The dynamic genetic architecture of early childhood BMI

The genetic architecture of polygenic childhood obesity remains poorly understood. New work characterizes the dynamic genetic architecture of childhood BMI during the first eight years of life, identifying genetic loci involved in the leptin-melanocortin pathway

The origins of the Irish Travellers and the genetic structure of Ireland

Ireland's unique and well-documented history provides insight into the formation and origins of population subdivisions. Of particular interest, is the controversial ethnogenesis of an itinerant population of Ireland: the Travellers. The objectives of this study were: (1) to determine the genetic affinity of the Travellers to the general Irish population based on gene frequency data, subdivided by county, and (2) to explore the relationship between subpopulations of Ireland, given its turbulent history. The gene frequencies of standard genetic markers collected from populations residing in counties of Ireland and the Travellers were calculated and analysed using several multivariate methods. First, a relationship (R) matrix was used to ascertain the scaled variance-covariance matrix of population similarity. Second, mean per locus heterozygosity (H) was regressed on distance of the region from the gene frequency centroid (r(ii)). The results of this study include: (1) the confirmation of Crawford's (1975, in Biosocial Interrelations in Population Adaptations, E. S. Watts et al. (eds), pp. 93-103) conclusions concerning the origins and genetic affinity of the Travellers; (2) based on several multivariate analyses, the major influence on population structure was unique historical events; and (3) Relethford and Crawford's (1995, American Journal of Physical Anthropology, 96, 25-38) hypothesis concerning the distinctiveness of the midland counties was verified by this study

Gravidity and parity in postmenopausal American Indian women: The strong heart study

The fertility of a large sample of American Indian women participating in the Strong Heart Study was examined to determine which factors are associated with variation in completed fertility among women in this population. The Strong Heart Study (SHS) is a study of cardiovascular disease (CVD) and its risk factors in American Indians living in Arizona, Oklahoma, and the Dakotas. Data were derived from a baseline examination between 1989 and 1992 of approximately 1,500 men and women, aged 45-74, from each of the 3 SHS centers. A personal interview elicited demographic information, family health history, and information on several life-style variables. A total of 1,955 ever-married, postmenopausal women were considered in these analyses. Women were considered to be postmenopausal if their menstrual cycles had stopped completely for at least 12 months, either because of natural or surgical processes. The average number of pregnancies (gravidity) for all women was 5.9, whereas the mean number of live births (parity) was 5.3. Women living in Arizona (5.6) and the Dakotas (5.8) had higher parity than those in Oklahoma (4.6). Furthermore, there was lower completed fertility in younger women: When American Indian women from all 3 centers were considered together, women born between 1910 and 1919 had a mean parity of 5.3, whereas women born between 1940 and 1949 had a mean parity of 4.0. Although previous research has suggested a relationship between parity and CVD risk factors, no linear associations between CVD risk factors and fertility were indicated in this population. We also examined the relationship of contraception, level of education, and income to fertility. While no significant relationship between contraception and the level of fertility was identified, there was a significant inverse linear relationship of both education and income with fertility. In summary, fertility rates in American Indian women are high, but appear to be decreasing in younger generations. Fertility is higher in those with less education and lower incomes

Genetics of Obesity in Diverse Populations

Purpose of Review: The prevalence of obesity continues to rise, fueling a global public health crisis characterized by dramatic increases in type 2 diabetes, cardiovascular disease, and many cancers. In the USA, several minority populations, who bear much of the obesity burden (47% in African Americans and Hispanic/Latinos, compared to 38% in European descent groups), are particularly at risk of downstream chronic disease. Compounding these disparities, most genome-wide association studies (GWAS)—including those of obesity—have largely been conducted in populations of European or East Asian ancestry. In fact, analysis of the GWAS Catalog found that while the proportion of participants of non-European or non-Asian descent had risen from 4% in 2009 to 19% in 2016, African-ancestry participants are still just 3% of GWAS, Hispanic/Latinos are < 0.5%, and other ancestries are < 0.3% or not represented at all. This review summarizes recent developments in obesity genomics in US minority populations, with the goal of reducing obesity health disparities and improving public health programs and access to precision medicine. Recent Findings: GWAS of populations with the highest burden of obesity are essential to narrow candidate variants for functional follow-up, to identify additional ancestry-specific variants that contribute to individual genetic susceptibility, and to advance both public health and precision medicine approaches to obesity. Summary: Given the global public health burden posed by obesity and downstream chronic conditions which disproportionately affect non-European populations, GWAS of obesity-related traits in diverse populations is essential to (1) locate causal variants in GWAS-identified regions through fine mapping, (2) identify variants which influence obesity across ancestries through generalization, and (3) discover novel ancestry-specific variants which may be low frequency in European populations but common in other groups. Recent efforts to expand obesity genomic studies to understudied and underserved populations, including AAAGC, PAGE, and HISLA, are working to reduce obesity health disparities, improve public health, and bring the promise of precision medicine to all

