The Impact of COVID-19 on the All of Us Research Program.

The All of Us Research Program, a health and genetics epidemiologic data collection program, has been substantially affected by the coronavirus disease 2019 (COVID-19) pandemic. Although the program is highly digital in nature, certain aspects of the data collection require in-person interaction between staff and participants. Before the pandemic, the program was enrolling approximately 12,500 participants per month at more than 400 clinical sites. In March 2020, because of the pandemic, all in-person activity at program sites and by engagement partners was paused to develop processes and procedures for in-person activities that incorporated strict safety protocols. In addition, the program adopted new data collection methodologies to reduce the need for in-person activities. Through February 2022, a total of 224 clinical sites had reactivated in-person activity, and all enrollment and engagement partners have adopted new data collection methods that can be used remotely. As the COVID-19 pandemic persists, the program continues to require safety procedures for in-person activity and continues to generate and pilot methodologies that reduce risk and make it easier for participants to provide information.

Design and Implementation of the All of Us Research Program COVID-19 Participant Experience (COPE) Survey.

In response to the rapidly evolving coronavirus disease 2019 (COVID-19) pandemic, the All of Us Research Program longitudinal cohort study developed the COVID-19 Participant Experience (COPE) survey to better understand the pandemic experiences and health impacts of COVID-19 on diverse populations within the United States. Six survey versions were deployed between May 2020 and March 2021, covering mental health, loneliness, activity, substance use, and discrimination, as well as COVID-19 symptoms, testing, treatment, and vaccination. A total of 104,910 All of Us Research Program participants, of whom over 73% were from communities traditionally underrepresented in biomedical research, completed 275,201 surveys; 9,693 completed all 6 surveys. Response rates varied widely among demographic groups and were lower among participants from certain racial and ethnic minority populations, participants with low income or educational attainment, and participants with a Spanish language preference. Survey modifications improved participant response rates between the first and last surveys (13.9% to 16.1%, P < 0.001). This paper describes a data set with longitudinal COVID-19 survey data in a large, diverse population that will enable researchers to address important questions related to the pandemic, a data set that is of additional scientific value when combined with the program's other data sources.

Testing structural models of DSM-IV symptoms of common forms of child and adolescent psychopathology.

Confirmatory factor analyses were conducted of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) symptoms of common mental disorders derived from structured interviews of a representative sample of 4,049 twin children and adolescents and their adult caretakers. A dimensional model based on the assignment of symptoms to syndromes in DSM-IV fit better than alternative models, but some dimensions were highly correlated. Modest sex and age differences in factor loadings and correlations were found that suggest that the dimensions of psychopathology are stable across sex and age, but slightly more differentiated at older ages and in males. The dimensions of symptoms were found to be hierarchically organized within higher-order "externalizing" and "internalizing" dimensions, which accounted for much of their variance. Major depression and generalized anxiety disorder were substantially correlated with both the "externalizing" dimension and the "internalizing" dimension, however, suggesting the need to reconceptualize the nature of these higher-order dimensions.

Number of risk genotypes is a risk factor for major depressive disorder: a case control study.

BACKGROUND: The objective of the study was to determine the genetic basis of Major Depressive Disorder, and the capacity to respond to antidepressant treatment. An association study of 21 candidate polymorphisms relevant to monoamine function and the mechanism of antidepressant response was conducted in 3 phenotypically distinct samples: a group with chronic or recurrent depression unable to respond to antidepressants (non-responders) (n = 58), a group capable of symptomatic improvement with or without treatment (responders) (n = 39), and volunteer controls (n = 85). The responders and non-responders constituted a larger group of depressed subjects. METHODS: A candidate gene approach was employed to asses the genetics basis of Major Depressive Disorder. The genotypic frequencies of selected polymorphisms were compared between the controls and depressed subjects. To asses the genetics basis of the capacity to respond to antidepressant treatment, the responders were compared to the non-responders. Candidate genes were chosen based on functional studies and proximity to whole genome linkage findings in the literature. Risk genotypes were identified by previous functional studies and association studies. RESULTS: A statistically significant difference in genotype frequency for the SLC6A4 intron 2 VNTR was detected between the subjects with a history of depression and controls (p = 0.004). Surprisingly, a statistically significant difference was detected between responders and non-responders for the DRD4 exon III VNTR genotype frequencies (p = 0.009). Furthermore, a difference between the controls and depressed subjects as well as between the controls and non-responders was detected for the number and distribution of risk genotypes in each group. CONCLUSION: An association between several monoamine-related genes and Major Depressive Disorder is supported. The data suggest that the two depressive phenotypes are genetically different, inferring that the genetic basis for the capacity to respond to standard antidepressant treatment, and the genetic susceptibility to Major Depressive Disorder may be independent. In addition, a proof of concept is provided demonstrating that the number of risk genotypes may be an indication of susceptibility of major depressive disorder and the severity of the disorder.

