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1.
Commun Med (Lond) ; 4(1): 159, 2024 Aug 07.
Article in English | MEDLINE | ID: mdl-39112679

ABSTRACT

BACKGROUND: Pubertal timing is heritable, varies between individuals, and has implications for life-course health. There are many different indicators of pubertal timing, and how they relate to each other is unclear. Our aim was to quantitatively compare nine indicators of pubertal timing. METHODS: We used data from questionnaires and height, weight, and bone measurements from ages 7-17 y in a population-based cohort of 4267 females and 4251 males to compare nine growth and development-based indicators of pubertal timing. We summarise age of each indicator, their phenotypic and genetic correlations, and how they relate to established genetic risk score (GRS) for puberty timing, and phenotypic childhood body composition measures. RESULTS: We show that pubic hair in males (mean: 12.6 y) and breasts in females (11.5 y) are early indicators of puberty, and voice breaking (14.2 y) and menarche (12.7 y) are late indicators however, there is substantial variation between individuals in pubertal age. All indicators show evidence of positive phenotypic intercorrelations (e.g., r = 0.49: male genitalia and pubic hair ages), and positive genetic intercorrelations. An age at menarche GRS positively associates with all other pubertal age indicators (e.g., difference in female age at peak height velocity per SD higher GRS: 0.24 y, 95%CI: 0.21 to 0.26), as does an age at voice breaking GRS (e.g., difference in age at male axillary hair: 0.11 y, 0.07 to 0.15). Higher childhood fat mass and lean mass associated with earlier puberty timing. CONCLUSIONS: Our findings provide insights into the measurements of the timing of pubertal growth and development and illustrate value of various pubertal timing indicators in life-course research.


Age of puberty varies between individuals and can affect a person's future health. We obtained information from 8500 British children as they progressed through puberty. We compared nine measures of pubertal timing. We found that the appearance of pubic hair in boys and breasts in girls are early indicators of puberty, and that voice change and onset of menstruation are late indicators. However, there was also substantial variability between individuals in age of puberty. All puberty measures were correlated with each other and related to an individual's adult body mass index, as well as to their childhood muscle and fat mass. Our findings are useful information for health care workers and researchers who are interested in assessing and studying puberty.

2.
JACC Adv ; 3(2): 100808, 2024 Feb.
Article in English | MEDLINE | ID: mdl-38939392

ABSTRACT

Background: Prenatal urban environmental exposures have been associated with blood pressure in children. The dynamic of these associations across childhood and later ages is unknown. Objectives: The purpose of this study was to assess associations of prenatal urban environmental exposures with blood pressure trajectories from childhood to early adulthood. Methods: Repeated measures of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were collected in up to 7,454 participants from a UK birth cohort. Prenatal urban exposures (n = 43) covered measures of noise, air pollution, built environment, natural spaces, traffic, meteorology, and food environment. An exposome-wide association study approach was used. Linear spline mixed-effects models were used to model associations of each exposure with trajectories of blood pressure. Replication was sought in 4 independent European cohorts (up to 9,261). Results: In discovery analyses, higher humidity was associated with a faster increase (mean yearly change in SBP for an interquartile range increase in humidity: 0.29 mm Hg/y, 95% CI: 0.20-0.39) and higher temperature with a slower increase (mean yearly change in SBP per interquartile range increase in temperature: -0.17 mm Hg/y, 95% CI: -0.28 to -0.07) in SBP in childhood. Higher levels of humidity and air pollution were associated with faster increase in DBP in childhood and slower increase in adolescence. There was little evidence of an association of other exposures with change in SBP or DBP. Results for humidity and temperature, but not for air pollution, were replicated in other cohorts. Conclusions: Replicated findings suggest that higher prenatal humidity and temperature could modulate blood pressure changes across childhood.

