Biology subjects

Kaprio, J.

Publications and source records attributed to Kaprio, J..

At least 19 recordsLinked to original sources

bioRxiv2025

Epigenome-wide association study meta-analysis of wellbeing

Wellbeing is associated with both behavioral phenotypes as well as several key life outcomes, such as health, employment, and coping with stressful events. These phenotypes associated with wellbeing could be potential indicators of differential epigenetic patterns between individuals that differ in their levels of wellbeing. We performed the largest epigenome-wide (EWAS) meta-analysis of wellbeing to date by combining whole blood DNA methylation data (Illumina 450k array) from 13 cohorts from Europe, Australia, and the USA (N = 10,757 participants). After correcting for smoking and BMI, no epigenome-wide significant methylation sites were identified. We tested whether a weighted methylation score (MS) based on leave-one-cohort-out EWAS meta-analysis summary statistics predicted wellbeing in an independent cohort, and whether prediction was significant over and above the polygenic score (PGS) for wellbeing. The MS was associated with wellbeing (variance explained=0.22%, p=0.03) and was no longer significant after adding the polygenic score (PGS; variance explained=0.43%, p=0.0046, MS; variance explained=0.07%, p=0.2842). We further compared DNA methylation levels in 16 pairs of monozygotic twins discordant for wellbeing. These analyses revealed no significant within-pair DNA methylation differences at the top-sites from the meta-analysis or in MS. Our results suggest that larger EWAS meta-analyses with uniform phenotype assessment are required to identify methylation sites associated with wellbeing.

genomics↗

bioRxiv2024

Human reproduction comes at the expense of faster aging and a shorter life

Evolutionary theories suggest a trade-off between resources allocated to reproduction and those allocated to self-maintenance, and predict that higher reproductive output entails a shorter lifespan. This study investigates the impact of childbearing on aging and lifespan using data from contemporary Finnish twin women. We model the association between reproductive trajectories and survival in 17,080 women, and assess biological aging in a subset of participants (N=1,117) using the PCGrimAge clock, an algorithm trained to predict biological aging and mortality risk from DNA methylation. Our findings suggest that early childbearing, numerous pregnancies or nulliparity all contribute to accelerated aging and increased mortality risk. These results provide strong evidence for the existence of a trade-off between reproduction, aging and lifespan in modern humans, and provide novel insights into the genetic and lifestyle determinants of healthspan.

evolutionary biology↗

bioRxiv2024

Associations between common genetic variants and income provide insights about the socioeconomic health gradient

We conducted a genome-wide association study (GWAS) on income among individuals of European descent and leveraged the results to investigate the socio-economic health gradient (N=668,288). We found 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes. Our GWAS-derived polygenic index captures 1 - 4% of income variance, with only one-fourth attributed to direct genetic effects. A phenome-wide association study using this polygenic index showed reduced risks for a broad spectrum of diseases, including hypertension, obesity, type 2 diabetes, coronary atherosclerosis, depression, asthma, and back pain. The income factor showed a substantial genetic correlation (0.92, s.e. = .006) with educational attainment (EA). Accounting for EAs genetic overlap with income revealed that the remaining genetic signal for higher income related to better mental health but reduced physical health benefits and increased participation in risky behaviours such as drinking and smoking.

genetics↗

bioRxiv2023

DNA methylation sites in early adulthood characterised by pubertal timing and development: A twin study

BackgroundPuberty is a highly heritable and variable trait, with environmental factors having a role in its eventual timing and development. Early and late pubertal onset are both associated with various diseases developing later in life, and epigenetic characterisation of pubertal timing and development could lead to important insights. Blood DNA methylation, reacting to both genotype and environment, has been associated with puberty; however, such studies are relatively scarce. We investigated peripheral blood DNA methylation profiles (using Illumina 450K and EPIC platforms) of 1539 young adult Finnish twins associated with pubertal development scale (PDS) and pubertal age (PA). ResultsFixed effect meta-analysis of the two platforms on 347521 CpGs in common identified 58 CpG sites associated (p < 1 x 10-5) with either PDS or PA. All four CpGs associated with PA and 45 CpGs associated with PDS were sex specific. Thirteen CpGs had a high heritability (h2: 0.51-0.98), while one CpG site (mapped to GET4) had a high shared environmental component accounting for 68% of the overall variance in methylation at the site. Utilising twin discordance analysis, we found 6 CpG sites (5 associated with PDS and 1 with PA) that had an environmentally driven association with puberty. Furthermore, genes with PDS- or PA-associated CpGs were linked to various developmental processes and diseases, such as breast, prostate and ovarian cancer, while methylation quantitative trait loci (meQTLs) of associated CpG sites were enriched in immune pathways developing during puberty. ConclusionsBy identifying puberty-associated DNA methylation sites and examining the effects of sex, environment and genetics, we shed light on the intricate interplay between environment and genetics in the context of puberty. Through our comprehensive analysis, we not only deepen the understanding of the significance of both genetic and environmental factors in the complex processes of puberty and its timing but also gain insights into potential links with disease risks.

