Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Influence of Serotonin Transporter Gene Polymorphisms and Adverse Life Events on Depressive Symptoms in the Elderly: A Population-Based Study

  • Annalisa Davin ,

    a.davin@golgicenci.it

    Affiliation ”Golgi Cenci” Foundation, Abbiategrasso, Italy

  • Maria Cristina Monti,

    Affiliation Section of Biostatistics and Clinical Epidemiology, Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy

  • Letizia Polito,

    Affiliation ”Golgi Cenci” Foundation, Abbiategrasso, Italy

  • Roberta Vaccaro,

    Affiliations ”Golgi Cenci” Foundation, Abbiategrasso, Italy, “C. Golgi” Geriatric Institute, Abbiategrasso, Italy

  • Simona Abbondanza,

    Affiliation ”Golgi Cenci” Foundation, Abbiategrasso, Italy

  • Marco Gnesi,

    Affiliation Section of Biostatistics and Clinical Epidemiology, Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy

  • Simona Villani,

    Affiliation Section of Biostatistics and Clinical Epidemiology, Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy

  • Antonio Guaita

    Affiliation ”Golgi Cenci” Foundation, Abbiategrasso, Italy

Influence of Serotonin Transporter Gene Polymorphisms and Adverse Life Events on Depressive Symptoms in the Elderly: A Population-Based Study

  • Annalisa Davin, 
  • Maria Cristina Monti, 
  • Letizia Polito, 
  • Roberta Vaccaro, 
  • Simona Abbondanza, 
  • Marco Gnesi, 
  • Simona Villani, 
  • Antonio Guaita
PLOS
x

Correction

29 Mar 2016: Davin A, Monti MC, Polito L, Vaccaro R, Abbondanza S, et al. (2016) Correction: Influence of Serotonin Transporter Gene Polymorphisms and Adverse Life Events on Depressive Symptoms in the Elderly: A Population-Based Study. PLOS ONE 11(3): e0152858. https://doi.org/10.1371/journal.pone.0152858 View correction

Abstract

Background

Depression is common in the elderly. The role of genetic and environmental factors in modulating depressive symptoms is not clear.

Methods

We evaluated the influence of serotonin transporter gene polymorphisms and recent adverse life events on depressive symptoms in an elderly Italian population. We used data from “InveCe.Ab”, a population-based study of 1321 subjects aged 70–74 years. We used the 15-item Geriatric Depression Scale (GDS) to assess depressive symptoms–a GDS score ≥5 points (GDS≥5) indicated the presence of clinically relevant symptoms–and performed 5-HTTLPR and rs25531 genotyping to obtain the triallelic polymorphism of the serotonin transporter. We used the Geriatric Adverse Life Events Scale to measure adverse life events, and logistic regression models to evaluate the role of genotype and recent adverse life events in depressive symptoms, controlling for potential confounders and independent predictors.

Results

Two hundred subjects (15.76%) had a GDS≥5. The 5-HTTLPR triallelic polymorphism was significantly associated with GDS≥5. Only S′S′ carriers showed an increased risk of depressive symptoms (ORadj = 1.81, p = .022); one extra adverse life event increased this risk by 14% (p = .061) independently of genotype. Other factors significantly related to GDS≥5 were: female gender (ORadj = 2.49, p < .001), age (ORadj = 1.19, p = .007), a history of depression (ORadj = 4.73, p < .001), and comorbidity (ORadj = 1.23, p = .001). One extra adverse life event increased the risk of depressive symptoms by 57% (p = .005) only in the L′L′ carriers, while antidepressant intake was directly related to GDS≥5 in the L′S′ carriers (ORadj = 2.46, p = .036) and borderline significant in the S′S′ carriers (ORadj = 2.41, p = .081).

Discussion

The S′S′ genotype and recent exposure to adverse life events were independently associated with depressive symptoms. The S′S′ genotype, compared with the environment, exerted a predominant effect on depressive symptoms, suggesting that it reduces the efficacy of antidepressant therapy. We conclude that genetics may be an important risk factor for depressive symptoms in late adulthood.

Introduction

Depression is a major health problem among the growing elderly population, estimated to affect around 17% of elderly people aged 75 years or older [1]. Late-life depression has detrimental effects not only on affected individuals and their families, but also on society, due to its impact on healthcare systems [2,3]. Indeed, late-life depression generates direct costs related to outpatient care and hospitalizations and indirect costs related to increased morbidity and mortality [35].

The causal mechanism underlying depressive symptoms in later life is still unclear, but socio-demographic, genetic and environmental risk factors are certainly involved [6]. Depressive symptoms in older people are more prevalent in women than in men [7] and in those with a history of depression [8]. Marital status also influences depression among the elderly: being unmarried or single is a risk factor for late-onset depression [9].

Recent genome-wide association studies have failed to identify any robust and replicable locus associated with depression [10], which suggests that specific genes may represent a risk factor for depression only under particular environmental conditions [11,12].

The human serotonin transporter gene (5-HTT), supposed to be associated with an increased risk of developing depression, has been extensively studied. Variations in 5-HTT negatively influence the response to environmental stress exposure [13], and in vitro experiments have shown that a 43 base pairs insertion/deletion in the promoter region of this gene (a polymorphism called 5-HTTLPR) regulates its expression [14,15]. The short allele (S), compared with the long allele (L), is associated with lower transcriptional efficiency, and related to anxiety [15], depression [16], bipolar disorder [17], post-traumatic stress disorder [18], and alcohol dependence [19]. Other studies, however, have not found an association of the 5-HTTLPR polymorphism with psychiatric disorders [2022]. Moreover, another variant (SNP rs25531) with an A>G polymorphism located upstream of the 5-HTTLPR insertion designates a third functional allele, LG, whose expression is equivalent to that of the S allele and lower than that of the LA allele [23,24]. Several other studies did not support these findings [2527]. These conflicting results might depend on differences in the samples considered, the methods used to assess depression, the stressors considered, and the genotype definitions used.