3.
Pediatr Res ; 2024 Jun 19.
Article in English | MEDLINE | ID: mdl-38898107

ABSTRACT

BACKGROUND: Globally, one in ten babies is born preterm (<37 weeks), and 1-2% preterm at very low birth weight (VLBW, <1500 g). As adults, they are at increased risk for a plethora of health conditions, e.g., cardiometabolic disease, which may partly be mediated by epigenetic regulation. We compared blood DNA methylation between young adults born at VLBW and controls. METHODS: 157 subjects born at VLBW and 161 controls born at term, from the Helsinki Study of Very Low Birth Weight Adults, were assessed for peripheral venous blood DNA methylation levels at mean age of 22 years. Significant CpG-sites (5'-C-phosphate-G-3') were meta-analyzed against continuous birth weight in four independent cohorts (pooled n = 2235) with cohort mean ages varying from 0 to 31 years. RESULTS: In the discovery cohort, 66 CpG-sites were differentially methylated between VLBW adults and controls. Top hits were located in HIF3A, EBF4, and an intergenic region nearest to GLI2 (distance 57,533 bp). Five CpG-sites, all in proximity to GLI2, were hypermethylated in VLBW and associated with lower birth weight in the meta-analysis. CONCLUSION: We identified differentially methylated CpG-sites suggesting an epigenetic signature of preterm birth at VLBW present in adult life. IMPACT: Being born preterm at very low birth weight has major implications for later health and chronic disease risk factors. The mechanism linking preterm birth to later outcomes remains unknown. Our cohort study of 157 very low birth weight adults and 161 controls found 66 differentially methylated sites at mean age of 22 years. Our findings suggest an epigenetic mark of preterm birth present in adulthood, which opens up opportunities for mechanistic studies.

4.
Aging Cell ; 23(8): e14194, 2024 Aug.
Article in English | MEDLINE | ID: mdl-38808605

ABSTRACT

Worldwide trends to delay childbearing have increased parental ages at birth. Older parental age may harm offspring health, but mechanisms remain unclear. Alterations in offspring DNA methylation (DNAm) patterns could play a role as aging has been associated with methylation changes in gametes of older individuals. We meta-analyzed epigenome-wide associations of parental age with offspring blood DNAm of over 9500 newborns and 2000 children (5-10 years old) from the Pregnancy and Childhood Epigenetics consortium. In newborns, we identified 33 CpG sites in 13 loci with DNAm associated with maternal age (PFDR < 0.05). Eight of these CpGs were located near/in the MTNR1B gene, coding for a melatonin receptor. Regional analysis identified them together as a differentially methylated region consisting of 9 CpGs in/near MTNR1B, at which higher DNAm was associated with greater maternal age (PFDR = 6.92 × 10-8) in newborns. In childhood blood samples, these differences in blood DNAm of MTNR1B CpGs were nominally significant (p < 0.05) and retained the same positive direction, suggesting persistence of associations. Maternal age was also positively associated with higher DNA methylation at three CpGs in RTEL1-TNFRSF6B at birth (PFDR < 0.05) and nominally in childhood (p < 0.0001). Of the remaining 10 CpGs also persistent in childhood, methylation at cg26709300 in YPEL3/BOLA2B in external data was associated with expression of ITGAL, an immune regulator. While further study is needed to establish causality, particularly due to the small effect sizes observed, our results potentially support offspring DNAm as a mechanism underlying associations of maternal age with child health.


Subject(s)
DNA Methylation , Maternal Age , DNA Methylation/genetics , Humans , Female , Infant, Newborn , Child , Adult , Male , Child, Preschool , CpG Islands/genetics , Pregnancy
5.
Environ Sci Technol ; 58(17): 7256-7269, 2024 Apr 30.
Article in English | MEDLINE | ID: mdl-38641325

ABSTRACT

Through investigating the combined impact of the environmental exposures experienced by an individual throughout their lifetime, exposome research provides opportunities to understand and mitigate negative health outcomes. While current exposome research is driven by epidemiological studies that identify associations between exposures and effects, new frameworks integrating more substantial population-level metadata, including electronic health and administrative records, will shed further light on characterizing environmental exposure risks. Molecular biology offers methods and concepts to study the biological and health impacts of exposomes in experimental and computational systems. Of particular importance is the growing use of omics readouts in epidemiological and clinical studies. This paper calls for the adoption of mechanistic molecular biology approaches in exposome research as an essential step in understanding the genotype and exposure interactions underlying human phenotypes. A series of recommendations are presented to make the necessary and appropriate steps to move from exposure association to causation, with a huge potential to inform precision medicine and population health. This includes establishing hypothesis-driven laboratory testing within the exposome field, supported by appropriate methods to read across from model systems research to human.


