1. Prenatal Nutrition and IQ: A causal analysis using a Mendelian randomization approach Sarah Lewis

2. A few earlier studies

3. Common problems in observational studies Measurement error Reporting/interviewer bias Reverse causation CONFOUNDING

4. 4

5. Mendelian randomization 5 Comparison of groups of individuals defined by genotype should only differ with respect to the locus under study. With control for population structure, there should be little confounding by any behavioural, socioeconomic or physiological factors.

6. Mendel’s second law – the law of independent assortment 6 “The behaviour of each pair of differentiating characteristics in hybrid union is independent of the other differences between the two original plants, and, further, the hybrid produces just so many kinds of egg and pollen cells as there are possible constant combination forms” Gregor Mendel, 1865.

7. Problems of observational epidemiology can be overcome using genetic variants as proxies Confounding Reverse causation Biological Due to reporting bias Measurement error 7 Independent assortment Fixed at conception Can be measured (genotyped)

8. Clustered environments and randomised genes (93 phenotypes, 23 SNPs) Phenotype / phenotype 4278 pairwise associations Phenotype / genotype 2139 pairwise combinations Genotype / genotype 253 pairwise combinations 43% significant at p<0.01 20 significant at p<0.01 vs 21 expected 4 / 253 significant at p<0.01 vs 3 expected Davey Smith et al. PLoS Medicine 2008

9. MR Vs RCT 9

10. Objective  To determine whether exposure to specific dietary factors in utero and infancy influences cognition Hypotheses  Suboptimum levels of nutrients in utero lead to impaired neurodevelopment and cognitive ability  Variation in genes related to nutrient metabolism is associated with neurodevelopment in infancy  Association of maternal genotype with measurements of cognitive ability, independent of child’s genotype, will indicate a role of the prenatal environment

11. Project design Maternal genetic variants affecting nutrient levels Nutrient exposure IQ at age 8 confounders Offspring genetic variants

12.  Association between diet and cognition can be affected by confounding by lifestyle factors, reverse causality and measurement error  Polymorphisms in genes that metabolise nutrients can be used as proxies for differences in dietary intake and therefore to infer causal relationships between nutrients and cognition without the above problems

13. ALSPAC (Avon Longitudinal Study of Parents and Children)  Population-based prospective study conducted in Bristol, England to evaluate factors that affect health and development of children  ~ 14,000 pregnant women enrolled between April 1991 and December 1992  Information on mother and child collected at regular intervals and ongoing  DNA samples available for mothers and children (~10000 each, ~7000 duos)

14. Population Characteristics

16. Potential Confounders Mother:  Age  Education  Social class  Marital status  Parity  Inter-pregnancy interval  Any infection during pregnancy  Housing tenure  Ever smoked  Alcohol consumption  Iron, zinc, calcium, folic acid, vitamins, other supplements during pregnancy

17. Potential Confounders Child:  Sex  Age  Gestation  Birth weight  Breastfeeding duration

19. Confounders continued

20. Do low levels of vitamin B in utero lead to a lower IQ at age 8?

21. Vitamin B12 facts  Only synthesised by microorganisms  Main sources: fish, shellfish, eggs, meat, dairy products  Recommended Daily Amount: 2-3 ug/day  Dietary deficiency rare (vegans at risk)  B12 deficiency: <150 pmol/l  Main functions: red blood cell formation, DNA synthesis, maintenance of healthy nervous system  Transport: 80% bound to transcobalamin I (HC) 20% bound to transcobalamin II (holoTC). holoTC delivers B12 to cells.  Stored in the liver

22. indicators of B12 deficiency modified from Nexo and Hoffmann-Lucke (2011) Birth defects Spontaneous abortion Pre-eclampsia Prematurity Low birth weight Cardiovascular disease Cognitive deficit Dementia

23. Vitamin B12 status during pregnancy and cognition in children  Lower cognition tests scores among offspring of mothers with deficient intake of B12 (Mexico; del Rio Garcia et al., 2009)  Children of mothers with low B12 levels performed worse in sustained-attention and working memory tests (India; Bhate et al., 2008)  No association of maternal B12 levels with cognitive performance in children. Although verbal ability scores were higher in children of mothers with low B12 (India; Veena et al., 2010)  Problem: residual confounding?

24. Observational Study Model 1: Adjusted for offspring sex and age at time of IQ assessment, and maternal energy intake. Model 2: Model 1 + maternal education, social class, age at delivery, parity, any infection in pregnancy, ever smoked, alcohol consumption before and during pregnancy, folate supplementation. Model 3: Model 2 + gestational length and birth weight. N = 5004 mean difference in child IQ per doubling of maternal vitamin B12 intake 95% CIp-value Model 12.031.30, 2.76< 0.001 Model 20.740.04, 1.440.04 Model 30.700.002, 1.390.05

25. Instrumental variables

26. Maternal SNPs vs offspring IQ SNPgenotypeN IQ mean (SD) FUT2 rs492602 TT 1009 103.3 (16.8) TC 1940 104.2 (16.1) CC 1012 105.0 (16.7) mean difference in child IQ per C allele (95% CI) 3961 0.86 (0.14, 1.58) p-value0.02 TCN2 rs1801198 GG 784 103.9 (16.6) CG 1978 104.1 (16.0) CC 1208 104.6 (17.0) mean difference in child IQ per C allele (95% CI) 3970 0.35 (-0.38, 1.08) p-value0.35 TCN2 rs9606756 AA 3673 104.5 (16.0) AG 1038 104.7 (17.0) GG 75 108.3 (14.5) mean difference in child IQ per G allele (95% CI) 4786 0.60 (-0.39, 1.58) p-value0.24

27. Conclusions Genotypes associated with high vitamin B12 levels are associated with higher IQ. However, the effect of genotype on exposure is small, therefore the power of the study to confidently detect an effect is low. Replication is needed.

