Publications

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Recent genome-wide association (GWA) studies have identified dozens of common variants associated with adult height. However, it is unknown how these variants influence height growth during childhood. We derived peak height velocity in infancy (PHV1) and puberty (PHV2) and timing of pubertal height growth spurt from parametric growth curves fitted to longitudinal height growth data to test their association with known height variants. The study consisted of N = 3,538 singletons from the prospective Northern Finland Birth Cohort 1966 with genotype data and frequent height measurements (on average 20 measurements per person) from 0-20 years. Twenty-six of the 48 variants tested associated with adult height (p<0.05, adjusted for sex and principal components) in this sample, all in the same direction as in previous GWA scans. Seven SNPs in or near the genes HHIP, DLEU7, UQCC, SF3B4/SV2A, LCORL, and HIST1H1D associated with PHV1 and five SNPs in or near SOCS2, SF3B4/SV2A, C17orf67, CABLES1, and DOT1L with PHV2 (p<0.05). We formally tested variants for interaction with age (infancy versus puberty) and found biologically meaningful evidence for an age-dependent effect for the SNP in SOCS2 (p = 0.0030) and for the SNP in HHIP (p = 0.045). We did not have similar prior evidence for the association between height variants and timing of pubertal height growth spurt as we had for PHVs, and none of the associations were statistically significant after correction for multiple testing. The fact that in this sample, less than half of the variants associated with adult height had a measurable effect on PHV1 or PHV2 is likely to reflect limited power to detect these associations in this dataset. Our study is the first genetic association analysis on longitudinal height growth in a prospective cohort from birth to adulthood and gives grounding for future research on the genetic regulation of human height during different periods of growth.

Background: Recent advances in metabolomic studies have shown promise in elucidating the biological pathways underpinning aging processes and mortality in animal models, but data in humans are lacking. We aimed to evaluate the associations between metabolite profiles, all-cause and cause-specific mortality, and longevity. Methods: Within three prospective cohorts (Nurses’ Health Study [NHS], NHSII, and Health Professional’s Follow-up Study), we measured plasma metabolites from 11,523 participants (mean age 54 years, 86% female) using high-throughput liquid chromatography-mass spectrometry. Participants were free of cardiovascular disease and cancer at blood collection. Metabolome-wide association analyses were conducted for all-cause, cardiovascular, and cancer mortality using Cox proportional hazards regression and longevity (attaining 85 years of age) using logistic regression. Both pre-defined and data-driven metabolite groups were also evaluated. We further developed a multi-metabolite profile score for all-cause mortality using an elastic-net regularized Cox model and assessed its associations with mortality and longevity. Results for all-cause mortality were replicated among 1878 participants (mean age 67 years, 58% female) from the PREDIMED trial. Results: We documented 4252 deaths (including 864 cardiovascular deaths and 1070 cancer deaths) and 3048 achieving longevity over a median follow-up of 22.6 years in the NHS/NHSII/HPFS, and 126 deaths during a follow-up of 4.7 years in the PREDIMED. Higher levels of three nucleosides (N2,N2-dimethylguanosine, pseudouridine, and N4-acetylcytidine), 4-acetamidobutanoic acid, triacylglycerols with ≤56 carbons and ≤3 double bonds, and several other lipids were associated with increased risk of all-cause mortality and corresponding decreased likelihood of longevity; whereas L-serine, L-glutamine, and TAGs with &gt;56 carbons or &gt;3 double bonds were associated with lower mortality risk and higher odds of achieving longevity. A multi-metabolite profile score comprising 73 metabolites was positively associated with all-cause (HR per 1-SD increment=1.25 [95% CI: 1.21, 1.30] in NHS/NHSII/HPFS and 1.47 [95% CI: 1.22, 1.78] in PREDIMED), cardiovascular (HR=1.34 [95% CI:1.24, 1.45]), and cancer mortality (HR=1.15 [95% CI:1.08, 1.24]) and inversely associated with longevity (OR=0.79 [95% CI: 0.74, 0.86]). Conclusions: We identified multiple metabolites associated with mortality and longevity. Our findings provide insights into the biological pathways that lead to death and open up new avenues to incorporate these metabolomic markers in clinical and research settings.

