., Söderström-Anttila, V., Bergh, C., Loft, A., Magnusson, Pinborg, A., Oldereid, N. B., Petzold, M., Romundstad, L. B., Laivuori, H., Pohjonen, E. M., Söderström-Anttila, V., Bergh, C., Loft, A., Magnusson, Pinborg, A., Oldereid, N. B., Petzold, M., Romundstad, L. B., and Laivuori, H.
- Abstract
Donor sperm is widely used in infertility treatments. The purpose of the study was to investigate, whether use of donor sperm in intrauterine insemination (IUI) or in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) treatments affect maternal and perinatal risks compared with spontaneously conceived pregnancies or use of partner sperm in IUI, IVF or ICSI. We provide a systematic review and meta-analyses on the most clinically relevant obstetric and perinatal outcomes after use of donor sperm compared with partner sperm: hypertensive disorders of pregnancy, preeclampsia, low birth weight, and preterm birth. Our meta-analyses showed an increased risk for preeclampsia (pooled adjusted odds ratio (aOR) 1.77, 95% CI 1.26–2.48) and hypertensive disorders of pregnancy (pooled aOR 1.55, 95%, CI 1.20–2.00) in pregnancies resulting from IUI with donor sperm compared with IUI with partner sperm. No increased risk was seen for low birth weight or preterm birth after the use of donor sperm in IUI compared with the use of partner sperm in IUI. Subgroup analysis for singletons only did not change these results. The meta-analysis on low birth weight showed a lower risk after in IVF with donor sperm compared with IVF with partner sperm (pooled aOR 0.89, 95% CI 0.83–0.94). For hypertensive disorders of pregnancy, preeclampsia and preterm birth, no difference was found between IVF with donor sperm vs. partner sperm. Patients need to be informed about the moderately increased risk of hypertensive disorders of pregnancy and preeclampsia in pregnancies after IUI with donor sperm.
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- 2022
30. Factor V Leiden as a risk factor for preterm birth – a population‐based nested case–control study
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HILTUNEN, L.M., LAIVUORI, H., RAUTANEN, A., KAAJA, R., KERE, J., KRUSIUS, T., RASI, V., and PAUNIO, M.
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- 2011
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31. External validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysis
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Snell, K, Allotey, J, Smuk, M, Hooper, R, Chan, C, Ahmed, A, Chappell, L, Von Dadelszen, P, Green, M, Kenny, L, Khalil, A, Khan, K, Mol, B, Myers, J, Poston, L, Thilaganathan, B, Staff, A, Smith, G, Ganzevoort, W, Laivuori, H, Odibo, A, Arenas Ramirez, J, Kingdom, J, Daskalakis, G, Farrar, D, Baschat, A, Seed, P, Prefumo, F, da Silva Costa, F, Groen, H, Audibert, F, Masse, J, Skrastad, R, Salvesen, K, Haavaldsen, C, Nagata, C, Rumbold, A, Heinonen, S, Askie, L, Smits, L, Vinter, C, Magnus, P, Eero, K, Villa, P, Jenum, A, Andersen, L, Norman, J, Ohkuchi, A, Eskild, A, Bhattacharya, S, Mcauliffe, F, Galindo, A, Herraiz, I, Carbillon, L, Klipstein-Grobusch, K, Yeo, S, Browne, J, Moons, K, Riley, R, Thangaratinam, S, Vergani, P, Snell K. I. E., Allotey J., Smuk M., Hooper R., Chan C., Ahmed A., Chappell L. C., Von Dadelszen P., Green M., Kenny L., Khalil A., Khan K. S., Mol B. W., Myers J., Poston L., Thilaganathan B., Staff A. C., Smith G. C. S., Ganzevoort W., Laivuori H., Odibo A. O., Arenas Ramirez J., Kingdom J., Daskalakis G., Farrar D., Baschat A. A., Seed P. T., Prefumo F., da Silva Costa F., Groen H., Audibert F., Masse J., Skrastad R. B., Salvesen K. A., Haavaldsen C., Nagata C., Rumbold A. R., Heinonen S., Askie L. M., Smits L. J. M., Vinter C. A., Magnus P., Eero K., Villa P. M., Jenum A. K., Andersen L. B., Norman J. E., Ohkuchi A., Eskild A., Bhattacharya S., McAuliffe F. M., Galindo A., Herraiz I., Carbillon L., Klipstein-Grobusch K., Yeo S. A., Browne J. L., Moons K. G. M., Riley R. D., Thangaratinam S., Vergani P., Snell, K, Allotey, J, Smuk, M, Hooper, R, Chan, C, Ahmed, A, Chappell, L, Von Dadelszen, P, Green, M, Kenny, L, Khalil, A, Khan, K, Mol, B, Myers, J, Poston, L, Thilaganathan, B, Staff, A, Smith, G, Ganzevoort, W, Laivuori, H, Odibo, A, Arenas Ramirez, J, Kingdom, J, Daskalakis, G, Farrar, D, Baschat, A, Seed, P, Prefumo, F, da Silva Costa, F, Groen, H, Audibert, F, Masse, J, Skrastad, R, Salvesen, K, Haavaldsen, C, Nagata, C, Rumbold, A, Heinonen, S, Askie, L, Smits, L, Vinter, C, Magnus, P, Eero, K, Villa, P, Jenum, A, Andersen, L, Norman, J, Ohkuchi, A, Eskild, A, Bhattacharya, S, Mcauliffe, F, Galindo, A, Herraiz, I, Carbillon, L, Klipstein-Grobusch, K, Yeo, S, Browne, J, Moons, K, Riley, R, Thangaratinam, S, Vergani, P, Snell K. I. E., Allotey J., Smuk M., Hooper R., Chan C., Ahmed A., Chappell L. C., Von Dadelszen P., Green M., Kenny L., Khalil A., Khan K. S., Mol B. W., Myers J., Poston L., Thilaganathan B., Staff A. C., Smith G. C. S., Ganzevoort W., Laivuori H., Odibo A. O., Arenas Ramirez J., Kingdom J., Daskalakis G., Farrar D., Baschat A. A., Seed P. T., Prefumo F., da Silva Costa F., Groen H., Audibert F., Masse J., Skrastad R. B., Salvesen K. A., Haavaldsen C., Nagata C., Rumbold A. R., Heinonen S., Askie L. M., Smits L. J. M., Vinter C. A., Magnus P., Eero K., Villa P. M., Jenum A. K., Andersen L. B., Norman J. E., Ohkuchi A., Eskild A., Bhattacharya S., McAuliffe F. M., Galindo A., Herraiz I., Carbillon L., Klipstein-Grobusch K., Yeo S. A., Browne J. L., Moons K. G. M., Riley R. D., Thangaratinam S., and Vergani P.
- Abstract
BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. METHODS: IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. RESULTS: Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model's calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions
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- 2020
32. Maternal depressive symptoms during pregnancy, placental expression of genes regulating glucocorticoid and serotonin function and infant regulatory behaviors
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Räikkönen, K., Pesonen, A.-K., OʼReilly, J. R., Tuovinen, S., Lahti, M., Kajantie, E., Villa, P., Laivuori, H., Hämäläinen, E., Seckl, J. R., and Reynolds, R. M.