Subject(s)
Environmental Exposure , Exposome , Humans , Molecular Biology
6.
Aging Cell ; 23(7): e14164, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38637937

ABSTRACT

Metabolomic age models have been proposed for the study of biological aging, however, they have not been widely validated. We aimed to assess the performance of newly developed and existing nuclear magnetic resonance spectroscopy (NMR) metabolomic age models for prediction of chronological age (CA), mortality, and age-related disease. Ninety-eight metabolic variables were measured in blood from nine UK and Finnish cohort studies (N ≈31,000 individuals, age range 24-86 years). We used nonlinear and penalized regression to model CA and time to all-cause mortality. We examined associations of four new and two previously published metabolomic age models, with aging risk factors and phenotypes. Within the UK Biobank (N ≈102,000), we tested prediction of CA, incident disease (cardiovascular disease (CVD), type-2 diabetes mellitus, cancer, dementia, and chronic obstructive pulmonary disease), and all-cause mortality. Seven-fold cross-validated Pearson's r between metabolomic age models and CA ranged between 0.47 and 0.65 in the training cohort set (mean absolute error: 8-9 years). Metabolomic age models, adjusted for CA, were associated with C-reactive protein, and inversely associated with glomerular filtration rate. Positively associated risk factors included obesity, diabetes, smoking, and physical inactivity. In UK Biobank, correlations of metabolomic age with CA were modest (r = 0.29-0.33), yet all metabolomic model scores predicted mortality (hazard ratios of 1.01 to 1.06/metabolomic age year) and CVD, after adjustment for CA. While metabolomic age models were only moderately associated with CA in an independent population, they provided additional prediction of morbidity and mortality over CA itself, suggesting their wider applicability.


Subject(s)
Aging , Magnetic Resonance Spectroscopy , Metabolomics , Humans , Aged , Middle Aged , Aged, 80 and over , Adult , Metabolomics/methods , Male , Female , Magnetic Resonance Spectroscopy/methods , Longevity , Cohort Studies , Young Adult , Risk Factors , Finland/epidemiology
7.
medRxiv ; 2024 Mar 16.
Article in English | MEDLINE | ID: mdl-38559031

ABSTRACT

Genetic effects on changes in human traits over time are understudied and may have important pathophysiological impact. We propose a framework that enables data quality control, implements mixed models to evaluate trajectories of change in traits, and estimates phenotypes to identify age-varying genetic effects in genome-wide association studies (GWASs). Using childhood body mass index (BMI) as an example, we included 71,336 participants from six cohorts and estimated the slope and area under the BMI curve within four time periods (infancy, early childhood, late childhood and adolescence) for each participant, in addition to the age and BMI at the adiposity peak and the adiposity rebound. GWAS on each of the estimated phenotypes identified 28 genome-wide significant variants at 13 loci across the 12 estimated phenotypes, one of which was novel (in DAOA) and had not been previously associated with childhood or adult BMI. Genetic studies of changes in human traits over time could uncover novel biological mechanisms influencing quantitative traits.

