Interaction between FokI polymorphism and vitamin D deficiency in the symptoms of mental disorders in adults: COVID-Inconfidentes, a population-based study in Brazil

doi:10.21203/rs.3.rs-2854327/v1

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Interaction between FokI polymorphism and vitamin D deficiency in the symptoms of mental disorders in adults: COVID-Inconfidentes, a population-based study in Brazil

https://doi.org/10.21203/rs.3.rs-2854327/v1

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Purpose

Mental disorders are intricate and multifaceted, encompassing social, economic, environmental, and biological factors. This study conducted in Brazil aimed to investigate whether the VDR gene polymorphism Fok I (rs2228570) interferes with the association between vitamin D deficiency and symptoms of anxiety and depression in adults.

Methods

This is a population-based cross-sectional study with stratified and cluster sampling, evaluating anxiety symptoms (AS) and depression symptoms (DS) in 1637 adults (50.9% women, mean age of 42.9 years) using Generalized Anxiety Disorder-7 and the Patient Health Questionnaire-9, respectively. Vitamin D levels were measured using electrochemiluminescence considered deficient when < 20 ng/mL in a healthy population or < 30 ng/mL for groups at risk. Genotyping was done using Taqman probes by real-time PCR.

Results

The prevalence of AS, DS and vitamin D deficiency were 23.5%, 15.8% and 30.9%, respectively. Genotypic frequency of the FokI was 9.9% AA, 44.7% AG, and 45.4% GG. No direct association was observed between vitamin D deficiency and AS and DS. However, an interaction analysis revealed a synergism between vitamin D deficiency and the FokI for DS, but not SA. Individuals with vitamin deficiency and one or two copies of the altered allele of the FokI exhibited a higher prevalence of DS than individuals homozygous for the wild-type allele and vitamin D sufficiency (AG: PR = 2.84, CI 95%: 1.04; 7.76; GG: PR = 4.37, CI 95%: 1.62; 11.83).

Conclusion

Our data suggest that an interaction between vitamin D deficiency and FokI polymorphism may interfere in the prevalence of DS.

Epidemiology

Anxiety

Depression

Vitamin D

Polymorphism

VDR

Vitamin D is a component of the steroid hormone family that plays classical roles in calcium metabolism and bone homeostasis [1]. Another relevance less explored of vitamin D for health is related to extra skeletal effects such as cell growth, neuromuscular and immune function [2], brain development, neuroprotection, regulation of neurotrophic factors, neurotransmission, and synaptic plasticity [3], which may have an impact on the development of mental disorders.

Vitamin D exists in two primary forms, ergocalciferol (vitamin D2) and cholecalciferol (vitamin D3). Vitamin D2 is obtained from a limited range of dietary sources, such as mushrooms, fortified foods, and supplements [4]. In contrast, vitamin D3 is primarily produced in the human body through a photochemical reaction in the skin that occurs when it is exposed to UVB radiation [4, 5]. However, it can also be obtained in smaller quantities by consuming animal-based foods such as milk, eggs [5], fish, and cod liver oil [4].

Vitamin D metabolism starts in the liver, where the first hydroxylation process takes place, forming 25-hydroxyvitamin D (25(OH)D) (calcidiol) [4, 6], which is a biomarker of serum vitamin D levels [4]. Subsequently, vitamin D binding protein (DBP) transports 25(OH)D from the liver to the kidneys, where the primary hydroxylation occurs, converting 25(OH)D into 1-α-25-dihydroxy vitamin D (1,25 (OH) 2 D) (calcitriol) [6], which is the biologically active form of the vitamin. This active form is responsible for most of vitamin D's biological functions [7].

One of the mechanisms that explains the association between serum vitamin D levels and mental disorders is the involvement of vitamin D in serotonin metabolism and its interface with the circadian rhythm [8]. During the COVID-19 pandemic, social distancing and isolation measures may have limited sun exposure, which is a predominant factor for maintaining serum levels of vitamin D [8]. Consequently, there may have been a reduction in maintaining optimal serum vitamin D levels, which could contribute to the development of AS and DS.

In the body, vitamin D functions are mediated by its binding to the vitamin D receptor (VDR), which is a member of the nuclear hormone receptor. The binding of active vitamin D to the VDR leads to the formation of a transcriptional complex [9], which modulates the transcription of genes that are related to the functions of vitamin D, such as CYP24A1, PTH, and FGF23 [10]. VDR is expressed in different cells [4] and tissues, including neurons, glial cells, and specific regions of the brain that have been implicated in the pathophysiology of mental disorders [8, 11].

