Author Correction: FinnGen provides genetic insights from a well-phenotyped isolated population

Kurki, Mitja; Karjalainen, Juha; Palta, Priit; Sipilä, Timo; Kristiansson, Kati; Donner, Kati; Reeve, Mary Pat; Laivuori, Hannele; Aavikko, Mervi; Kaunisto, Mari; Loukola, Anu; Lahtela, Elisa; Mattsson, Hannele; Laiho, Päivi; Parolo, Pietro Della Briotta; Lehisto, Arto; Kanai, Masahiro; Mars, Nina; Rämö, Joel; Kiiskinen, Tuomo; Heyne, Henrike O.; Veerapen, Kumar; Rüeger, Sina; Lemmelä, Susanna; Zhou, Wei; Ruotsalainen, Sanni; Pärn, Kalle; Hiekkalinna, Tero; Koskelainen, Sami; Paajanen, Teemu; Llorens, Vincent; Gracia‐Tabuenca, Javier; Siirtola, Harri; Reis, Kadri; Elnahas, Abdelrahman G.; Sun, Benjamin B.; Foley, Christopher N.; Aalto‐Setälä, Katriina; Alasoo, Kaur; Arvas, Mikko; Auro, Kirsi; Biswas, Shameek; Bizaki-Vallaskangas, Argyro; Carpén, Olli; Chen, Chia‐Yen; Dada, Oluwaseun Alexander; Ding, Zhihao; Ehm, Margaret G.; Eklund, Kari K.; Färkkilä, Martti; Finucane, Hilary; Ganna, Andrea; Ghazal, Awaisa; Graham, Robert; Green, Eric M.; Hakanen, Antti; Hautalahti, Marco; Hedman, Åsa K.; Hiltunen, Mikko; Hinttala, Reetta; Hovatta, Iiris; Hu, Xinli; Huertas‐Vazquez, Adriana; Huilaja, Laura; Hu, Michele T.M.; Jacob, Howard J.; Jensen, Jan-Nygaard; Joensuu, Heikki; John, Sally; Julkunen, Valtteri; Jung, Marc; Junttila, Juhani; Kaarniranta, Kai; Kähönen, Mika; Kajanne, Risto; Kallio, Lila; Kälviäinen, Reetta; Kaprio, Jaakko; Kerimov, Nurlan; Kettunen, Johannes; Kilpeläinen, Elina; Kilpi, Terhi; Klinger, Katherine W.; Kosma, Veli‐Matti; Kuopio, Teijo; Kurra, Venla; Laisk, Triin; Laukkanen, Jari; Lawless, Nathan; A, Liu; Longerich, Simonne; Mägi, Reedik; Mäkelä, Johanna; Mäkitie, Antti; Mälarstig, Anders; Mannermaa, Arto; Maranville, Joseph; Matakidou, Athena; Meretoja, Tuomo J.; Mozaffari, Sahar V.; Niemi, Mari; Niemi, Marianna; Niiranen, Teemu J.; Donnell, Christopher J O; Obeidat, Ma En; Okafo, George; Ollila, Hanna; Palomäki, Antti; Palotie, Tuula; Partanen, Jukka; Paul, Dirk S.; Pelkonen, Margit; Pendergrass, Sarah A.; Petrovski, Steve; Pitkäranta, Anne; Platt, Adam; Pulford, David; Punkka, Eero; Pussinen, Pirkko J.; Raghavan, Neha; Rahimov, Fedik; Rajpal, Deepak K.; Renaud, Nicole; Riley-Gillis, Bridget; Rodosthenous, Rodosthenis; Saarentaus, Elmo; Salminen, Aino; Salminen, Eveliina; Salomaa, Veikko; Schleutker, Johanna; Serpi, Raisa; Shen, Huei-Yi; Siegel, Richard W.; Silander, Kaisa; Siltanen, Sanna; Soini, Sirpa; Soininen, Hilkka; Sul, Jae Hoon; Tachmazidou, Ioanna; Tasanen, Kaisa; Tienari, Pentti; Toppila‐Salmi, Sanna; Tukiainen, Taru; Tuomi, T.; Turunen, Joni A.; Ulirsch, Jacob C.; Vaura, Felix; Virolainen, Petri; Waring, Jeffrey F.; Waterworth, Dawn; Yang, Robert Z.; Nelis, Mari; Reigo, Anu; Metspalu, Andres; Milani, Lili; Esko, Tõnu; Fox, Caroline S.; Havulinna, Aki S.; Perola, Markus; Ripatti, Samuli; Jalanko, Anu; Laitinen, Tarja; Mäkelä, Tomi P.; Plenge, Robert M.; McCarthy, Mark; Runz, Heiko; Daly, Mark J.; Palotie, Aarno

doi:10.1038/s41586-023-05837-8

Cited by 31 publications

(24 citation statements)

