Scientific hypothesis – Dagulfs Ghost http://dagulfsghost.com/ Mon, 27 Sep 2021 03:21:52 +0000 en-US hourly 1 https://wordpress.org/?v=5.8 https://dagulfsghost.com/wp-content/uploads/2021/09/icon-2-150x150.png Scientific hypothesis – Dagulfs Ghost http://dagulfsghost.com/ 32 32 No Support for Historical Candidate Gene or Candidate Gene-by-Interaction Hypotheses for Major Depression Across Multiple Large Samples https://dagulfsghost.com/no-support-for-historical-candidate-gene-or-candidate-gene-by-interaction-hypotheses-for-major-depression-across-multiple-large-samples/ https://dagulfsghost.com/no-support-for-historical-candidate-gene-or-candidate-gene-by-interaction-hypotheses-for-major-depression-across-multiple-large-samples/#respond Mon, 27 Sep 2021 03:16:56 +0000 https://dagulfsghost.com/?p=369 Major depressive disorder (hereafter referred to as “depression”) is moderately heritable (twin-based heritability, ∼37%) (1), but its genetic architecture is complex, and identifying specific polymorphisms underlying depression susceptibility has been challenging. With the ability to genotype particular genetic variants and optimism about the potential public health impact of identifying reliable biomarkers for depression (2), early […]]]>

Major depressive disorder (hereafter referred to as “depression”) is moderately heritable (twin-based heritability, ∼37%) (1), but its genetic architecture is complex, and identifying specific polymorphisms underlying depression susceptibility has been challenging. With the ability to genotype particular genetic variants and optimism about the potential public health impact of identifying reliable biomarkers for depression (2), early research focused on the effects of specific candidate polymorphisms in genes hypothesized to underlie depression liability. These genes were chosen on the basis of hypotheses regarding the biological underpinnings of depression. The 5-HTTLPR variable number tandem repeat (VNTR) polymorphism in the promoter region of the serotonin transporter gene SLC6A4, the most commonly studied polymorphism in relation to depression (Figure 1; see also Table S1.1 in the online supplement), serves as a prototypical example: Given the theorized importance of the serotonergic system in the etiology of depression, a logical target for early association studies was a common, large (and hence relatively easy to genotype), and potentially functional repeat polymorphism in a serotonergic gene (3–5). Early investigations, although by necessity focused on a small number of variants (low-cost genome-wide arrays were not yet available), reported promising positive associations. However, replication attempts produced inconsistent results (6–8).

FIGURE 1. Estimated lower bounds of studies per candidate genea

a Panel A shows cumulative sums of the estimated number of depression candidate gene studies identified by our algorithm per year per gene from 1991 through 2016. Estimates reflect the number of correctly classified studies among identified studies, excluding studies not detected by our protocol, and thus comprise lower bounds for the true number of studies per gene. Panel B shows the 18 candidate genes studied ≥10 times between 1991 and 2016. The estimated number of studies focused on the top polymorphism (see Table S1.1 in the online supplement) is displayed relative to the other identified studies within each gene. No top polymorphisms were identified for DTNBP1 or TPH2 (see section S1 of the online supplement).

To critics of candidate gene findings, replication failures suggested that the initial findings were artifactual (9–11). However, at least two alternative explanations could account for the inability to replicate early findings and the inconsistent results across studies. First, in the early 2000s, Caspi et al. (12) posited that previous inconsistencies might reflect the effects of candidate polymorphisms that were dependent on environment exposures (gene-by-environment interaction [G×E] effects). In what would become one of the most highly cited (>8,000 citations as of July 2018) and influential papers in psychiatric genetics, Caspi et al. (13) reported that the impact of the 5-HTTLPR repeat polymorphism in SLC6A4 on depression was moderated by exposure to stressful life events, such that the positive association between stressful life events and depression was stronger in individuals carrying the “short” allele. This early work led many researchers to shift their attention to G×E hypotheses, focusing on the same polymorphisms first investigated for main effects (8). Second, in an alternative but complementary line of reasoning, other researchers suggested that polymorphisms in the same candidate genes, other than those studied previously, were likely to explain depression risk, given the genes’ putative biological relevance (14). These lines of inquiry are well represented in the literature of the past 25 years. Thousands of investigations of depression or depression endophenotypes have examined 1) the direct effects of the most studied polymorphisms within candidate genes, 2) the moderation of their effects by environmental stressors, or 3) the effects of alternative polymorphisms within the same candidate genes. The popularity of these lines of inquiry has not diminished over time (Figure 1; see also Figures S1.4 and S1.5 of the online supplement), and many studies have reported statistically significant associations.