8.
Article in English | MEDLINE | ID: mdl-38366065

ABSTRACT

Understanding the biological mechanisms behind multimorbidity patterns in adolescence is important as they may act as intermediary risk factor for long-term health. We aimed to explore relationship between prenatal exposures and adolescent's psycho-cardiometabolic intermediary traits mediated through epigenetic biomarkers, using structural equation modeling (SEM). We used data from mother-child dyads from pregnancy and adolescents at 16-17 years from two prospective cohorts: Northern Finland Birth Cohort 1986 (NFBC1986) and Raine Study from Australia. Factor analysis was applied to generate two different latent factor structures: (a) prenatal exposures and (b) adolescence psycho-cardiometabolic intermediary traits. Furthermore, three types of epigenetic biomarkers were included: (1) DNA methylation score for maternal smoking during pregnancy (DNAmMSS), (2) DNAm age estimate PhenoAge and (3) DNAm estimate for telomere length (DNAmTL). Similar factor structure was observed between both cohorts yielding three prenatal factors, namely BMI (Body Mass Index), SOP (Socio-Obstetric-Profile), and Lifestyle, and four adolescent factors: Anthropometric, Insulin-Triglycerides, Blood Pressure, and Mental health. In the SEM pathways, stronger direct effects of F1prenatal-BMI (NFBC1986 = ß: 0.27; Raine = ß: 0.39) and F2prenatal-SOP (ß: -0.11) factors were observed on adolescent psycho-cardiometabolic multimorbidity. We observed an indirect effect of prenatal latent factors through epigenetic markers on a psycho-cardiometabolic multimorbidity factor in Raine study (P < 0.05). The present study exemplifies an evidence-based approach in two different birth cohorts to demonstrate similar composite structure of prenatal exposures and psycho-cardiometabolic traits (despite cultural, social, and genetic differences) and a common plausible pathway between them through underlying epigenetic markers.

9.
Commun Biol ; 7(1): 66, 2024 01 09.
Article in English | MEDLINE | ID: mdl-38195839

ABSTRACT

Higher birth order is associated with altered risk of many disease states. Changes in placentation and exposures to in utero growth factors with successive pregnancies may impact later life disease risk via persistent DNA methylation alterations. We investigated birth order with Illumina DNA methylation array data in each of 16 birth cohorts (8164 newborns) with European, African, and Latino ancestries from the Pregnancy and Childhood Epigenetics Consortium. Meta-analyzed data demonstrated systematic DNA methylation variation in 341 CpGs (FDR adjusted P < 0.05) and 1107 regions. Forty CpGs were located within known quantitative trait loci for gene expression traits in blood, and trait enrichment analysis suggested a strong association with immune-related, transcriptional control, and blood pressure regulation phenotypes. Decreasing fertility rates worldwide with the concomitant increased proportion of first-born children highlights a potential reflection of birth order-related epigenomic states on changing disease incidence trends.


Subject(s)
Birth Order , DNA Methylation , Child , Female , Humans , Infant, Newborn , Pregnancy , Epigenesis, Genetic , Epigenomics
10.
Acta Paediatr ; 113(4): 654-669, 2024 04.
Article in English | MEDLINE | ID: mdl-38216530

ABSTRACT

AIM: Globally, 1 in 10 babies are born preterm. Families with preterm born infants may suffer strains related to the presence of a preterm child. To date, most evidence focuses on the outcome of children born preterm and of their parents. Our objective was to investigate the evidence on the impact of having a preterm born sibling on cognitive function, mental health and quality of life of term-born siblings and critically appraise the evidence. METHODS: We searched five electronic databases, Google Scholar and reference lists. Two reviewers independently conducted screening, data extraction and critical appraisal. RESULTS: We retrieved 9121 articles. After duplicates, titles, abstract and full text review, seven studies met the inclusion criteria. One study reported higher anxiety and depression scores on index cases in the term born comparison group, compared to the index cases in the preterm born sibling group. Another study reported more feelings of reduced parental attention, and more interpersonal problems in the preterm born sibling group, than the comparison group. CONCLUSIONS: Although two studies reported a difference in outcomes between index cases in preterm born sibling groups and comparison groups, the scarce evidence did not allow us to delineate an effect or lack of it.


Subject(s)
Cognition , Infant, Premature , Mental Health , Quality of Life , Siblings , Humans , Siblings/psychology , Infant, Newborn , Child
11.
Psychol Health ; : 1-20, 2024 Jan 25.
Article in English | MEDLINE | ID: mdl-38270065

