scholarly journals Puberty Status Modifies the Effects of Genetic Variants, Lifestyle Factors and Their Interactions on Adiponectin: The BCAMS Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Yunpeng Wu ◽  
Ling Zhong ◽  
Ge Li ◽  
Lanwen Han ◽  
Junling Fu ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Pubertal Development ◽  
Lifestyle Factors ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Exercise Frequency ◽  
Cross Sectional ◽  
Individual Snps ◽  
Diet Score

BackgroundHypoadiponectinemia has been associated with various cardiometabolic disease states. Previous studies in adults have shown that adiponectin levels were regulated by specific genetic and behavioral or lifestyle factors. However, little is known about the influence of these factors on adiponectin levels in children, particularly as mitigated by pubertal development.MethodsWe performed a cross-sectional analysis of data from 3,402 children aged 6-18 years from the Beijing Child and Adolescent Metabolic Syndrome (BCAMS) study. Pubertal progress was classified as prepubertal, midpuberty, and postpuberty. Six relevant single nucleotide polymorphisms (SNPs) were selected from previous genome-wide association studies of adiponectin in East Asians. Individual SNPs and two weighted genetic predisposition scores, as well as their interactions with 14 lifestyle factors, were analyzed to investigate their influence on adiponectin levels across puberty. The effect of these factors on adiponectin was analyzed using general linear models adjusted for age, sex, and BMI.ResultsAfter adjustment for age, sex, and BMI, the associations between adiponectin levels and diet items, and diet score were significant at prepuberty or postpuberty, while the effect of exercise on adiponectin levels was more prominent at mid- and postpuberty. Walking to school was found to be associated with increased adiponectin levels throughout puberty. Meanwhile, the effect of WDR11-FGFR2-rs3943077 was stronger at midpuberty (P = 0.002), and ADIPOQ-rs6773957 was more effective at postpuberty (P = 0.005), while CDH13-rs4783244 showed the strongest association with adiponectin levels at all pubertal stages (all P < 3.24 × 10-15). We further found that effects of diet score (Pinteraction = 0.022) and exercise (Pinteraction = 0.049) were stronger in children with higher genetic risk of hypoadiponectinemia, while higher diet score and exercise frequency attenuated the differences in adiponectin levels among children with different genetic risks.ConclusionsOur study confirmed puberty modulates the associations between adiponectin, and genetic variants, lifestyle factors, and gene-by-lifestyle interactions. These findings provide new insight into puberty-specific lifestyle suggestions, especially in genetically susceptible individuals.

scholarly journals Identification of three genetic variants as novel susceptibility loci for body mass index in a Japanese population

2018 ◽  
Vol 50 (3) ◽  
pp. 179-189 ◽  
Author(s):  
Yoshiki Yasukochi ◽  
Jun Sakuma ◽  
Ichiro Takeuchi ◽  
Kimihiko Kato ◽  
Mitsutoshi Oguri ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Genetic Variants ◽  
Japanese Population ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Susceptibility Loci ◽  
Cross Sectional ◽  
Japanese Subjects

Recent genome-wide association studies have identified various obesity or metabolic syndrome (MetS) susceptibility loci. However, most studies were conducted in a cross-sectional manner. To address this gap, we performed a longitudinal exome-wide association study to identify susceptibility loci for obesity and MetS in a Japanese population. We traced clinical data of 6,022 Japanese subjects who had annual health check-ups for several years (mean follow-up period, 5 yr) and genotyped ~244,000 genetic variants. The association of single nucleotide polymorphisms (SNPs) with body mass index (BMI) or the prevalence of obesity and MetS was examined in a generalized estimating equation model. Our longitudinal exome-wide association studies detected 21 BMI- and five MetS-associated SNPs (false discovery rate, FDR <0.01). Among these SNPs, 16 have not been previously implicated as determinants of BMI or MetS. Cross-sectional data for obesity- and MetS-related phenotypes in 7,285 Japanese subjects were examined in a replication study. Among the 16 SNPs, three ( rs9491140 , rs145848316 , and rs7863248 ) were related to BMI in the replication cohort ( P < 0.05). In conclusion, three SNPs [ rs9491140 of NKAIN2 (FDR = 0.003, P = 1.9 × 10−5), rs145848316 of KMT2C (FDR = 0.007, P = 4.5 × 10−5), and rs7863248 of AGTPBP1 (FDR = 0.006, P = 4.2 × 10−5)] were newly identified as susceptibility loci for BMI.