genomics↗

bioRxiv2023

Proteomic insights into mental health status: plasma markers in young adults

Global emphasis on enhancing prevention and treatment strategies necessitates increased understanding of biological mechanisms of psychopathology. Plasma proteomics is a powerful tool that has been applied in the context of specific mental disorders for biomarker identification. The p-factor, also known as the "general psychopathology factor", is a concept in psychopathology suggesting that there is a common underlying factor that contributes to the development of various forms of mental disorders. It has been proposed that the p-factor can be used to understand the overall mental health status of an individual. Here we aimed to discover plasma proteins associated with the p-factor in 775 young adults in the FinnTwin12 cohort. Using liquid chromatography-tandem mass spectrometry, 14 proteins with a significant connection with the p-factor were identified, 9 of which were linked to epidermal growth factor receptor (EGFR) signalling. This exploratory study provides new insight into biological alterations associated with mental health status in young adults.

neuroscience↗

bioRxiv2022

The heritability of BMI varies across the range of BMI: a heritability curve analysis in a twin cohort

The heritability of traits such as body mass index (BMI), a measure of obesity, is generally estimated using family, twin, and increasingly by molecular genetic approaches. These studies generally assume that genetic effects are uniform across all trait values, yet there is emerging evidence that this may not always be the case. This paper analyzes twin data using a recently developed measure of heritability called the heritability curve. Under the assumption that trait values in twin pairs are governed by a flexible Gaussian mixture distribution, heritability curves may vary across trait values. The data consist of repeated measures of BMI on 1506 monozygotic (MZ) and 2843 like-sexed dizygotic (DZ) adult twin pairs, gathered from multiple surveys in older Finnish Twin Cohorts. The heritability curve and BMI value-specific MZ and DZ pairwise correlations were estimated, and these varied across the range of BMI. MZ correlations were highest at BMI values from 21 to 24, with a stronger decrease for women than for men at higher values. Models with additive and dominance effects fit best at low and high BMI values, while models with additive genetic and common environmental effects fit best in the normal range of BMI. Thus, we demonstrate that twin and molecular genetic studies need to consider how genetic effects vary across trait values. Such variation may reconcile findings of traits with high heritabilities and major differences in mean values between countries or over time.

genetics↗

bioRxiv2020

Patient iPSC-astrocytes show transcriptional and functional dysregulation in schizophrenia

Human astrocytes are multifunctional brain cells and may contribute to the pathophysiology of schizophrenia (SCZ). We differentiated astrocytes from induced pluripotent stem cells of monozygotic twins discordant for SCZ, and found sex-specific gene expression and signaling pathway alterations related particularly to inflammation and synaptic functions. While Ingenuity Pathway Analysis identified SCZ disease and synaptic transmission pathway changes in SCZ astrocytes, the most consistent findings were related to collagen and cell adhesion associated pathways. Neuronal responses to glutamate and GABA differed between astrocytes from control persons, affected twins, and their unaffected co-twins, and were normalized by clozapine treatment. SCZ astrocyte cell transplantation to the mouse forebrain caused gene expression changes in demyelination, synaptic dysfunction and inflammation pathways of mouse brain cells and resulted in behavioral changes in cognitive and olfactory functions. Altogether, our results show that astrocytes contribute to both familial risk and clinical manifestation of SCZ in a sex-specific manner.

neuroscience↗

bioRxiv2020

Large-scale analysis of DNA methylation identifies cellular alterations in blood from psychosis patients and molecular biomarkers of treatment-resistant schizophrenia.