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- 2015
- Full Text
- View/download PDF
33. The role of endothelial surface layer and renal markers to predict superimposed pre-eclampsia in women with chronic hypertension: O1.4
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Bramham, K, Villa, P, Laivuori, H, Seed, P, Poston, L, and Chappell, L
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- 2015
34. External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications ( <scp>IPPIC</scp> ) Network database: individual participant data meta‐analysis
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Allotey, J, Whittle, R, Snell, KIE, Smuk, M, Townsend, R, Dadelszen, P, Heazell, AEP, Magee, L, Smith, GCS, Sandall, J, Thilaganathan, B, Zamora, J, Riley, RD, Khalil, A, Thangaratinam, S, Coomarasamy, A, Kwong, A, Savitri, AI, Salvesen, KÅ, Bhattacharya, S, Uiterwaal, CSPM, Staff, AC, Andersen, LB, Olive, EL, Redman, C, Sletner, L, Daskalakis, G, Macleod, M, Abdollahain, M, Ramírez, JA, Massé, J, Audibert, F, Magnus, PM, Jenum, AK, Baschat, A, Ohkuchi, A, McAuliffe, FM, West, J, Askie, LM, Mone, F, Farrar, D, Zimmerman, PA, Smits, LJM, Riddell, C, Kingdom, JC, Post, J, Illanes, SE, Holzman, C, Kuijk, SMJ, Carbillon, L, Villa, PM, Eskild, A, Chappell, L, Prefumo, F, Velauthar, L, Seed, P, Oostwaard, M, Verlohren, S, Poston, L, Ferrazzi, E, Vinter, CA, Nagata, C, Brown, M, Vollebregt, KC, Takeda, S, Langenveld, J, Widmer, M, Saito, S, Haavaldsen, C, Carroli, G, Olsen, J, Wolf, H, Zavaleta, N, Eisensee, I, Vergani, P, Lumbiganon, P, Makrides, M, Facchinetti, F, Sequeira, E, Gibson, R, Ferrazzani, S, Frusca, T, Norman, JE, Figueiró‐Filho, EA, Lapaire, O, Laivuori, H, Lykke, JA, Conde‐Agudelo, A, Galindo, A, Mbah, A, Betran, AP, Herraiz, I, Trogstad, L, Smith, GGS, Steegers, EAP, Salim, R, Huang, T, Adank, A, Zhang, J, Meschino, WS, Browne, JL, Allen, RE, Costa, F Da Silva, Klipstein‐Grobusch, K, Crowther, CA, Jørgensen, JS, Forest, J‐C, Rumbold, AR, Mol, BW, Giguère, Y, Kenny, LC, Ganzevoort, W, Odibo, AO, Myers, J, Yeo, SA, Goffinet, F, McCowan, L, Pajkrt, E, Teede, HJ, Haddad, BG, Dekker, G, Kleinrouweler, EC, LeCarpentier, É, Roberts, CT, Groen, H, Skråstad, RB, Heinonen, S, Eero, K, Anggraini, D, Souka, A, Cecatti, JG, Monterio, I, Pillalis, A, Souza, R, Hawkins, LA, Gabbay‐Benziv, R, Crovetto, F, Figuera, F, Jorgensen, L, Dodds, J, Patel, M, Aviram, A, Papageorghiou, A, and Khan, K
- Abstract
Objective: Stillbirth is a potentially preventable complication of pregnancy. Identifying women at risk can guide decisions on closer surveillance or timing of birth to prevent fetal death.Prognostic models have been developed to predict the risk of stillbirth, but none have yet been externally validated. We externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods: We searched Medline, EMBASE, DH-DATA and AMED databases from inception to December 2020 to identify stillbirth prediction models. We included studies that developed or updated prediction models for stillbirth for use at any time during pregnancy. IPD from cohorts within the International Prediction of Pregnancy Complication (IPPIC) Network were used to externally validate the identified prediction models whose individual variables were available in the IPD. We assessed the risk of bias of the models and IPD using PROBAST, and reported discriminative performance using the C-statistic, and calibration performance using calibration plots, calibration slopeand calibration-in-the-large. We estimated performance measures separately in each study, and then summarised across studies using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results: We identified 17 studies reporting the development of 40 prognostic models for stillbirth. None of the models were previously externally validated, and only a fifth (20%, 8/40) reported the full model equation. We were able to validate three of these models using the IPD from 19 cohort studies (491,201 pregnant women) within the IPPIC Network database. Based on evaluating their development studies, all three models had an overall high risk of bias according to PROBAST. In our IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65; summary calibration slopes of 0.40to 0.88, and generally with observed risks predictions that were too extreme compared to observed risks; and little to no clinical utility as assessed by net benefit. However, there remained uncertainty in performance for some models due to small available sample sizes. Conclusion: The three validated models generally showed poor and uncertain predictive performancein new data, with limited evidence to support their clinical application. Findings suggest methodological shortcomings in their development including overfitting of models. Further research is needed to further validate these and other models, identify stronger prognostic factors, and to develop more robust prediction models
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- 2021
35. Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices
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Natarajan, P. (Pradeep), Pampana, A. (Akhil), Graham, S. E. (Sarah E.), Ruotsalainen, S. E. (Sanni E.), Perry, J. A. (James A.), de Vries, P. S. (Paul S.), Broome, J. G. (Jai G.), Pirruccello, J. P. (James P.), Honigbere, M. C. (Michael C.), Aragam, K. (Krishna), Wolford, B. (Brooke), Brody, J. A. (Jennifer A.), Antonacci-Fulton, L. (Lucinda), Arden, M. (Moscati), Aslibekyan, S. (Stella), Assimes, T. L. (Themistocles L.), Ballantyne, C. M. (Christie M.), Bielak, L. F. (Lawrence F.), Bisl, J. C. (Joshua C.), Cade, B. E. (Brian E.), Do, R. (Ron), Doddapaneni, H. (Harsha), Emery, L. S. (Leslie S.), Hung, Y.-J. (Yi-Jen), Irvin, M. R. (Marguerite R.), Khan, A. T. (Alyna T.), Lange, L. (Leslie), Lee, J. (Jiwon), Lemaitre, R. N. (Rozenn N.), Martin, L. W. (Lisa W.), Metcalf, G. (Ginger), Montasser, M. E. (May E.), Moon, J.-Y. (Jee-Young), Muzny, D. (Donna), Connell, J. R. (Jeffrey R. O.), Palmer, N. D. (Nicholette D.), Peralta, J. M. (Juan M.), Peyser, P. A. (Patricia A.), Stilp, A. M. (Adrienne M.), Tsai, M. (Michael), Wang, F. F. (Fei Fei), Weeks, D. E. (Daniel E.), Yanek, L. R. (Lisa R.), Wilson, J. G. (James G.), Abecasis, G. (Goncalo), Arnett, D. K. (Donna K.), Becker, L. C. (Lewis C.), Blangercy, J. (John), Boerwinkle, E. (Eric), Bowden, D. W. (Donald W.), Chang, Y.