scholarly journals Association of GWAS-Based Candidate Genes with HDL-Cholesterol Levels before and after Bariatric Surgery in the Swedish Obese Subjects Study

2011 ◽  
Vol 96 (6) ◽  
pp. E953-E957 ◽  
Author(s):  
Mark A. Sarzynski ◽  
Peter Jacobson ◽  
Tuomo Rankinen ◽  
Björn Carlsson ◽  
Lars Sjöström ◽  
...  
Keyword(s):  
Bariatric Surgery ◽  
Weight Loss ◽  
Candidate Genes ◽  
Association Studies ◽  
Statistical Significance ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Cross Sectional ◽  
Time Points ◽  
Obese Subjects

Context and Objective: The magnitude of weight loss-induced high-density lipoprotein cholesterol (HDL-C) changes may depend on genetic factors. We examined the associations of eight candidate genes, identified by genome-wide association studies, with HDL-C at baseline and 10 yr after bariatric surgery in the Swedish Obese Subjects study. Methods: Single-nucleotide polymorphisms (SNP) (n = 60) in the following gene loci were genotyped: ABCA1, APOA5, CETP, GALNT2, LIPC, LIPG, LPL, and MMAB/MVK. Cross-sectional associations were tested before (n = 1771) and 2 yr (n = 1583) and 10 yr (n = 1196) after surgery. Changes in HDL-C were tested between baseline and yr 2 (n = 1518) and yr 2 and 10 (n = 1149). A multiple testing corrected threshold of P = 0.00125 was used for statistical significance. Results: In adjusted multivariate models, CETP SNP rs3764261 explained from 3.2–4.2% (P &lt; 10−14) of the variation in HDL-C at all three time points, whereas CETP SNP rs9939224 contributed an additional 0.6 and 0.9% at baseline and yr 2, respectively. LIPC SNP rs1077834 showed consistent associations across all time points (R2 = 0.4–1.1%; 3.8 × 10−6 &lt; P &lt; 3 × 10−3), whereas LPL SNP rs6993414 contributed approximately 0.5% (5 × 10−4 &lt; P &lt; 0.0012) at yr 2 and 10. In aggregate, four SNP in three genes explained 4.2, 6.8, and 5.6% of the HDL-C variance at baseline, yr 2, and yr 10, respectively. None of the SNP was significantly associated with weight loss-related changes in HDL-C. Conclusions: SNP in the CETP, LIPC, and LPL loci contribute significantly to plasma HDL-C levels in obese individuals, and the associations persist even after considerable weight loss due to bariatric surgery. However, they are not associated with surgery-induced changes in HDL-C levels.

scholarly journals Lipid associated polygenic enrichment in Alzheimer’s disease

2018 ◽  
Author(s):  
Iris J. Broce ◽  
Chin Hong Tan ◽  
Chun Chieh Fan ◽  
Aree Witoelar ◽  
Natalie Wen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Variants ◽  
Plasma Lipids ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genetic Pleiotropy ◽  
Common Genetic Variants

