Search bioRxivSearch

Biology subjects

Terho Lehtimaki

Publications and source records attributed to Terho Lehtimaki.

3 recordsLinked to original sources

Metabolic signatures of birth weight in 18288 adolescents and adults

BackgroundLower birth weight is associated with increased susceptibility to cardiometabolic diseases in adulthood, but the underlying molecular pathways are incompletely understood. We examined associations of birth weight with a comprehensive metabolic profile measured in adolescents and adults.\n\nMethodsHigh-throughput nuclear magnetic resonance metabolomics and biochemical assays were used to quantify 87 circulating metabolic measures in seven cohorts from Finland and the United Kingdom comprising altogether 18 288 individuals (mean age 26 years, range 15-75). Metabolic associations with birth weight were assessed by linear regression models adjusted for sex, gestational age, and age at blood sampling. The metabolic associations with birth weight were compared to the corresponding associations with adult body mass index (BMI).\n\nResultsLower birth weight was adversely associated with cardiometabolic biomarkers, including lipoprotein subclasses, fatty acids, amino acids, and markers of inflammation and impaired liver function (P<0.0015 for 46 measures). Associations were consistent across cohorts with different ages at metabolic profiling, but the magnitudes were weak. The pattern of metabolic deviations associated with lower birth weight resembled the metabolic signature of higher adult BMI (R2=0.77). The resemblance indicated that 1-kg lower birth weight is associated with similar metabolic aberrations as caused by 0.92-units higher BMI in adulthood.\n\nConclusionLower birth weight is associated with adverse biomarker aberrations across multiple metabolic pathways. Coherent metabolic signatures between lower birth weight and higher adult adiposity suggest potentially shared underlying molecular mechanisms. However, the magnitudes of metabolic associations with birth weight are modest in comparison to the effects of adiposity, implying that birth weight is only a weak indicator of metabolic risk in adulthood.\n\nKEY POINTSO_LILower birth weight is adversely associated with a wide range of established and emerging circulating cardiometabolic biomarkers in adulthood, including lipoprotein subclasses and their lipids, fatty acid balance, amino acids, and markers of inflammation and liver function.\nC_LIO_LIThe metabolic associations are consistent across a wide age span from adolescence to retirement age, and similar for men and women.\nC_LIO_LIThe magnitudes of metabolic aberrations are weak for the variation in birth weight observed in general population cohorts. Although the metabolic associations with birth weight are statistically significant, they are likely to be of minor public health relevance.\nC_LIO_LIThe overall metabolic association pattern with lower birth weight closely resembles the metabolic signature of higher adult adiposity, suggesting that shared underlying metabolic pathways may be involved.\nC_LIO_LI1-kg lower birth weight ({approx}2 SD) is associated with similar adverse metabolic effects as caused by 0.92 higher BMI ({approx}0.25 SD) in adulthood. These findings indicate that fetal growth, as assessed by birth weight, only has minor effects on the adult metabolic risk profile in general population settings.\nC_LI

Systems Biology

Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine

Migraine is a debilitating neurological disorder affecting around 1 in 7 people worldwide, but its molecular mechanisms remain poorly understood. Some debate exists over whether migraine is a disease of vascular dysfunction, or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we performed the largest genetic study of migraine to date, comprising 59,674 cases and 316,078 controls from 22 GWA studies. We identified 45 independent single nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 x 10-8) that map to 38 distinct genomic loci, including 28 loci not previously reported and the first locus identified on chromosome X. Furthermore, a subset analysis for migraine without aura (MO) identified seven of the same loci as from the full sample, whereas no loci reached genome-wide significance in the migraine with aura (MA) subset. In subsequent computational analyzes, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies.

Genetics

Integrative approaches for large-scale transcriptome-wide association studies

Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance levels of one or multiple proteins. In this work we introduce a powerful strategy that integrates gene expression measurements with large-scale genome-wide association data to identify genes whose cis-regulated expression is associated to complex traits. We use a relatively small reference panel of individuals for which both genetic variation and gene expression have been measured to impute gene expression into large cohorts of individuals and identify expression-trait associations. We extend our methods to allow for indirect imputation of the expression-trait association from summary association statistics of large-scale GWAS1-3. We applied our approaches to expression data from blood and adipose tissue measured in [~]3,000 individuals overall. We then imputed gene expression into GWAS data from over 900,000 phenotype measurements4-6 to identify 69 novel genes significantly associated to obesity-related traits (BMI, lipids, and height). Many of the novel genes were associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Overall our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits.

Genetics