Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multiancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.

Background and Aims Twin and family studies suggest that genetic influences are shared across substances of abuse. However, despite evidence of heritability, genome-wide association and candidate gene studies have indicated numerous markers of limited effects, suggesting that much of the heritability remains missing. We estimated (1) the aggregate effect of common single nucleotide polymorphisms (SNPs) on multiple indicators of comorbid drug problems that are typically employed across community and population-based samples, and (2) the genetic covariance across these measures. Participants 2596 unrelated subjects from the “Study of Addiction: Genetics and Environment” provided information on alcohol, tobacco, cocaine, cannabis, and other illicit substance dependence. Phenotypic measures included: (1) a factor score based on DSM-IV drug dependence diagnoses (DD), (2) a factor score based on problem use (PU; i.e., 1+ DSM-IV symptoms), and (3) dependence vulnerability (DV; a ratio of DSM-IV symptoms to the number of substances used). Findings Univariate and bivariate Genome-wide complex trait analyses of this selected sample indicated that common SNPs explained 25-36% of the variance across measures, with DD and DV having the largest effects [h2SNP (CI)=0.36 (0.11-0.62) and 0.33(0.07-0.58), respectively; PU = 0.25 (-0.01-0.51)]. Genetic effects were shared across the three phenotypic measures of comorbid drug problems (rSNP; rDD-PU = 0.92 (0.76-1.00), rDD-DV = 0.97 (0.87-1.00), and rPU-DV = 0.96 (0.82-1.00)). Conclusion At least 20% of the variance in the generalized vulnerability to substance dependence is attributable to common single nucleotide polymorphisms. The additive effect of common single nucleotide polymorphisms is shared across important indicators of comorbid drug problems.

The transition from childhood to adolescence is a crucial period for the development of healthy behaviors to be sustained later in life. With obesity a leading public health problem, the promotion of healthy behaviors has the potential to make a huge impact. The current study evaluated Stage of Change progression in a large (N = 4158) computer-delivered, Transtheoretical Model-tailored intervention focusing on physical activity and fruit and vegetable consumption (FV). Markov models were used to explore stage transitions and patterns of discrete change from sixth to ninth grade. Nested model comparisons examined the consistency of these patterns across time and intervention condition. Major findings supported models in which participants were free to transition forward and backward to any of the stages, but higher probabilities were observed for remaining in the same stage or for transitioning one or two stages forward. Participants in the intervention group had higher probabilities of transitioning toward Maintenance, with more change occurring relative to the comparison group during transitions from grades six to eight but not for grades eight to nine.

Childhood maltreatment is highly prevalent and serves as a risk factor for mental and physical disorders. Self-reported childhood maltreatment appears heritable, but the specific genetic influences on this phenotype are largely unknown. The aims of this study were to (1) identify genetic variation associated with self-reported childhood maltreatment, (2) estimate SNP-based heritability (h2snp), (3) assess predictive value of polygenic risk scores (PRS) for childhood maltreatment, and (4) quantify genetic overlap of childhood maltreatment with mental and physical health-related phenotypes, and condition the top hits from our analyses when such overlap is present. Genome-wide association analysis for childhood maltreatment was undertaken, using a discovery sample from the UK Biobank (UKBB) (n = 124,000) and a replication sample from the Psychiatric Genomics Consortium-posttraumatic stress disorder group (PGC-PTSD) (n = 26,290). h2snp for childhood maltreatment and genetic correlations with mental/physical health traits were calculated using linkage disequilibrium score regression. PRS was calculated using PRSice and mtCOJO was used to perform conditional analysis. Two genome-wide significant loci associated with childhood maltreatment (rs142346759, p = 4.35 × 10−8, FOXP1; rs10262462, p = 3.24 × 10−8, FOXP2) were identified in the discovery dataset but were not replicated in PGC-PTSD. h2snp for childhood maltreatment was ~6% and the PRS derived from the UKBB was significantly predictive of childhood maltreatment in PGC-PTSD (r2 = 0.0025; p = 1.8 × 10−15). The most significant genetic correlation of childhood maltreatment was with depressive symptoms (rg = 0.70, p = 4.65 × 10−40), although we show evidence that our top hits may be specific to childhood maltreatment. This is the first large-scale genetic study to identify specific variants associated with self-reported childhood maltreatment. Speculatively, FOXP genes might influence externalizing traits and so be relevant to childhood maltreatment. Alternatively, these variants may be associated with a greater likelihood of reporting maltreatment. A clearer understanding of the genetic relationships of childhood maltreatment, including particular abuse subtypes, with a range of phenotypes, may ultimately be useful in in developing targeted treatment and prevention strategies.