Stephanie Zellers

STUDY QUESTION: Does twin status and zygosity (monozygotic vs dizygotic; same-sex vs opposite-sex) predict fertility outcomes and intergenerational reproductive patterns compared with singletons? SUMMARY ANSWER: Dizygotic female twins had a modestly higher number of biological children than singletons and monozygotic twins and were more likely to have a twin birth, but we did not observe differences for males or intergenerational differences. WHAT IS KNOWN ALREADY: Dizygotic twinning is associated with heritable hyperovulation and higher natural fertility but less is known about whether being a twin or zygosity influences reproductive outcomes across generations. STUDY DESIGN, SIZE, DURATION: A population-based longitudinal cohort study using part of the Finnish Twin Cohort and national population registers. Participants included an Anchor Generation composed of monozygotic (MZ; N = 4068), same-sex dizygotic (SSDZ; N = 8890), opposite-sex dizygotic (OSDZ; N = 8474), unknown zygosity (XZ; N = 2320) twins, and singleton controls (N = 1 193 404) born between 1945 and 1957 (total N = 1 217 156; 49.1% female), their mothers, their children, and their grandchildren. PARTICIPANTS/MATERIALS, SETTING, METHODS: Fertility outcomes (number of biological children, age at first birth, childlessness, multiple births) were derived from Finnish population registers. Analyses followed a preregistered plan (https://osf.io/qbwv3). MAIN RESULTS AND THE ROLE OF CHANCE: Differences in fertility between singletons and twins were modest and varied by sex and zygosity. Differences were observed generally in the mothers of twins and female twins themselves, with limited differences in the offspring of twins as compared to the offspring of singletons. Twins were slightly older at first birth, had fewer total biological offspring, but were more likely to have a twin birth. Dizygotic twins in particular differed from monozygotic twins and singletons. LIMITATIONS, REASONS FOR CAUTION: Findings are limited to individuals born in mid-20th-century Finland and thus generalizability to recent populations or non-Nordic contexts may be restricted. Further, analyses are observational, and causal inference is limited due to alternative motivation behind fertility rates like social or cultural reasons. WIDER IMPLICATIONS OF THE FINDINGS: These findings suggest that zygosity and sex interact to shape reproductive outcomes, offering insight into genetic and environmental contributions to fertility. They highlight the value of large twin cohorts for studying intergenerational reproductive trends and the representativeness of twins in population-based fertility research. FUNDING: As a supporting activity to ongoing research projects, funding for this project was provided by the Broad Trauma Initiative at the Broad Institute of MIT and Harvard. DISCLOSURES: The authors declare no conflict of interest. TRIAL REGISTRATION NUMBER: N/A.

Title: Fertility Rates Across Generations in Monozygotic Twins, Dizygotic Twins, and Non-Twin Controls in the Finnish Twin Cohort Study question: Does twin status and zygosity (monozygotic vs. dizygotic; same-sex vs. opposite-sex) predict fertility outcomes and intergenerational reproductive patterns compared with singletons? Summary answer: Among females, dizygotic twins had modestly higher completed fertility than singletons and monozygotic twins and were more likely to have a twin birth. Fertility did not differ meaningfully among males. These differences were restricted to the twin generation and did not persist in the next generation, indicating sex-specific and generation-specific effects rather than intergenerational transmission. What is known already: Dizygotic twinning is associated with heritable hyperovulation and higher natural fertility but less is known about whether being a twin or zygosity influences reproductive outcomes across generations. Study design, size, duration: A population-based longitudinal cohort study using part of the Finnish Twin Cohort and national population registers. Participants included monozygotic (MZ; N = 4,068), same-sex dizygotic (SSDZ; N = 8,890), opposite-sex dizygotic (OSDZ; N = 8,474) twins, and singleton controls (N = 1,193,404) born between 1945-1957 (total N =1,254,103; 49.1% female), their mothers, their children, and their grandchildren. Participants/materials, setting, methods: Fertility outcomes (number of biological children, age at first birth, childlessness, multiple births) were derived from Finnish population registers. Analyses followed a preregistered plan ( https://osf.io/qbwv3 ) Main results and the role of chance: Differences in fertility between singletons and twins were modest and varied by sex and zygosity. Differences were observed generally in the mothers of twins and female twins themselves, with limited differences in the offspring of twins as compared to the offspring of singletons. Twins were slightly older at first birth, had fewer total biological offspring, but were more likely to have a twin birth. Dizygotic twins in particular differed from monozygotic twins and singletons. Limitations, reasons for caution: Findings are limited to individuals born in mid-20th-century Finland and thus generalizability to recent populations or non-Nordic contexts may be restricted. Further, analyses are observational, and causal inference is limited due to alternative motivation behind fertility rates like social or cultural reasons. Wider implications of the findings: These findings suggest that zygosity and sex interact to shape reproductive outcomes, offering insight into genetic and environmental contributions to fertility. They highlight the value of large twin cohorts for studying intergenerational reproductive trends and the representativeness of twins in population-based fertility research. Study funding/competing interest(s): As a supporting activity to ongoing research projects, funding for this project was provided by the Broad Trauma Initiative at the Broad Institute of MIT and Harvard. The authors declare no conflict of interest.