ObjectivePsychosis - a complex and heterogeneous neuropsychiatric condition characterized by hallucinations and delusions - is a common feature of schizophrenia. There is evidence for altered DNA methylation (DNAm) associated with schizophrenia in both brain and peripheral tissues. We aimed to undertake a systematic analysis of variable DNAm associated with psychosis, schizophrenia, and treatment-resistant schizophrenia, also exploring measures of biological ageing, smoking, and blood cell composition derived from DNAm data to identify molecular biomarkers of disease. MethodsWe quantified DNAm across the genome in blood samples from 4,483 participants from seven case-control cohorts including patients with schizophrenia or first-episode psychosis. Measures of biological age, cellular composition and smoking status were derived from DNAm data using established algorithms. DNAm and derived measures were analyzed within each cohort and the results combined by meta-analysis. ResultsPsychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNAm data, with the largest differences seen in treatment-resistant schizophrenia patients. DNAm at 95 CpG sites was significantly different between psychosis cases and controls, with 1,048 differentially methylated positions (DMPs) identified between schizophrenia cases and controls. Schizophrenia-associated DMPs colocalize to regions identified in genetic association studies, with genes annotated to these sites enriched for pathways relevant to disease. Finally, a number of the schizophrenia associated differences were only present in the treatment-resistant schizophrenia subgroup. ConclusionsWe show that DNAm data can be leveraged to derive measures of blood cell counts and smoking that are strongly associated with psychosis. Our DNAm meta-analysis identified multiple DMPs associated with both psychosis and a more refined diagnosis of schizophrenia, with evidence for differential methylation associated with treatment-resistant schizophrenia that potentially reflects exposure to clozapine.

genomics↗

bioRxiv2020

Expanding the Genetic Architecture of Nicotine Dependence and its Shared Genetics with Multiple Traits: Findings from the Nicotine Dependence GenOmics (iNDiGO) Consortium

Cigarette smoking is the leading cause of preventable morbidity and mortality. Knowledge is evolving on genetics underlying initiation, regular smoking, nicotine dependence (ND), and cessation. We performed a genome-wide association study using the Fagerstrom Test for ND (FTND) in 58,000 smokers of European or African ancestry. Five genome-wide significant loci, including two novel loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416) were identified, and loci reported for other smoking traits were extended to ND. Using the heaviness of smoking index (HSI) in the UK Biobank (N=33,791), rs2714700 was consistently associated, but rs1862416 was not associated, likely reflecting ND features not captured by the HSI. Both variants were cis-eQTLs (rs2714700 for MAGI2-AS3 in hippocampus, rs1862416 for TENM2 in lung), and expression of genes spanning ND-associated variants was enriched in cerebellum. SNP-based heritability of ND was 8.6%, and ND was genetically correlated with 17 other smoking traits (rg=0.40-0.95) and co-morbidities. Our results emphasize the FTND as a composite phenotype that expands genetic knowledge of smoking, including loci specific to ND.

genomics↗

bioRxiv2020

A healthy childhood environment helps to combat inherited susceptibility to obesity

ObjectivesTo investigate the degree by which the inherited susceptibility to obesity is modified by environmental factors during childhood and adolescence. DesignCohort study with repeated measurements of diet, lifestyle factors and anthropometry. SettingThe pan-European IDEFICS/I.Family cohort Participants8,609 repeated observations from 3,098 children aged 2 to 16 years, examined between 2007 and 2014. Main outcome measuresBody mass index (BMI) and waist circumference. Genome-wide polygenic risk scores (PRS) to capture the inherited susceptibility of obesity were calculated using summary statistics from independent genome-wide association studies of BMI. Gene-environment interactions of the PRS with sociodemographic (European region, socioeconomic status) and lifestyle factors (diet, screen time, physical activity) were estimated. ResultsThe PRS was strongly associated with BMI (r2 = 0.11, p-value = 7.9 x 10-81) and waist circumference (r2 = 0.09, p-value = 1.8 x 10-71) in our cohort. The associations with BMI increased from r2=0.03 in 3-year olds to r2=0.18 in 14-year olds and associations with waist circumference from r2=0.03 to r2=0.14. Being in the top decile of the PRS distribution was associated with 3.63 times higher odds for obesity (95% confidence interval (CI): [2.57, 5.14]). We observed significant interactions with demographic and lifestyle factors for BMI as well as waist circumference. The risk of becoming obese among those with higher genetic susceptibility was ~38% higher in children from Southern Europe (BMI: p-interaction = 0.0066, Central vs. Southern Europe) and ~61% higher in children with a low parental education (BMI: p-interaction = 0.0012, low vs. high). Furthermore, the risk was attenuated by a higher intake of dietary fiber (BMI: p-interaction=0.0082) and shorter screen times (BMI: p-interaction=0.018). ConclusionsOur results highlight that a healthy childhood environment might partly offset a genetic predisposition to obesity during childhood and adolescence.