Exposure to threatening life events is an environmental factor commonly associated with depressive symptoms across the adult life span [28]. However, the profile (i.e. type and frequency) of adverse life events varies with age; this applies particularly to stressful events such as financial difficulties, bereavements, interpersonal conflicts, and physical illnesses or disabilities (affecting the subject and/or family members).

Aging is often associated with bereavement and the death of a spouse is a major negative life event for an elderly adult [29]. The death of a sibling, too, can increase an older person’s fear of death and, in turn, aggravate his/her depressive symptoms [30].

Depression is commonly associated with medical illness [3134], vision or hearing loss [35], and functional limitation or pain due to a chronic disorder [36]. The caregiving experience, too, can increase the risk of depression, particularly in those caring for a person with dementia [37,38].

Depression in the elderly, therefore, is related not only to physical decline but also to the loss of contact with close ties [39].

Since only a small proportion of individuals experiencing severe negative life events develop adverse health outcomes, such as depression, it is possible that an individual’s likelihood of developing depressive symptoms depends on other factors (personality [40], coping strategies [41], social support [42,43], genetic makeup).

The influence of environmental and genetic factors on depression changes during life. Exposure to threatening life events seems to increase the risk of depression both in younger people and in the over-70s, while genes have been shown to exert their negative effect more strongly earlier in life [44]. In the elderly, it could prove crucial not only to consider how adverse life events modulate the symptoms of depression, but also to investigate the role of genetic variations capable of influencing an individual’s response to the environment, e.g. the triallelic polymorphism of the serotonin transporter.

Few studies have investigated how the association of this triallelic polymorphism with the occurrence of adverse life events affects depressive symptoms in the elderly [45,46], and their results are conflicting.

We set out to investigate the influence of serotonin transporter gene polymorphisms and adverse life events on depressive symptoms in an elderly Italian population.

Materials and Methods

Population and setting

This work was conducted within the framework of InveCe.Ab (Invecchiamento Cerebrale in Abbiategrasso), an ongoing longitudinal population-based study (ClinicalTrials.gov, NCT01345110). The study design and methodology have already been detailed elsewhere [47]. For the purposes of the present study, we used data from the first (cross-sectional) phase of the InveCe.Ab study, which was carried out in 2009–2010. In that phase, 1773 individuals were eligible (born between 1935 and 1939 and resident in Abbiategrasso, a small town in the hinterland of Milan); of these, 1644 were available and 1321 were enrolled. We submitted all the participants to a multidimensional evaluation to assess social, clinical and neuropsychological aspects. In addition, the participants were asked to provide a blood sample for biological analyses and DNA extraction. Subjects with dementia diagnosed according to the Italian version of the Diagnostic and Statistical Manual of Mental Disorders IV (DSM IV-TR) [48] were included if they could adequately answer the evaluation questions (21 out of 39 subjects). All the participants were Caucasian.

Depressive symptoms

We used the 15-item Geriatric Depression Scale—short form (GDS-15) [49,50], administered to all the participants by trained neuropsychologists, to assess depressive symptoms over the previous month. Each item required a “yes”/“no” answer. When the answer indicated the presence of a depressive symptom, one point was assigned; otherwise, no point was assigned. Thus, the GDS-15 had a score range of 0–15. In accordance with the literature, a score of four or less (GDS<5) was taken to indicate the absence of clinically relevant depressive symptoms, whereas a score of between 5 and 15 (GDS≥5) was taken to indicate the presence of such symptoms [51].

Genotyping

We performed 5-HTTLPR and rs25531 genotyping, as previously described [52], to identify polymorphisms of the SLC6A4 serotonin transporter gene promoter. Genomic DNA (gDNA) was extracted from whole blood (Maxwell, Promega) and stored at 4°C.

To assess the 5-HTTLPR genotype, 50 ng of gDNA were amplified by polymerase chain reaction (PCR) with the following primers: forward 5′-GGCGTTGCCGCTCTGAATGC-3′, reverse 5′-GAGGGACTGAGCTGGACAACCA-3′ (PCR product size: L allele 529 bp; S allele 486 bp). PCR products were separated for two hours at 3 V/cm on 2% weight/volume agarose gel and stained with GelRed Nucleic Acid stain (Biotium).

Genotyping of rs25531 was performed by allele-specific PCR, using the following primers: forward A-allele specific 5′-ACCCCTCGCGGCATCCCCCCTGCACCCACA-3′; forward G-allele specific 5′-ACCCCTCGCGGCATCCCCCCTGCACCCACG-3′; common reverse 5′-TGGAGTCCGCGCGGGATTCTGGTGCCACCT-3′. The A or G specific amplification was loaded separately on 1% weight/volume agarose gel, stained with GelRed Nucleic Acid Stain (Biotium), and run for 1 hour at 5 V/cm. To check for possible genotype errors, two investigators independently interpreted the electrophoresis results; if their interpretations were not concordant, the specific genotype was re-tested.

The 5-HTTLPR and rs25531 genotypes were then combined (5-HTTLPR-rs25531), resulting in six genotypes: SS, SLA, SLG, LALA, LALG, and LGLG.

In view of the findings of previous studies that also combined 5-HTTLPR and rs25531 [5355], the low-expressing genotypes SS, SLG and LGLG were designated as S′S′, the intermediate-expressing genotypes LA S and LALG as S′L′, and the higher-expressing genotype LALA as L′L′.

The genotyping analysis was successfully performed in 1312 participants: nine did not consent to provide a blood sample.