There is a possibility that genetic variants, such as the single nucleotide polymorphism FokI (rs2228570), can affect the responsiveness of this receptor [12]. FokI is located in exon 2 of the VDR gene, and it modifies the transcription initiation site [7]. It is the only variant associated with a change in the length of the encoded protein [2], resulting in a less active protein [7, 13]. This polymorphism also alters the efficiency of vitamin D binding [9] and reduces the receptor's transcriptional capacity [7, 13].

In light of the aforementioned, it may be postulated that this alteration in the VDR protein could result in functional consequences similar to those of vitamin D deficiency. While the FokI polymorphism has been investigated in relation to major depressive disorder [11], cognitive functioning and depressive symptoms [14], and self-reported depression [12], it has not been studied in relation to anxiety. Moreover, these studies were conducted in other countries and do not necessarily reflect the Brazilian population, which is characterized by miscegenation [15] and high sun exposure [16]. Therefore, there is a pressing need for studies in other contexts that investigate this association.

Given that vitamin D deficiency can potentially impact AS and DS and considering the high prevalence of this deficiency even in tropical countries like Brazil [16, 17], which may have been exacerbated by social isolation during the pandemic, it is crucial to investigate the factors involved in vitamin D metabolism and their associations with mental disorders.

The hypothesis is that vitamin D deficiency is associated with both AS and DS; and the presence of the VDR gene polymorphism (rs2228570) FokI has an interactive effect on this association. Therefore, this study aims to investigate whether this polymorphism influences the association between vitamin D deficiency and both AS and DS in adults during the COVID-19 pandemic.

Study design

This study was part of a study entitled “Epidemiological surveillance of COVID-19 in the Inconfidentes Region/MG” (COVID-Inconfidentes Study). The COVID-Inconfidentes Study was a population-based cross-sectional survey with a probabilistic sample conducted between October and December 2020 (Spring weather in Brazil) in two medium-sized cities in the state of Minas Gerais, Brazil (Ouro Preto and Mariana).

The sample size was calculated using the OpenEpi tool (https://www.openepi.com/Menu/OE_Menu.htm) considering the 2010 population census [18] for the urban area of each city, adopting a 95% confidence level, design effect equal to 1.5 and a 20% re-composition percentage for any losses. After performing the sample calculation, it was determined that a minimum of 1,464 individuals is required for the study.

A three-stage conglomerate sampling design was adopted: census sector, household, and resident. For each city, strata were defined according to the average monthly incomes available in the 2010 census, to ensure representativeness of different socioeconomic strata in the sample [18]. The sample weight for each selection unit was calculated according to the methodology described by Silva et al. (2002) [19].

Data collection

Data collection was conducted through face-to-face interviews conducted by trained interviewers, who applied a questionnaire in an electronic device in the Data Goal® application. The questionnaire, based on previously validated instruments, contained questions about sociodemographic characteristics, lifestyle, health conditions, and diet. In addition, blood samples were collected for biochemical and genetic analyses. Considering data were collected in person, all the recommendations of the national protocols to contain the spread of the coronavirus were adopted, including the use of personal protective equipment.

Detailed information about the study methodology and questionnaire can be accessed in the study by Meireles et al. (2023) [20].

Analytic Sample

A total of 1,789 participants were selected to take part in the survey. Individuals who did not answer the questionnaire (n = 9), those with incomplete information on the scales assessing the study outcomes (n = 69), those whose answers contained no information for sample weight calculation (n = 18), and those with insufficient blood samples for biochemical and genetic analyses were excluded from the study (n = 56). Therefore, the final sample consisted of 1,637 participants.

Measures

Outcome: Symptoms of mental disorders

The AS and DS were measured using the 7-item Generalized Anxiety Disorder (GAD-7) and 9-item Patient Health Questionnaire (PHQ-9) scales, both validated in Brazil [21–23]. The scales assess the presence of negative symptoms related to the presence of the mental disorders in the last two weeks. The GAD-7 score ranges from 0 to 21 points, and the PHQ-9 from 0 to 27 points. In this study, the presence of AS and DS was defined when the score obtained was ≥ 10 [24, 25].