ABSTRACTCardiovascular (CV) and lifestyle associated risk factors (RFs) are increasingly recognized as important for Alzheimer’s disease (AD) pathogenesis. Beyond the ∊4 allele of apolipoprotein E (APOE), comparatively little is known about whether CV associated genes also increase risk for AD (genetic pleiotropy). Using large genome-wide association studies (GWASs) (total n > 500,000 cases and controls) and validated tools to quantify genetic pleiotropy, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with AD and one or more CV RFs, namely body mass index (BMI), type 2 diabetes (T2D), coronary artery disease (CAD), waist hip ratio (WHR), total cholesterol (TC), low-density (LDL) and high-density lipoprotein (HDL). In fold enrichment plots, we observed robust genetic enrichment in AD as a function of plasma lipids (TC, LDL, and HDL); we found minimal AD genetic enrichment conditional on BMI, T2D, CAD, and WHR. Beyond APOE, at conjunction FDR < 0.05 we identified 57 SNPs on 19 different chromosomes that were jointly associated with AD and CV outcomes including APOA4, ABCA1, ABCG5, LIPG, and MTCH2/SPI1. We found that common genetic variants influencing AD are associated with multiple CV RFs, at times with a different directionality of effect. Expression of these AD/CV pleiotropic genes was enriched for lipid metabolism processes, over-represented within astrocytes and vascular structures, highly co-expressed, and differentially altered within AD brains. Beyond APOE, we show that the polygenic component of AD is enriched for lipid associated RFs. Rather than a single causal link between genetic loci, RF and the outcome, we found that common genetic variants influencing AD are associated with multiple CV RFs. Our collective findings suggest that a network of genes involved in lipid biology also influence Alzheimer’s risk.

scholarly journals Polygenic risk score based on weight gain trajectories is predictive of childhood obesity

2019 ◽  
Author(s):  
Sarah J. C. Craig ◽  
Ana M. Kenney ◽  
Junli Lin ◽  
Ian M. Paul ◽  
Leann L. Birch ◽  
...  
Keyword(s):  
Weight Gain ◽  
Childhood Obesity ◽  
Risk Score ◽  
Genetic Variants ◽  
Association Studies ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide

AbstractObesity is highly heritable, yet only a small fraction of its heritability has been attributed to specific genetic variants. These variants are traditionally ascertained from genome-wide association studies (GWAS), which utilize samples with tens or hundreds of thousands of individuals for whom a single summary measurement (e.g., BMI) is collected. An alternative approach is to focus on a smaller, more deeply characterized sample in conjunction with advanced statistical models that leverage detailed phenotypes. Here we use novel functional data analysis (FDA) techniques to capitalize on longitudinal growth information and construct a polygenic risk score (PRS) for obesity in children followed from birth to three years of age. This score, comprised of 24 single nucleotide polymorphisms (SNPs), is significantly higher in children with (vs. without) rapid infant weight gain—a predictor of obesity later in life. Using two independent cohorts, we show that genetic variants identified in early childhood are also informative in older children and in adults, consistent with early childhood obesity being predictive of obesity later in life. In contrast, PRSs based on SNPs identified by adult obesity GWAS are not predictive of weight gain in our cohort of children. Our research provides an example of a successful application of FDA to GWAS. We demonstrate that a deep, statistically sophisticated characterization of a longitudinal phenotype can provide increased statistical power to studies with relatively small sample sizes. This study shows how FDA approaches can be used as an alternative to the traditional GWAS.Author SummaryFinding genetic variants that confer an increased risk of developing a particular disease has long been a focus of modern genetics. Genome wide association studies (GWAS) have catalogued single nucleotide polymorphisms (SNPs) associated with a variety of complex diseases in humans, including obesity, but by and large have done so using increasingly large samples-- tens or even hundreds of thousands of individuals, whose phenotypes are thus often only superficially characterized. This, in turn, may hide the intricacies of the genetic influence on disease. GWAS findings are also usually study-population dependent. We found that genetic risk scores based on SNPs from large adult obesity studies are not predictive of the propensity to gain weight in very young children. However, using a small cohort of a few hundred children deeply characterized with growth trajectories between birth and two years, and leveraging such trajectories through novel functional data analysis (FDA) techniques, we were able to produce a strong childhood obesity genetic risk score.