Adverse life events

We used the Geriatric Adverse Life Events Scale (GALES) to investigate the stressful life events and difficulties experienced by our study participants. Administered by trained personnel, GALES is a 26-item checklist designed to evaluate the occurrence of major adverse life events over the previous 12 months in elderly subjects [56]. For each confirmed event, we asked two further questions to assess the degree of stress related to the reported event and to investigate how the event affected the subject’s mood. For the purpose of the present study, however, we analyzed only the occurrence (number) of adverse life events.

Other variables

Several other socio-demographic factors considered in this study were collected from municipal registers and from a social questionnaire administered by trained interviewers: gender, age at the beginning of the study (November 1st, 2009), marital status (defined as: coupled [currently married/cohabiting], single [never married] or uncoupled [separated/divorced/widowed]), and years of education.

We also considered depression history and current use of pharmacological drugs for depression (antidepressants [tricyclic, selective serotonin reuptake inhibitors and serotonin-norepinephrine reuptake inhibitors] or anxiolytic/hypnotic medications [benzodiazepines]) as ascertained by a geriatrician during the medical assessment. We defined subjects taking antidepressant drugs, with or without anxiolytic/hypnotic treatment, as under antidepressant treatment, and subjects using only anxiolytic/hypnotic medications as under anxiolytic treatment. We also considered comorbidity, as measured using the Cumulative Illness Rating Scale (CIRS), in which a five-level Likert scale is used to rate disease severity for each of 14 anatomical domains. The Comorbidity Index (CIRS-CI) represents the total number of categories (excluding the category Psychiatric/Behavioral) in which moderate or severe disease (CIRS score of 3, 4 or 5) is reported [57]. This clinical information was also collected from each participant by a geriatrician during the medical assessment.

Statistical analysis

The baseline characteristics of the population were expressed as mean values and standard deviation (SD), for quantitative variables, or as percentages, for categorical variables. Differences between subjects with and without relevant depressive symptoms were evaluated by unpaired t test for quantitative variables and chi-square test for categorical variables (χ2 test). Similarly, we explored the association between the genotype of the combined serotonin transporter gene polymorphism (5HTTLPR-rs25531) and demographic or clinical features, applying a χ2 test for categorical or ANOVA for quantitative variables.

Unconditional logistic regression analysis, specifically a genotypic model that estimated the S′S′ and L′S′ genotype risk compared to L′L′ (reference category) was applied to assess the adjusted association of depressive symptoms with the 5HTTLPR-rs25531 combined genotype and adverse life events. For the adjusted association all the relevant predictors obtained from univariate analyses were included in the model. Adjusted odds ratios (ORadj, respectively) with 95% confidence intervals (95% CI) were derived as measures of effect and precision. Moreover, we investigated interactions between 5HTTLPR-rs25531 genotypes and the number of adverse life events and antidepressant drug use. We also stratified analyses by genotype, in order to highlight the size of the environmental risk components.

Allele frequencies were examined for each polymorphism to detect any significant deviation from the Hardy-Weinberg Equilibrium (HWE), using goodness-of-fit χ2 test when appropriate. The level of statistical significance was set at .05 (.10 for interactions only). Statistical analyses were performed using Stata 12 (StataCorp. 2011. Stata Statistical Software: Release 12. College Station, TX: StataCorp LP).

Ethics statement

All the participants gave their written informed consent to the study. The study procedures were in accordance with the Declaration of Helsinki and the study protocol was approved by the Ethics Committee of the University of Pavia on October 6th, 2009 (Committee report 3/2009).

Results

Slightly more than 50% of the participants were females and almost a third were single or uncoupled at the time of assessment (Table 1). The average duration of education was greater than six years.

The most frequent 5-HTTLPR genotype was LS, while around one in five participants had the SS genotype (Table 1). Most of the subjects had the rs25531 AA genotype, while GG was carried by less than 1%. Combining these polymorphisms, the low-expressing S′S′ genotype was present in 23% of the individuals. Genotype frequencies did not deviate from the HWE (p>.05). The mean number of adverse life events, as resulting from the administration of the GALES, was low and rarely higher than seven (Table 1).

thumbnail
Table 1. Overview of the baseline characteristics of the cohort.

The summary statistics (mean and standard deviation) or the frequency distribution of each variable are shown in the overall population and by the presence/absence of clinically relevant depressive symptoms (GDS≥5 vs GDS<5).The statistical tests and p-values relative to analyses by GDS categories are also reported.

https://doi.org/10.1371/journal.pone.0143395.t001

Only 1269 subjects completed the GDS assessment and were therefore included in the analysis. Two hundred subjects (15.76%) showed clinically relevant depressive symptoms (GDS≥5) and they showed significant differences with respect to those without clinically relevant depression (GDS<5) (Table 1). In detail, people with relevant depressive symptoms were more frequently females, uncoupled, and carriers of the S′S′ genotype. They were more likely to have a positive history of depression and to be under pharmacological treatment for depression. They were also, on average, significantly older and presented a higher number of adverse life events and comorbidity than those without relevant depressive symptoms. We found no difference in mean years of education between the subjects with and those without relevant depressive symptoms.

Gender, age, marital status, number of adverse life events, history of depression, pharmacological treatment for depression, and comorbidity, therefore emerged as significant predictors of clinically relevant depressive symptoms in the multivariable analyses.