Biological sample

Blood collection was obtained by puncture in the region of the cubital fossa, performed by a trained professional and according to protocol. Two samples were obtained and stored in two distinct tubes: one containing 7.5 mL S-Monovette® (Sarstedt) serum gel for vitamin D analysis; and the other containing 2.7 mL S-Monovette® (Sarstedt) K3 EDTA for genetic analysis.

The samples were then checked, stored in a cool box, and taken to the Epidemiology Laboratory of the Medical School of the Federal University of Ouro Preto (UFOP). Subsequently, the samples with serum gel were centrifuged at 2500 rpm for 15 minutes, aliquots were prepared, and stored in an -80°C freezer for the biochemical analysis. The samples containing EDTA were stored at -20 ºC until genetic analyses were carried out.

Exposure variable: Serum vitamin D levels

The serum level of 25(OH)D was determined by indirect electrochemiluminescence in the Access 2 Immunoassay System® (Beckman Coulter, USA) using the commercial Roche Diagnostics® kit (Roche, Switzerland). For the analyzes of this study, the serum levels were evaluated as continuous and categorical variables, being classified according to the Brazilian Society of Metabolism and Endocrinology as deficiency when the levels of 25(OH)D < 20 ng/mL in the healthy population, or < 30 ng/mL for the risk groups, such as older adults, pregnant and lactating women, patients with rickets/osteomalacia, osteoporosis, patients with a history of falls and fractures, secondary causes of osteoporosis, hyperparathyroidism, inflammatory diseases, autoimmune diseases, chronic kidney disease, and malabsorption syndromes [26].

Interaction variable: Polymorphism FokI

For the detection of the VDR gene polymorphism (rs2228570) FokI, extraction of genomic DNA from venous blood samples was performed. To perform the manufacturer's protocol, a 600µL sample of whole blood was used immediately after thawing and the Wizard® Genomic DNA Purification kit (Promega, USA). After extraction, the DNA was kept in a hydration solution at 4 ºC for 24 hours. Then, the samples were stored at -20°C until quantification, which was performed using fluorometry (Fluorometer Qubit 2.0, Invitrogen®), and subsequent genotyping.

Polymorphism detection was performed by means of amplification of DNA fragments by the TaqMan® SNP Genotyping Assay (Applied Biosystems, Foster City, USA) of real-time PCR (initial denaturation: 95ºC, 10min; ringing: 40 cycles of 95ºC, 15sec; final extension: 60ºC, 1min) using specific primers from Thermo Scientific (Assay ID__12060045_20).

Genotyping was performed using TaqMan allelic discrimination with sequence detection software on the 7500 fast Real Time PCR System (Applied Biosystems, Foster City, USA), according to the manufacturer's instructions, for detection of transition substitution A > G. Individuals were classified as homozygous wild (AA), heterozygous (AG), or homozygous mutant (GG).

Descriptive variables and covariates

It was evaluated: age; sex (female, male); skin color (white or non-white); education level (no schooling, ≤ 9 years of schooling, > 9 years of schooling); work status (not work/housework, currently employed); work routine during the pandemic (work outside, no work at all, work from home); social restriction (yes, no); current alcohol consumption (yes, no); smoking (yes, no); vitamin D supplementation (yes, no); self-reported chronic physical pain, considering physical pain present for 3 months or more (yes, no); self-rated health (fair/poor/very poor health; very good, good); and reported morbidity was assessed through the question, "Has any doctor or other health professional ever informed you of having a chronic disease?" Individuals who responded affirmatively were categorized as having reported morbidity. The available response options included chronic disease such as, hypertension, diabetes, asthma or bronchitis, chronic lung disease, cancer (any type), chronic kidney disease, any heart disease, depression, anxiety disorder, sleep apnea, hypo- or hyperthyroidism, other and none of the above. In addition to these were evaluated the COVID-19 test, using Wondfo SARS-CoV-2 Antibody Rapid Test (soropositive, soronegative); sleep quality (good, poor), assessed by the Pittsburgh Sleep Quality Index (PSQI) questionnaire, with scores ≥ 5 classified as poor sleep quality [27]. Current family income was categorized according to the number of minimum wages received (≤ 2 minimum wages or up to 388.5 dollars, > 2 and ≤ 4 minimum wages or greater than 388.5 dollars, up to 770.0 dollars, > 4 minimum wages or greater than 770.0 dollars). In Brazil, the minimum wage is the lowest salary that employers can legally pay to their employees, and it is used as a national reference.

