Genetic predisposition to hypertension is associated with preeclampsia in European and Central Asian women

Steinthórsdóttir, Valgerður; McGinnis, Ralph; Williams, Nicholas; Stefánsdóttir, Lilja; Þorleifsson, Guðmar; Shooter, Scott; Fadista, João; Sigurdsson, Jon K.; Auro, Kirsi; Berezina, Galina; Borges, Maria Carolina; Bumpstead, Suzannah; Bybjerg‐Grauholm, Jonas; Colgiu, Irina; Dolby, Vivien A.; Dudbridge, Frank; Engel, Stephanie M.; Franklin, Christopher S.; Frigge, Michael L.; Frisbæk, Yr; Geirsson, Reynir Tómas; Geller, Frank; Grétarsdóttir, Sólveig; Guðbjartsson, Daníel F.; Harmon, Quaker E.; Hougaard, David M.; Hegay, Tatyana; Helgadóttir, Anna; Hjartardottir, Sigrun; Jääskeläinen, Tiina; Johannsdottir, Hrefna; Jónsdóttir, Ingileif; Juliusdottir, Thorhildur; Kalsheker, Noor; Kasimov, A. K.; Kemp, John P.; Kivinen, Katja; Klungsøyr, Kari; Lee, Wai Kwong; Melbye, Mads; Miedzybrodska, Zosia; Moffett, Ashley; Najmutdinova, Dilbar; Nishanova, Firuza; Olafsdottir, Thorunn A.; Perola, Markus; Pipkin, Fiona Broughton; Poston, Lucilla; Prescott, Gordon; Saevarsdóttir, Saedís; Salimbayeva, Damilya; Scaife, Paula J.; Skotte, Line; Staines-Urias, Eleonora; Stefansson, Olafur A.; Sørensen, Karina Meden; Thomsen, Liv Cecilie Vestrheim; Tragante, Vinicius; Trogstad, Lill; Simpson, Nigel; Aripova, Tamara; Casas, Juan P.; Dominiczak, Anna F.; Walker, James J.; Þorsteinsdóttir, Unnur; Iversen, Ann‐Charlotte; Feenstra, Bjarke; Lawlor, Debbie A.; Boyd, Heather A.; Magnus, Per; Laivuori, Hannele; Zakhidova, Nodira; Svyatova, Gulnara; Stefánsson, Kāri; Morgan, Linda

doi:10.1038/s41467-020-19733-6

Cited by 113 publications

(142 citation statements)

References 78 publications

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“…Using a quantitative assessment of the main COVID-19 radiological features (through volumes of GGO and fibrotic alterations) did not increase sensitivity and specificity (0.68 and 0.59 with GGO, respectively, and 0.86 and 0.44 with fibrotic alterations, respectively) 31 . The AUCs of these deep learning models mostly ranged between 0.70 and 0.95, while sensitivity and specificity, when given, ranged between 0.84 and 1, and 0.25 and 0.96, respectively 15 – 20 .…”

Section: Discussionmentioning

confidence: 99%

“…In parallel, predictive models have been issued to facilitate and even automate the diagnosis of COVID-19 on chest CT with good performances and in an objective manner. Indeed, regarding deep-learning models, diagnostic performances (estimated with area under the receiver operating characteristics curves [AUC]) ranged from 0.70 to 0.95 in retrospective testing cohorts 15 – 20 . When detailed, sensitivity and specificity were 0.84–1 and 0.25–0.96, respectively.…”

Section: Introductionmentioning

confidence: 99%

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Practical clinical and radiological models to diagnose COVID-19 based on a multicentric teleradiological emergency chest CT cohort