ABSTRACT

The study aims to investigate the associations of compassion and self-compassion with body composition, and whether adulthood compassion and self-compassion moderate the relationship between childhood SEP and adulthood body composition. The participants came from the Northern Finland Birth Cohort 1986 Study (n = 789, 52.1% women), with a mean age of 34.0 years. Compassion and self-compassion were measured with the Dispositional Positive Emotions Scale and Self-Compassion Scale-Short Form, respectively. Body composition was assessed using anthropometric and body fat measurements at a clinic. Childhood SEP included parental occupation, education, and employment. The results showed that high compassion was associated with three out of the five body composition measurements, namely lower waist circumference (B = -0.960, p = 0.039, 95% CI: -1.870; -0.498), body fat percentage (B = -0.693, p = 0.030, 95% CI: -1.317; -0.069), and fat mass index (B = -0.325, p = 0.023, 95% CI: -0.605; -0.044) (adjusted for sex, and childhood and adulthood SEP) but not with body mass index or waist-to-hip ratio. Self-compassion was not associated with body composition. Neither compassion nor self-compassion moderated the association between childhood SEP and adulthood body composition, as the interaction effects were not significant. Therefore, the dispositions did not protect against the negative effects of childhood SEP on adulthood body composition. High other-directed compassion may be, however, associated with healthier body composition.

12.
medRxiv ; 2023 Nov 08.
Article in English | MEDLINE | ID: mdl-37986811

ABSTRACT

Metabolomic age models have been proposed for the study of biological aging, however they have not been widely validated. We aimed to assess the performance of newly developed and existing nuclear magnetic resonance spectroscopy (NMR) metabolomic age models for prediction of chronological age (CA), mortality, and age-related disease. 98 metabolic variables were measured in blood from nine UK and Finnish cohort studies (N ≈ 31,000 individuals, age range 24-86 years). We used non-linear and penalised regression to model CA and time to all-cause mortality. We examined associations of four new and two previously published metabolomic age models, with ageing risk factors and phenotypes. Within the UK Biobank (N≈ 102,000), we tested prediction of CA, incident disease (cardiovascular disease (CVD), type-2 diabetes mellitus, cancer, dementia, chronic obstructive pulmonary disease) and all-cause mortality. Cross-validated Pearson's r between metabolomic age models and CA ranged between 0.47-0.65 in the training set (mean absolute error: 8-9 years). Metabolomic age models, adjusted for CA, were associated with C-reactive protein, and inversely associated with glomerular filtration rate. Positively associated risk factors included obesity, diabetes, smoking, and physical inactivity. In UK Biobank, correlations of metabolomic age with chronological age were modest (r = 0.29-0.33), yet all metabolomic model scores predicted mortality (hazard ratios of 1.01 to 1.06 / metabolomic age year) and CVD, after adjustment for CA. While metabolomic age models were only moderately associated with CA in an independent population, they provided additional prediction of morbidity and mortality over CA itself, suggesting their wider applicability.

13.
Sci Rep ; 13(1): 18434, 2023 10 27.
Article in English | MEDLINE | ID: mdl-37891192

ABSTRACT

Hearing loss and hearing disorders represent possible mediating pathways in the associations between noise exposures and non-auditory health outcomes. In this context, we assessed whether the noise-obesity associations should consider hearing functions as possible mediators and applied Mendelian randomisation (MR) to investigate causal relationships between body constitution and hearing impairments. We obtained genetic associations from publicly available summary statistics from genome-wide association studies in European ancestry adult populations (N= from 210,088 to 360,564) for (i) body constitution: body mass index (BMI), waist circumference (WC) and body fat percentage (BFP), and (ii) hearing loss: sensorineural hearing loss, noise-induced hearing loss, and age-related hearing impairment (ARHI). We employed colocalisation analysis to investigate the genetic associations for BMI and ARHI liability within an FTO locus. We conducted bi-directional MR for the 'forward' (from body constitution to hearing) and 'reverse' directions. We applied the random effects inverse variance-weighted method as the main MR method, with additional sensitivity analyses. Colocalisation analysis suggested that BMI and ARHI shared a causal variant at the FTO gene. We did not find robust evidence for causal associations from body constitution to hearing loss and suggested that some associations may be driven by FTO variants. In the reverse analyses, ARHI was negatively associated with BMI [effect size - 0.22 (95% CI - 0.44 to - 0.01)] and BFP [effect size - 0.23 (95% CI - 0.45 to 0.00)], supporting the notion that ARHI may diminish body constitution. Finally, our data suggest that there is no strong evidence that hearing explains the association between noise exposure and body constitution.