Physical activity (dichotomous nominal variable - inactive, active); those who had at least 150 min per week of moderately intense physical activity or at least 75 min per week of vigorously intense physical activity were classified as active [28].

Sun exposure (dichotomous nominal variable - sufficient or insufficient) was categorized according to the average daily sun exposure: [total time of daily sun exposure (minutes) x frequency of sun exposure weekly / 7]. It was then classified as “insufficient sun exposure” when less than 30 minutes per day [29]. Finally, body mass index (BMI) (dichotomous nominal variable - not overweight, overweight) was classified as not being overweight (BMI < 25 kg/m² for adults and < 27 kg/m2 for older adults) and overweight (BMI ≥ 25 kg/m2 for adults and ≥ 27 kg/m2 for older adults), according to the World Health Organization (WHO) [30] for adults and Lipschitz [31] for older adults, respectively.

Statistical analysis

Categorical variables were described as relative frequencies and 95% confidence interval (95% CI), and continuous variables were described as means and 95% CI.

To guide the analysis, a causality model based on a directed acyclic graph (DAG) was developed with the exposure variable (vitamin D deficiency), the outcomes (AS and DS), interaction variable (polymorphism FokI) and possible confounding variables (Fig. 1), using the online software Dagitty, version 3.2 [32]. T-test was performed to verify difference of means. Crude and adjusted Poisson regression for the variables indicated by DAG were performed. Therefore, the model was fitted by the following minimum set of variables: sex, age, skin color, alcohol consumption, body mass index, physical activity, sun exposure, chronic disease, and social restriction.

In addition, multiplicative interaction analysis was performed to verify how FokI interferes in the association between exposure and outcomes. The same adjustment was adopted for these analyses, except for the association between FokI and outcomes, which were only adjusted for sex and age.

All statistical analyses were performed considering a complex sample design using the "svy" package of Stata® software, version 13.1 (version 13.1; Stata Corporation, College Station, Texas, USA) with a statistical significance of 5%.

Ethical considerations

All procedures followed Brazilian guidelines and standards for research involving human beings of the Declaration of Helsinki, the seroepidemiological investigation protocol for SARS-CoV-2 infection by the WHO [33] and were approved by the Research Ethics Committee (Ethics Submission Certificate No. 32815620.0.1001.5149).

Study population

Among the 1637 participants, 50.9% were female with a mean age of 42.9 years. The most participants had >9 years of schooling, were employed and had current family income ≤2 minimum wages or up to 388.5 dollars. Regarding skin color, the majority identified themselves as non-white (Table 1). Of the participants, 23.5% reported having identified SA, 15.8% reported having SD, and 30.9% had vitamin D deficiency (Figure 2). There was no difference in mean vitamin D levels among individuals with AS (without AS: mean 26.5; Std. Err: 0.55; 95% CI: 25.40 - 27.59 vs with AS: mean 25.3, Std. Err: 0.61; 95% CI: 24.05 - 26.48; p=0.084). However, levels were slightly lower among those with depression (without DS: mean 26.5; Std. Err: 0.52; 95% CI: 25.51 - 27.58 vs with DS: mean 24.4; Std. Err: 0.69; 95% CI: 23.06 - 25.81; p=0.015) (Figure 3).

Vitamin D deficiency-associated factors

Vitamin D deficiency was positively associated with a higher age, diagnosis of chronic disease and worse self-rated health. In counterpoint, vitamin D deficiency was negatively associated with education level, work status and alcohol consumption (Table 1).

Vitamin D deficiency, mental disorders, and FokI polymorphism

In the multivariate model, no association was observed between vitamin D deficiency and AS and DS. Similarly, no association was observed between the polymorphism and the outcome. However, in the interaction analyses, a synergism between vitamin D deficiency and the presence of the altered allele was observed for DS, but not for AS (Table 2). Worth noting, individuals with vitamin D deficiency and the presence of one altered allele had a 2.84 higher prevalence of DS (95% CI: 1.04 - 7.76) while individuals with the presence of two altered alleles had a 4.37 higher prevalence of DS (95% CI: 1.62 - 11.83) (Table 2).

This study investigated the association between vitamin D deficiency and AS and DS during the coronavirus disease (COVID-19) pandemic, and the influence of a polymorphism related to vitamin D metabolism and activity, the FokI, in this association. Our main findings were that the vitamin D deficiency, as well as the presence of the FokI polymorphism alone, were not associated with AS and DS; and a synergism was observed between AG and GG genotypes and vitamin D deficiency in relation to DS, but not in relation to AS. Noteworthy, the prevalence ratio of DS was even greater among individuals who had two copies of the altered allele.