scholarly journals DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning

2016 ◽  
Author(s):  
Janine Arloth ◽  
Gökcen Eraslan ◽  
Till F.M. Andlauer ◽  
Jade Martins ◽  
Stella Iurato ◽  
...  
Keyword(s):  
Deep Learning ◽  
Disease Risk ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Cell Type ◽  
Individual Snps ◽  
Multivariate Gwas ◽  
Regulatory Effects ◽  
Joint Contribution

AbstractGenome-wide association studies (GWAS) identify genetic variants associated with quantitative traits or disease. Thus, GWAS never directly link variants to regulatory mechanisms, which, in turn, are typically inferred during post-hoc analyses. In parallel, a recent deep learning-based method allows for prediction of regulatory effects per variant on currently up to 1,000 cell type-specific chromatin features. We here describe “DeepWAS”, a new approach that directly integrates predictions of these regulatory effects of single variants into a multivariate GWAS setting. As a result, single variants associated with a trait or disease are, by design, coupled to their impact on a chromatin feature in a cell type. Up to 40,000 regulatory single-nucleotide polymorphisms (SNPs) were associated with multiple sclerosis (MS, 4,888 cases and 10,395 controls), major depressive disorder (MDD, 1,475 cases and 2,144 controls), and height (5,974 individuals) to each identify 43-61 regulatory SNPs, called deepSNPs, which are shown to reach at least nominal significance in large GWAS. MS- and height-specific deepSNPs resided in active chromatin and introns, whereas MDD-specific deepSNPs located mostly to intragenic regions and repressive chromatin states. We found deepSNPs to be enriched in public or cohort-matched expression and methylation quantitative trait loci and demonstrate the potential of the DeepWAS method to directly generate testable functional hypotheses based on genotype data alone. DeepWAS is an innovative GWAS approach with the power to identify individual SNPs in non-coding regions with gene regulatory capacity with a joint contribution to disease risk. DeepWAS is available at https://github.com/cellmapslab/DeepWAS.

scholarly journals Genetic Variants Shaping Inter-individual Differences in Response to Dietary Intakes—A Narrative Review of the Case of Vitamins

2020 ◽  
Vol 7 ◽  
Author(s):  
Aikaterini Niforou ◽  
Valentini Konstantinidou ◽  
Androniki Naska
Keyword(s):  
Vitamin D ◽  
Vitamin C ◽  
Genetic Variants ◽  
Current Knowledge ◽  
Association Studies ◽  
Genetic Variations ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Dietary Intakes ◽  
Genes Encoding

Recent advances in the field of nutrigenetics have provided evidence on how genetic variations can impact the individuals' response to dietary intakes. An objective and reliable assessment of dietary exposures should rely on combinations of methodologies including frequency questionnaires, short-term recalls or records, together with biological samples to evaluate markers of intake or status and to identify genetic susceptibilities. In an attempt to present current knowledge on how genetic fingerprints contribute to an individual's nutritional status, we present a review of current literature describing associations between genetic variants and levels of well-established biomarkers of vitamin status in free-living and generally healthy individuals. Based on the outcomes of candidate gene, genome-wide-association studies and meta-analyses thereof, we have identified several single nucleotide polymorphisms (SNPs) involved in the vitamins' metabolic pathways. Polymorphisms in genes encoding proteins involved in vitamin metabolism and transport are reported to have an impact on vitamin D status; while genetic variants of vitamin D receptor were most frequently associated with health outcomes. Genetic variations that can influence vitamin E status include SNPs involved in its uptake and transport, such as in SCAR-B1 gene, and in lipoprotein metabolism. Variants of the genes encoding the sodium-dependent vitamin C transport proteins are greatly associated with the body's status on vitamin C. Regarding the vitamins of the B-complex, special reference is made to the widely studied variant in the MTHFR gene. Methodological attributes of genetic studies that may limit the comparability and interpretability of the findings are also discussed. Our understanding of how genes affect our responses to nutritional triggers will enhance our capacity to evaluate dietary exposure and design personalized nutrition programs to sustain health and prevent disease.