No statistically significant difference was observed (S1 Table) when comparing mean numbers of adverse life events recorded in the different 5HTTLPR-rs25531 combined genotypes (L′L′, L′S′ and S′S′ carriers). Similarly, we found no differences in pharmacological treatment for depression, history of depression, comorbidity, gender, marital status or mean age among the 5HTTLPR-rs25531 combined genotypes, excluding that a confounding effect may act on the association between depressive symptoms and 5HTTLPR-rs25531 genotype. The multivariable analysis (Table 2) revealed an increased risk of clinically relevant depressive symptoms in subjects presenting the S′S′ as opposed to the L′L′ genotype, after controlling for the effect of the significant predictors uncovered by the univariate tests (number of adverse life events, history of depression, pharmacological treatment for depression, comorbidity, marital status, gender and age). The greater risk found in the L′S′ carriers compared with the L′L′ carriers did not reach statistical significance.

thumbnail
Table 2. Mutually adjusted associations of depressive symptoms* (relevant vs not relevant) with genotype, adverse life events, pharmacological treatment for depression, history of depression, marital status, comorbidity index, gender and age distribution.

Adjusted odds ratios (ORadj) with confidence intervals (95%CI) and p-values are reported^.

https://doi.org/10.1371/journal.pone.0143395.t002

Interestingly, a one-unit change in the number of adverse life events (i.e. one extra adverse life event measured by GALES) produced a 14% (borderline significant) increase in the adjusted estimate of risk of clinically relevant depressive symptoms, a result which suggests that life events may act as an independent predictor with respect to genetic background. The adjusted risk of relevant depressive symptoms in the females was more than twice that found in the males, and a one-year increment in age led to a significant increase in this risk (19%). Comorbidity, as evaluated using the CIRS-CI, increased the risk of having clinically relevant depressive symptoms by 23%. On the other hand, being single or uncoupled as opposed to being coupled did not significantly change the estimated risk of depressive symptoms. As expected, treatment with anxiolytic/antidepressant medications and a history of depression were significant predictors of clinically relevant depressive symptoms, independently of all the other factors.

There was no significant interaction between 5HTTLPR-rs25531 genotype and GALES scores (p for interaction = .25) or antidepressant drug use (p for interaction = .51), which excludes a role for these factors as effect modifiers.

Nevertheless, to explore the role of environmental risk, we ran the same multivariable analysis among subjects with the same 5HTTLPR-rs25531 genotype (Table 3).

thumbnail
Table 3. Within combined genotypes, mutually adjusted associations of depressive symptoms* (relevant vs not relevant) with adverse life events, pharmacological treatment for depression, history of depression, marital status, comorbidity index, gender and age distribution.

Adjusted odds ratios (ORadj) with confidence intervals (95%CI) and p-values are reported^.

https://doi.org/10.1371/journal.pone.0143395.t003

The stratified analysis showed differences in the influence of adverse life events on depressive symptoms (Table 3). One extra adverse life event measured by GALES significantly increased, by 57%, the risk of clinically relevant depressive symptoms in the L′L′ carriers (p = .005) independently of the other factors included in the model, while one extra adverse life event did not significantly increase the risk of clinically relevant depressive symptoms among the L′S′ or S′S′ carriers only (p>.05). The presence of clinically relevant depressive symptoms was similar in subjects taking anxiolytic drugs and in those not receiving pharmacological treatment for depression in all genotype categories, although it was slightly greater (borderline significant difference) in the L′S′ carriers. The CIRS-CI modified the risk of GDS≥5 both in the L′L′ (borderline significant increase) and the S′S′ carriers, increasing it by 28% and 35% respectively, but the effect was not significant in the L′S′ carriers (Table 3). Conversely, clinically relevant depressive symptoms were directly related to antidepressant treatment in both the L′S′ and the S′S′ carriers, but in the latter this association was only borderline significant (Table 3). Finally, with regard to the effect of gender, the females, except in the L′L′ group, showed a significantly greater risk of clinically relevant depressive symptoms.

Discussion

In this study, conducted in an elderly population, the prevalence of depressive symptoms among S′S′ carriers of the combined serotonin transporter gene polymorphism (5HTTLPR-rs25531) was higher than among L′L′ carriers. The significantly increased estimate of risk of clinically relevant depressive symptoms in the S′S′ versus the L′L′ carriers was independent of environmental and socio-demographic factors. Moreover, we showed a direct (borderline significant) relationship between the risk of depressive symptoms and the number of recent adverse life events. Finally, within the sub-cohorts with genetically homogeneous 5HTTLPR-rs25531 backgrounds, an extra adverse life event significantly increased the risk of relevant depressive symptoms only in the L′L′ carriers.

This study shows that genes could represent a main risk factor for depressive symptoms: in particular, we found that subjects who are homozygous for the S′ allele show an increased vulnerability to depression even in late adulthood. This result agrees with the findings of several studies, both in vitro and in vivo, which have demonstrated that a reduction of serotonin transporter gene expression is associated with depression. Since it is hypothesized that cognitive impairment may influence depressive symptoms [58,59], we performed a sensitivity analysis excluding the subpopulation with dementia: in this analysis, the S′S′ genotype remained a determinant of clinically relevant depressive symptoms (ORadj = 1.79, p = .028). Consequently, it can be assumed that the association between depressive symptoms and being an S′S′ carrier of the combined serotonin transporter gene polymorphism is stable. Our findings also showed a slight association between the number of recent adverse life events and clinically relevant depressive symptoms in the elderly. Since the cross-sectional study design did not allow us to establish whether these events predated the onset of depressive symptoms, it is difficult to determine whether our findings are consistent with the accumulating evidence documenting a relationship between exposure to stressful life events and the onset of depression [28,60].

We showed that genetics, compared with environment, may play a predominant role in determining depressive symptoms in the elderly. Indeed, analyzing subjects with homogeneous 5-HTTLPR-rs25531 backgrounds we found that the S′S′ carriers were at higher risk of depression per se, and that environment did not constitute an additional risk, while a single extra adverse life event was significantly associated with an increased risk of clinically relevant depressive symptoms only in the L′L′ carriers. Similarly, other authors have found the influence of stressful life events on depression to vary considerably depending on prior individual characteristics such as genetic makeup [13].