genetics↗

bioRxiv2019

Nightmares share strong genetic risk with sleep and psychiatric disorders

Nightmares are vivid, extended and extremely dysphoric dreams that awaken the dreamer. Twin studies indicate that nightmare frequency has a heritability between 36 and 51% providing evidence for genetic factors underlying predisposition to nightmares. Furthermore, while cross-sectional epidemiological findings suggest that heavy alcohol usage, traumatic experiences and psychiatric diseases associate with nightmares, the causal relationships between these conditions and nightmares have remained unknown. To examine the biological mechanisms behind nightmares, we performed a genome-wide association study in 28,596 individuals from Finland and the United States. We identified individual genetic variants that predispose to nightmares near MYOF (rs701873, p=2.18e-8) and PTPRJ (rs11039471,p=3.7e-8), a gene previously associated with sleep duration. We found a strong genetic correlation between the frequency of nightmares and traits related to personality and psychiatric disorders; neuroticism (rg=0.59, p=8e-7), post-traumatic stress disorder (PTSD) (rg=0.58, p=0.004) as well as major depressive disorder (rg=0.68, p=7e-4), and sleep traits; and daytime sleepiness (rg=0.62, p=1e-6) and insomnia (rg=0.50, p=1.87e-5). Analysis of directionality using mendelian randomization showed a significant effect from feelings of fed-up (p=0.001), nervous (p=0.004) and miserableness (p=0.0045) to nightmares with no evidence of pleiotropy and no evidence of nightmares predisposing to psychiatric or psychological problems. Our findings suggest that nightmares are caused by unique genetic risk factors, and here we identify the first individual genetic associations. In addition, a substantial effect on nightmares is conveyed through underlying psychological and sleep problems, with psychological problems being causal for nightmares.

genetics↗

bioRxiv2019

Genome-wide association study identifies 49 common genetic variants associated with handedness.

Handedness, a consistent asymmetry in skill or use of the hands, has been studied extensively because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and 32 studies from the International Handedness Consortium, we conducted the worlds largest genome-wide association study of handedness (1,534,836 right-handed, 194,198 (11.0%) left-handed and 37,637 (2.1%) ambidextrous individuals). We found 41 genetic loci associated with left-handedness and seven associated with ambidexterity at genome-wide levels of significance (P < 5x10-8). Tissue enrichment analysis implicated the central nervous system and brain tissues including the hippocampus and cerebrum in the etiology of left-handedness. Pathways including regulation of microtubules, neurogenesis, axonogenesis and hippocampus morphology were also highlighted. We found suggestive positive genetic correlations between being left-handed and some neuropsychiatric traits including schizophrenia and bipolar disorder. SNP heritability analyses indicated that additive genetic effects of genotyped variants explained 5.9% (95% CI = 5.8% - 6.0%) of the underlying liability of being left-handed, while the narrow sense heritability was estimated at 12% (95% CI = 7.2% - 17.7%). Further, we show that genetic correlation between left-handedness and ambidexterity is low (rg = 0.26; 95% CI = 0.08 - 0.43) implying that these traits are largely influenced by different genetic mechanisms. In conclusion, our findings suggest that handedness, like many other complex traits is highly polygenic, and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders that has been observed in multiple observational studies.

genetics↗

bioRxiv2019

Polygenic Prediction of Substance Use Disorders in Clinical and Population Samples