28. Do low prenatal iron levels affect IQ?

29. Iron deficiency anemia in pregnant women Source: Worldwide Prevalence of Anemia - WHO report 2008

30. Effects of iron deficiency in early life developing brain structures (striatum, hippocampus) neurotransmitter systems (dopamine, serotonin) Synaptogenesis Myelination different gene and protein profiles in the ID brain

31. Consequences for the child recognition memory function temperament (irritability, lower alertness and soothability) hand-eye movement locomotion comprehension of language fine motor skills school performance long lasting abnormalities, even after iron repletion

32. Instruments: TF, TMPRSS6, HFE SNPs rs3811647 G/A serum transferrin serum ferritin transferrin saturation A = iron lowering Benyamin et al. (2009) rs4820268 A/G D521D serum iron haemoglobin transferrin saturation G = iron lowering Benyamin et al. (2009) rs1799945 C/G H63D rs1800562 G/A C282Y serum iron serum transferrin serum ferritin haemoglobin transferrin saturation C & G= iron lowering Kullo et al. (2010)

33. Maternal genotype & Hb levels *p-value adjusted by gestational age at the time of measurement

34. Maternal genotypes and iron supplementation P = 0.001 P = 4x10 -5

35. Maternal genetic score and child’s IQ

36. dbSNPgenegenotypefull scale IQSDN unadjusted a effect (95% CI) p-value N adjusted a,b effect (95% CI) p-value N rs1799945HFE GG105.917.079 0.50 (-0.59, 1.58) 0.37 3543 1.09 (-0.27, 2.45) 0.39 2402 CG102.916.3850 CC104.116.42614 rs1800562HFE AA107.112.815 -0.52 (-2.05, 1.00) 0.50 3535 0.38 (-1.57, 2.32) 0.71 2352 GA104.216.6455 GG103.816.53065 rs3811647TF GG104.016.31511 -0.13 (-0.95, 0.69) 0.76 3514 -0.36 (-1.40, 0.68) 0.50 2378 GA103.916.31613 AA103.617.3390 rs4820268TMPRSS6 AA104.316.0962 -0.74 (-1.52, 0.05) 0.07 3527 -0.23 (-1.23, 0.77) 0.66 2389 AG104.116.71837 GG102.716.3728 rs1799945/rs1800 562 2 risk alleles0106.116.3156 0.11 (-0.83, 1.05) 0.82 3490 0.99 (-0.19, 2.18) 0.10 2312 3 risk alleles1103.116.51163 4 risk alleles2104.016.42171 genotypic score ≤3 risk alleles0103.816.1464 -0.32 (-0.94, 0.30) 0.31 3444 0.22 (-0.54, 0.98) 0.57 2254 4 risk alleles1104.416.71143 5 risk alleles2103.516.11392 6 risk alleles3103.316.8445 Table 5. Maternal genotypes at SNPs in iron-related genes and full scale IQ of their children at 8 years of age.

37. Limitations instrument is associated with confounder supplementation blurs association of genotype and Hb small numbers for stratified analysis HFE variants are rare

38. Conclusions HFE and TMPRSS6 variants were strongly associated with Hb levels. Not so TF rs3811647. Genotypes associated with low Hb levels were also associated with higher risk of iron supplementation. Mothers with rare HFE homozygote genotypes were more likely to have an educational level greater than O-level. The association between iron-related genotypes and child’s IQ was strongest for women who took iron supplements during pregnancy. Adjustment by child’s genotype, maternal education, confounders and ancestry informative markers did not change this result. Results suggest that exposure to low levels of iron in fetal life adversely affects brain development and therefore IQ in childhood. Replication is needed.

39. Lipids and cognition lipids are vital for membrane biogenesis during cellular growth processes On the other hand, elevated serum cholesterol is a well-known risk factor for cognitive decline, dementia and Alzheimer’s disease. And higher serum LDL has been recently associated with decreased white matter integrity among healthy older adults.

40. Genetic scores for Lipid levels TG score = 27 SNPs LDL-C score = 35 SNPs HDL-C score = 44 SNPs TC score = 46 SNPs Weighted by effect sizes reported by Teslovich et al. (2010), Aulchenko et al. (2009) and Kettunen et al. (2012) Additive model Risk alleles increase TG, LDL-C and TC, and decrease HDL-C Scores are not associated with confounders

41. Association between offspring lipid genetic scores and plasma lipids, adjusted for age and sex.

42. Association between offspring and maternal genotype scores and offspring IQ

43. Quartiles of LDL-C score, LDL-C plasma levels and IQ in ALSPAC children.

44. Conclusions Scores have been developed which are strongly related to lipid levels. Maternal lipid scores are not associated with offspring IQ Offspring LDL score is associated with offspring IQ such that an increase in score increases IQ

45. Acknowledgements Bristol Luisa ZuccoloOxford Carolina BonillaDavid Smith Jean GoldingHelga Refsum Andy Ness Yoav Ben-ShlomoAustralia David GunnellMarie-Jo Brion George Davey SmithCraig Pennell Debbie Lawlor Raine team and participants Amy Taylor Pauline Emmett Nic Timpson Beate St. Pourcain Kate Northstone Phil Lobb & Sue Ring ALSPAC team and participants