The present study confirmed the importance of risk factors such as socio-demographic and clinical characteristics in the modulation of depressive symptoms in later life. The conflicting results reported in previous studies investigating the association of depression with serotonin transporter genotype and stressful life events [13,27] could be attributable to differences in the methodology used to assess depression or stressors, or in the age composition of the samples studied and the procedures used for their selection. Indeed, most studies in this field are conducted on selected populations, such as women [61], children [62], or people with affective disorders [63]. Few studies have investigated these associations in the elderly and sought to evaluate not only the effect of 5-HTTLPR, but also the functional polymorphism rs25531 [45,46,64]. Furthermore, to our knowledge, none of these studies took into account the role of crucial potential confounders such as a history of depression or use of anxiolytic/antidepressant drugs. The present study is concordant with previous research [8] in which older people with a history of depression showed a higher risk of having a high number of clinically relevant depressive symptoms than those who had no history of depression. Furthermore, we feel that our analysis of anxiolytic/antidepressant drug intake may represent a particular strength of the present study. Since anxiolytic/antidepressant drugs, generally used to treat depression, influence the serotonergic system, they will directly affect the primary outcome. Use of antidepressant drugs therefore likely plays an important role, modulating the depressive symptoms outcome. Indeed, we found use of these drugs to be more common in the S′S′ and L′S′ carriers, which seems to suggest that carrying the S′ allele, already an indicator of more severe depressive symptoms, may be related to a reduced ability of antidepressants to buffer depressive symptoms. This hypothesis is supported by more recent and exhaustive meta-analytic studies on the Caucasian population, which report a lower response to antidepressant treatment in association with the presence of the short allele [65,66].

Like other authors [67], we showed that females are at marked risk of developing clinically relevant depressive symptoms. In addition, an increase of just one year in age seemed to act as a major risk factor for depressive symptoms, and we hypothesize that this may also be linked to physical decline with aging. As several studies have reported, age is an important factor that is associated not only with a greater number of depressive symptoms, but also with a greater number of adverse life events and with increased comorbidity [28].

Contrary to published evidence [9], we found that being single/uncoupled was not associated with an increased risk of depressive symptoms. This discrepancy with literature data may be due to differences in the classification of marital status or to the fact that the potential role of this risk factor is very limited with respect to the role of other crucial determinants of depressive symptoms (triallelic polymorphism of the serotonin transporter, gender, history of depression and antidepressant/anxiolytic drug intake) included in the analyses.

Our study presents several limitations. First, our findings derived from cross-sectional analyses which may have produced weak evidence. Since our research is a prospective ongoing study, we plan to evaluate, in the near future, the role of genotype configuration and adverse life events on the incidence of depressive symptoms. Second, our use of the GDS may have introduced a misclassification; indeed, we may have overlooked a few subjects who are depressed but have no insight into their condition. Third, it was not possible to evaluate the potential existence of associations with traumatic events, personality traits and participants’ coping strategies, and we therefore considered only the number of adverse life events and not perceived stress in response to adversity. Several studies report that the effect of adverse life events may depend on the type of depressive disorder and decrease with age, in association with the use of different coping strategies [56,68]. Evaluation of stress and the emotional effects of adverse life events would require a specific study, taking into account not only the number of events and the genetic aspect, but also other factors such as depression diagnosis, age at onset of the disorder, and duration and recurrence of depression.

Conclusion

Our data suggest that, even in late adulthood, a key role in depressive manifestations is played by genetics. In a population of elderly subjects presenting clinically relevant depressive symptoms we found that some had a genetic background making them more vulnerable and, independently, another portion of individuals was found to be more likely to be affected by life’s adversities.

In particular, the 5HTTLPR-rs25531 combined polymorphism, compared with environmental factors, was found to exert a predominant effect on depressive symptomatology and seemed to interfere with the antidepressant treatment response. Therefore, activities enhancing social support, generally helpful in depressed elderly people, may be particularly important in people carrying the short allele of the 5HTTLPR-rs25531 combined polymorphism who are particularly susceptible to depressive symptoms [69]. Furthermore, there exist multiple preventive and treatment approaches, including educational interventions, for subjects with chronic illness, as well as cognitive-behavioral interventions that are effective in the elderly, but too infrequently used by this population [70].

Assessment of genetic makeup and previous life events could enhance the approach to elderly subjects at risk of depression, helping to protect them against first onsets, recurrences or post-treatment relapses of depressive symptoms.

Supporting Information

S1 Checklist. This is the STROBE-STREGA checklist.

https://doi.org/10.1371/journal.pone.0143395.s001

(PDF)

S1 Dataset. This is the dataset containing all data underlying the findings reported in the manuscript.

https://doi.org/10.1371/journal.pone.0143395.s002

(XLSX)

S1 Table. Depressive symptoms, environmental and socio-demographic factors by 5HTTLPR-rs25531 combined genotypes.

https://doi.org/10.1371/journal.pone.0143395.s003

(DOCX)

Acknowledgments

The authors are grateful to “Federazione Alzheimer Italia”, Milan, for for overseeing the recruitment phase and the correct execution of the InveCe.Ab study and also acknowledge Valeria Marzagalli, Golgi Cenci Foundation, Abbiategrasso, for her contribution to the data collection and quality control.

Author Contributions

Conceived and designed the experiments: AD. Performed the experiments: AD LP RV SA. Analyzed the data: MCM SV. Contributed reagents/materials/analysis tools: MG. Wrote the paper: AD MCM. Contributed to the interpretation and the discussion of results: LP RV SA SV AG.