Objective: BMI is influenced by both genetic and environmental factors, including features of the obesogenic environment such as walkability. This study investigated the interplay between residential walkability, genetics, and BMI among 4312 individuals from two Finnish twin cohorts (mean age: 43). Methods: Residential walkability was quantified using a composite index including built and natural environmental features. Results: Multiple linear regression, adjusted for sociodemographic factors, showed that higher walkability was associated with lower BMI (coefficient: −0.02, 95% CI: −0.04, −0.01), but pairwise twin analyses indicated that this association was not independent of genetic and early shared environmental influences. Univariate twin modeling revealed that additive genetic effects accounted for 22% of the variation in walkability when participants were middle‐aged. Bivariate moderation twin modeling showed that the additive genetic influence on BMI was significantly stronger among individuals living in areas with average or moderately low residential walkability. The unique environmental component played a larger role among those living in areas with either very low or very high residential walkability. Conclusions: These findings underscored the complex gene–environment interplay between walkability and BMI. While genetic susceptibility cannot be modified, public health strategies that focus on the obesogenic environment, such as improving walkability, may still help mitigate obesity risk.

Background: Alcohol use disorder (AUD) criteria emphasize physiological and psychological consequences of alcohol use without direct evaluation of quantity and frequency of consumption. It remains unclear whether alcohol dependence is an extreme outcome on the alcohol use spectrum or if it represents a separate pattern of behavior with different genetic and environmental influences. To investigate this, we evaluated relationships between alcohol consumption and dependence from adolescence to middle age in a large twin sample. Methods: Participants were twins (monozygotic pairs = 1205, dizygotic pairs = 676; 52% female) assessed at six waves from adolescence into midlife (age range = 13.6–49.4 years) on frequency of alcohol use, quantity of use, and dependence/abuse symptoms. At each assessment, we fit a longitudinal factor model with a single latent factor loading onto the three alcohol measures. Common and specific factor variance was decomposed into genetic and environmental components. Results: Alcohol use frequency peaked in early adulthood and remained stable; alcohol use quantity and dependence symptoms peaked in early adulthood and declined thereafter. Factor loadings within waves could not be constrained to be equal at all timepoints without significant detriment to model fit (increases in AIC = 1149 and BIC = 1081). Models constraining loadings at individual timepoints indicate that the measures can be reasonably equated at ages 24 and 29 (decreases in BIC = 3.1 and 2.9, respectively). Genetic factors accounted for about 50% of variance in the latent alcohol behavior factor from ages 14 through 29 but decreased ( p = 0.007) to 24% by age 37. Conclusions: Alcohol use and dependence are distinct in adolescence and young adulthood but show convergence in adulthood, such that alcohol dependence symptom count does not clearly measure a construct separate from alcohol consumption longitudinally. These developmental shifts have clinical implications, with AUD screening reliant on assessment of alcohol use patterns expected to perform more reliably in adults than adolescents.

Alcohol use is common in older adults and linked to poor health and aging outcomes. Studies have demonstrated genetic and environmental contributions to the quantity of alcohol consumption in mid-to-late life, but less is known about whether these influences are moderated by sociodemographic factors such as age, sex, and educational attainment. This study sought to better understand sociodemographic trends in alcohol consumption across the second half of the life course and their underlying genetic and environmental influences. Primary analyses were based on 64,140 middle-aged or older adult twins (40-102 years) from 14 studies in the Interplay of Genes and Environment Across Multiple Studies consortium. We harmonized a measure of weekly alcohol consumption (in grams of ethanol per week) across all studies. Older age was associated with lower alcohol consumption, primarily for adults over age 75, for individuals with higher education, and for males. Trends were similar across birth cohorts and after excluding current abstainers. At mean age 56, alcohol use was moderately heritable in females (.34, 95% CI [.26, .41]) and more heritable in males (.42, 95% CI [.38, .45]). Heritability was lower in older aged adults and in females with higher education. This study represents the largest twin study of alcohol consumption in middle-aged and older adults. Results highlight that genetic and environmental factors influence alcohol consumption differently across age, sex, and educational attainment and that intervention efforts may need to be tailored based on individuals' backgrounds. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

The Older Finnish Twin Cohort was established 50 years ago and includes twins born in Finland before 1958. Members of the cohort have responded to detailed questionnaires about their health, habits, and lifestyle up to four times, in 1975, 1981, 1991, and 2011. In 2019, the Finnish Parliament approved the Act on the Secondary Use of Health and Social Data, which enables wider use of data from national social and healthcare registers as well as various patient systems and social services. This data resource article describes the linkage of the Older Finnish Twin Cohort to numerous social and healthcare registers, alongside linked data from their families and the broader Finnish population born in 1945−1957, which serves as a reference population for generalizability and other analyses.