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“…After removing 12 152 duplicates, we screened 50 124 records from the literature and 2 GWAS datasets, UK Biobank and FinnGen. In total, we identified 98 studies for full review (eFigure 2 in Supplement 1), including 83 candidate gene studies, 2 GWASs, 2 single-cohort GWAS summary statistics, 5 genetic linkage analysis, 3 mitochondrial sequencing studies, and 3 whole-exome sequencing studies (eFigure 3 in Supplement 1). In these 98 studies, 4 linkage analysis, 3 mitochondrial sequencing, and 3 whole-exome sequencing studies were not eligible for meta-analysis as they did not provide analyzable data or replications.…”

Section: Resultsmentioning

confidence: 99%

Genetic Associations of Primary Angle-Closure Disease

Liang,

Wang,

Rong

et al. 2024

JAMA Ophthalmol

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ImportanceEffects of genetic variants on primary angle-closure disease remained uncertain.ObjectiveTo systematically review the associations of common single-nucleotide variants (SNVs) and rare coding variants with primary angle-closure disease, its subtypes (including primary angle-closure glaucoma, primary angle-closure suspect, and primary angle-closure) and progression.Data SourcesEligible studies from PubMed, Embase, and Web of Science were retrieved up to April 3, 2023. SNV information was extracted from eligible reports and 2 genome-wide association studies summary statistics, UK BioBank and FinnGen.Study SelectionStudies providing analyzable genotype or allele data in a case-control design for primary angle-closure disease association and longitudinal case-only design for primary angle-closure disease progression.Data Extraction and SynthesisPRISMA guidelines were used for literature screening and the Newcastle Ottawa Scale for data quality assessment. Pooled effect size with 95% CIs of SNV associations were calculated using fixed- or random-effect models according to I2 statistics.Main Outcomes and MeasuresSNVs reported in 2 or more studies were meta-analyzed to generate pooled odds ratios and P values. Common and rare coding variants from single reports were summarized.ResultsSixty-nine citations were eligible for meta-analysis on overall primary angle-closure disease, involving 206 SNVs in 64 genes or loci. Seventeen SNVs in 15 genes or loci showed associations with primary angle-closure disease, and 15 SNVs in 13 genes or loci showed associations with primary angle-closure glaucoma. Two SNVs, ABCA1 rs2422493 and ZNRF3 rs3178915, were associated only with primary angle-closure disease. Two SNVs, PCMTD1-ST18 rs1015213 and COL11A1 rs3753841, were associated with primary angle-closure suspect, and 1 SNV, MMP9 rs3918249, was associated with primary angle-closure. This systematic review and meta-analysis newly confirmed 7 genes or loci associated with primary angle-closure glaucoma: ATOH7, CALCRL, FBN1, IL6, LOXL1, MMP19, and VAV3. Common and rare coding variants in 16 genes or loci that have been associated with primary angle-closure disease were cataloged. Stratification analysis revealed different primary angle-closure disease–associated genes in different ethnic populations. Only 1 study regarding the genetic association of primary angle-closure glaucoma progression was identified.Conclusions and RelevanceThis study revealed the genetic complexity of primary angle-closure disease, involving common SNVs and rare coding variants in more than 30 genes or loci, with ethnic and phenotypic diversities. Further replication, genotype-phenotype correlation, and pathway analyses are warranted.

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Section: Resultsmentioning

confidence: 99%

Genetic Associations of Primary Angle-Closure Disease

Liang,

Wang,

Rong

et al. 2024

JAMA Ophthalmol

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“…Exposure to interest included anorexia nervosa (AN) ( Watson et al, 2019 ), anxiety disorder ( Purves et al, 2020 ), BD ( Mullins et al, 2021 ), insomnia ( Watanabe et al, 2022 ), major depressive disorder (MDD) ( Howard et al, 2019 ), neuroticism ( Nagel et al, 2018 ), obsessive–compulsive disorder (OCD) [ International Obsessive Compulsive Disorder Foundation Genetics Collaborative (LOCDF-GC) and OCD Collaborative Genetics Association Studies (OCGAS), 2018 ], and schizophrenia ( Trubetskoy et al, 2022 ). For PD, we used the largest GWAS conducted in the European population ( Nalls et al, 2019 ) as a discovery study and a GWAS conducted in the Finnish population ( Kurki et al, 2023 ) as a validation study. Detailed information regarding genotype platforms, statistical analysis protocols, and participants for each study is available in the corresponding papers (Data presentation).…”

Section: Methodsmentioning

confidence: 99%

Bidirectional Mendelian randomization study of psychiatric disorders and Parkinson’s disease

Liu

Huang

et al. 2023

Front. Aging Neurosci.