References

  1. 1. Luppa M, Sikorski C, Luck T, Ehreke L, Konnopka A, Wiese B et al. (2012) Age- and gender-specific prevalence of depression in latest-life—systematic review and meta-analysis. J Affect Disord 136: 212–221. pmid:21194754
  2. 2. Choi S, Hasche L, Nguyen D (2014) Effects of Depression on the Subsequent Year’s Healthcare Expenditures Among Older Adults: Two-Year Panel Study. Psychiatric Quarterly. Available: http://link.springer.com/10.1007/s11126-014-9324-4.
  3. 3. Luppa M, König H- H, Heider D, Leicht H, Motzek T, Schomerus G et al. (2013) Direct costs associated with depressive symptoms in late life: a 4.5-year prospective study. Int Psychogeriatr 25: 292–302. pmid:23083505
  4. 4. Diniz BS, Reynolds CF, Butters MA, Dew MA, Firmo JOA, Lima-Costa MF et al. (2013) The effect of gender, age, and symptom severity in late-life depression on the risk of all-cause mortality: The bambuí cohort study of aging. Depress Anxiety 31: 787–795. pmid:24353128
  5. 5. Sobocki P, Jönsson B, Angst J, Rehnberg C (2006) Cost of depression in Europe. J Ment Health Policy Econ 9: 87–98. pmid:17007486
  6. 6. Blazer DG, Hybels CF (2005) Origins of depression in later life. Psychol Med 35: 1241–1252. pmid:16168147
  7. 7. Buber I, Engelhardt H (2011) The Association between Age and Depressive Symptoms among Older Men and Women in Europe. Findings from SHARE. Comparative Population Studies 36: 103–125.
  8. 8. Luijendijk HJ, van den Berg JF, Dekker MJHJ, van Tuijl HR, Otte W, Smit F et al. (2008) Incidence and recurrence of late-life depression. Arch Gen Psychiatry 65: 1394–1401. pmid:19047526
  9. 9. Yan XY, Huang SM, Huang CQ, Wu WH, Qin Y (2011) Marital status and risk for late life depression: a meta-analysis of the published literature. J Int Med Res 39: 1142–1154. pmid:21986116
  10. 10. Ripke S, Wray NR, Lewis CM, Hamilton SP, Weissman MM, Breen G et al. (2013) A mega-analysis of genome-wide association studies for major depressive disorder. Mol Psychiatry 18: 497–511. pmid:22472876
  11. 11. Cohen-Woods S, Craig IW, McGuffin P (2013) The current state of play on the molecular genetics of depression. Psychol Med 43: 673–687. pmid:22687339
  12. 12. Kendler KS, Kessler RC, Walters EE, MacLean C, Neale MC, Heath AC et al. (1995) Stressful life events, genetic liability, and onset of an episode of major depression in women. Am J Psychiatry 152: 833–842. pmid:7755111
  13. 13. Caspi A, Hariri AR, Holmes A, Uher R, Moffitt TE (2010) Genetic sensitivity to the environment: the case of the serotonin transporter gene and its implications for studying complex diseases and traits. Am J Psychiatry 167: 509–527. pmid:20231323
  14. 14. Heils A, Teufel A, Petri S, Stöber G, Riederer P, Bengel D et al. (1996) Allelic variation of human serotonin transporter gene expression. J Neurochem 66: 2621–2624. pmid:8632190
  15. 15. Lesch KP, Bengel D, Heils A, Sabol SZ, Greenberg BD, Petri S et al. (1996) Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science 274: 1527–1531. pmid:8929413
  16. 16. Lotrich FE, Pollock BG (2004) Meta-analysis of serotonin transporter polymorphisms and affective disorders. Psychiatr Genet 14: 121–129. pmid:15318024
  17. 17. Cho HJ, Meira-Lima I, Cordeiro Q, Michelon L, Sham P, Vallada H et al. (2005) Population-based and family-based studies on the serotonin transporter gene polymorphisms and bipolar disorder: a systematic review and meta-analysis. Mol Psychiatry 10: 771–781. pmid:15824745
  18. 18. Lee HJ, Lee MS, Kang RH, Kim H, Kim SD, Kee BS et al. (2005) Influence of the serotonin transporter promoter gene polymorphism on susceptibility to posttraumatic stress disorder. Depress Anxiety 21: 135–139. pmid:15965993
  19. 19. McHugh RK, Hofmann SG, Asnaani A, Sawyer AT, Otto MW (2010) The serotonin transporter gene and risk for alcohol dependence: a meta-analytic review. Drug Alcohol Depend 108: 1–6. pmid:20060655
  20. 20. Furlong RA, Ho L, Walsh C, Rubinsztein JS, Jain S, Paykel ES et al. (1998) Analysis and meta-analysis of two serotonin transporter gene polymorphisms in bipolar and unipolar affective disorders. Am J Med Genet 81: 58–63. pmid:9514589
  21. 21. Hoehe MR, Wendel B, Grunewald I, Chiaroni P, Levy N, Morris-Rosendahl D et al. (1998) Serotonin transporter (5-HTT) gene polymorphisms are not associated with susceptibility to mood disorders. Am J Med Genet 81: 1–3. pmid:9514579
  22. 22. Mendlewicz J, Massat I, Souery D, Del-Favero J, Oruc L, Nöthen MM et al. (2004) Serotonin transporter 5HTTLPR polymorphism and affective disorders: no evidence of association in a large European multicenter study. Eur J Hum Genet 12: 377–382. pmid:14735161
  23. 23. Hu XZ, Lipsky RH, Zhu G, Akhtar LA, Taubman J, Greenberg BD et al. (2006) Serotonin transporter promoter gain-of-function genotypes are linked to obsessive-compulsive disorder. Am J Hum Genet 78: 815–826. pmid:16642437
