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Monozygotic (MZ) and dizygotic (DZ) twins are studied to understand genetic and environmental influences on complex traits, however the mechanisms behind twinning are not completely understood. (Epi)genomic studies identified SNPs associated with DZ twinning and DNA methylation sites with MZ twinning. To find molecular biomarkers of twinning, we compared transcriptomics and metabolomics data from MZ and DZ twins. We analyzed 42,663 RNA transcripts in 1453 MZ twins and 1294 DZ twins from the Netherlands Twin Register (NTR), followed by sex-stratified analyses. The top 5% transcripts with lowest p-values were analyzed for replication in 217 MZ and 158 DZ twins from the older Finnish Twin cohort (FTC). In the NTR, one transcript (PURG) was significantly differentially expressed between MZ and DZ twins; but this did not replicate in FTC. Pathway analyses highlighted the WNT-pathway, previously associated with MZ twinning, and the TGF-B and SMAD pathway, previously associated with DZ twinning. Meta-analysis of 169 serum metabolites in 2797 MZ and 2040 DZ twins from the NTR, FTC and FinnTwin12, showed no metabolomic differences. Overall, we did not find replicable transcript-level expression differences in blood between MZ and DZ twins, but highlighted the TGF-B/SMAD pathway as a potential transcriptional biomarker for DZ twinning., (© 2024 The Author(s). American Journal of Medical Genetics Part A published by Wiley Periodicals LLC.)

Previous studies have shown that mothers of naturally conceived dizygotic (DZ) twins tend to be taller, older, and smoke more than mothers of naturally conceived monozygotic (MZ) twin and mothers of singletons. Here, we investigate whether mothers of naturally conceived DZ twins differ from mothers who conceived their DZ twins after medically assisted reproduction (MAR) in eight maternal traits related to fertility based on observational survey data. We include data from 33,648 mothers from the Netherlands Twin Register (NTR) and 1660 mothers of twins from the Norwegian Mother, Father and Child Cohort Study (MoBA). We contrast mothers of naturally conceived DZ twins with mothers of MAR DZ twins. Next, we further segment the MAR group into mothers who underwent hormonal induction of ovulation but not in vitro fertilization (IVF) and those who IVF twins, comparing them both to each other and against the mothers of naturally conceived DZ twins. Mothers of naturally conceived DZ twins smoke more often, differ in body composition, have a higher maternal age and have more offspring before the twins than mothers of MZ twins. Compared to MAR DZ twin mothers, mothers of naturally conceived DZ twins have fewer miscarriages, lower maternal age and increased height, more offspring and are more often smokers. BMI before the twin pregnancy is similar in both natural and MAR DZ twin mothers. Mothers who received hormonal induction of ovulation (OI) have a lower maternal age, fewer miscarriages, and a higher number of offspring before their twin pregnancy than twin mothers who received IVF and/or intracytoplasmic sperm injection (ICSI) treatments. Our study shows that twin mothers are a heterogenous group and the differences between twin mothers should be taken into account in epidemiological and genetic research that includes twins.

The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD., (© 2023 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics published by Wiley Periodicals LLC.)

Familial twinning and fertility traits were investigated in Nigerian mothers of dizygotic (DZ) twins (MoDZT; N = 972) and controls ( N = 525) who responded to our person-to-person interview, which included questions on pregnancy history and family history of DZ twinning. Controls were defined as women who are not twins themselves and do not have twins in their first-degree relatives. Over 95% of the participants were Yoruba. We found that Nigerian MoDZT had an average of 4.0 (±2.6) pairs of twins among their relatives, and of these, the prevalence of DZ twins was significantly higher than that of monozygotic (MZ) twins (45.9% vs. 25.8%). Controls had an average of 0.5 (±0.4) pairs, and over 95% of the controls had no twins in their relatives. These results suggest genetic influences on DZ twinning in Nigerians. MoDZT were significantly younger in their mean age at first child, and had higher parity than controls, suggesting increased fertility in MoDZT. As compared to mothers with a single set of twins, mothers ( N = 130) with multiple sets had significantly more twins among their relatives (5.4 pairs vs. 3.7 pairs) and had their first twins at a younger age (28.4 vs. 30.7 years), indicating that mothers with multiple sets of twins might have higher genetic propensity for twinning associated with earlier age at twin pregnancy. Our findings argue for genomewide association studies for DZ twinning in Nigerians, and may help to develop intervention strategies to overcome infertility/subfertility problems.

Spontaneous dizygotic (DZ) twins, i.e. twins conceived without the use of ARTs, run in families and their prevalence varies widely around the globe. In contrast, monozygotic (MZ) twins occur at a constant rate across time and geographical regions and, with some rare exceptions, do not cluster in families. The leading hypothesis for MZ twins, which arise when a zygote splits during preimplantation stages of development, is random occurrence. We have found the first series of genes underlying the liability of being the mother of DZ twins and have shown that being an MZ twin is strongly associated with a stable DNA methylation signature in child and adult somatic tissues. Because identical twins keep this molecular signature across the lifespan, this discovery opens up completely new possibilities for the retrospective diagnosis of whether a person is an MZ twin whose co-twin may have vanished in the early stages of pregnancy. Here, we summarize the gene finding results for mothers of DZ twins based on genetic association studies followed by meta-analysis, and further present the striking epigenetic results for MZ twins., (© The Author(s) 2023. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology.)