Subject(s)
Deafness , Genome-Wide Association Study , Adult , Humans , Obesity/complications , Body Constitution , Deafness/complications , Body Mass Index , Mendelian Randomization Analysis , Polymorphism, Single Nucleotide , Alpha-Ketoglutarate-Dependent Dioxygenase FTO/genetics
14.
Diabetes Care ; 46(11): 2067-2075, 2023 11 01.
Article in English | MEDLINE | ID: mdl-37756535

ABSTRACT

OBJECTIVE: Dietary glycemic index (GI) and glycemic load (GL) are associated with cardiometabolic health in children and adolescents, with potential distinct effects in people with increased BMI. DNA methylation (DNAm) may mediate these effects. Thus, we conducted meta-analyses of epigenome-wide association studies (EWAS) between dietary GI and GL and blood DNAm of children and adolescents. RESEARCH DESIGN AND METHODS: We calculated dietary GI and GL and performed EWAS in children and adolescents (age range: 4.5-17 years) from six cohorts (N = 1,187). We performed stratified analyses of participants with normal weight (n = 801) or overweight or obesity (n = 386). We performed look-ups for the identified cytosine-phosphate-guanine (CpG) sites (false discovery rate [FDR] <0.05) with tissue-specific gene expression of 832 blood and 223 subcutaneous adipose tissue samples from children and adolescents. RESULTS: Dietary GL was positively associated with DNAm of cg20274553 (FDR <0.05), annotated to WDR27. Several CpGs were identified in the normal-weight (GI: 85; GL: 17) and overweight or obese (GI: 136; GL: 298; FDR <0.05) strata, and none overlapped between strata. In participants with overweight or obesity, identified CpGs were related to RNA expression of genes associated with impaired metabolism (e.g., FRAT1, CSF3). CONCLUSIONS: We identified 537 associations between dietary GI and GL and blood DNAm, mainly in children and adolescents with overweight or obesity. High-GI and/or -GL diets may influence epigenetic gene regulation and thereby promote metabolic derangements in young people with increased BMI.


Subject(s)
Glycemic Index , Glycemic Load , Humans , Child , Adolescent , Child, Preschool , Glycemic Index/physiology , Overweight , DNA Methylation/genetics , Epigenome , Diet , Obesity , Proto-Oncogene Proteins , Adaptor Proteins, Signal Transducing
15.
Int J Med Inform ; 179: 105209, 2023 Nov.
Article in English | MEDLINE | ID: mdl-37729839

ABSTRACT

BACKGROUND: The human exposome encompasses all exposures that individuals encounter throughout their lifetime. It is now widely acknowledged that health outcomes are influenced not only by genetic factors but also by the interactions between these factors and various exposures. Consequently, the exposome has emerged as a significant contributor to the overall risk of developing major diseases, such as cardiovascular disease (CVD) and diabetes. Therefore, personalized early risk assessment based on exposome attributes might be a promising tool for identifying high-risk individuals and improving disease prevention. OBJECTIVE: Develop and evaluate a novel and fair machine learning (ML) model for CVD and type 2 diabetes (T2D) risk prediction based on a set of readily available exposome factors. We evaluated our model using internal and external validation groups from a multi-center cohort. To be considered fair, the model was required to demonstrate consistent performance across different sub-groups of the cohort. METHODS: From the UK Biobank, we identified 5,348 and 1,534 participants who within 13 years from the baseline visit were diagnosed with CVD and T2D, respectively. An equal number of participants who did not develop these pathologies were randomly selected as the control group. 109 readily available exposure variables from six different categories (physical measures, environmental, lifestyle, mental health events, sociodemographics, and early-life factors) from the participant's baseline visit were considered. We adopted the XGBoost ensemble model to predict individuals at risk of developing the diseases. The model's performance was compared to that of an integrative ML model which is based on a set of biological, clinical, physical, and sociodemographic variables, and, additionally for CVD, to the Framingham risk score. Moreover, we assessed the proposed model for potential bias related to sex, ethnicity, and age. Lastly, we interpreted the model's results using SHAP, a state-of-the-art explainability method. RESULTS: The proposed ML model presents a comparable performance to the integrative ML model despite using solely exposome information, achieving a ROC-AUC of 0.78±0.01 and 0.77±0.01 for CVD and T2D, respectively. Additionally, for CVD risk prediction, the exposome-based model presents an improved performance over the traditional Framingham risk score. No bias in terms of key sensitive variables was identified. CONCLUSIONS: We identified exposome factors that play an important role in identifying patients at risk of CVD and T2D, such as naps during the day, age completed full-time education, past tobacco smoking, frequency of tiredness/unenthusiasm, and current work status. Overall, this work demonstrates the potential of exposome-based machine learning as a fair CVD and T2D risk assessment tool.