  24. 24. Wendland JR, Martin BJ, Kruse MR, Lesch K-P, Murphy DL (2006) Simultaneous genotyping of four functional loci of human SLC6A4, with a reappraisal of 5-HTTLPR and rs25531. Mol Psychiatry 11: 224–226. pmid:16402131
  25. 25. Eley TC, Sugden K, Corsico A, Gregory AM, Sham P, McGuffin P et al. (2004) Gene-environment interaction analysis of serotonin system markers with adolescent depression. Mol Psychiatry 9: 908–915. pmid:15241435
  26. 26. Grabe HJ, Lange M, Wolff B, Völzke H, Lucht M, Freyberger HJ et al. (2005) Mental and physical distress is modulated by a polymorphism in the 5-HT transporter gene interacting with social stressors and chronic disease burden. Mol Psychiatry 10: 220–224. pmid:15263905
  27. 27. Risch N, Herrell R, Lehner T, Liang K-Y, Eaves L, Hoh J et al. (2009) Interaction between the serotonin transporter gene (5-HTTLPR), stressful life events, and risk of depression: a meta-analysis. JAMA 301: 2462–2471. pmid:19531786
  28. 28. Nolen-Hoeksema S, Ahrens C (2002) Age differences and similarities in the correlates of depressive symptoms. Psychol Aging 17: 116–124. pmid:11931280
  29. 29. Whitbourne SK, Meeks S (2011) Handbook of the Psychology of Aging. 5th ed. Elsevier. 311–323 p.
  30. 30. Cicirelli VG (2009) Sibling death and death fear in relation to depressive symptomatology in older adults. J Gerontol B Psychol Sci Soc Sci 64: 24–32. pmid:19181691
  31. 31. Starkstein SE, Mizrahi R, Power BD (2008) Depression in Alzheimer’s disease: phenomenology, clinical correlates and treatment. Int Rev Psychiatry 20: 382–388. pmid:18925487
  32. 32. Reijnders JSAM, Ehrt U, Weber WEJ, Aarsland D, Leentjens AFG (2008) A systematic review of prevalence studies of depression in Parkinson’s disease. Mov Disord 23: 183–189; quiz 313. pmid:17987654
  33. 33. Mast BT, Miles T, Penninx BW, Yaffe K, Rosano C, Satterfield S et al. (2008) Vascular disease and future risk of depressive symptomatology in older adults: findings from the Health, Aging, and Body Composition study. Biol Psychiatry 64: 320–326. pmid:18367153
  34. 34. Regan CO, Kearney PM, Savva GM, Cronin H, Kenny RA (2013) Age and sex differences in prevalence and clinical correlates of depression: first results from the Irish Longitudinal Study on Ageing. Int J Geriatr Psychiatry 28: 1280–1287. pmid:23553681
  35. 35. Chou KL (2008) Combined effect of vision and hearing impairment on depression in older adults: evidence from the English Longitudinal Study of Ageing. J Affect Disord 106: 191–196. pmid:17602753
  36. 36. Mezuk B, Edwards L, Lohman M, Choi M, Lapane K (2012) Depression and frailty in later life: a synthetic review. Int J Geriatr Psychiatry 27: 879–892. pmid:21984056
  37. 37. Knight BG, Longmire CVF, Dave J, Kim JH, David S (2007) Mental health and physical health of family caregivers for persons with dementia: a comparison of African American and white caregivers. Aging Ment Health 11: 538–546. pmid:17882592
  38. 38. Ornstein K, Gaugler JE, Zahodne L, Stern Y (2014) The heterogeneous course of depressive symptoms for the dementia caregiver. Int J Aging Hum Dev 78: 133–148. pmid:24956922
  39. 39. Mazure CM, Maciejewski PK, Jacobs SC, Bruce ML (2002) Stressful life events interacting with cognitive/personality styles to predict late-onset major depression. Am J Geriatr Psychiatry 10: 297–304. pmid:11994217
  40. 40. Parker GB, Graham RK (2015) Anxious, irritable and hostile depression re-appraised. J Affect Disord 182: 91–94. pmid:25978719
  41. 41. Bjørkløf GH, Engedal K, Selbæk G, Kouwenhoven SE, Helvik A-S (2013) Coping and depression in old age: a literature review. Dement Geriatr Cogn Disord 35: 121–154. pmid:23392253
  42. 42. Peerenboom L, Collard RM, Naarding P, Comijs HC (2015) The association between depression and emotional and social loneliness in older persons and the influence of social support, cognitive functioning and personality: A cross-sectional study. J Affect Disord 182: 26–31. pmid:25965692
  43. 43. Schwarzbach M, Luppa M, Forstmeier S, König H-H, Riedel-Heller SG (2014) Social relations and depression in late life-a systematic review. Int J Geriatr Psychiatry 29: 1–21. pmid:23720299
  44. 44. Fiske A, Wetherell JL, Gatz M (2009) Depression in older adults. Annu Rev Clin Psychol 5: 363–389. pmid:19327033
  45. 45. Kim JM, Stewart R, Kim SW, Yang SJ, Shin IS, Kim YH et al. (2007) Interactions between life stressors and susceptibility genes (5-HTTLPR and BDNF) on depression in Korean elders. Biol Psychiatry 62: 423–428. pmid:17482146
  46. 46. Surtees PG, Wainwright NWJ, Willis-Owen SAG, Luben R, Day NE, Flint J (2006) Social adversity, the serotonin transporter (5-HTTLPR) polymorphism and major depressive disorder. Biol Psychiatry 59: 224–229. pmid:16154545
  47. 47. Guaita A, Colombo M, Vaccaro R, Fossi S, Vitali SF, Forloni G et al. (2013) Brain aging and dementia during the transition from late adulthood to old age: design and methodology of the “Invece.Ab” population-based study. BMC Geriatr 13: 98. pmid:24063518