Background: Observational studies have repeatedly linked cannabis use to increased suicidality, yet cannabis use rarely exists in isolation from other risk factors. We therefore tested whether these associations reflect a causal effect, reverse causation, or residual confounding.Methods: We analyzed twin cohorts based in Colorado and Minnesota (N = 6,420) followed from late adolescence into middle adulthood, with repeated assessments of cannabis use and suicidal thoughts/behavior (STB). Prospective and co-twin control analyses examined (a) cross-sectional and prospective links between cannabis use and STB, (b) whether these links persisted after adjusting for genetic and environmental confounds, and (c) whether middle-adulthood associations were moderated by legalized recreational cannabis.Findings: More frequent cannabis use was associated with elevated STB. After accounting for shared familial factors via co-twin control, this relationship remained significant in cross-sectional, but not prospective, analyses. In middle adulthood, associations between cannabis use and STB did not differ across states, regardless of recreational cannabis legalization status. Interpretation: Findings support a contemporaneous link between cannabis use and STB within twin pairs, potentially reflecting causal effects. However, the absence of a prospective within-pair association provides little support for the notion that cannabis use elevates future STB risk independent of familial liability. This pattern suggests causation may be limited to short-term effects, or that the cannabis-STB relationship may primarily reflect confounding by unmeasured time-varying factors (e.g., acute stressors).

Publications reporting research conducted on human participants, such as clinical trials,commonly include a table summarising the relevant characteristics of the study participants.These tables are crucial to compare studies, assess generalisabillity and identify understudiedpopulations. In metaresearch and evidence syntheses, where the sample is instead comprisedof research papers, tables describing features such as the proportion of open access papers,publication language, or authors’ gender are uncommon. Collating these additionalcharacteristics manually would require substantial time and resources. Without thisinformation, however, our understanding of the generalisability of study findings is limited.Furthermore, researchers cannot compare sample characteristics across studies or assess theimpact of different sampling methods. This project aims to: 1) propose a standard samplecharacteristics table structure for studies performed on research papers, 2) determine which ofthese characteristics can be assessed by automated tools, and 3) create a web application thatallows researchers to quickly generate a sample characteristics table using existing automatedtools. We will share progress by updating this preprint as we complete these goals, allowingothers to provide feedback and contribute. We hope that this project will mainstream samplecharacteristics reporting for studies on research papers, stimulate automated tool developmentto fill gaps, and facilitate studies on sample characteristics and generalisability in metaresearch.

Reducing sugar intake is a key component of global health policies and dietary guidelines. However, individuals vary substantially in sweet-liking, commonly characterized by sweet-liking status (extreme sweet-likers, moderate sweet-likers, and sweet-dislikers), yet the heritability of these categories remains unexplored. Monozygotic and dizygotic twins from Finland (FinnTwin12; n = 468; 60% female, aged 21–24) and the UK (TwinsUK; n = 967; 90% female, aged 18–81) rated their liking and perceived intensity of a 20% (w/v) sucrose solution, reported their liking and consumption-frequency of food and beverages and completed additional behavioral, eating and personality measures. We estimated the contribution of additive genetic (A), nonadditive genetic (D), shared (C), and unshared environmental factors (E) in the variance and covariance of sweet-liking (defined ordinally through sweet-liking status and continuously) with related traits to see if they share similar proportions of genetic and environmental factors. Model-fitting indicated 30–48% of the variability in sweet-liking was attributed to (A) additive genetic factors and 52–70% to (E) environmental exposures not shared by siblings. Importantly, such AE models consistently fit best, regardless of sex, cohort, or sweet-liking assessment method. Broadly, correlations between sweet-liking and behavioral, eating, and personality measures were modest (–0.19 to 0.21), mostly positive and largely driven by shared genetic rather than environmental factors, with the strongest relationship seen for reported liking, consumption-frequency and craving for sweet foods. We demonstrate that unshared environment modulates individual differences in sweet-liking alongside a substantial genetic component that is partly shared with reported liking, consumption-frequency and craving for sweet foods.

Publications reporting research conducted on human participants, such as clinical trials,commonly include a table summarising the relevant characteristics of the study participants.These tables are crucial to compare studies, assess generalisabillity and identify understudiedpopulations. In metaresearch and evidence syntheses, where the sample is instead comprisedof research papers, tables describing features such as the proportion of open access papers,publication language, or authors’ gender are uncommon. Collating these additionalcharacteristics manually would require substantial time and resources. Without thisinformation, however, our understanding of the generalisability of study findings is limited.Furthermore, researchers cannot compare sample characteristics across studies or assess theimpact of different sampling methods. This project aims to: 1) propose a standard samplecharacteristics table structure for studies performed on research papers, 2) determine which ofthese characteristics can be assessed by automated tools, and 3) create a web application thatallows researchers to quickly generate a sample characteristics table using existing automatedtools. We will share progress by updating this preprint as we complete these goals, allowingothers to provide feedback and contribute. We hope that this project will mainstream samplecharacteristics reporting for studies on research papers, stimulate automated tool developmentto fill gaps, and facilitate studies on sample characteristics and generalisability in metaresearch.