Subject(s)
Cardiovascular Diseases , Diabetes Mellitus, Type 2 , Exposome , Humans , Diabetes Mellitus, Type 2/epidemiology , Risk Factors , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/etiology , Machine Learning
16.
Bioinformatics ; 39(7)2023 07 01.
Article in English | MEDLINE | ID: mdl-37348543

ABSTRACT

MOTIVATION: Genome-wide association studies (GWAS) have been successful in identifying genomic loci associated with complex traits. Genetic fine-mapping aims to detect independent causal variants from the GWAS-identified loci, adjusting for linkage disequilibrium patterns. RESULTS: We present "FiniMOM" (fine-mapping using a product inverse-moment prior), a novel Bayesian fine-mapping method for summarized genetic associations. For causal effects, the method uses a nonlocal inverse-moment prior, which is a natural prior distribution to model non-null effects in finite samples. A beta-binomial prior is set for the number of causal variants, with a parameterization that can be used to control for potential misspecifications in the linkage disequilibrium reference. The results of simulations studies aimed to mimic a typical GWAS on circulating protein levels show improved credible set coverage and power of the proposed method over current state-of-the-art fine-mapping method SuSiE, especially in the case of multiple causal variants within a locus. AVAILABILITY AND IMPLEMENTATION: https://vkarhune.github.io/finimom/.


Subject(s)
Genome-Wide Association Study , Genomics , Genome-Wide Association Study/methods , Bayes Theorem , Chromosome Mapping/methods , Linkage Disequilibrium , Polymorphism, Single Nucleotide
17.
PLoS Genet ; 19(6): e1010508, 2023 Jun.
Article in English | MEDLINE | ID: mdl-37390107

ABSTRACT

Coronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree of multimorbidity, which may be explained by shared genetic influences. However, research exploring the presence of pleiotropic variants and genes common to CAD, T2D and depression is lacking. The present study aimed to identify genetic variants with effects on cross-trait liability to psycho-cardiometabolic diseases. We used genomic structural equation modelling to perform a multivariate genome-wide association study of multimorbidity (Neffective = 562,507), using summary statistics from univariate genome-wide association studies for CAD, T2D and major depression. CAD was moderately genetically correlated with T2D (rg = 0.39, P = 2e-34) and weakly correlated with depression (rg = 0.13, P = 3e-6). Depression was weakly correlated with T2D (rg = 0.15, P = 4e-15). The latent multimorbidity factor explained the largest proportion of variance in T2D (45%), followed by CAD (35%) and depression (5%). We identified 11 independent SNPs associated with multimorbidity and 18 putative multimorbidity-associated genes. We observed enrichment in immune and inflammatory pathways. A greater polygenic risk score for multimorbidity in the UK Biobank (N = 306,734) was associated with the co-occurrence of CAD, T2D and depression (OR per standard deviation = 1.91, 95% CI = 1.74-2.10, relative to the healthy group), validating this latent multimorbidity factor. Mendelian randomization analyses suggested potentially causal effects of BMI, body fat percentage, LDL cholesterol, total cholesterol, fasting insulin, income, insomnia, and childhood maltreatment. These findings advance our understanding of multimorbidity suggesting common genetic pathways.