-C. (Yi-Cheng), Chen, Y. I. (Yii-Der, I), Choi, W. J. (Won Jung), Correa, A. (Adolfo), Curran, J. E. (Joanne E.), Daly, M. J. (Mark J.), DutcherE, S. K. (Susan K.), Ellinor, P. T. (Patrick T.), Fornage, M. (Myriam), Freedman, B. I. (Barry, I), Gabriel, S. (Stacey), Germer, S. (Soren), Gibbs, R. A. (Richard A.), He, J. (Jiang), Hveem, K. (Kristian), Jarvik, G. P. (Gail P.), Kaplan, R. C. (Robert C.), Kardia, S. L. (Sharon L. R.), Kennyn, E. (Eimear), Kim, R. W. (Ryan W.), Kooperberg, C. (Charles), Laurie, C. C. (Cathy C.), Lee, S. (Seonwook), Lloyd-Jones, D. M. (Don M.), Loos, R. J. (Ruth J. F.), Lubitz, S. A. (Steven A.), Mathias, R. A. (Rasika A.), Martinez, K. A. (Karine A. Viaud), McGarvey, S. T. (Stephen T.), Mitche, B. D. (Braxton D.), Nickerson, D. A. (Deborah A.), North, K. E. (Kari E.), Palotie, A. (Aarno), Park, C. J. (Cheol Joo), Psat, B. M. (Bruce M. Y.), Rao, D. C. (D. C.), Redline, S. (Susan), Reiner, A. P. (Alexander P.), Seo, D. (Daekwan), Seo, J.-S. (Jeong-Sun), Smith, A. V. (Albert, V), Tracy, R. P. (Russell P.), Kathiresan, S. (Sekar), Cupples, L. A. (L. Adrienne), Rotten, J. I. (Jerome, I), Morrison, A. C. (Alanna C.), Rich, S. S. (Stephen S.), Ripatti, S. (Samuli), Wilier, C. (Cristen), Peloso, G. M. (Gina M.), Vasan, R. S. (Ramachandran S.), Abe, N. (Namiko), Albert, C. (Christine), Almasy, L. (Laura), Alonso, A. (Alvaro), Ament, S. (Seth), Anderson, P. (Peter), Applebaum-Bowden, D. (Deborah), Arking, D. (Dan), Ashley-Koch, A. (Allison), Auer, P. (Paul), Avramopoulos, D. (Dimitrios), Barnard, J. (John), Barnes, K. (Kathleen), Barr, R. G. (R. Graham), Barron-Casella, E. (Emily), Beaty, T. (Terri), Becker, D. (Diane), Beer, R. (Rebecca), Begum, F. (Ferdouse), Beitelshees, A. (Amber), Benjamin, E. (Emelia), Bezerra, M. (Marcos), Bielak, L. (Larry), Blackwel, T. (Thomas), Bowler, R. (Russell), Broecke, U. (Ulrich), Bunting, K. (Karen), Burchard, E. (Esteban), Buth, E. (Erin), Cardwel, J. (Jonathan), Carty, C. (Cara), Casaburi, R. (Richard), Casella, J. (James), Chaffin, M. (Mark), Chang, C. (Christy), Chasman, D. (Daniel), Chavan, S. (Sameer), Chen, B.-J. (Bo-Juen), Chen, W.-M. (Wei-Min), Chol, M. (Michael), Choi, S. H. (Seung Hoan), Chuang, L.-M. (Lee-Ming), Chung, M. (Mina), Conomos, M. P. (Matthew P.), Cornell, E. (Elaine), Crapo, J. (James), Curtis, J. (Jeffrey), Custer, B. (Brian), Damcott, C. (Coleen), Darbar, D. (Dawood), Das, S. (Sayantan), David, S. (Sean), Davis, C. (Colleen), Daya, M. (Michelle), de Andrade, M. (Mariza), DeBaunuo, M. (Michael), Duan, Q. (Qing), Devine, R. D. (Ranjan Deka Dawn DeMeo Scott), Duggirala, Q. R. (Qing Ravi), Durda, J. P. (Jon Peter), Dutcher, S. (Susan), Eaton, C. (Charles), Ekunwe, L. (Lynette), Farber, C. (Charles), Farnaml, L. (Leanna), Fingerlin, T. (Tasha), Flickinger, M. (Matthew), Franceschini, N. (Nora), Fu, M. (Mao), Fullerton, S. M. (Stephanie M.), Fulton, L. (Lucinda), Gan, W. (Weiniu), Gao, Y. (Yan), Gass, M. (Margery), Ge, B. (Bruce), Geng, X. P. (Xiaoqi Priscilla), Gignoux, C. (Chris), Gladwin, M. (Mark), Glahn, D. (David), Gogarten, S. (Stephanie), Gong, D.-W. (Da-Wei), Goring, H. (Harald), Gu, C. C. (C. Charles), Guan, Y. (Yue), Guo, X. (Xiuqing), Haessler, J. (Jeff), Hall, M. (Michael), Harris, D. (Daniel), Hawle, N. Y. (Nicola Y.), Heavner, B. (Ben), Heckbert, S. (Susan), Hernandez, R. (Ryan), Herrington, D. (David), Hersh, C. (Craig), Hidalgo, B. (Bertha), Hixson, J. (James), Hokanson, J. (John), Hong, E. (Elliott), Hoth, K. (Karin), Hsiung, C. A. (Chao Agnes), Huston, H. (Haley), Hwu, C. M. (Chii Min), Jackson, R. (Rebecca), Jain, D. (Deepti), Jaquish, C. (Cashell), Jhun, M. A. (Min A.), Johnsen, J. (Jill), Johnson, A. (Andrew), Johnson, C. (Craig), Johnston, R. (Rich), Jones, K. (Kimberly), Kang, H. M. (Hyun Min), Kaufman, L. (Laura), Kell, S. Y. (Shannon Y.), Kessler, M. (Michael), Kinney, G. (Greg), Konkle, B. (Barbara), Kramer, H. (Holly), Krauter, S. (Stephanie), Lange, C. (Christoph), Lange, E. (Ethan), Laurie, C. (Cecelia), LeBoff, M. (Meryl), Lee, S. S. (Seunggeun Shawn), Lee, W.-J. (Wen-Jane), LeFaive, J. (Jonathon), Levine, D. (David), Levy, D. (Dan), Lewis, J. (Joshua), Li, Y. (Yun), Lin, H. (Honghuang), Lin, K. H. (Keng Han), Lin, X. (Xihong), Liu, S. (Simin), Liu, Y. (Yongmei), Lunetta, K. (Kathryn), Luo, J. (James), Mahaney, M. (Michael), Make, B. (Barry), Manichaikul, A. (Ani), Mansonl, J. (JoAnn), Margolin, L. (Lauren), Mathai, S. (Susan), McArdle, P. (Patrick), Mcdonald, M.-L. (Merry-Lynn), McFarland, S. (Sean), McHugh, C. (Caitlin), Mei, H. (Hao), Meyers, D. A. (Deborah A.), Mikulla, J. (Julie), Min, N. (Nancy), Minear, M. (Mollie), Minster, R. L. (Ryan L.), Musani, S. (Solomon), Mwasongwe, S. (Stanford), Mychaleckyj, J. C. (Josyf C.), Nadkarni, G. (Girish), Naik, R. (Rakhi), Naseri, T. (Take), Nekhai, S. (Sergei), Nelson, S. C. (Sarah C.), Nickerson, D. (Deborah), Connell, J. O. (Jeff O.), Connor, T. O. (Tim O.), Ochs-Balcom, H. (Heather), Pankow, J. (James), Papanicolaou, G. (George), Parkerl, M. (Margaret), Parsa, A. (Afshin), Penchey, S. (Sara), Perez, M. (Marco), Peters, U. (Ulrike), Phillips, L. S. (Lawrence S.), Phillips, S. (Sam), Pollin, T. (Toni), Post, W. (Wendy), Becker, J. P. (Julia Powers), Boorgula, M. P. (Meher Preethi), Preuss, M. (Michael), Prokopenko, D. (Dmitry), Qasba, P. (Pankaj), Qiao, D. (Dandi), Rafaels, N. (Nicholas), Raffield, L. (Laura), Rasmussen-Torvik, L. (Laura), Ratan, A. (Aakrosh), Reed, R. (Robert), Reganl, E. (Elizabeth), Reupena, M. S. (Muagututi Sefuiva), Rice, K. (Ken), Roden, D. (Dan), Roselli, C. (Carolina), Ruczinski, I. (Ingo), Russel, P. (Pamela), Ruuska, S. (Sarah), Ryan, K. (Kathleen), Sabino, E. C. (Ester Cerdeira), Sakornsakolpatl, P. (Phuwanat), Salzberg, S. (Steven), Sandow, K. (Kevin), Sankaran, V. G. (Vijay G.), Scheller, C. (Christopher), Schmidt, E. (Ellen), Schwander, K. (Karen), Schwartz, D. (David), Sciurba, F. (Frank), Seidman, C. (Christine), Seidman, J. (Jonathan), Sheehan, V. (Vivien), Shetty, A. (Amol), Shetty, A. (Aniket), Sheu, W. H. (Wayne Hui-Heng), Shoemaker, M. B. (M. Benjamin), Silver, B. (Brian), Silvermanl, E. (Edwin), Smith, J. (Jennifer), Smith, J. (Josh), Smith, N. (Nicholas), Smith, T. (Tanja), Smoller, S. (Sylvia), Snively, B. (Beverly), Soferlm, T. (Tamar), Streeten, E. (Elizabeth), Su, J. L. (Jessica Lasky), Sung, Y. J. (Yun Ju), Sylvia, J. (Jody), Sztalryd, C. (Carole), Taliun, D. (Daniel), Tang, H. (Hua), Taub, M. (Margaret), Taylor, K. D. (Kent D.), Taylor, S. (Simeon), Telen, M. (Marilyn), Thornton, T. A. (Timothy A.), Tinker, L. (Lesley), Tirschwel, D. (David), Tiwari, H. (Hemant), Vaidya, D. (Dhananjay), VandeHaar, P. (Peter), Vrieze, S. (Scott), Walker, T. (Tarik), Wallace, R. (Robert), Waits, A. (Avram), Wan, E. (Emily), Wang, H. (Heming), Watson, K. (Karol), Weir, B. (Bruce), Weiss, S. (Scott), Weng, L.