Background: It is still unclear if sustained intake of artificially sweetened beverages (ASB) in lieu of sugar-sweetened beverages (SSB) is associated with long-term weight reduction or maintenance. This study aimed to evaluate the long-term changes in weight and BMI in relation to changes in ASB intake, and to estimate the effects of replacing SSB with ASB or water on body weight. Hypothesis: Habitual ASB intake is unrelated to weight or BMI changes. The modeled substitutions are expected to show a reduction in weight and BMI, larger for water than for ASB. Methods: We used data from the Nurses' Health Study I, a prospective cohort study conducted among female US nurses aged 39 to 65y at enrolment and assessed every four years from 1986 to 2010. Food-frequency questionnaires evaluated usual dietary intake including beverages (in 12 oz servings/day). Self-administered questionnaires collected lifestyle and anthropometric information. We excluded participants with any major disease at baseline (e.g., diabetes, cancer, cardiovascular disease), and censored those reaching 65 years during follow-up. Pregnant or lactating women were not considered during these periods. We evaluated the association between changes in ASB intake with changes in weight and BMI using generalized estimating models adjusting for multiple dietary and lifestyle risk factors. Substitution models assessed how replacing SSB with ASB, SSB with water, or ASB with water relates to weight and BMI changes, adjusting for the same covariates. Results: Among 51,805 participants, 64.6% consumed ASB at baseline averaging 0.25 ± 0.53 servings/day. Over 4-year follow-up intervals, a one-serving/day increase of ASB was associated with an estimated weight change of -0.06 kg (95% CI: -0.11, -0.02) and BMI change of -0.02 kg/m 2 (95% CI: -0.04, -0.01). Substituting SSB with ASB was associated with -0.37 kg change in weight (95% CI: -0.41, -0.33) and -0.14 kg/m 2 in BMI (95% CI: -0.17, -0.11). Similar estimates were observed when replacing SSB with water ( β =-0.35 kg, 95% CI: -0.41, -0.30 for weight and β =-0.13, kg/m 2 , 95% CI: -0.15, -0.11 for BMI). Substituting ASB with water was not associated with changes in weight ( β =-0.004 kg, 95% CI: -0.05, 0.04) or BMI ( β =-0.0002 kg/m 2 , 95% CI: -0.02, 0.02). Conclusion: A long-term daily increase in ASB intake was not associated with greater weight gain in US women. Replacing SSB with ASB was associated with significantly less weight gain, likely by reducing energy intake. Change in water was not associated with weight changes, suggesting it may help sustain weight maintenance when replacing SSB. Future studies should evaluate the roles of changes in intakes of water, ASB, and SSB in relation to changes in other weight- and metabolically-related outcomes in diverse populations of both sexes.

Objective: The Northern Finland 1966 Birth Cohort was studied in order to investigate the association between birth order and schizophrenia.Method: Four categories of birth order status (®rst-born, last-born, only child and other status) were formed and linked to data on psychiatric morbidity.Effects were adjusted for wantedness of pregnancy, perinatal complications, maternal age at delivery, family type and number of siblings.Results: The risk for schizophrenia was elevated among male ®rst-borns (ratio 1.5; 95% CI 1.0±2.2) and female last-borns (ratio 1.3; 95% CI 0.9± 1.9).The risk was lower than expected among male last-borns (ratio 0.7; 95% CI 0.5±0.9)and females belonging to other status (ratio 0.6; 95% CI 0.3±0.9).Conclusion: These results suggest that speci®c birth order status is an independent risk factor for schizophrenia.

Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. Results: We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness. Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Availability and implementation: Code is available at https://github.com/aalto-ics-kepaco Contacts: if.iknisleh@aksnohcic.anna or if.iknisleh@nenirip.ittam Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract Background Associations of low lung function with features of poor cardio-metabolic health have been reported. It is, however, unclear whether these co-morbidities reflect causal associations, shared genetic heritability or are confounded by environmental factors. Methods We performed three analyses: 1) cardio-metabolic health to lung function association tests in NFBC1966, 2) cross trait LD score regression to compare genetic backgrounds and 3) Mendelian Randomization (MR) analysis to assess the causal effect of cardio-metabolic traits and disease on lung function, and vice versa (bidirectional MR). Genetic associations were obtained from UK Biobank data or published large-scale genome-wide association studies (N &gt; 82,000). Results We observed negative genetic correlation between lung function and cardio-metabolic traits and diseases. In Mendelian Randomisation analysis (MR) we found associations between Type 2 Diabetes instruments and FVC as well as FEV1/FVC. BMI instruments were associated to all lung function traits and CRP instruments to FVC. These genetic association provide evidence for a causal effect of cardio-metabolic traits on lung function. Multivariable MR suggested independence of these causal effects from other tested cardio-metabolic traits and diseases. Analysis of lung function specific SNPs revealed a potential causal effect of FEV1/FVC on blood pressure. Conclusions The present study overcomes many limitations of observational studies by using Mendelian Randomisation. We provide evidence for an independent causal effect of T2D, CRP and BMI on lung function with some of the T2D effect on lung function being mediated by CRP. Furthermore, this analysis suggests a potential causal effect of FEV1/FVC on blood pressure. Our detailed analysis of the interplay between cardio-metabolic traits and impaired lung function provides the opportunity to improve the quality of existing intervention strategies.