Subject(s)
Coronary Artery Disease , Diabetes Mellitus, Type 2 , Humans , Diabetes Mellitus, Type 2/epidemiology , Diabetes Mellitus, Type 2/genetics , Diabetes Mellitus, Type 2/metabolism , Genome-Wide Association Study , Multimorbidity , Risk Factors , Coronary Artery Disease/epidemiology , Coronary Artery Disease/genetics , Mendelian Randomization Analysis , Polymorphism, Single Nucleotide/genetics
18.
Nutrients ; 15(11)2023 May 29.
Article in English | MEDLINE | ID: mdl-37299485

ABSTRACT

BACKGROUND: Infertility and fecundability problems have been linked with lower 25-hydroxyvitamin D (25(OH)D) concentrations, but studies conducted with small, heterogenous or selected populations have shown inconsistent results. METHODS: This study included women at age 31 from prospective population-based Northern Finland Birth Cohort 1966. Serum 25(OH)D concentrations were evaluated between women with or without previous infertility examinations or treatments (infertility group, n = 375, reference group, n = 2051) and time to pregnancy (TTP) of over 12 months (decreased fecundability group, n = 338) with a wide range of confounders. Furthermore, 25(OH)D concentrations were also compared among reproductive outcomes. RESULTS: The mean 25(OH)D concentration was lower and 25(OH)D < 30 nmol/L was more frequent in women with a history of infertility compared to reference group. Moreover, 25(OH)D > 75 nmol/L was more frequent in the reference group. The mean 25(OH)D concentration was lower in women who had had multiple miscarriages. Both history of infertility (ß = -2.7, 95% confidence interval (CI) -4.6, -0.7) and decreased fecundability associated with lower 25(OH)D concentration (ß = -4.1, 95% CI -7.4, -0.8) after adjustments. In conclusion, this population-based study demonstrated that previous infertility and decreased fecundability were associated with lower 25(OH)D.


Subject(s)
Infertility , Vitamin D Deficiency , Pregnancy , Humans , Female , Adult , Prospective Studies , Vitamin D , Fertility , Vitamins
19.
Int J Mol Sci ; 24(8)2023 Apr 19.
Article in English | MEDLINE | ID: mdl-37108669

ABSTRACT

Cell-secreted extracellular vesicles (EVs), carrying components such as RNA, DNA, proteins, and metabolites, serve as candidates for developing non-invasive solutions for monitoring health and disease, owing to their capacity to cross various biological barriers and to become integrated into human sweat. However, the evidence for sweat-associated EVs providing clinically relevant information to use in disease diagnostics has not been reported. Developing cost-effective, easy, and reliable methodologies to investigate EVs' molecular load and composition in the sweat may help to validate their relevance in clinical diagnosis. We used clinical-grade dressing patches, with the aim being to accumulate, purify and characterize sweat EVs from healthy participants exposed to transient heat. The skin patch-based protocol described in this paper enables the enrichment of sweat EVs that express EV markers, such as CD63. A targeted metabolomics study of the sweat EVs identified 24 components. These are associated with amino acids, glutamate, glutathione, fatty acids, TCA, and glycolysis pathways. Furthermore, as a proof-of-concept, when comparing the metabolites' levels in sweat EVs isolated from healthy individuals with those of participants with Type 2 diabetes following heat exposure, our findings revealed that the metabolic patterns of sweat EVs may be linked with metabolic changes. Moreover, the concentration of these metabolites may reflect correlations with blood glucose and BMI. Together our data revealed that sweat EVs can be purified using routinely used clinical patches, setting the foundations for larger-scale clinical cohort work. Furthermore, the metabolites identified in sweat EVs also offer a realistic means to identify relevant disease biomarkers. This study thus provides a proof-of-concept towards a novel methodology that will focus on the use of the sweat EVs and their metabolites as a non-invasive approach, in order to monitor wellbeing and changes in diseases.


Subject(s)
Diabetes Mellitus, Type 2 , Extracellular Vesicles , Humans , Sweat , Diabetes Mellitus, Type 2/diagnosis , Diabetes Mellitus, Type 2/metabolism , Extracellular Vesicles/metabolism , Metabolomics , Biological Transport
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