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Investigating the genetic factors influencing human birth weight may lead to biological insights into fetal growth and long-term health. Genome-wide association studies of birth weight have highlighted associated variants in more than 200 regions of the genome, but the causal genes are mostly unknown. Rare genetic variants with robust evidence of association are more likely to point to causal genes, but to date, only a few rare variants are known to influence birth weight. We aimed to identify genes that harbour rare variants that impact birth weight when carried by either the fetus or the mother, by analysing whole exome sequence data in UK Biobank participants. We annotated rare (minor allele frequency <0.1%) protein-truncating or high impact missense variants on whole exome sequence data in up to 234,675 participants with data on their own birth weight (fetal variants), and up to 181,883 mothers who reported the birth weight of their first child (maternal variants). Variants within each gene were collapsed to perform gene burden tests and for each associated gene, we compared the observed fetal and maternal effects. We identified 8 genes with evidence of rare fetal variant effects on birth weight, of which 2 also showed maternal effects. One additional gene showed evidence of maternal effects only. We observed 10/11 directionally concordant associations in an independent sample of up to 45,622 individuals (sign test P =0.01). Of the genes identified, IGF1R and PAPPA2 (fetal and maternal-acting) have known roles in insulin-like growth factor bioavailability and signalling. PPARG, INHBE and ACVR1C (all fetal-acting) have known roles in adipose tissue regulation and rare variants in the latter two also showed associations with favourable adiposity patterns in adults. We highlight the dual role of PPARG in both adipocyte differentiation and placental angiogenesis. NOS3, NRK, and ADAMTS8 (fetal and maternal-acting) have been implicated in both placental function and hypertension. Analysis of rare coding variants has identified regulators of fetal adipose tissue and fetoplacental angiogenesis as determinants of birth weight, as well as further evidence for the role of insulin-like growth factors., Competing Interests: Competing interests J.R.B.P. and E.J.G. are employees/shareholders of Insmed. J.R.B.P. also receives research funding from GSK. Y.Z. is a UK University worker at GSK. S.O. has undertaken remunerated consultancy work for Pfizer, Third Rock Ventures, AstraZeneca, NorthSea Therapeutics and Courage Therapeutics. V.S., V.T., T.O., G.T., and K.S. are employees of deCODE genetics, a subsidiary of Amgen.

Findings from genome-wide association studies have facilitated the generation of genetic predictors for many common human phenotypes. Stratifying individuals misaligned to a genetic predictor based on common variants may be important for follow-up studies that aim to identify alternative causal factors. Using genome-wide imputed genetic data, we aimed to classify 158,951 unrelated individuals from the UK Biobank as either concordant or deviating from two well-measured phenotypes. We first applied our methods to standing height: our primary analysis classified 244 individuals (0.15%) as misaligned to their genetically predicted height. We show that these individuals are enriched for self-reporting being shorter or taller than average at age 10, diagnosed congenital malformations, and rare loss-of-function variants in genes previously catalogued as causal for growth disorders. Secondly, we apply our methods to LDL cholesterol. We classified 156 (0.12%) individuals as misaligned to their genetically predicted LDL cholesterol and show that these individuals were enriched for both clinically actionable cardiovascular risk factors and rare genetic variants in genes previously shown to be involved in metabolic processes. Individuals whose LDL-C was higher than expected based on the genetic predictor were also at higher risk of developing coronary artery disease and type-two diabetes, even after adjustment for measured LDL-C, BMI and age, suggesting upward deviation from genetically predicted LDL-C is indicative of generally poor health. Our results remained broadly consistent when performing sensitivity analysis based on a variety of parametric and non-parametric methods to define individuals deviating from polygenic expectation. Our analyses demonstrate the potential importance of quantitatively identifying individuals for further follow-up based on deviation from genetic predictions., Author Summary: Human genetics is becoming increasingly useful to help predict human traits across a population owing to findings from large-scale genetic association studies and advances in the power of genetic predictors. This provides an opportunity to potentially identify individuals that deviate from genetic predictions for a common phenotype under investigation. For example, an individual may be genetically predicted to be tall, but be shorter than expected. It is potentially important to identify individuals who deviate from genetic predictions as this can facilitate further follow-up to assess likely causes. Using 158,951 unrelated individuals from the UK Biobank, with height and LDL cholesterol, as exemplar traits, we demonstrate that approximately 0.15% & 0.12% of individuals deviate from their genetically predicted phenotypes respectively. We observed these individuals to be enriched for a range of rare clinical diagnoses, as well as rare genetic factors that may be causal. Our analyses also demonstrate several methods for detecting individuals who deviate from genetic predictions that can be applied to a range of continuous human phenotypes.

Determining how high body-mass index (BMI) at different time points influences the risk of developing type two diabetes (T2D), and affects insulin secretion and insulin sensitivity, is critical. By estimating childhood BMI in 441,761 individuals in the UK Biobank, we identified which genetic variants had larger effects on adulthood BMI than on childhood BMI, and vice-versa. All genome-wide significant genetic variants were then used to separate the independent genetic effects of high childhood BMI from high adulthood BMI on the risk of T2D and insulin related phenotypes using Mendelian randomisation and studies of T2D, and oral and intravenous measures of insulin secretion and sensitivity. We found that a 1.s.d. (= 1.97kg/m 2 ) higher childhood BMI, corrected for the independent genetic liability to adulthood BMI, was associated with a protective effect for seven measures of insulin sensitivity and secretion, including an increased insulin sensitivity index (β = 0.15 [0.067, 0.225], p = 2.79×10 -4 ), and reduced fasting glucose (β = -0.053 [-0.089, -0.017], p = 4.31×10 -3 ). There was however little to no evidence of a direct protective effect on T2D (OR = 0.94 [0.85 - 1.04], p = 0.228), independently of genetic liability to adulthood BMI. Our results thus cumulatively provide evidence of the protective effect of higher childhood BMI on insulin secretion and sensitivity, which are crucial intermediate diabetes traits. However, we stress that our results should not currently lead to any change in public health or clinical practice, given the uncertainty in biological pathway of these effects, and the limitations of this type of study., Research in Context: High BMI in adulthood is associated with higher risk of type two diabetes, coupled with lower insulin sensitivity and secretion.Richardson et al [2020] used genetics to show that high BMI in childhood does not appear to increase the risk of type diabetes independently from its effect on adult BMI.We asked: does high childhood BMI affect insulin related traits such as fasting glucose and insulin sensitivity, independently of adulthood BMI?We used genetics to show that high childhood BMI has a protective effect on seven insulin sensitivity and secretion traits, including fasting glucose and measures of insulin sensitivity and secretion, independently of adulthood BMI.Our work has the potential to turn conventional understanding on its head - high BMI in childhood improves insulin sensitivity (when adjusting for knock on effects to high adult BMI) and opens up important questions about plasticity in childhood and compensatory mechanisms.