24Background: The influence of genetics on variation in DNA methylation (DNAme) is well 25documented. Yet confounding from population stratification is often unaccounted for in DNAme 26 association studies. Existing approaches to address confounding by population stratification 27 using DNAme data may not generalize to populations or tissues outside those in which they were 28 developed. To aid future placental DNAme studies in assessing population stratification, we 29 developed an ethnicity classifier, PlaNET (Placental DNAme Elastic Net Ethnicity Tool), using 30 five cohorts with Infinium Human Methylation 450k BeadChip array (HM450k) data from 31 placental samples that is also compatible with the newer EPIC platform. 32Results: Data from 509 placental samples was used to develop PlaNET and show that it 33 accurately predicts (accuracy = 0.938, kappa = 0.823) major classes of self-reported 34 ethnicity/race (African: n = 58, Asian: n = 53, Caucasian: n = 389), and produces ethnicity 35 probabilities that are highly correlated with genetic ancestry inferred from genome-wide SNP 36 arrays (>2.5 million SNP) and ancestry informative markers (n = 50 SNPs). PlaNET's ethnicity 37 classification relies on 1860 HM450K microarray sites, and over half of these were linked to 38 nearby genetic polymorphisms (n = 955). Our placental-optimized method outperforms existing 39 approaches in assessing population stratification in placental samples from individuals of Asian, 40African, and Caucasian ethnicities. 41 Conclusion:PlaNET provides an improved approach to address population stratification in 42placental DNAme association studies. The method can be applied to predict ethnicity as a 43 discrete or continuous variable and will be especially useful when self-reported ethnicity 44 information is missing and genotyping markers are unavailable. PlaNET is available as an R 45 package at (https://github.com/wvictor14/planet). 46 3

Abstract Background: Fetal growth restriction (FGR) is associated with increased risks for complications before, during, and after birth, in addition to risk of disease through to adulthood. Although placental insufficiency, failure to supply the fetus with adequate nutrients, underlies most cases of FGR, its causes are diverse and not fully understood. One of the few diagnosable causes of placental insufficiency in ongoing pregnancies is the presence of large chromosomal imbalances such as trisomy confined to the placenta; however, the impact of smaller copy number variants (CNVs) has not yet been adequately addressed. In this study, we comprehensively evaluate the contribution of both placental aneuploidy and CNVs to fetal growth. Methods: We used molecular-cytogenetic approaches to identify aneuploidy in placentas from N=101 infants born small-for-gestational age (SGA), typically used as a surrogate for FGR, and from N=173 non-SGA controls from uncomplicated pregnancies. We confirmed aneuploidies and assessed mosaicism by microsatellite genotyping. We then profiled CNVs using high-resolution microarrays in a subset of N=53 SGA and N=61 control euploid placentas, and compared the load, impact, gene enrichment and clinical relevance of CNVs between groups. Candidate CNVs were confirmed using quantitative PCR.Results: Aneuploidy was over 10-fold more frequent in SGA-associated placentas compared to controls (11.9% vs. 1.1%; p=0.0002, OR=11.4), was confined to the placenta, and typically involved autosomes, whereas only sex chromosome abnormalities were observed in controls. We found no significant difference in CNV load or number of placental-expressed or imprinted genes in CNVs between SGA and controls, however, a rare and likely clinically-relevant germline CNV was identified in 5.7% of SGA cases. These CNVs involved candidate genes INHBB, HSD11B2, CTCF, and CSMD3. Conclusions: We conclude that placental genomic imbalances at the cytogenetic and submicroscopic level may underlie up to ~18% of SGA cases in our population. This work contributes to the understanding of the underlying causes of placental insufficiency and FGR, which is important for counselling and prediction of long term outcomes for affected cases.

Background: Fetal growth restriction (FGR) is associated with increased risks for complications before, during, and after birth, in addition to risk of disease through to adulthood. Although placental insufficiency, failure to supply the fetus with adequate nutrients, underlies most cases of FGR, its causes are diverse and not fully understood. One of the few diagnosable causes of placental insufficiency in ongoing pregnancies is the presence of large chromosomal imbalances such as trisomy confined to the placenta; however, the impact of smaller copy number variants (CNVs) has not yet been adequately addressed. In this study, we confirm the importance of placental aneuploidy, and assess the potential contribution of CNVs to fetal growth.Methods: We used molecular-cytogenetic approaches to identify aneuploidy in placentas from N=101 infants born small-for-gestational age (SGA), typically used as a surrogate for FGR, and from N=173 non-SGA controls from uncomplicated pregnancies. We confirmed aneuploidies and assessed mosaicism by microsatellite genotyping. We then profiled CNVs using high-resolution microarrays in a subset of N=53 SGA and N=61 control euploid placentas, and compared the load, impact, gene enrichment and clinical relevance of CNVs between groups. Candidate CNVs were confirmed using quantitative PCR.Results: Aneuploidy was over 10-fold more frequent in SGA-associated placentas compared to controls (11.9% vs. 1.1%; p=0.0002, OR=11.4, 95% CI 2.5-107.4), was confined to the placenta, and typically involved autosomes, whereas only sex chromosome abnormalities were observed in controls. We found no significant difference in CNV load or number of placental-expressed or imprinted genes in CNVs between SGA and controls, however, a rare and likely clinically-relevant germline CNV was identified in 5.7% of SGA cases. These CNVs involved candidate genes INHBB, HSD11B2, CTCF, and CSMD3.Conclusions: We conclude that placental genomic imbalances at the cytogenetic and submicroscopic level may underlie up to ~18% of SGA cases in our population. This work contributes to the understanding of the underlying causes of placental insufficiency and FGR, which is important for counselling and prediction of long term outcomes for affected cases.

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