Association Study of Genotype by Depressive Response during Tryptophan Depletion in Subjects Recovered from Major Depression.

PURPOSE: The brief and reversible mood response to acute tryptophan (TRP) depletion (ATD) is being studied as a trait marker in subjects considered at risk for major depression (MD). PROCEDURES: ATD was administered to 64 subjects (54 European-Americans, and10 from other races) with personal and family history of MD. They were in remission and had been medication-free for at least three months. Subjects received an active and sham condition in a random assignment, double-blind crossover design. They were genotyped for serotonin-related candidate genes, and mood response was quantified with the Hamilton Depression Rating Scale (HDRS). Data were analyzed using Poisson regression with repeated measures and latent trajectory models. RESULTS: Compared to the sham control, active ATD caused modest depressive changes showing significant main effects of test condition (χ2=5.14, df=1, p=0.023) and time (χ2=12.22, df=3, p=0.007), but no significant interaction of time and test condition. Latent trajectory analysis revealed two groups, identified as depletion responders and non-responders. Those with the HTR2A rs6313 CC genotype had significantly higher HDRS scores during ATD (χ2=11.72, df=1, p=.0006). CONCLUSIONS AND MESSAGE: ATD may help the identification of biological subtypes of MD. These data are consistent with imaging reports implicating 5-HT2A receptor function in ATD phenotypes.

A genome-wide association study of a sustained pattern of antidepressant response.

Genome-wide association studies (GWAS) have failed to replicate common genetic variants associated with antidepressant response, as defined using a single endpoint. Genetic influences may be discernible by examining individual variation between sustained versus unsustained patterns of response, which may distinguish medication effects from non-specific, or placebo responses to active medication. We conducted a GWAS among 1116 subjects with Major Depressive Disorder from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial who were characterized using Growth Mixture Modeling as showing a sustained versus unsustained pattern of clinical response over 12 weeks of treatment with citalopram. Replication analyses examined 585 subjects from the Genome-based Therapeutic Drugs for Depression (GENDEP) trial. The strongest association with sustained as opposed to unsustained response in STAR*D involved a single nucleotide polymorphism (SNP; rs10492002) within the acyl-CoA synthetase short-chain family member 3 gene (ACSS3, p-value=4.5×10(-6), odds ratio=0.61). No SNPs met our threshold for genome-wide significance. SNP data were available in GENDEP for 18 of the top 25 SNPs in STAR*D. The most replicable association was with SNP rs7816924 (p=0.008, OR=1.58); no SNP met the replication p-value threshold of 0.003. Joint analysis of these 18 SNPs resulted in the strongest signal coming from rs7816924 (p=2.11×10(-7)), which resides in chondroitin sulfate N-acetylgalactosaminyltransferase 1 gene (CSGALNACT1). An exploratory genetic pathway analysis revealed evidence for an involvement of the KEGG pathway of long-term potentiation (FDR=.02). Results suggest novel genetic associations to sustained response.

A genomewide association study of citalopram response in major depressive disorder.