-C. (Lu-Chen), Williams, K. (Kayleen), Williams, L. K. (L. Keoki), Wilson, C. (Carla), Wong, Q. (Quenna), Xu, H. (Huichun), Yang, I. (Ivana), Yang, R. (Rongze), Zaghlou, N. (Norann), Zekavat, M. (Maryam), Zhang, Y. (Yingze), Zhao, S. X. (Snow Xueyan), Zhao, W. (Wei), Zni, D. (Degui), Zhou, X. (Xiang), Zhu, X. (Xiaofeng), Zody, M. (Michael), Zoellner, S. (Sebastian), Daly, M. (Mark), Jacob, H. (Howard), Matakidou, A. (Athena), Runz, H. (Heiko), John, S. (Sally), Plenge, R. (Robert), McCarthy, M. (Mark), Hunkapiller, J. (Julie), Ehm, M. (Meg), Waterworth, D. (Dawn), Fox, C. (Caroline), Malarstig, A. (Anders), Klinger, K. (Kathy), Call, K. (Kathy), Mkel, T. (Tomi), Kaprio, J. (Jaakko), Virolainen, P. (Petri), Pulkki, K. (Kari), Kilpi, T. (Terhi), Perola, M. (Markus), Partanen, J. (Jukka), Pitkranta, A. (Anne), Kaarteenaho, R. (Riitta), Vainio, S. (Seppo), Savinainen, K. (Kimmo), Kosma, V.-M. (Veli-Matti), Kujala, U. (Urho), Tuovila, O. (Outi), Hendolin, M. (Minna), Pakkanen, R. (Raimo), Waring, J. (Jeff), Riley-Gillis, B. (Bridget), Liu, J. (Jimmy), Biswas, S. (Shameek), Diogo, D. (Dorothee), Marshall, C. (Catherine), Hu, X. (Xinli), Gossel, M. (Matthias), Schleutker, J. (Johanna), Arvas, M. (Mikko), Hinttala, R. (Reetta), Kettunen, J. (Johannes), Laaksonen, R. (Reijo), Mannermaa, A. (Arto), Paloneva, J. (Juha), Soininen, H. (Hilkka), Julkunen, V. (Valtteri), Remes, A. (Anne), Klviinen, R. (Reetta), Hiltunen, M. (Mikko), Peltola, J. (Jukka), Tienari, P. (Pentti), Rinne, J. (Juha), Ziemann, A. (Adam), Waring, J. (Jeffrey), Esmaeeli, S. (Sahar), Smaoui, N. (Nizar), Lehtonen, A. (Anne), Eaton, S. (Susan), Landenper, S. (Sanni), Michon, J. (John), Kerchner, G. (Geoff), Bowers, N. (Natalie), Teng, E. (Edmond), Eicher, J. (John), Mehta, V. (Vinay), Gormle, P. Y. (Padhraig Y.), Linden, K. (Kari), Whelan, C. (Christopher), Xu, F. (Fanli), Pulford, D. (David), Frkkil, M. (Martti), Pikkarainen, S. (Sampsa), Jussila, A. (Airi), Blomster, T. (Timo), Kiviniemi, M. (Mikko), Voutilainen, M. (Markku), Georgantas, B. (Bob), Heap, G. (Graham), Rahimov, F. (Fedik), Usiskin, K. (Keith), Maranville, J. (Joseph), Lu, T. (Tim), Oh, D. (Danny), Kalpala, K. (Kirsi), Miller, M. (Melissa), McCarthy, L. (Linda), Eklund, K. (Kari), Palomki, A. (Antti), Isomki, P. (Pia), Piri, L. (Laura), Kaipiainen-Seppnen, O. (Oili), Lertratanaku, A. (Apinya), Bing, D. C. (David Close Marla Hochfeld Nan), Gordillo, J. E. (Jorge Esparza), Mars, N. (Nina), Laitinen, T. (Tarja), Pelkonen, M. (Margit), Kauppi, P. (Paula), Kankaanranta, H. (Hannu), Harju, T. (Terttu), Greenberg, S. (Steven), Chen, H. (Hubert), Betts, J. (Jo), Ghosh, S. (Soumitra), Salomaa, V. (Veikko), Niiranen, T. (Teemu), Juonala, M. (Markus), Metsrinne, K. (Kaj), Khnen, M. (Mika), Junttila, J. (Juhani), Laakso, M. (Markku), Pihlajamki, J. (Jussi), Sinisalo, J. (Juha), Taskinen, M.-R. (Marja-Riitta), Tuomi, T. (Tiinamaija), Laukkanen, J. (Jari), Challis, B. (Ben), Peterson, A. (Andrew), Chu, A. (Audrey), Parkkinen, J. (Jaakko), Muslin, A. (Anthony), Joensuu, H. (Heikki), Meretoja, T. (Tuomo), Aaltonen, L. (Lauri), Auranen, A. (Annika), Karihtala, P. (Peeter), Kauppila, S. (Saila), Auvinen, P. (Pivi), Elenius, K. (Klaus), Popovic, R. (Relja), Schutzman, J. (Jennifer), Loboda, A. (Andrey), Chhibber, A. (Aparna), Lehtonen, H. (Heli), McDonough, S. (Stefan), Crohns, M. (Marika), Kulkarni, D. (Diptee), Kaarniranta, K. (Kai), Turunen, J. (Joni), Ollila, T. (Terhi), Seitsonen, S. (Sanna), Uusitalo, H. (Hannu), Aaltonen, V. (Vesa), Uusitalo-Jrvinen, H. (Hannele), Luodonp, M. (Marja), Hautala, N. (Nina), Strauss, E. (Erich), Chen, H. (Hao), Podgornaia, A. (Anna), Hoffman, J. (Joshua), Tasanen, K. (Kaisa), Huilaja, L. (Laura), Hannula-Jouppi, K. (Katariina), Salmi, T. (Teea), Peltonen, S. (Sirkku), Koulu, L. (Leena), Harvima, I. (Ilkka), Wu, Y. (Ying), Choy, D. (David), Jalanko, A. (Anu), Kajanne, R. (Risto), Lyhs, U. (Ulrike), Kaunisto, M. (Mari), Davis, J. W. (Justin Wade), Quarless, D. (Danjuma), Petrovski, S. (Slav), Chen, C.-Y. (Chia-Yen), Bronson, P. (Paola), Yang, R. (Robert), Chang, D. (Diana), Bhangale, T. (Tushar), Holzinger, E. (Emily), Wang, X. (Xulong), Chen, X. (Xing), Auro, K. (Kirsi), Wang, C. (Clarence), Xu, E. (Ethan), Auge, F. (Franck), Chatelain, C. (Clement), Kurki, M. (Mitja), Karjalainen, J. (Juha), Havulinna, A. (Aki), Palin, K. (Kimmo), Palta, P. (Priit), Parolo, P. D. (Pietro Della Briotta), Zhou, W. (Wei), Lemmel, S. (Susanna), Rivas, M. (Manuel), Harju, J. (Jarmo), Lehisto, A. (Arto), Ganna, A. (Andrea), Llorens, V. (Vincent), Karlsson, A. (Antti), Kristiansson, K. (Kati), Hyvrinen, K. (Kati), Ritari, J. (Jarmo), Wahlfors, T. (Tiina), Koskinen, M. (Miika), Pylkäs, K. (Katri), Kalaoja, M. (Marita), Karjalainen, M. (Minna), Mantere, T. (Tuomo), Kangasniemi, E. (Eeva), Heikkinen, S. (Sami), Laakkonen, E. (Eija), Kononen, J. (Juha), Loukola, A. (Anu), Laiho, P. (Pivi), Sistonen, T. (Tuuli), Kaiharju, E. (Essi), Laukkanen, M. (Markku), Jrvensivu, E. (Elina), Lhteenmki, S. (Sini), Mnnikk, L. (Lotta), Wong, R. (Regis), Mattsson, H. (Hannele), Hiekkalinna, T. (Tero), Jimnez, M. G. (Manuel Gonzlez), Donner, K. (Kati), Prn, K. (KaIle), Nunez-Fontarnau, J. (Javier), Kilpelinen, E. (Elina), Sipi, T. P. (Timo P.), Brein, G. (Georg), Dada, A. (Alexander), Awaisa, G. (Ghazal), Shcherban, A. (Anastasia), Sipil, T. (Tuomas), Laivuori, H. (Hannele), Kiiskinen, T. (Tuomo), Siirtola, H. (Harri), Tabuenca, J. G. (Javier Gracia), Kallio, L. (Lila), Soini, S. (Sirpa), Pitknen, K. (Kimmo), and Kuopio, T. (Teijo)
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Cardiovascular genetics ,Genome-wide association studies - Abstract
Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10−72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10−4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10−5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.