Schuster

Crombé

Nivet

et al. 2021

Sci Rep

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Our aim was to develop practical models built with simple clinical and radiological features to help diagnosing Coronavirus disease 2019 [COVID-19] in a real-life emergency cohort. To do so, 513 consecutive adult patients suspected of having COVID-19 from 15 emergency departments from 2020-03-13 to 2020-04-14 were included as long as chest CT-scans and real-time polymerase chain reaction (RT-PCR) results were available (244 [47.6%] with a positive RT-PCR). Immediately after their acquisition, the chest CTs were prospectively interpreted by on-call teleradiologists (OCTRs) and systematically reviewed within one week by another senior teleradiologist. Each OCTR reading was concluded using a 5-point scale: normal, non-infectious, infectious non-COVID-19, indeterminate and highly suspicious of COVID-19. The senior reading reported the lesions’ semiology, distribution, extent and differential diagnoses. After pre-filtering clinical and radiological features through univariate Chi-2, Fisher or Student t-tests (as appropriate), multivariate stepwise logistic regression (Step-LR) and classification tree (CART) models to predict a positive RT-PCR were trained on 412 patients, validated on an independent cohort of 101 patients and compared with the OCTR performances (295 and 71 with available clinical data, respectively) through area under the receiver operating characteristics curves (AUC). Regarding models elaborated on radiological variables alone, best performances were reached with the CART model (i.e., AUC = 0.92 [versus 0.88 for OCTR], sensitivity = 0.77, specificity = 0.94) while step-LR provided the highest AUC with clinical-radiological variables (AUC = 0.93 [versus 0.86 for OCTR], sensitivity = 0.82, specificity = 0.91). Hence, these two simple models, depending on the availability of clinical data, provided high performances to diagnose positive RT-PCR and could be used by any radiologist to support, modulate and communicate their conclusion in case of COVID-19 suspicion. Practically, using clinical and radiological variables (GGO, fever, presence of fibrotic bands, presence of diffuse lesions, predominant peripheral distribution) can accurately predict RT-PCR status.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Practical clinical and radiological models to diagnose COVID-19 based on a multicentric teleradiological emergency chest CT cohort

Schuster

Crombé

Nivet

et al. 2021

Sci Rep

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“…To do this, we assessed the association with pre-eclampsia of the SNP rs1050458 on chromosome 6 (6p21), coding the À21M or À21T HLA-B dimorphism in a genome-wide meta-analysis of 9,515 maternal pre-eclampsia cases and 157,719 controls from multiple cohorts (Steinthorsdottir et al, 2020). The analysis revealed that the G allele coding the À21T HLA-B variant was associated with increased pre-eclampsia risk (p = 0.02).…”

Section: Ll Open Accessmentioning

confidence: 99%

The CD94/NKG2A inhibitory receptor educates uterine NK cells to optimize pregnancy outcomes in humans and mice

et al. 2021

Self Cite

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“…Genome-wide linkage studies on pedigrees have identified risk loci on chromosomes 2p13, 2q23, 11q23, 10q22, 22q12, 2p25, 9p13, 4q32 and 9p11 32 - 36 . Genome-wide association studies (GWAS) have found some variants associated with PE 37 - 39 .…”

Section: Introductionmentioning

confidence: 99%

Distinct placental molecular processes associated with early-onset and late-onset preeclampsia

Ren¹,

Gao²,

Gao³

et al. 2021

Theranostics

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Background: Patients with preeclampsia display a spectrum of onset time and severity of clinical presentation, yet the underlying molecular bases for the early-onset and late-onset clinical subtypes are not known. Although several transcriptome studies have been done on placentae from PE patients, only a small number of differentially expressed genes have been identified due to very small sample sizes and no distinguishing of clinical subtypes. Methods: We carried out RNA-seq on 65 high-quality placenta samples, including 33 from 30 patients and 32 from 30 control subjects, to search for dysregulated genes and the molecular network and pathways they are involved in. Results: We identified two functionally distinct sets of dysregulated genes in the two major subtypes: 2,977 differentially expressed genes in early-onset severe preeclampsia, which are enriched with metabolism-related pathways, notably transporter functions; and 375 differentially expressed genes in late-onset severe preeclampsia, which are enriched with immune-related pathways. We also identified some key transcription factors, which may drive the widespread gene dysregulation in both early-onset and late-onset patients. Conclusion: These results suggest that early-onset and late-onset severe preeclampsia have different molecular mechanisms, whereas the late-onset mild preeclampsia may have no placenta-specific causal factors. A few regulators may be the key drivers of the dysregulated molecular pathways.

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Genetic predisposition to hypertension is associated with preeclampsia in European and Central Asian women

Cited by 113 publications

References 78 publications

Practical clinical and radiological models to diagnose COVID-19 based on a multicentric teleradiological emergency chest CT cohort

Practical clinical and radiological models to diagnose COVID-19 based on a multicentric teleradiological emergency chest CT cohort

The CD94/NKG2A inhibitory receptor educates uterine NK cells to optimize pregnancy outcomes in humans and mice

Distinct placental molecular processes associated with early-onset and late-onset preeclampsia

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