BACKGROUND: Antidepressant response is likely influenced by genetic constitution, but the actual genes involved have yet to be determined. We have carried out a genomewide association study to determine whether common DNA variation influences antidepressant response. METHODS: Our sample is derived from Level 1 participants in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, all treated with citalopram. Association for the response phenotype included 883 responders and 608 nonresponders. For the remission phenotype, 743 subjects that achieved remission were compared with 608 nonresponders. We used a subset of single nucleotide polymorphisms (SNPs; n = 430,198) from the Affymetrix 500K and 5.0 Human SNP Arrays, and association analysis was carried out after correcting for population stratification. RESULTS: We identified three SNPs associated with response with p values less than 1 x 10(-5) near the UBE3C gene (rs6966038, p = 4.65 x 10(-7)), another 100 kb away from BMP7 (rs6127921, p = 3.45 x 10(-6)), and a third that is intronic in the RORA gene (rs809736, p = 8.19 x 10(-6)). These same SNPs were also associated with remission. Thirty-nine additional SNPs are of interest with p values < or = .0001 for the response and remission phenotypes. CONCLUSIONS: Although the findings reported here do not meet a genomewide threshold for significance, the regions identified from this study provide targets for independent replication and novel pathways to investigate mechanisms of antidepressant response. This study was not placebo controlled, making it possible that we are also observing associations to nonspecific aspects of drug treatment of depression.

Association of mu-opioid receptor variants and response to citalopram treatment in major depressive disorder.

OBJECTIVE: Because previous preclinical and clinical studies have implicated the endogenous opioid system in major depression and in the neurochemical action of antidepressants, the authors examined how DNA variation in the mu-opioid receptor gene may influence population variation in response to citalopram treatment. METHOD: A total of 1,953 individuals from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study were treated with citalopram and genotyped for 53 single nucleotide polymorphisms (SNPs) in a 100-kb region of the OPRM1 gene. The sample consisted of Non-Hispanic Caucasians, Hispanic Caucasians, and African Americans. Population stratification was corrected using 119 ancestry informative markers and principal components analysis. Markers were tested for association with phenotypes for general and specific citalopram response as well as remission. RESULTS: Association between one SNP and specific citalopram response was observed. After Bonferroni correction, the strongest finding was the association between the rs540825 SNP and specific response. The rs540825 polymorphism is a nonsynonymous SNP in the final exon of the mu-opioid receptor-1X isoform of the OPRM1 gene, resulting in a histidine to glutamine change in the intracellular domain of the receptor. When Hispanic and Non-Hispanic Caucasians were analyzed separately, similar results in the population-corrected analyses were detected. CONCLUSIONS: These results suggest that rates of response to antidepressants and consequent remission from major depressive disorder are influenced by variation in the mu-opioid receptor gene as a result of either an effect on placebo response or true pharmacologic response.

Resequencing of serotonin-related genes and association of tagging SNPs to citalopram response.

Several reports have been published investigating the relationship between common variants in serotonin-related candidate genes and antidepressant response, and most of the results have been equivocal. We previously reported a significant association between variants in serotonin-related genes and response to the selective serotonin reuptake inhibitor fluoxetine. Here, we attempt to expand upon and replicate these results by (i) resequencing the exonic and putatively regulatory regions of five serotonin-related candidate genes (HTR1A, HTR2A, TPH1, TPH2, and MAOA) in our fluoxetine-treated sample to uncover novel variants; (ii) selecting tagging single nucleotide polymorphisms (SNPs) for these genes from the resequencing data; and (iii) evaluating these tagging SNPs for association with response to the selective serotonin reuptake inhibitor citalopram in an independent sample of participants who are enrolled in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) clinical study (N=1953). None of the variants associated previously with fluoxetine response were found to be associated with citalopram response in the STAR*D sample set. Nor were any of the additional tagging SNPs found to be associated with citalopram response. An additional SNP in HTR2A (rs7997012), previously reported to be associated with outcome of citalopram treatment in this sample, but not well tagged by any of the other SNPs we studied, was also genotyped, and was associated with citalopram response (P=0.0002), strongly supporting the previous observation in the same STAR*D sample. Our results suggest that resequencing the serotonin-related genes did not identify any additional common SNPs that have not been identified previously. It appears that genetic variation in these five genes has a marginal effect on response to citalopram, although a previously observed association was supported and awaits replication in an independent sample.