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- 2021
36. A non-targeted LC–MS metabolic profiling of pregnancy:longitudinal evidence from healthy and pre-eclamptic pregnancies
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Jääskeläinen, T. (Tiina), Kärkkäinen, O. (Olli), Jokkala, J. (Jenna), Klåvus, A. (Anton), Heinonen, S. (Seppo), Auriola, S. (Seppo), Lehtonen, M. (Marko), T. F. (The FINNPEC Core Investigator Group), Hanhineva, K. (Kati), and Laivuori, H. (Hannele)
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Pregnancy ,Metabolomics ,Preeclampsia ,LC–MS ,humanities - Abstract
Introduction: Maternal metabolism changes substantially during pregnancy. However, few studies have used metabolomics technologies to characterize changes across gestation. Objectives and methods: We applied liquid chromatography–mass spectrometry (LC–MS) based non-targeted metabolomics to determine whether the metabolic profile of serum differs throughout the pregnancy between pre-eclamptic and healthy women in the FINNPEC (Finnish Genetics of Preeclampsia Consortium) Study. Serum samples were available from early and late pregnancy. Results: Progression of pregnancy had large-scale effects to the serum metabolite profile. Altogether 50 identified metabolites increased and 49 metabolites decreased when samples of early pregnancy were compared to samples of late pregnancy. The metabolic signatures of pregnancy were largely shared in pre-eclamptic and healthy women, only urea, monoacylglyceride 18:1 and glycerophosphocholine were identified to be increased in the pre-eclamptic women when compared to healthy controls. Conclusions: Our study highlights the need of large-scale longitudinal metabolomic studies in non-complicated pregnancies before more detailed understanding of metabolism in adverse outcomes could be provided. Our findings are one of the first steps for a broader metabolic understanding of the physiological changes caused by pregnancy per se. Collaborators for The FINNPEC Core Investigator Group Eero Kajantie (Chronic Disease Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland; Children’s Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland; PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland). Juha Kere (Department of Biosciences and Nutrition, and Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden; Molecular Neurology Research Program, University of Helsinki, Helsinki, Finland; Folkhälsan Institute of Genetics, Helsinki, Finland), Katja Kivinen (Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland), Anneli Pouta (Department of Government Services, National Institute for Health and Welfare, Helsinki, Finland).
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- 2021
37. External validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysis.
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Kingdom J., Poston L., Thilaganathan B., Staff A.C., Smith G.C.S., Ganzevoort W., Laivuori H., Odibo A.O., Arenas Ramirez J., Daskalakis G., Farrar D., Baschat A.A., Seed P.T., Prefumo F., da Silva Costa F., Groen H., Audibert F., Masse J., Skrastad R.B., Salvesen K.A., Haavaldsen C., Nagata C., Rumbold A.R., Heinonen S., Askie L.M., Smits L.J.M., Vinter C.A., Magnus P., Eero K., Villa P.M., Jenum A.K., Andersen L.B., Norman J.E., Ohkuchi A., Eskild A., Bhattacharya S., McAuliffe F.M., Galindo A., Herraiz I., Carbillon L., Klipstein-Grobusch K., Yeo S.A., Browne J.L., Moons K.G.M., Riley R.D., Thangaratinam S., Snell K.I.E., Allotey J., Smuk M., Hooper R., Chan C., Ahmed A., Chappell L.C., Von Dadelszen P., Green M., Kenny L., Khalil A., Khan K.S., Mol B.W., Myers J., Kingdom J., Poston L., Thilaganathan B., Staff A.C., Smith G.C.S., Ganzevoort W., Laivuori H., Odibo A.O., Arenas Ramirez J., Daskalakis G., Farrar D., Baschat A.A., Seed P.T., Prefumo F., da Silva Costa F., Groen H., Audibert F., Masse J., Skrastad R.B., Salvesen K.A., Haavaldsen C., Nagata C., Rumbold A.R., Heinonen S., Askie L.M., Smits L.J.M., Vinter C.A., Magnus P., Eero K., Villa P.M., Jenum A.K., Andersen L.B., Norman J.E., Ohkuchi A., Eskild A., Bhattacharya S., McAuliffe F.M., Galindo A., Herraiz I., Carbillon L., Klipstein-Grobusch K., Yeo S.A., Browne J.L., Moons K.G.M., Riley R.D., Thangaratinam S., Snell K.I.E., Allotey J., Smuk M., Hooper R., Chan C., Ahmed A., Chappell L.C., Von Dadelszen P., Green M., Kenny L., Khalil A., Khan K.S., Mol B.W., and Myers J.
- Abstract
BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. METHOD(S): IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. RESULT(S): Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model's calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decis
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- 2021
38. Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: An individual participant data meta-analysis.