  48. 48. Andreoli V, Cassano GB, Rossi R (2007) DSM-IV-TR. Manuale diagnostico e statistico dei disturbi mentali. 4th ed. Milan: Elsevier-Masson.
  49. 49. Wancata J, Alexandrowicz R, Marquart B, Weiss M, Friedrich F (2006) The criterion validity of the Geriatric Depression Scale: a systematic review. Acta Psychiatr Scand 114: 398–410. pmid:17087788
  50. 50. Yesavage JA, Sheikh JI (1986) Geriatric Depression Scale (GDS): Recent evidence and development of a shorter version. Clin Gerontol 5: 165–173.
  51. 51. Almeida OP, Almeida SA (1999) Short versions of the geriatric depression scale: a study of their validity for the diagnosis of a major depressive episode according to ICD-10 and DSM-IV. Int J Geriatr Psychiatry 14: 858–865. pmid:10521885
  52. 52. Polito L, Davin A, Vaccaro R, Abbondanza S, Govoni S, Racchi M et al. (2015) Serotonin transporter polymorphism modifies the association between depressive symptoms and sleep onset latency complaint in elderly people: results from the “InveCe.Ab” study. J Sleep Res 24: 215–222. pmid:25297871
  53. 53. Brown SM, Hariri AR (2006) Neuroimaging studies of serotonin gene polymorphisms: exploring the interplay of genes, brain, and behavior. Cogn Affect Behav Neurosci 6: 44–52. pmid:16869228
  54. 54. Hariri AR, Drabant EM, Munoz KE, Kolachana BS, Mattay VS, Egan MF et al. (2005) A susceptibility gene for affective disorders and the response of the human amygdala. Arch Gen Psychiatry 62: 146–152. pmid:15699291
  55. 55. Zalsman G, Huang YY, Oquendo MA, Burke AK, Hu XZ, Brent DA et al. (2006) Association of a triallelic serotonin transporter gene promoter region (5-HTTLPR) polymorphism with stressful life events and severity of depression. Am J Psychiatry 163: 1588–1593. pmid:16946185
  56. 56. Devanand DP, Kim MK, Paykina N, Sackeim HA (2002) Adverse life events in elderly patients with major depression or dysthymic disorder and in healthy-control subjects. Am J Geriatr Psychiatry 10: 265–274. pmid:11994213
  57. 57. Conwell Y, Forbes NT, Cox C, Caine ED (1993) Validation of a measure of physical illness burden at autopsy: the Cumulative Illness Rating Scale. J Am Geriatr Soc 41: 38–41. pmid:8418120
  58. 58. Janzing JGE, Hooijer C, van ‘t Hof MA, Zitman FG (2002) Depression in subjects with and without dementia: a comparison using GMS-AGECAT. Int J Geriatr Psychiatry 17: 1–5. pmid:11802223
  59. 59. De Craen AJM, Heeren TJ, Gussekloo J (2003) Accuracy of the 15-item geriatric depression scale (GDS-15) in a community sample of the oldest old. Int J Geriatr Psychiatry 18: 63–66. pmid:12497557
  60. 60. Kessler RC (1997) The effects of stressful life events on depression. Annu Rev Psychol 48: 191–214. pmid:9046559
  61. 61. Favaro A, Manara R, Pievani M, Clementi M, Forzan M, Bruson A et al. (2014) Neural signatures of the interaction between the 5-HTTLPR genotype and stressful life events in healthy women. Psychiatry Res 223: 157–163. pmid:24914006
  62. 62. Bogdan R, Agrawal A, Gaffrey MS, Tillman R, Luby JL (2014) Serotonin transporter-linked polymorphic region (5-HTTLPR) genotype and stressful life events interact to predict preschool-onset depression: a replication and developmental extension. J Child Psychol Psychiatry 55: 448–457. pmid:24117502
  63. 63. Costafreda SG, McCann P, Saker P, Cole JH, Cohen-Woods S, Farmer AE et al. (2013) Modulation of amygdala response and connectivity in depression by serotonin transporter polymorphism and diagnosis. J Affect Disord 150: 96–103. pmid:23643106
  64. 64. Power T, Stewart R, Ancelin M-L, Jaussent I, Malafosse A, Ritchie K (2010) 5-HTTLPR genotype, stressful life events and late-life depression: no evidence of interaction in a French population. Neurobiol Aging 31: 886–887. pmid:18640745
  65. 65. Fabbri C, Porcelli S, Serretti A (2014) From pharmacogenetics to pharmacogenomics: the way toward the personalization of antidepressant treatment. Can J Psychiatry 59: 62–75. pmid:24881125
  66. 66. Narasimhan S, Lohoff FW (2012) Pharmacogenetics of antidepressant drugs: current clinical practice and future directions. Pharmacogenomics 13: 441–464. pmid:22380000
  67. 67. Djernes JK (2006) Prevalence and predictors of depression in populations of elderly: a review. Acta Psychiatr Scand 113: 372–387. pmid:16603029
  68. 68. Aldwin CM, Sutton KJ, Chiara G, Spiro A (1996) Age differences in stress, coping, and appraisal: findings from the Normative Aging Study. J Gerontol B Psychol Sci Soc Sci 51: P179–P188. pmid:8673639
  69. 69. Way BM, Taylor SE (2010) Social influences on health: is serotonin a critical mediator? Psychosom Med 72: 107–112. pmid:20145277
  70. 70. Cole MG (2008) Brief interventions to prevent depression in older subjects: a systematic review of feasibility and effectiveness. Am J Geriatr Psychiatry 16: 435–443. pmid:18515687