Biology subjects

Pahkala, K.

Publications and source records attributed to Pahkala, K..

3 recordsLinked to original sources

bioRxiv2026

Male youth BMI is associated with epigenetic ageing of female descendants but not blood or sperm DNA methylation

Studies based on harvest records indicate that grandparental nutrition in youth is associated with the health traits of grandchildren in a sex-specific lineage. We investigated whether male early adulthood anthropometrics associate with epigenetic age, a measure of general well-being, and DNA methylation, a potential molecular inheritance mechanism, in three generations of descendants. Data on weight, height, BMI and chest circumference measured at military draft examinations (at age 18-24 yrs.) were retrieved from national archives for 1,013 men, herein referred to as Generation Archives (GA). The genome-wide DNA methylation of their descendants participating in the Young Finns Study (YFS) was measured from the blood and sperm from the children (59-80 yrs., nblood = 362, nsperm = 51), grandchildren (34-49 yrs., nblood = 421, nsperm = 98) and great-grandchildren (7-30 yrs., nblood = 200). The men's (GA) BMI had an inverse association with the epigenetic pace of ageing (DunedinPACE) of their daughters ({beta} = -0.01, p = 0.002, n = 169) and the daughters' daughters ({beta} = -0.01, p = 0.049, n = 126) but not with that of their male descendants. From within the YFS cohort, maternal, but not paternal, BMI at ages 13-34 also had an inverse association with the DunedinPACE of the immediate offspring. However, robust evidence for the inheritance mechanism was not found in the analyses between the anthropometric measurements of the GA men and the DNA methylation profiles in the blood and sperm of their descendants.

molecular biology↗

bioRxiv2026

Traditional disease risk factors outperform epigenetic clocks as predictors of non-communicable disease morbidity in a middle-aged cohort

DNA methylation-based epigenetic clocks have been highlighted as promising biomarkers of ageing, and they have been shown to robustly predict morbidity and mortality. However, current literature is lacking a formal analysis of the increased prediction accuracy, or the added value, of the epigenetic clocks over traditional risk factors of common chronic diseases. Here, we have compared the most commonly used epigenetic clocks and traditional risk factors as predictors of incidence of ageing-associated non-communicable chronic disease in a 7-to-9-year follow-up in a middle-aged population cohort (n=1108, aged 34 to 49 years at baseline). In our cohort, a statistical model consisting of a combination of traditional risk factors outperforms any model including an epigenetic clock. The added value of epigenetic clock measurements over simple and affordable traditional risk factors should be clearly established, if epigenetic clocks are to be used in clinical settings or as tools of personal health monitoring.

molecular biology↗

bioRxiv2017

Maternal and fetal genetic contribution to gestational weight gain

BackgroundClinical recommendations to limit gestational weight gain (GWG) imply high GWG is causally related to adverse outcomes in mother or offspring, but GWG is the sum of several inter-related complex phenotypes (maternal fat deposition and vascular expansion, placenta, amniotic fluid and fetal growth). Understanding the genetic contribution to GWG could help clarify the potential effect of its different components on maternal and offspring health. Here we explore the genetic contribution to total, early and late GWG.\n\nParticipants and MethodsA genome-wide association study was used to identify maternal and fetal variants contributing to GWG in up to 10,543 mothers and up to 16,317 offspring of European origin, with replication in 10,660 mothers and 7,561 offspring. Additional analyses determined the proportion of variability in GWG from maternal and fetal common genetic variants and the overlap of established genome-wide significant variants for phenotypes relevant to GWG (e.g. maternal BMI and glucose, birthweight).\n\nResultsWe found that approximately 20% of the variability in GWG was tagged by common maternal genetic variants, and that the fetal genome made a surprisingly minor contribution to explaining variation in GWG. We were unable to identify any genetic variants that reached genome-wide levels of significance (P<5x10-8) and replicated. Some established maternal variants associated with increased BMI, fasting glucose and type 2 diabetes were associated with lower early, and higher later GWG. Maternal variants related to higher systolic blood pressure were related to lower late GWG. Established maternal and fetal birthweight variants were largely unrelated to GWG.\n\nConclusionWe found a modest contribution of maternal common variants to GWG and some overlap of maternal BMI, glucose and type 2 diabetes variants with GWG. These findings suggest that associations between GWG and later offspring/maternal outcomes may be due to the relationship of maternal BMI and diabetes with GWG.

genetics↗