Perhaps surprisingly given the continued interest in studying these historical depression candidate genes and the large number of associations documented in the candidate gene literature, many researchers have expressed skepticism about the validity of such findings (11, 15–17). There are several reasons for this. First, genome-wide association studies (GWASs), which agnostically examine associations at millions of common single-nucleotide polymorphisms (SNPs) across the genome in large samples, have consistently found that individual SNPs exert small effects on genetically complex traits such as depression (18–20). For example, in the most recent GWAS of depression, which utilized a sample of 135,458 case subjects and 344,901 control subjects, the strongest individual signal detected (rs12552; odds ratio=1.044, p=6.07×10−19) would require a sample of approximately 34,100 individuals to be detected with 80% power at an alpha level of 0.05, assuming a balanced case-control design (18). In contrast, the median study sample size in a review of 103 candidate G×E studies published between 2000 and 2009 was 345, with 65% of studies reporting positive results (15). Thus, given the small sample sizes typically employed, candidate gene research has likely been severely underpowered (21, 22). This, in turn, may suggest that the false discovery rate for the many positive reports in the candidate gene literature is high. Consistent with this possibility, targeted, well-powered genetic association studies of depression and other psychiatric phenotypes in large samples have not supported candidate gene hypotheses (18, 23–27). For example, a preregistered collaborative meta-analysis of the interaction of stressful life events and 5-HTTLPR genotype in a sample of 38,802 individuals failed to support the original finding of Caspi et al. (28), although we note that this variant and several other candidate VNTRs have not previously been examined in a GWAS context (29, 30). The absence of previous large-sample investigations of VNTR hypotheses is noteworthy, as VNTRs comprise several of the earliest candidate polymorphisms to be examined in the context of behavioral research; concerns about variability in VNTR genotyping procedures and analytic methods over time have further complicated the interpretation of the literature (31). Additionally, a number of researchers have suggested that incorrect analytic methods and inadequate control for population stratification characterize the majority of published candidate gene studies (21, 32–34), and other researchers have questioned the clinical utility of focusing on individual polymorphisms or polymorphism-by-environment interactions (35). Finally, there is evidence of systematic publication bias in the candidate gene literature; in the aforementioned review of all candidate G×E studies published between 2000 and 2009, 96% percent of novel findings were significant, compared with only 27% of replication attempts, and replication attempts reporting null findings had larger sample sizes than those presenting positive findings (15). In response to such skepticism, candidate gene proponents have argued that lack of replication of candidate gene associations in large-sample studies may reflect poor or limited phenotyping (36–38), exclusion of non-SNP polymorphisms such as VNTRs (14, 30), the “multiple-testing burden” associated with genome-wide scans (36), and failure to account for environmental moderators (36, 37, 39).

The present study is the most comprehensive and well-powered investigation of historical candidate polymorphism and candidate gene hypotheses in depression to date. We focus on three lines of inquiry concerning how historical candidate genes may affect depression liability: 1) main effects of the most commonly studied candidate polymorphisms, 2) moderation of the effects of these polymorphisms by environmental exposures, and 3) main effects of common SNPs across each of the candidate genes.

We first empirically identified 18 commonly studied candidate genes represented in at least 10 peer-reviewed depression-focused journal articles between 1991 and 2016 from the body of publications indexed in PubMed. Within these candidate genes, we identified the most commonly studied polymorphisms, as well as their canonical risk alleles, at which point our primary analysis plan was preregistered. Using multiple large samples (Ns ranging from 62,138 to 443,264 across subsamples; total N=621,214 individuals), we examined multiple measures of depression (e.g., lifetime diagnostic status, symptom severity among individuals reporting mood disturbances, lifetime number of depressive episodes) (Table 1), employing multiple statistical frameworks (e.g., main effects of polymorphisms and genes, interaction effects on both the additive and multiplicative scales) and, in G×E analyses, considering multiple indices of environmental exposure (e.g., traumatic events in childhood or adulthood). Previous large-sample studies of depression have largely focused on genetic main effects on depression diagnosis in the context of SNP data across the genome. In contrast, we examined several alternative depression phenotypes, analyzed both main effects and interactions with multiple potential moderators, included the most studied polymorphisms, including VNTRs (Figure 1), and employed a liberal significance threshold. We also quantified the extent to which phenotypic measurement error may have biased our results. The unifying question underlying this “multiverse” analytic approach (44) was the following: Do the large data sets of the whole-genome-data era support any previous depression candidate gene hypotheses?