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Allotey J., Smuk M., Hooper R., Chan C.L., Ahmed A., Chappell L.C., von Dadelszen P., Dodds J., Green M., Kenny L., Khalil A., Khan K.S., Mol B.W., Myers J., Poston L., Thilaganathan B., Eskild A., Bhattacharya S., McAuliffe F.M., Galindo A., Herraiz I., Carbillon L., Klipstein-Grobusch K., Yeo S., Teede H.J., Browne J.L., Moons K.G.M., Riley R.D., Thangaratinam S., Snell K.I.E., Staff A.C., Smith G.C.S., Ganzevoort W., Laivuori H., Odibo A.O., Ramirez J.A., Kingdom J., Daskalakis G., Farrar D., Baschat A.A., Seed P.T., Prefumo F., da Silva Costa F., Groen H., Audibert F., Masse J., Skrastad R.B., Salvesen K.A., Haavaldsen C., Nagata C., Rumbold A.R., Heinonen S., Askie L.M., Smits L.J.M., Vinter C.A., Magnus P.M., Eero K., Villa P.M., Jenum A.K., Andersen L.B., Norman J.E., Ohkuchi A., Allotey J., Smuk M., Hooper R., Chan C.L., Ahmed A., Chappell L.C., von Dadelszen P., Dodds J., Green M., Kenny L., Khalil A., Khan K.S., Mol B.W., Myers J., Poston L., Thilaganathan B., Eskild A., Bhattacharya S., McAuliffe F.M., Galindo A., Herraiz I., Carbillon L., Klipstein-Grobusch K., Yeo S., Teede H.J., Browne J.L., Moons K.G.M., Riley R.D., Thangaratinam S., Snell K.I.E., Staff A.C., Smith G.C.S., Ganzevoort W., Laivuori H., Odibo A.O., Ramirez J.A., Kingdom J., Daskalakis G., Farrar D., Baschat A.A., Seed P.T., Prefumo F., da Silva Costa F., Groen H., Audibert F., Masse J., Skrastad R.B., Salvesen K.A., Haavaldsen C., Nagata C., Rumbold A.R., Heinonen S., Askie L.M., Smits L.J.M., Vinter C.A., Magnus P.M., Eero K., Villa P.M., Jenum A.K., Andersen L.B., Norman J.E., and Ohkuchi A.
- Abstract
Background: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk is needed to plan management. Objective(s): To assess the performance of existing pre-eclampsia prediction models and to develop and validate models for pre-eclampsia using individual participant data meta-analysis. We also estimated the prognostic value of individual markers. Design(s): This was an individual participant data meta-analysis of cohort studies. Setting(s): Source data from secondary and tertiary care. Predictors: We identified predictors from systematic reviews, and prioritised for importance in an international survey. Primary outcomes: Early-onset (delivery at < 34 weeks' gestation), late-onset (delivery at >= 34 weeks' gestation) and any-onset pre-eclampsia. Analysis: We externally validated existing prediction models in UK cohorts and reported their performance in terms of discrimination and calibration.We developed and validated 12 new models based on clinical characteristics, clinical characteristics and biochemical markers, and clinical characteristics and ultrasound markers in the first and second trimesters. We summarised the data set-specific performance of each model using a random-effects meta-analysis. Discrimination was considered promising for C-statistics of >= 0.7, and calibration was considered good if the slope was near 1 and calibration-in-the-large was near 0. Heterogeneity was quantified using I2 and 2. A decision curve analysis was undertaken to determine the clinical utility (net benefit) of the models. We reported the unadjusted prognostic value of individual predictors for pre-eclampsia as odds ratios with 95% confidence and prediction intervals. Result(s): The International Prediction of Pregnancy Complications network comprised 78 studies (3,570,993 singleton pregnancies) identified from systematic reviews of tests to predict pre-eclampsia. Twenty-four of the 131 published prediction models c
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- 2021
39. Betamethasone administration during pregnancy is associated with placental epigenetic changes with implications for inflammation
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Czamara, D. (Darina), Dieckmann, L. (Linda), Röh, S. (Simone), Kraemer, S. (Sarah), Rancourt, R. C. (Rebecca C.), Sammallahti, S. (Sara), Kajantie, E. (Eero), Laivuori, H. (Hannele), Eriksson, J. G. (Johan G.), Räikkönen, K. (Katri), Henrich, W. (Wolfgang), Plagemann, A. (Andreas), Binder, E. B. (Elisabeth B.), Braun, T. (Thorsten), Entringer, S. (Sonja), Czamara, D. (Darina), Dieckmann, L. (Linda), Röh, S. (Simone), Kraemer, S. (Sarah), Rancourt, R. C. (Rebecca C.), Sammallahti, S. (Sara), Kajantie, E. (Eero), Laivuori, H. (Hannele), Eriksson, J. G. (Johan G.), Räikkönen, K. (Katri), Henrich, W. (Wolfgang), Plagemann, A. (Andreas), Binder, E. B. (Elisabeth B.), Braun, T. (Thorsten), and Entringer, S. (Sonja)
- Abstract
Background: Glucocorticoids (GCs) play a pivotal role in fetal programming. Antenatal treatment with synthetic GCs (sGCs) in individuals in danger of preterm labor is common practice. Adverse short- and long-term effects of antenatal sGCs have been reported, but their effects on placental epigenetic characteristics have never been systematically studied in humans. Results: We tested the association between exposure to the sGC betamethasone (BET) and placental DNA methylation (DNAm) in 52 exposed cases and 84 gestational-age-matched controls. We fine-mapped associated loci using targeted bisulfite sequencing. The association of placental DNAm with gene expression and co-expression analysis on implicated genes was performed in an independent cohort including 494 placentas. Exposure to BET was significantly associated with lower placenta DNAm at an enhancer of FKBP5. FKBP5 (FK506-binding protein 51) is a co-chaperone that modulates glucocorticoid receptor activity. Lower DNAm at this enhancer site was associated with higher expression of FKBP5 and a co-expressed gene module. This module is enriched for genes associated with preeclampsia and involved in inflammation and immune response. Conclusions: Our findings suggest that BET exposure during pregnancy associates with few but lasting changes in placental DNAm and may promote a gene expression profile associated with placental dysfunction and increased inflammation. This may represent a pathway mediating GC-associated negative long-term consequences and health outcomes in offspring.
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- 2021
40. Longitudinal metabolic profiling of maternal obesity, gestational diabetes, and hypertensive pregnancy disorders
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Kivelä, J. (Jemina), Sormunen-Harju, H. (Heidi), Girchenko, P. V. (Polina V.), Huvinen, E. (Emilia), Stach-Lempinen, B. (Beata), Kajantie, E. (Eero), Villa, P. M. (Pia M.), Reynolds, R. M. (Rebecca M.), Hämäläinen, E. K. (Esa K.), Lahti-Pulkkinen, M. (Marius), Murtoniemi, K. K. (Katja K.), Laivuori, H. (Hannele), Eriksson, J. G. (Johan G.), Räikkönen, K. (Katri), Koivusalo, S. B. (Saila B.), Kivelä, J. (Jemina), Sormunen-Harju, H. (Heidi), Girchenko, P. V. (Polina V.), Huvinen, E. (Emilia), Stach-Lempinen, B. (Beata), Kajantie, E. (Eero), Villa, P. M. (Pia M.), Reynolds, R. M. (Rebecca M.), Hämäläinen, E. K. (Esa K.), Lahti-Pulkkinen, M. (Marius), Murtoniemi, K. K. (Katja K.), Laivuori, H. (Hannele), Eriksson, J. G. (Johan G.), Räikkönen, K. (Katri), and Koivusalo, S. B. (Saila B.)
- Abstract
Context: Comprehensive assessment of metabolism in maternal obesity and pregnancy disorders can provide information about the shared maternal-fetal milieu and give insight into both maternal long-term health and intergenerational transmission of disease burden. Objective: To assess levels, profiles, and change in the levels of metabolic measures during pregnancies complicated by obesity, gestational diabetes (GDM), or hypertensive disorders. Design, Setting and Participant: A secondary analysis of 2 study cohorts, PREDO and RADIEL, including 741 pregnant women. Main Outcome Measures: We assessed 225 metabolic measures by nuclear magnetic resonance in blood samples collected at median 13 [interquartile range (IQR) 12.4–13.7], 20 (IQR 19.3–23.0), and 28 (27.0–35.0) weeks of gestation. Results: Across all 3 time points women with obesity [body mass index (BMI) ≥ 30kg/m²] in comparison to normal weight (BMI 18.5–24.99 kg/m²) had significantly higher levels of most very-low-density lipoprotein-related measures, many fatty and most amino acids, and more adverse metabolic profiles. The change in the levels of most metabolic measures during pregnancy was smaller in obese than in normal weight women. GDM, preeclampsia, and chronic hypertension were associated with metabolic alterations similar to obesity. The associations of obesity held after adjustment for GDM and hypertensive disorders, but many of the associations with GDM and hypertensive disorders were rendered nonsignificant after adjustment for BMI and the other pregnancy disorders. Conclusions: This study shows that the pregnancy-related metabolic change is smaller in women with obesity, who display metabolic perturbations already in early pregnancy. Metabolic alterations of obesity and pregnancy disorders resembled each other suggesting a shared metabolic origin.