Genome-wide, polygenic risk scores (PRS) have emerged as a useful way to characterize genetic liability using genotypic data. There is growing evidence that PRS may prove useful to identify those at increased risk for developing certain diseases. The current utility of PRS in relation to alcohol use disorders (AUD) remains an open question. Using data from both a population-based sample [the FinnTwin12 (FT12) study] and a high risk sample [the Collaborative Study on the Genetics of Alcoholism (COGA)], we examined the association between PRSs derived from genome-wide association studies (GWASs) of 1) alcohol dependence/alcohol problems, 2) alcohol consumption, and 3) risky behaviors with AUD and other substance use disorder (SUD) symptoms. Individuals in the top 20%, 10%, and 5% of PRSs had increasingly greater odds of having an AUD compared to the lower end of the continuum in both COGA (80th % OR = 1.95; 90th % OR = 2.03; 95th % OR = 2.13) and FT12 (80th % OR = 1.77; 90th % OR = 2.27; 95th % OR = 2.39). Those in the top 5% reported greater levels of licit (alcohol and nicotine) and illicit (cannabis) SUD symptoms. PRSs can predict elevated risk for SUD in independent samples. However, clinical utility of these scores in their current form is modest. As these scores become more predictive of SUD, they may become useful to practitioners. Improvement in predictive ability will likely be dependent on increasing the size of well-phenotyped discovery samples.

genetics↗

bioRxiv2019

Polygenic risk score of alcohol consumption predicts alcohol-related morbidity and all-cause mortality

ObjectiveTo develop a highly polygenic risk score (PRS) for alcohol consumption and study whether it predicts alcohol-related morbidity and all-cause mortality.\n\nDesignBiobank-based prospective cohort study\n\nSettingFinnGen Study (Finland)\n\nParticipants96,499 genotyped participants from the nationwide prospective FinnGen study and 36,499 participants from prospective cohorts (Health 2000, FINRISK, Twin Cohort) with detailed baseline data and up to 25 years of follow-up time.\n\nMain outcome measuresIncident alcohol-related morbidity and alcohol-related or all-cause mortality, based on hospitalizations, outpatient specialist care, drug purchases, and death reports.\n\nResultsIn 96,499 FinnGen participants there were in total 4,785 first-observed incident alcohol-related health events. The PRS of alcohol consumption was associated with alcohol-related morbidity and the risk estimate (hazard ratio, HR) between the highest and lowest quintiles of the PRS was 1.67 [ 95 % confidence interval: 1.52-1.84], p=3.2*10-27). In 28,639 participants with comprehensive baseline data from prospective Health 2000 and FINRISK cohorts, 911 incident first alcohol-related events were observed. When adjusted for self-reported alcohol consumption, education, marital status, and gamma-glutamyl transferase blood levels, the risk estimate between the highest and lowest quintiles of the PRS was 1.58 (CI=[1.26-1.99], p=8.2*10-5). The PRS was also associated with all-cause mortality with a risk estimate of 1.33 between the highest and lowest quintiles (CI=[1.2-1.47], p=4.5e-08) in the adjusted model. In all 39,695 participants with self-reported alcohol consumption available, a 1 SD increase in the PRS was associated with 11.2 g (=0.93 drinks) higher weekly alcohol consumption ({beta}=11.2 [9.85-12.58 g], p = 2.3*10-58).\n\nConclusionsThe PRS for alcohol consumption associates for both alcohol-related morbidity and all-cause mortality. These findings underline the importance of heritable factors in alcohol-related behavior and the related health burden. The results highlight how measured genetic risk for an important behavioral risk factor can be used to predict related health outcomes.

genomics↗

bioRxiv2019

Within-family studies for Mendelian randomization: avoiding dynastic, assortative mating, and population stratification biases

Mendelian randomization (MR) is a widely-used method for causal inference using genetic data. Mendelian randomization studies of unrelated individuals may be susceptible to bias from family structure, for example, through dynastic effects which occur when parental genotypes directly affect offspring phenotypes. Here we describe methods for within-family Mendelian randomization and through simulations show that family-based methods can overcome bias due to dynastic effects. We illustrate these issues empirically using data from 61,008 siblings from the UK Biobank and Nord-Trondelag Health Study. Both within-family and population-based Mendelian randomization analyses reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while MR estimates from population-based samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects largely disappeared in within-family MR analyses. We found differences between population-based and within-family based estimates, indicating the importance of controlling for family effects and population structure in Mendelian randomization studies.

genetics↗

bioRxiv2019

Genome wide meta-analysis identifies genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders.