Study Question: Which genetic factors regulate female propensity for giving birth to spontaneous dizygotic (DZ) twins?, Summary Answer: We identified four new loci, GNRH1, FSHR, ZFPM1, and IPO8, in addition to previously identified loci, FSHB and SMAD3., What Is Known Already: The propensity to give birth to DZ twins runs in families. Earlier, we reported that FSHB and SMAD3 as associated with DZ twinning and female fertility measures., Study Design, Size, Duration: We conducted a genome-wide association meta-analysis (GWAMA) of mothers of spontaneous dizygotic (DZ) twins (8265 cases, 264 567 controls) and of independent DZ twin offspring (26 252 cases, 417 433 controls)., Participants/materials, Setting, Methods: Over 700 000 mothers of DZ twins, twin individuals and singletons from large cohorts in Australia/New Zealand, Europe, and the USA were carefully screened to exclude twins born after use of ARTs. Genetic association analyses by cohort were followed by meta-analysis, phenome wide association studies (PheWAS), in silico and in vivo annotations, and Zebrafish functional validation., Main Results and the Role of Chance: This study enlarges the sample size considerably from previous efforts, finding four genome-wide significant loci, including two novel signals and a further two novel genes that are implicated by gene level enrichment analyses. The novel loci, GNRH1 and FSHR, have well-established roles in female reproduction whereas ZFPM1 and IPO8 have not previously been implicated in female fertility. We found significant genetic correlations with multiple aspects of female reproduction and body size as well as evidence for significant selection against DZ twinning during human evolution. The 26 top single nucleotide polymorphisms (SNPs) from our GWAMA in European-origin participants weakly predicted the crude twinning rates in 47 non-European populations (r = 0.23 between risk score and population prevalence, s.e. 0.11, 1-tail P = 0.058) indicating that genome-wide association studies (GWAS) are needed in African and Asian populations to explore the causes of their respectively high and low DZ twinning rates. In vivo functional tests in zebrafish for IPO8 validated its essential role in female, but not male, fertility. In most regions, risk SNPs linked to known expression quantitative trait loci (eQTLs). Top SNPs were associated with in vivo reproductive hormone levels with the top pathways including hormone ligand binding receptors and the ovulation cycle., Large Scale Data: The full DZT GWAS summary statistics will made available after publication through the GWAS catalog (https://www.ebi.ac.uk/gwas/)., Limitations, Reasons for Caution: Our study only included European ancestry cohorts. Inclusion of data from Africa (with the highest twining rate) and Asia (with the lowest rate) would illuminate further the biology of twinning and female fertility., Wider Implications of the Findings: About one in 40 babies born in the world is a twin and there is much speculation on why twinning runs in families. We hope our results will inform investigations of ovarian response in new and existing ARTs and the causes of female infertility., Study Funding/competing Interest(s): Support for the Netherlands Twin Register came from the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organization for Health Research and Development (ZonMW) grants, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, 911-09-032, Biobanking and Biomolecular Resources Research Infrastructure (BBMRI.NL, 184.021.007), Royal Netherlands Academy of Science Professor Award (PAH/6635) to DIB, European Research Council (ERC-230374), Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the Avera Institute, Sioux Falls, South Dakota (USA) and the National Institutes of Health (NIH R01 HD042157-01A1) and the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health and Grand Opportunity grants 1RC2 MH089951. The QIMR Berghofer Medical Research Institute (QIMR) study was supported by grants from the National Health and Medical Research Council (NHMRC) of Australia (241944, 339462, 389927, 389875, 389891, 389892, 389938, 443036, 442915, 442981, 496610, 496739, 552485, 552498, 1050208, 1075175). L.Y. is funded by Australian Research Council (Grant number DE200100425). The Minnesota Center for Twin and Family Research (MCTFR) was supported in part by USPHS Grants from the National Institute on Alcohol Abuse and Alcoholism (AA09367 and AA11886) and the National Institute on Drug Abuse (DA05147, DA13240, and DA024417). The Women's Genome Health Study (WGHS) was funded by the National Heart, Lung, and Blood Institute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913), with support for genotyping provided by Amgen. Data collection in the Finnish Twin Registry has been supported by the Wellcome Trust Sanger Institute, the Broad Institute, ENGAGE-European Network for Genetic and Genomic Epidemiology, FP7-HEALTH-F4-2007, grant agreement number 201413, National Institute of Alcohol Abuse and Alcoholism (grants AA-12502, AA-00145, AA-09203, AA15416, and K02AA018755) and the Academy of Finland (grants 100499, 205585, 118555, 141054, 264146, 308248, 312073 and 336823 to J. Kaprio). TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. For NESDA, funding was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10000-1002), the Center for Medical Systems Biology (CSMB, NVVO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University's Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, ROI D0042157-01A, MH081802, Grand Opportunity grants 1 RC2 Ml-1089951 and IRC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO. Work in the Del Bene lab was supported by the Programme Investissements d'Avenir IHU FOReSIGHT (ANR-18-IAHU-01). C.R. was supported by an EU Horizon 2020 Marie Skłodowska-Curie Action fellowship (H2020-MSCA-IF-2014 #661527). H.S. and K.S. are employees of deCODE Genetics/Amgen. The other authors declare no competing financial interests., Trial Registration Number: N/A., (© The Author(s) 2023. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology.)

Background: The influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remains underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers., Methods: Our study included two cohorts of longitudinally followed twins: FinnTwin12 (N = 651) and the Netherlands Twin Register (NTR) (N = 665). Follow-up comprised 4 BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated in latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. In FinnTwin12, the sources of genetic and environmental variation underlying the protein abundances were quantified by twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) applying mixed-effects models and correlation networks., Results: We identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 7 and 3 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers., Conclusions: Associations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels., (© 2023. The Author(s).)