The perils of standardizing infant weight to assess weight change differences across exposure groups

Purpose: When conducting analyses of child weight growth trajectories, researchers commonly use Z-scores from a standard instead of the observed weights. However, these Z-scores, calculated from cross-sectional data, may introduce methodological limitations when used in the context of longitudinal analyses. We assessed analytic limitations when analyzing infant growth data with three anthropometric measures: weight and the corresponding Z-scores and percentiles from a standard. Methods: We undertook a series of Monte Carlo simulations and compared tests of differences in postnatal weight change across time (growth velocity) between two exposure groups. Models with the observed weight outcome were compared to the corresponding weight World Health Organization (WHO) Z-score or weight percentile outcomes. We calculated power, type I error, and median product term coefficient estimates to assess differences between the models. Results: There was lower power to detect velocity differences across exposure groups for WHO Z-scores and percentiles as outcomes compared to the use of observed weight values. We also noted instances in which velocity differences between exposed and unexposed groups were in the opposite direction in analyses with WHO Z-score outcomes. Conclusions: In our simulations of infant weight velocity differences across exposure groups, we observed lower power and effect inconsistencies when applying a standard-derived Z-score transformation. These results emphasize the need for careful consideration of the appropriate scale when assessing infant growth trajectories across categorical groups

The genetics of obesity and the metabolic syndrome

In this review, we discuss the genetic architecture of obesity and the metabolic syndrome, highlighting recent advances in identifying genetic variants and loci responsible for a portion of the variation in components of the metabolic syndrome, namely, adiposity traits, serum HDL and triglycerides, blood pressure, and glycemic traits. We focus particularly on recent progress from large-scale genome-wide association studies (GWAS), by detailing their successes and how lessons learned can pave the way for future discovery. Results from recent GWAS coalesce with earlier work suggesting numerous interconnections between obesity and the metabolic syndrome, developed through several potentially pleiotropic effects. We detail recent work by way of a case study on the cadherin 13 gene and its relation with adiponectin in the HyperGEN and the Framingham Heart Studies, and its association with obesity and the metabolic syndrome. We provide also a gene network analysis of recent variants related to obesity and metabolic syndrome discovered through genome-wide association studies, and 4 gene networks based on searching the NCBI database

Discrimination and leukocyte telomere length by depressive symptomatology: The jackson heart study

Background: Psychosocial stressors, such as perceived discrimination and depressive symptoms, may shorten telomeres and exacerbate aging-related illnesses. Methods: Participants from the Jackson Heart Study at visit 1 (2000–2004) with LTL data and Center for Epidemiological Studies-Depression (CES-D) scores (n = 580 men, n = 910 women) were utilized. The dimensions of discrimination scores (everyday, lifetime, burden of lifetime, and stress from lifetime discrimination) were standardized and categorized as low, moderate, and high. Coping responses to everyday and lifetime discrimination were categorized as passive and active coping. Multivariable linear regression analyses were performed to estimate the mean difference (standard errors-SEs) in LTL by dimensions of discrimination and coping responses stratified by CES-D scores < 16 (low) and ≥ 16 (high) and sex. Covariates were age, education, waist circumference, smoking and CVD status. Results: Neither everyday nor lifetime discrimination was associated with mean differences in LTL for men or women by levels of depressive symptoms. Burden of lifetime discrimination was marginally associated with LTL among women who reported low depressive symptoms after full adjustment (b = 0.11, SE = 0.06, p = 0.08). Passive coping with lifetime discrimination was associated with longer LTL among men who reported low depressive symptoms after full adjustment (b = 0.18, SE = 0.09, p < 0.05); and active coping with lifetime discrimination was associated with longer LTL among men who reported high depressive symptoms after full adjustment (b = 1.18, SE = 0.35, p < 0.05). Conclusions: The intersection of perceived discrimination and depressive symptomatology may be related to LTL, and the effects may vary by sex

Chronic Periodontitis Genome-wide Association Studies: Gene-centric and Gene Set Enrichment Analyses