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed a meta-analysis of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders identifying three groups of inter-related disorders. We detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning in the second trimester prenatally, and play prominent roles in a suite of neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

genomics↗

bioRxiv2019

Polygenic Risk for Alcohol Misuse is Moderated by Romantic Partnerships: Primarily in Men

ImportanceProblematic alcohol use remains a leading influence on preventable mortality and morbidity across the globe. Those in committed relationships consistently report lower levels of alcohol misuse and problems. ObjectiveTo determine 1) whether genetic risk for alcohol misuse is moderated by romantic relationships (gene-environment interaction; GxE), and 2) whether GxE results are consistent across sex. DesignData came from the young adult wave of the Finnish Twin Study (FinnTwin12), a nationally representative sample of twins. Predictors included genome-wide polygenic scores (GPS), derived from a recent genome-wide association study (GWAS) of alcohol consumption in ~1 million participants; and participant reports of relationship status. SettingFinland ParticipantsAn intensively studied subset of FinnTwin12 received a diagnostic interview during the young adult phase (1,312 of 1,347 individuals provided genotypic data). The analytic sample includes those with complete interview and genetic data (N=1,201, 54% female). ExposureSelf-reported involvement in a romantic partnership. Main Outcomes and MeasuresDrinking frequency, intoxication frequency, and DSM-IV alcohol dependence (AD) symptoms from a diagnostic interview. ResultsGPS predicted drinking frequency (b = 0.109; 95% CI = 0.051, 0.167), intoxication frequency (b = 0.111; 95% CI = 0.054, 0.168), and AD symptoms (b = 0.123; 95% CI = 0.064, 0.182). Relationship moderated the association between GPS and drinking frequency (b = -0.105; 95% CI = -0.211, -0.001), intoxication frequency (b = -0.118; 95% CI = -0.220, -0.015), and AD symptoms (b = -0.119; 95% CI = -0.229, -0.010). The interaction for drinking frequency was not significant after correcting for covariates. There was a 3-way interaction between sex, relationship status, and GPS for intoxication frequency (b = 0.223; 95% CI = 0.014, 0.432), with the two-way interaction of relationship status and PRS on intoxication frequency being significant only in men. Conclusions and RelevanceBeing in a relationship reduced the association between genetic predisposition and high risk drinking. Part of the protective effect of committed partnerships on alcohol misuse observed in epidemiological research may be in limiting genetic liability. However, this protective effect was largely limited to males, mapping onto earlier findings suggesting that males benefit more from romantic partnerships. Key PointsO_ST_ABSQuestionC_ST_ABSDo romantic relationships moderate polygenic risk on alcohol misuse in young adulthood? FindingsInvolvement in romantic relationships moderated the polygenic risk on frequency of intoxication and DSM-IV alcohol dependence symptoms, such that polygenic associations with alcohol misuse were stronger among those not in a romantic relationship. Males experienced a stronger protective effect of romantic relationship in limiting the manifestation of genetic predispositions toward intoxication frequency. MeaningThe interplay between genes and environment is important in understanding etiology of problematic alcohol use, and romantic relationships appear to buffer genetic risk for alcohol misuse in young adulthood. Findings underscore how social relationships may alter the risk posed by genetic predispositions.

epidemiology↗

bioRxiv2018

EpiSmokEr: A robust classifier to determine smoking status from DNA methylation data

Self-reported smoking status is prone to misclassification due to under-reporting, while biomarkers like cotinine can only measure recent exposure. Smoking strongly influences DNA methylation, with current, former and never smokers exhibiting different methylation profiles. Recently, two approaches were proposed to calculate scores based on smoking-responsive DNA methylation loci, to serve as reliable indicators of long-term exposure and potential biomarkers to estimate smoking behavior. However, these two methodologies need significant improvements to make them globally applicable to all populations and to achieve an optimal classification of individuals with unknown smoking habits. To advance the practical applicability of the smoking-associated methylation signals, we used machine learning methodology to train a classifier for smoking status prediction. We show the prediction performance of our classifier on three independent whole-blood test datasets demonstrating its robustness and global applicability. Furthermore, we show the cross-tissue functionality of our classifier in tissues other than blood. Additionally, we provide the community with an R package, EpiSmokEr, facilitating implementation of our classifier to predict smoking status in future studies.

bioinformatics↗