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- 2021
41. Maternal depression and inflammation during pregnancy
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Lahti-Pulkkinen, M. (Marius), Girchenko, P. (Polina), Robinson, R. (Rachel), Lehto, S. M. (Soili M.), Toffol, E. (Elena), Heinonen, K. (Kati), Reynolds, R. M. (Rebecca M.), Kajantie, E. (Eero), Laivuori, H. (Hannele), Villa, P. M. (Pia M.), Hämäläinen, E. (Esa), Lahti, J. (Jari), Räikkönen, K. (Katri), Lahti-Pulkkinen, M. (Marius), Girchenko, P. (Polina), Robinson, R. (Rachel), Lehto, S. M. (Soili M.), Toffol, E. (Elena), Heinonen, K. (Kati), Reynolds, R. M. (Rebecca M.), Kajantie, E. (Eero), Laivuori, H. (Hannele), Villa, P. M. (Pia M.), Hämäläinen, E. (Esa), Lahti, J. (Jari), and Räikkönen, K. (Katri)
- Abstract
Background: Maternal depression during pregnancy increases the risk for adverse developmental outcomes in children. However, the underpinning biological mechanisms remain unknown. We tested whether depression was associated with levels of and change in the inflammatory state during pregnancy, if early pregnancy overweight/obesity or diabetes/hypertensive pregnancy disorders accounted for/mediated these effects, and if depression added to the inflammation that typically accompanies these conditions. Methods: We analyzed plasma high-sensitivity C-reactive protein (hsCRP) and glycoprotein acetyls at three consecutive stages during pregnancy, derived history of depression diagnoses before pregnancy from Care Register for Healthcare (HILMO) (N = 375) and self-reports (N = 347) and depressive symptoms during pregnancy using the Center for Epidemiological Studies Depression Scale completed concurrently to blood samplings (N = 295). Data on early pregnancy body mass index (BMI) and diabetes/hypertensive pregnancy disorders came from medical records. Results: Higher overall hsCRP levels, but not change, during pregnancy were predicted by history of depression diagnosis before pregnancy [HILMO: mean difference (MD) = 0.69 standard deviation (s.d.) units; 95% confidence interval (CI) 0.26–1.11, self-report: MD = 0.56 s.d.; 95% CI 0.17–0.94] and higher depressive symptoms during pregnancy (0.06 s.d. per s.d. increase; 95% CI 0.00–0.13). History of depression diagnosis before pregnancy also predicted higher overall glycoprotein acetyls (HILMO: MD = 0.52 s.d.; 95% CI 0.12–0.93). These associations were not explained by diabetes/hypertensive disorders, but were accounted for and mediated by early pregnancy BMI. Furthermore, in obese women, overall hsCRP levels increased as depressive symptoms during pregnancy increased (p = 0.006 for interaction). Conclusions: Depression is associated with a proinflammatory state during pregnancy. These associations are mediated by early
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- 2021
42. Serum inhibin-A and PAPP-A2 in the prediction of pre-eclampsia during the first and second trimesters in high-risk women
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Keikkala, E. (Elina), Forstén, J. (Janina), Ritvos, O. (Olli), Stenman, U.-H. (Ulf-Håkan), Kajantie, E. (Eero), Hämäläinen, E. (Esa), Räikkönen, K. (Katri), Villa, P. M. (Pia M.), Laivuori, H. (Hannele), Keikkala, E. (Elina), Forstén, J. (Janina), Ritvos, O. (Olli), Stenman, U.-H. (Ulf-Håkan), Kajantie, E. (Eero), Hämäläinen, E. (Esa), Räikkönen, K. (Katri), Villa, P. M. (Pia M.), and Laivuori, H. (Hannele)
- Abstract
Objectives: Maternal serum inhibin-A, pregnancy associated plasma protein-A (PAPP-A) and PAPP-A2 together with placental growth factor (PlGF), maternal risk factors and uterine artery pulsatility index (UtA PI) were analysed to study their ability to predict pre-eclampsia (PE). Study design: Serial serum samples for the nested case-control study were collected prospectively at 12–14, 18–20 and 26–28 weeks of gestation from 11 women who later developed early-onset PE (EO PE, diagnosis < 34 + 0 weeks of gestation), 34 women who developed late-onset PE (LO PE, diagnosis ≥ 34 + 0 weeks) and 89 controls. Main outcome measures: Gestational age -adjusted multiples of the median (MoM) values were calculated for biomarker concentrations. Multivariate regression analyses were performed to combine first trimester biomarkers, previously reported results on PlGF, maternal risk factors and UtA PI. Area under curve (AUC) values and 95% confidence intervals (CIs) for the prediction of PE and its subtypes were calculated. Results: A high first trimester inhibin-A predicted PE (AUC 0.618, 95%CI, 0.513–0.724), whereas PAPP-A and PlGF predicted only EO PE (0.701, 0.562–0.840 and 0.798, 0.686–0.909, respectively). At 26–28 weeks PAPP-A2 and inhibin-A predicted all PE subtypes. In the multivariate setting inhibin-A combined with maternal pre-pregnancy body mass index, prior PE and mean UtA PI predicted PE (0.811,0.726–0.896) and LO PE (0.824, 0.733–0.914). Conclusions: At first trimester inhibin-A show potential ability to predict not only EO PE but also LO PE whereas PlGF and PAPP-A predict only EO PE. At late second trimester inhibin-A and PAPP-A2 might be useful for short-term prediction of PE.