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IntroductionAlthough the relationship between psychiatric disorders and Parkinson’s disease (PD) has attracted continuous research attention, the causal linkage between them has not reached a definite conclusion.MethodsTo identify the causal relationship between psychiatric disorders and PD, we used public summary-level data from the most recent and largest genome-wide association studies (GWASs) on psychiatric disorders and PD to conduct a bidirectional two-sample Mendelian randomization (MR). We applied stringent control steps in instrumental variable selection using the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) method to rule out pleiotropy. The inverse-variance weighted (IVW) method was used to identify the causal relationship between psychiatric disorders and PD. Multiple MR analysis methods, including MR-Egger, weighted-median, and leave-one-out analyses, were used for sensitivity analysis, followed by heterogeneity tests. Further validation and reverse MR analyses were conducted to strengthen the results of the forward MR analysis.ResultsThe lack of sufficient estimation results could suggest a causal relationship between psychiatric disorders and PD in the forward MR analysis. However, the subsequent reverse MR analysis detected a causal relationship between PD and bipolar disorder (IVW: odds ratios [OR] =1.053, 95% confidence interval [CI] =1.02–1.09, p = 0.001). Further analysis demonstrated a causal relationship between genetically predicted PD and the risk of bipolar disorder subtype. No pleiotropy or heterogeneity was detected in the analyses.DiscussionOur study suggested that while psychiatric disorders and traits might play various roles in the risk of developing PD, PD might also be involved in the risk of developing psychiatric disorders.

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“…GWAS datasets for BCC and cSCC are available from the GWAS catalogue (https://www.ebi.ac.uk/gwas/publications/36496446). Genetic variants for AK were extracted from the largest and most recent GWAS data from FinnGen study (version r9, https://www.finngen.fi/en), which included 11,081 cases and 364,831 controls 22 . We obtained genetic association data of CMM from the summary‐level GWAS data from UK Biobank (http://www.nealelab.is/uk-biobank), including 4602 cases and 356,592 controls.…”

Section: Methodsmentioning

confidence: 99%

“…fi/ en), which included 11,081 cases and 364,831 controls. 22 We obtained genetic association data of CMM from the summary-level GWAS data from UK Biobank (http:// www. neale lab.…”

Section: Data Sourcesmentioning

confidence: 99%

The causal effects of atopic dermatitis on the risk of skin cancers: A two‐sample Mendelian randomization study

Luo,

Zheng,

Zhuo

et al. 2023

Acad Dermatol Venereol

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BackgroundObservational and epidemiological studies show conflicting results on the relationship between atopic dermatitis and skin cancer. Additionally, observational studies are susceptible to the reverse causation and confounders, thus, may not interpret true causal relationships. The causal effects of atopic dermatitis on the risk of skin cancers remains unclear.ObjectivesTo investigate the causal relationship between atopic dermatitis and skin cancer including cutaneous malignant melanoma, cutaneous squamous cell carcinoma, basal cell carcinoma and actinic keratosis.MethodsWe performed a two‐sample Mendelian randomization analysis based on summary datasets of public genome‐wide association studies of European ancestry. The inverse variance‐weighted approach was applied as the main analysis. MR–Egger and weighted median methods were used to complement the inverse variance‐weighted results. A series of sensitivity analyses were used to ensure the robustness of the causality estimates.ResultsInverse variance‐weighted method showed that genetically predicted dermatitis patients were significantly associated with an increased incidence of basal cell carcinoma (OR, 1.20; 95% CI, 1.10–1.31; p = 4.07E‐05) and cutaneous squamous cell carcinoma (OR, 1.14; 95% CI, 1.10–1.19; p = 1.05E‐11). However, we did not find a significant causality for atopic dermatitis on melanoma neither did we find actinic keratosis. Subsequent sensitive analyses supported these results.ConclusionsOur study identified the causality between atopic dermatitis basal cell carcinoma and squamous cell carcinoma. Accordingly, regular skin cancer screening is recommended for patients with atopic dermatitis.

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Author Correction: FinnGen provides genetic insights from a well-phenotyped isolated population

Cited by 31 publications

References 0 publications

Genetic Associations of Primary Angle-Closure Disease

Genetic Associations of Primary Angle-Closure Disease

Bidirectional Mendelian randomization study of psychiatric disorders and Parkinson’s disease

The causal effects of atopic dermatitis on the risk of skin cancers: A two‐sample Mendelian randomization study

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