Recent genome-wide association studies (GWAS) of chronic periodontitis (CP) offer rich data sources for the investigation of candidate genes, functional elements, and pathways. We used GWAS data of CP (n = 4,504) and periodontal pathogen colonization (n = 1,020) from a cohort of adult Americans of European descent participating in the Atherosclerosis Risk in Communities study and employed a MAGENTA approach (i.e., meta-analysis gene set enrichment of variant associations) to obtain gene-centric and gene set association results corrected for gene size, number of single-nucleotide polymorphisms, and local linkage disequilibrium characteristics based on the human genome build 18 (National Center for Biotechnology Information build 36). We used the Gene Ontology, Ingenuity, KEGG, Panther, Reactome, and Biocarta databases for gene set enrichment analyses. Six genes showed evidence of statistically significant association: 4 with severe CP (NIN, p = 1.6 × 10−7; ABHD12B, p = 3.6 × 10−7; WHAMM, p = 1.7 × 10−6; AP3B2, p = 2.2 × 10−6) and 2 with high periodontal pathogen colonization (red complex–KCNK1, p = 3.4 × 10−7; Porphyromonas gingivalis–DAB2IP, p = 1.0 × 10−6). Top-ranked genes for moderate CP were HGD (p = 1.4 × 10−5), ZNF675 (p = 1.5 × 10−5), TNFRSF10C (p = 2.0 × 10−5), and EMR1 (p = 2.0 × 10−5). Loci containing NIN, EMR1, KCNK1, and DAB2IP had showed suggestive evidence of association in the earlier single-nucleotide polymorphism–based analyses, whereas WHAMM and AP2B2 emerged as novel candidates. The top gene sets included severe CP (“endoplasmic reticulum membrane,” “cytochrome P450,” “microsome,” and “oxidation reduction”) and moderate CP (“regulation of gene expression,” “zinc ion binding,” “BMP signaling pathway,” and “ruffle”). Gene-centric analyses offer a promising avenue for efficient interrogation of large-scale GWAS data. These results highlight genes in previously identified loci and new candidate genes and pathways possibly associated with CP, which will need to be validated via replication and mechanistic studies

Novel diabetes gene discovery through comprehensive characterization and integrative analysis of longitudinal gene expression changes

Type 2 diabetes is a complex, systemic disease affected by both genetic and environmental factors. Previous research has identified genetic variants associated with type 2 diabetes risk; however, gene regulatory changes underlying progression to metabolic dysfunction are still largely unknown. We investigated RNA expression changes that occur during diabetes progression using a two-stage approach. In our discovery stage, we compared changes in gene expression using two longitudinally collected blood samples from subjects whose fasting blood glucose transitioned to a level consistent with type 2 diabetes diagnosis between the time points against those who did not with a novel analytical network approach. Our network methodology identified 17 networks, one of which was significantly associated with transition status. This 822-gene network harbors many genes novel to the type 2 diabetes literature but is also significantly enriched for genes previously associated with type 2 diabetes. In the validation stage, we queried associations of genetically determined expression with diabetes-related traits in a large biobank with linked electronic health records. We observed a significant enrichment of genes in our identified network whose genetically determined expression is associated with type 2 diabetes and other metabolic traits and validated 31 genes that are not near previously reported type 2 diabetes loci. Finally, we provide additional functional support, which suggests that the genes in this network are regulated by enhancers that operate in human pancreatic islet cells. We present an innovative and systematic approach that identified and validated key gene expression changes associated with type 2 diabetes transition status and demonstrated their translational relevance in a large clinical resource

Association Between Midlife Obesity and Kidney Function Trajectories: The Atherosclerosis Risk in Communities (ARIC) Study

Rationale &amp; Objective: Obesity has been related to risk for chronic kidney disease. However, the associations of different measures of midlife obesity with long-term kidney function trajectories and whether they differ by sex and race are unknown. Study Design: Observational study. Setting &amp; Participants: 13,496 participants from the Atherosclerosis Risk in Communities (ARIC) Study. Predictors: Midlife obesity status as measured by body mass index (BMI), waist-to-hip ratio, and predicted percent fat at baseline. Outcomes: Estimated glomerular filtration rate (eGFR) calculated using serum creatinine level measured at 5 study visits, and incident kidney failure with replacement therapy (KFRT). Analytical Approach: Mixed models with random intercepts and random slopes for eGFR. Cox proportional hazards models for KFRT. Results: Baseline mean age was 54 years, median eGFR was 103 mL/min/1.73 m2, and median BMI was 27 kg/m2. Over 30 years of follow-up, midlife obesity measures were associated with eGFR decline in White and Black women but not consistently in men. Adjusted for age, center, smoking, and coronary heart disease, the differences in eGFR slope per 1-SD higher BMI, waist-to-hip ratio, and predicted percent fat were 0.09 (95% CI, −0.18 to 0.36), −0.25 (95% CI, −0.50 to 0.01), and −0.14 (95% CI, −0.41 to 0.13) mL/min/1.73 m2 per decade for White men; −0.91 (95% CI, −1.15 to −0.67), −0.82 (95% CI, −1.06 to −0.58), and −1.02 (95% CI, −1.26 to −0.78) mL/min/1.73 m2 per decade for White women; −0.70 (95% CI, −1.54 to 0.14), −1.60 (95% CI, −2.42 to −0.78), and −1.24 (95% CI, −2.08 to −0.40) mL/min/1.73 m2 per decade for Black men; and −1.24 (95% CI, −2.08 to −0.40), −1.50 (95% CI, −2.05 to −0.95), and −1.43 (95% CI, −2.00 to −0.86) mL/min/1.73 m2 per decade for Black women. Obesity indicators were independently associated with risk for KFRT for all sex-race groups except White men. Limitations: Loss to follow-up during 3 decades of follow-up with 5 eGFR assessments. Conclusions: Obesity status is a risk factor for future decline in kidney function and development of KFRT in Black and White women, with less consistent associations among men