TABLE 1. Depression and environmental moderator phenotypes

Phenotype Description Sample Size
Depression phenotypesa
Estimated lifetime depression diagnosis Binary indicator of lifetime DSM-5 depression diagnosis assessed in the UK Biobank online mental health follow-up questionnaire. To meet criteria, participants had to endorse at least four of eight DSM-5 depression symptoms (motor agitation/retardation was not assessed), as well as duration, frequency, and impairment criteria. N=115,458 (control subjects: 85,513; case subjects: 29,945)
Current depression severity Sum score of all nine DSM-5 depression symptom severities (using a 4-point Likert scale to index the severity of each symptom) over the 2 weeks preceding to assessment. Assessed in the UK Biobank online mental health follow-up questionnaire. N=115,463 (mean=2.502, SD=3.347)
Conditional lifetime symptom count Sum of symptom indicators for eight of nine lifetime DSM-5 depression symptoms (motor agitation/retardation was not assessed) among individuals endorsing lifetime incidence of a period of at least 2 weeks characterized by anhedonia and/or depressed mood (questionnaire skip patterns necessitated this precondition). Assessed in the UK Biobank online mental health follow-up questionnaire. N=62,138 (mean=4.746, SD=1.745)
Lifetime episode count Ordinal measure of incidence/recurrence of a period of at least 2 weeks characterized by anhedonia and/or depressed mood indicating zero episodes, a single episode, or recurrent episodes. Assessed in the UK Biobank online mental health follow-up questionnaire. N=115,457 (zero: 55,388; single: 30,724; recurrent: 26,345)
Touchscreen probable lifetime diagnosis, ordinal classification Ordinal measure of depression diagnostic status based on a selection of items from the Patient Health Questionnaire (40), the Structured Clinical Interview for DSM-IV Axis I Disorders–Research Version (41), and items assessing treatment-seeking behavior specific to the UK Biobank touchscreen interview, as described in Smith et al. (42). Categories included no depression, single depressive episode, recurrent episodes (moderate), and recurrent episodes (severe), in that order. Assessed as part of the UK Biobank initial touchscreen interview. N=91,121 (control subjects: 66,605; one episode: 6,209; ≥2 moderate episodes: 11,634; ≥2 severe episodes: 6,633)
Touchscreen probable lifetime diagnosis Dichotomized coding of the touchscreen probable life diagnosis ordinal classification, contrasting no depression with the three diagnosis categories. N=91,121 (control subjects: 66,605; case subjects: 84,516)
Severe recurrent depression Binary indicator of case/control status for depression, excluding case and control subjects with mild to moderate depressive symptoms. Control subjects were individuals who did not endorse incidence of a period of at least 2 weeks characterized by anhedonia and/or depressed mood. Case subjects were individuals who met criteria for estimated lifetime depression diagnosis, endorsed at least five of the eight measured DSM-5 symptoms, and experienced recurrent depressive episodes. Assessed in the UK Biobank online mental health follow-up questionnaire. N=64,432 (control subjects: 53,218; case subjects: 14,214)
PGC lifetime depression diagnosis Binary indicator of lifetime depression diagnosis as measured in the PGC2 depression GWAS (18). The present study utilized data from the full expanded cohort meta-analysis, excepting UK-based cohorts (UK Biobank and Generation Scotland). N=443,264 (control subjects: 323,063; case subjects: 120,201)
Moderator phenotypesb
Childhood trauma Binary indicator of sexual and/or physical abuse during childhood. Assessed in the UK Biobank online mental health follow-up questionnaire. N=157,146 (unexposed: 118,800; exposed: 38,346)
Adulthood trauma Binary indicator of any of the following traumatic events during adulthood: physical assault, sexual assault, witness to sudden/violent death, diagnosis of a life-threatening illness, involvement in a life-threatening accident, and exposure to combat or war zone conditions. Assessed in the UK Biobank online mental health follow-up questionnaire. N=157,223 (unexposed: 64,286; exposed: 92,937)
Recent trauma Binary indicator of whether any of the above events occurred in the year preceding assessment. N=157,220 (unexposed: 142,008; exposed: 15,212)
Stressor-induced depression Binary indicator of whether a period of depressed mood or anhedonia was a possible consequence of a traumatic event among individuals endorsing lifetime incidence of a period of at least 2 weeks characterized by anhedonia and/or depressed mood (questionnaire skip patterns necessitated this precondition). Assessed in the UK Biobank online mental health follow-up questionnaire. N=88,585 (unrelated to stressor: 23,746; stressor-induced: 64,839)
Townsend deprivation index Measure of socioeconomic adversity (43), with higher values indicating greater adversity. Standardized to have zero mean and unit standard deviation. Assessed during the UK Biobank initial touchscreen interview. N=187,094