Publications

A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests.We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies.Code is available at https://github.com/aalto-ics-kepacoanna.cichonska@helsinki.fi or matti.pirinen@helsinki.fiSupplementary data are available at Bioinformatics online.

OBJECTIVE Lesbian and bisexual (LB) women are more likely than heterosexual women to exhibit risk factors for type 2 diabetes, but studies estimating the burden of type 2 diabetes among LB women are uncommon and limited to cross-sectional designs. This study investigated incidence of type 2 diabetes in LB women and heterosexual women in a large, longitudinal U.S. cohort. RESEARCH DESIGN AND METHODS Women participating in the Nurses’ Health Study II (NHS II) ages 24–44 years in 1989 were prospectively followed through 2013. Self-reported clinician diagnosis of type 2 diabetes was assessed every other year to identify incidence. Of the participants, 1,267 identified as lesbian or bisexual and 92,983 identified as heterosexual. Cox proportional hazards regression was used to model incidence of type 2 diabetes. RESULTS LB women had a 27% higher risk of developing type 2 diabetes than heterosexual women (adjusted incidence rate ratio [IRR] 1.27, 95% CI 1.05, 1.54). Differences between LB women and heterosexual women in risk of type 2 diabetes were greater during younger ages (sexual orientation–by-age interaction, P < 0.001). BMI mediated the relationship between sexual orientation and type 2 diabetes; the IRR was completely attenuated when BMI was added to the model (IRR 0.85, 95% CI 0.70, 1.03). CONCLUSIONS Findings indicate that LB women develop type 2 diabetes at younger ages than heterosexual women. Higher BMI in LB women is an important contributor to this disparity. Public health and clinical efforts to prevent, detect, and manage obesity and type 2 diabetes among LB women are warranted.

ABSTRACT Although the maternal intrauterine metabolic environment has been recognized to have a profound impact on fetal growth and development with lifelong health implications, to our knowledge, there have been few large-scale birth cohort studies linking the cord metabolome (reflecting both the maternal and fetal metabolic state) with postnatal height measurements across the pediatric age range. Using data from the Boston Birth Cohort, an ongoing prospective birth cohort, this study investigated the association of cord plasma metabolites with children's height from birth to adolescence. Height was analyzed as attained height and longitudinal trajectories. Distinctive cord metabolite types were associated with attained height at different developmental windows: triacylglycerols [TAGs], diacylglycerols [DAGs], cholesterol ester [CEs], phospholipids, amino acids [AAs], acylcarnitines [ACs], and nucleotides in early (age 0–4 years) and middle (age 6–12 years) childhood; various metabolite types other than TAGs in later childhood (after age 14 years). Functional principal component analysis on children's repeated height measurements summarized two typical height trajectory components: loadings on first eigenfunction [FPC1] representing overall height by age, and loadings on second eigenfunction [FPC2] representing speed of pubertal height growth. Although only one cord metabolite was correlated with FPC1 after accounting for multiple testing, the study found 27 metabolites with significant overall effect on FPC2 among females and 18 among males. These metabolites were mostly phospholipids (including phosphatidylethanolamines [PEs], phosphatidylethanolamine plasmalogens [PE_Ps], phosphatidylcholines [PCs], lysophosphatidylethanolamines [LPEs], and lysophosphatidylcholines [LPCs]), AAs, and nucleotides. Their associations with height differed between overweight/obesity (OWO) and non-OWO children, especially among females. In this prospective study of US understudied urban, low-income, racially diverse children, we demonstrated that cord plasma metabolites were significantly associated with postnatal attained height at different age windows as well as height trajectories from birth to adolescence. We also revealed how these associations differed by children's sex and OWO status. Our findings help elucidate metabolic pathways underlying fetal origins of height growth across developmental stages. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

To understand how the nature of scientific collaboration between individuals and sites in team-based research initiatives affect collaboration and research output, we examined four waves of prospective survey data to measure collaboration across investigators, disciplines, and sites to measure structural determinants of research success. 116 investigators in the five sites of the NIH-funded U54 Transdisciplinary Research on Energetics and Cancer (TREC) initiative were surveyed about their research ties with a 2011 baseline measure and followed by three additional iterations and augmented by bibliometric data. Social network analysis describes the changing structure of contact and cooperation. We found that the network structure of a team science project affects the nature and rate of publications, implying that funded projects vary in research output based on how investigators interact with each other and that the design of scientific research projects affects research output by determining levels of contact between actual and potential collaborators.

Abstract Objective To examine the associations between the intake of total and individual whole grain foods and the risk of type 2 diabetes. Design Prospective cohort studies. Setting Nurses’ Health Study (1984-2014), Nurses’ Health Study II (1991-2017), and Health Professionals Follow-Up Study (1986-2016), United States. Participants 158 259 women and 36 525 men who did not have type 2 diabetes, cardiovascular disease, or cancer at baseline. Main outcome measures Self-reports of incident type 2 diabetes by participants identified through follow-up questionnaires and confirmed by a validated supplementary questionnaire. Results During 4 618 796 person years of follow-up, 18 629 participants with type 2 diabetes were identified. Total whole grain consumption was categorized into five equal groups of servings a day for the three cohorts. After adjusting for lifestyle and dietary risk factors for diabetes, participants in the highest category for total whole grain consumption had a 29% (95% confidence interval 26% to 33%) lower rate of type 2 diabetes compared with those in the lowest category. For individual whole grain foods, pooled hazard ratios (95% confidence intervals) for type 2 diabetes in participants consuming one or more servings a day compared with those consuming less than one serving a month were 0.81 (0.77 to 0.86) for whole grain cold breakfast cereal, 0.79 (0.75 to 0.83) for dark bread, and 1.08 (1.00 to 1.17) for popcorn. For other individual whole grains with lower average intake levels, comparing consumption of two or more servings a week with less than one serving a month, the pooled hazard ratios (95% confidence intervals) were 0.79 (0.75 to 0.83) for oatmeal, 0.88 (0.82 to 0.94) for brown rice, 0.85 (0.80 to 0.90) for added bran, and 0.88 (0.78 to 0.98) for wheat germ. Spline regression showed a non-linear dose-response association between total whole grain intake and the risk of type 2 diabetes where the rate reduction slightly plateaued at more than two servings a day (P<0.001 for curvature). For whole grain cold breakfast cereal and dark bread, the rate reduction plateaued at about 0.5 servings a day. For consumption of popcorn, a J shaped association was found where the rate of type 2 diabetes was not significantly raised until consumption exceeded about one serving a day. The association between higher total whole grain intake and lower risk of type 2 diabetes was stronger in individuals who were lean than in those who were overweight or obese (P=0.003 for interaction), and the associations did not vary significantly across levels of physical activity, family history of diabetes, or smoking status. Conclusion Higher consumption of total whole grains and several commonly eaten whole grain foods, including whole grain breakfast cereal, oatmeal, dark bread, brown rice, added bran, and wheat germ, was significantly associated with a lower risk of type 2 diabetes. These findings provide further support for the current recommendations of increasing whole grain consumption as part of a healthy diet for the prevention of type 2 diabetes.