scholarly journals Genetic Variants behind Cardiovascular Diseases and Dementia

Genes ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1514
Author(s):  
Wei-Min Ho ◽  
Yah-Yuan Wu ◽  
Yi-Chun Chen
Keyword(s):  
White Matter ◽  
Cardiovascular Diseases ◽  
Genetic Variants ◽  
White Matter Hyperintensities ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genetic Associations ◽  
Pubmed Database ◽  
Risk Snps

Cardiovascular diseases (CVDs) and dementia are the leading causes of disability and mortality. Genetic connections between cardiovascular risk factors and dementia have not been elucidated. We conducted a scoping review and pathway analysis to reveal the genetic associations underlying both CVDs and dementia. In the PubMed database, literature was searched using keywords associated with diabetes mellitus, hypertension, dyslipidemia, white matter hyperintensities, cerebral microbleeds, and covert infarctions. Gene lists were extracted from these publications to identify shared genes and pathways for each group. This included high penetrance genes and single nucleotide polymorphisms (SNPs) identified through genome wide association studies. Most risk SNPs to both diabetes and dementia participate in the phospholipase C enzyme system and the downstream nositol 1,4,5-trisphosphate and diacylglycerol activities. Interestingly, AP-2 (TFAP2) transcription factor family and metabolism of vitamins and cofactors were associated with genetic variants that were shared by white matter hyperintensities and dementia, and by microbleeds and dementia. Variants shared by covert infarctions and dementia were related to VEGF ligand–receptor interactions and anti-inflammatory cytokine pathways. Our review sheds light on future investigations into the causative relationships behind CVDs and dementia, and can be a paradigm of the identification of dementia treatments.

scholarly journals Host Genetic Variants Potentially Associated with SARS-Cov-2: A Multi-Population Analysis

2020 ◽  
Author(s):  
Maria K. Smatti ◽  
Yasser Al-Sarraj ◽  
Omar Albagha ◽  
Hadi M. Yassine
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Population Analysis ◽  
Fold Change ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Risk Alleles ◽  
Risk Variants ◽  
Genome Wide ◽  
Ifn Γ

Background: Clinical outcomes of Coronavirus Disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) showed enormous inter-individual and interpopulation differences, possibly due to host genetics differences. Earlier studies identified single nucleotide polymorphisms (SNPs) associated with SARS-CoV-1 in Eastern Asian (EAS) populations. In this report, we aimed at exploring the frequency of a set of genetic polymorphisms that could affect SARS-CoV-2 susceptibility or severity, including those that were previously associated with SARS-CoV-1. Methods: We extracted the list of SNPs that could potentially modulate SARS-CoV-2 from the genome wide association studies (GWAS) on SARS-CoV-1 and other viruses. We also collected the expression data of these SNPs from the expression quantitative trait loci (eQTLs) databases. Sequences from Qatar Genome Programme (QGP, n=6,054) and 1000Genome project were used to calculate and compare allelic frequencies (AF). Results: A total of 74 SNPs, located in 10 genes: ICAM3, IFN-γ, CCL2, CCL5, AHSG, MBL, Furin, TMPRSS2, IL4, and CD209 promoter, were identified. Analysis of Qatari genomes revealed significantly lower AF of risk variants linked to SARS-CoV-1 severity (CCL2, MBL, CCL5, AHSG, and IL4) compared to that of 1000Genome and/or the EAS population (up to 25-fold change). Conversely, SNPs in TMPRSS2, IFN-γ, ICAM3, and Furin were more common among Qataris (average 2-fold change). Inter-population analysis showed that the distribution of risk alleles among Europeans differs substantially from Africans and EASs. Remarkably, Africans seem to carry extremely lower frequencies of SARS-CoV-1 susceptibility alleles, reaching to 32-fold decrease compared to other populations. Conclusion: Multiple genetic variants, which could potentially modulate SARS-CoV-2 infection, are significantly variable between populations, with the lowest frequency observed among Africans. Our results highlight the importance of exploring population genetics to understand and predict COVID-19 outcomes. Indeed, further studies are needed to validate these findings as well as to identify new genetic determinants linked to SARS-CoV-2.