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- 2021
43. Normal gestational weight gain protects from large-for-gestational-age birth among women with obesity and gestational diabetes
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Mustaniemi, S. (Sanna), Nikkinen, H. (Hilkka), Bloigu, A. (Aini), Pouta, A. (Anneli), Kaaja, R. (Risto), Eriksson, J. G. (Johan G.), Laivuori, H. (Hannele), Gissler, M. (Mika), Kajantie, E. (Eero), Vääräsmäki, M. (Marja), Mustaniemi, S. (Sanna), Nikkinen, H. (Hilkka), Bloigu, A. (Aini), Pouta, A. (Anneli), Kaaja, R. (Risto), Eriksson, J. G. (Johan G.), Laivuori, H. (Hannele), Gissler, M. (Mika), Kajantie, E. (Eero), and Vääräsmäki, M. (Marja)
- Abstract
Background: Pre-pregnancy obesity, excess gestational weight gain (GWG), and gestational diabetes (GDM) increase fetal growth. Our aim was to assess whether normal GWG is associated with lower risk for a large-for-gestational-age (LGA; over the 90th percentile of birth weight for sex and gestational age) infant and lower birth weight standard deviation (SD) score in the presence of GDM and maternal obesity. Methods: This multicenter case-control study is part of the Finnish Gestational Diabetes (FinnGeDi) Study and includes singleton pregnancies of 1,055 women with GDM and 1,032 non-diabetic controls. Women were divided into 12 subgroups according to their GDM status, pre-pregnancy body mass index (BMI; kg/m²), and GWG. Non-diabetic women with normal BMI and normal GWG (according to Institute of Medicine recommendations) served as a reference group. Results: The prevalence of LGA birth was 12.2% among women with GDM and 6.2% among non-diabetic women (p < 0.001). Among all women, normal GWG was associated with lower odds of LGA [odds ratio (OR) 0.57, 95% CI: 0.41–0.78]. Among women with both obesity and GDM, the odds for giving birth to a LGA infant was 2.25-fold (95% CI: 1.04–4.85) among those with normal GWG and 7.63-fold (95% CI: 4.25–13.7) among those with excess GWG compared with the reference group. Compared with excess GWG, normal GWG was associated with 0.71 SD (95% CI: 0.47–0.97) lower birth weight SD score among women with GDM and obesity. Newborns of normal weight women with GDM and normal GWG had 0.28 SD (95% CI: 0.05–0.51) lower birth weight SD scores compared with their counterparts with excess GWG. In addition, in the group of normal weight non-diabetic women, normal GWG was associated with 0.46 SD (95% CI: 0.30–0.61) lower birth weight SD scores compared with excess GWG. Conclusion: GDM, obesity, and excess GWG are associated with higher risk for LGA infants. Interventions aiming at normal GWG have the potential to lower LGA rate and birth
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- 2021
44. Characteristics of epigenetic aging across gestational and perinatal tissues
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Dieckmann, L. (Linda), Lahti-Pulkkinen, M. (Marius), Kvist, T. (Tuomas), Lahti, J. (Jari), DeWitt, P. E. (Peter E.), Cruceanu, C. (Cristiana), Laivuori, H. (Hannele), Sammallahti, S. (Sara), Villa, P. M. (Pia M.), Suomalainen-König, S. (Sanna), Eriksson, J. G. (Johan G.), Kajantie, E. (Eero), Räikkönen, K. (Katri), Binder, E. B. (Elisabeth B.), Czamara, D. (Darina), Dieckmann, L. (Linda), Lahti-Pulkkinen, M. (Marius), Kvist, T. (Tuomas), Lahti, J. (Jari), DeWitt, P. E. (Peter E.), Cruceanu, C. (Cristiana), Laivuori, H. (Hannele), Sammallahti, S. (Sara), Villa, P. M. (Pia M.), Suomalainen-König, S. (Sanna), Eriksson, J. G. (Johan G.), Kajantie, E. (Eero), Räikkönen, K. (Katri), Binder, E. B. (Elisabeth B.), and Czamara, D. (Darina)
- Abstract
Background: Epigenetic clocks have been used to indicate differences in biological states between individuals of same chronological age. However, so far, only few studies have examined epigenetic aging in newborns—especially regarding different gestational or perinatal tissues. In this study, we investigated which birth- and pregnancy-related variables are most important in predicting gestational epigenetic age acceleration or deceleration (i.e., the deviation between gestational epigenetic age estimated from the DNA methylome and chronological gestational age) in chorionic villus, placenta and cord blood tissues from two independent study cohorts (ITU, n = 639 and PREDO, n = 966). We further characterized the correspondence of epigenetic age deviations between these tissues. Results: Among the most predictive factors of epigenetic age deviations in single tissues were child sex, birth length, maternal smoking during pregnancy, maternal mental disorders until childbirth, delivery mode and parity. However, the specific factors related to epigenetic age deviation and the direction of association differed across tissues. In individuals with samples available from more than one tissue, relative epigenetic age deviations were not correlated across tissues. Conclusion: Gestational epigenetic age acceleration or deceleration was not related to more favorable or unfavorable factors in one direction in the investigated tissues, and the relative epigenetic age differed between tissues of the same person. This indicates that epigenetic age deviations associate with distinct, tissue specific, factors during the gestational and perinatal period. Our findings suggest that the epigenetic age of the newborn should be seen as a characteristic of a specific tissue, and less as a general characteristic of the child itself
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- 2021
45. Maternal antenatal stress and mental and behavioral disorders in their children
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Tuovinen, S. (Soile), Lahti-Pulkkinen, M. (Marius), Girchenko, P. (Polina), Heinonen, K. (Kati), Lahti, J. (Jari), Reynolds, R. M. (Rebecca M.), Hämäläinen, E. (Esa), Villa, P. M. (Pia M.), Kajantie, E. (Eero), Laivuori, H. (Hannele), Raikkonen, K. (Katri), Tuovinen, S. (Soile), Lahti-Pulkkinen, M. (Marius), Girchenko, P. (Polina), Heinonen, K. (Kati), Lahti, J. (Jari), Reynolds, R. M. (Rebecca M.), Hämäläinen, E. (Esa), Villa, P. M. (Pia M.), Kajantie, E. (Eero), Laivuori, H. (Hannele), and Raikkonen, K. (Katri)
- Abstract
Background: Maternal antenatal stress, including symptoms of depression, anxiety and perceived stress, is associated with mental and behavioral problems in children. Whether it is associated with child mental and behavioral disorders remains uncertain. We examined if maternal antenatal symptoms of depression, anxiety and perceived stress were associated with mental and behavioral disorders in their children, if the associations varied according to gestational week, stress type, fluctuating or consistently high symptoms, and if they were driven by maternal or paternal lifetime mood or anxiety disorders. Methods: 3365 mothers participating in the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study completed the Center for Epidemiologic Studies Depression Scale, the State Anxiety Inventory and the Perceived Stress Scale up to 14 times throughout pregnancy. The Care Register for Health Care provided data on mental and behavioral (including neurodevelopmental) disorders for their children from birth (11/07/2006–07/24/2010) until 12/31/2016 and for parental lifetime mood and anxiety disorders until 12/31/2016. Results: The hazard of any childhood mental and behavioral disorder (HR=1.91, 95% CI: 1.39–2.51) was significantly higher for children whose mothers reported consistently high in comparison to consistently low levels of all types of stress throughout pregnancy. The associations remained significant when adjusted for maternal and paternal lifetime mood and anxiety disorders (and their comorbidity and timing and mood disorder type). Conclusions: Maternal antenatal stress is associated with higher risk of childhood mental and behavioral disorders. Efforts to reduce maternal antenatal stress should be given a high priority to improve child mental health.
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- 2021
46. Corrigendum. Imprinting disorders in children born after ART: a Nordic study from the CoNARTaS group
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Henningsen, A A, primary, Gissler, M, additional, Rasmussen, S, additional, Opdahl, S, additional, Wennerholm, U B, additional, Spangmose, A L, additional, Tiitinen, A, additional, Bergh, C, additional, Romundstad, L B, additional, Laivuori, H, additional, Forman, J L, additional, Pinborg, A, additional, and Lidegaard, Ø, additional
- Published
- 2021
- Full Text
- View/download PDF
47. OP04_5. Risk for cardiovascular and cerebrovascular diseases in women during first ten years after pre-eclampsia pregnancy in the FINNPEC study
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Kivelä, A., Jääskeläinen, T., Eija, K., and Laivuori, H.
- Published
- 2023
- Full Text
- View/download PDF
48. PO4_2. Genome-wide association study sheds more light on the pathophysiology of preeclampsia
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Tyrmi, J., Kaartokallio, T., Laisk, T., Kettunen, J., and Laivuori, H.
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- 2023
- Full Text
- View/download PDF
49. Blood pressure levels but not hypertensive complications have increased in Type 1 diabetes pregnancies during 1989–2010
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Klemetti, M. M., Teramo, K., Nuutila, M., Tikkanen, M., Hiilesmaa, V., and Laivuori, H.
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- 2013
- Full Text
- View/download PDF
50. Aspirin in the prevention of pre-eclampsia in high-risk women
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Villa, P M, Kajantie, E, Räikkönen, K, Pesonen, A-K, Hämäläinen, E, Vainio, M, Taipale, P, and Laivuori, H
- Published
- 2013
- Full Text
- View/download PDF
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