scholarly journals A Genome-Wide Association Study of Novel Genetic Variants Associated With Anthropometric Traits in Koreans

2021 ◽  
Vol 12 ◽  
Author(s):  
Hye-Won Cho ◽  
Hyun-Seok Jin ◽  
Yong-Bin Eom
Keyword(s):  
Genetic Variants ◽  
Genetic Factors ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Fat Distribution ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
A Genome

Most previous genome-wide association studies (GWAS) have identified genetic variants associated with anthropometric traits. However, most of the evidence were reported in European populations. Anthropometric traits such as height and body fat distribution are significantly affected by gender and genetic factors. Here we performed GWAS involving 64,193 Koreans to identify the genetic factors associated with anthropometric phenotypes including height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip ratio. We found nine novel single-nucleotide polymorphisms (SNPs) and 59 independent genetic signals in genomic regions that were reported previously. Of the 19 SNPs reported previously, eight genetic variants at RP11-513I15.6 and one genetic variant at the RP11-977G19.10 region and six Asian-specific genetic variants were newly found. We compared our findings with those of previous studies in other populations. Five overlapping genetic regions (PAN2, ANKRD52, RNF41, HGMA1, and C6orf106) had been reported previously but none of the SNPs were independently identified in the current study. Seven of the nine newly found novel loci associated with height in women revealed a statistically significant skeletal expression of quantitative trait loci. Our study provides additional insight into the genetic effects of anthropometric phenotypes in East Asians.

scholarly journals Differential Impact of Genetic Loci on Age at Thelarche and Menarche in Healthy Girls

2017 ◽  
Vol 103 (1) ◽  
pp. 228-234 ◽  
Author(s):  
Alexander S Busch ◽  
Casper P Hagen ◽  
Maria Assens ◽  
Katharina M Main ◽  
Kristian Almstrup ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Population Based ◽  
Age At Menarche ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Differential Impact ◽  
Cross Sectional ◽  
Z Scores ◽  
Allele Count

Abstract Context Recent genetic studies have identified genetic variants associated with age at pubertal onset. Whereas genome-wide association studies reported associations of several hundred genetic variants with timing of self-reported age at menarche, a recent clinical study focused on genetic variation affecting follicle-stimulating hormone action and clinically determined age at thelarche. The observations appear to be incongruent, as effect sizes varied substantially among the studies. Alternatively, this may point to a differential impact of specific genetic loci on distinct pubertal events. Objective To investigate whether top-candidate genetic variants exhibit a different impact on timing of thelarche vs menarche, respectively. Design Cross-sectional and longitudinal study of healthy girls. Setting Population-based study in the Copenhagen area. Patients or Other Participants Girls (1478) were followed through puberty and genotyped for FSHB c.−211G&gt;T (rs10835638), FSHR c.−29G&gt;A (rs1394205), FSHR c.2039A&gt;G (rs6116), LIN28B (rs7759938), INHA (rs4141153), MKRN3 (rs12148769), TMEM38B (rs10453225), and ZNF483 (rs10980921). Main Outcome Measures Clinical pubertal staging and anthropometric data. Results We observed an association of LIN28B (rs7759938) with age at thelarche (P &lt; 0.001, effect size: 0.27 year, 95% confidence interval: 0.12 to 0.42) and age at menarche (P = 0.005, 0.17 year, 0.05 to 0.29). FSHB c.−211G&gt;T (rs10835638) and FSHR c.−29G&gt;A (rs1394205) minor allele count was associated with age at thelarche (P = 0.004, 0.19 year, 0.06 to 0.31) but not with age at menarche (P = 0.97; all adjusted for body mass index z scores). Conclusion Our results indicate a differential impact of specific genetic loci on age at thelarche and menarche in healthy girls.

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