Vitamin D deficiency is highly prevalent globally, and has been found in different populations, such as children, adolescents, adults, and older adults, irrespective of the race, ethnicity, or country [34]. Recently, vitamin D deficiency has been suggested to be associated with an increased risk of humor disorders, such as anxiety and depression, and is associated with neuropsychophysiological implications in general [34]. Therefore, it has been the subject of investigation.

Several studies have shown that low serum levels of vitamin D are associated with depressive symptoms [8, 35, 36]. In contrast with our results, a meta-analysis of observational studies revealed that individuals with lower levels of vitamin D were 1.31 times more depressed (95%CI 1.0-1.71, p = 0.05), as a summary measure of nine cross-sectional studies, and had a 2.21 higher risk of depression (95%CI 1.40–3.49, p = 0.0007) as a summary measure of three cohort studies [36]. Although we did not find an association between serum levels of vitamin D and AS and DS, we observed that DS individuals have lower mean serum levels of vitamin D. It is possible that there is a bidirectional relationship between lower serum vitamin D levels and mental health disorders. That is, lower levels of vitamin D can lead to the development of mental health disorders, but individuals with mental health disorders may be in social isolation and reduced exposure to sunlight, so the opposite could be equally true [37].

Regarding anxiety, the association between low serum vitamin levels and symptoms of anxiety was explored in a reduced number of studies and in specific subgroups [38–40], however the result of a cross-sectional study demonstrated a negative association between serum vitamin D levels and self-reported state of anxiety (OR = 0.92, p < 0.001) [1].

There are various mechanisms that explain the association between serum levels and mental health disorders. One of these involves the role of vitamin D in the metabolism of serotonin and its interaction with the circadian rhythm [8]. An experimental study showed that sufficient serum levels of vitamin D can enhance the production of serotonin, suppress its reuptake and catabolism [41]. Serotonin is a neurotransmitter that plays a central role in the pathogenesis of anxiety and depression [42], making this a plausible mechanism for the link between vitamin D and these mental health disorders. Furthermore, serotonin is a precursor of melatonin, which is a hormone involved in the regulation of the circadian rhythm and is associated with sleep quality [8]. Thus, lower levels of vitamin D could compromise sleep quality and could play a fundamental role in the symptomatology of both mental disorders [8, 43].

In addition to the aforementioned pathways, there are other plausible mechanisms linking vitamin D to mental health disorders. Vitamin D is known to regulate the detoxification process in the brain by controlling the activity of γ-glutamyl transpeptidase. It also regulates the expression of neuronal growth factors such as neurotrophin-3 (NT-3) and neurotrophin-4 (NT-4) [44] and the secretion of brain-derived neurotrophic factor (BDNF) [45, 46]. Additionally, vitamin D acts by reducing neuronal calcium levels, which result from an imbalance between excitatory and inhibitory neurons that can contribute to the development of mental health disorders [47].

As previously mentioned, the function of vitamin D in target tissues is mediated by its binding to the VDR receptor [9]. Disparities in the affinity of vitamin D with the VDR receptor can be attributed to the presence of polymorphisms in the VDR gene, especially FokI [12]. Our study did not demonstrate a direct association between the genotypes of the FokI polymorphism and AS and DS. Similarly, a cross-sectional study conducted with 86 patients in Turkey diagnosed with major depressive disorder showed no association between depression and FokI polymorphism [11]. The results of a prospective population-based study conducted with 563 participants in The Netherlands showed that polymorphisms in the VDR gene such as BsmI (rs1544410) and TaqI (rs731236), but not FokI, influenced susceptibility to age-related changes in cognitive functioning and depressive symptoms [14]. A study conducted with 153 patients in Ukraine with different types of thyroid pathology did not reveal an association between the presence of this genetic alteration and anxiety [48]. So, it is important to evaluate the presence of polymorphisms in combination with other factors, such as serum vitamin D levels.

A noteworthy result of our study is the interaction observed between vitamin D deficiency and the FokI polymorphism for DS. While the isolated factors were not associated with symptoms, their combination was linked to a higher prevalence of DS. This finding highlights the complex and multifactorial nature of mental health disorders, which involve a combination of social, economic, environmental, and biological factors [49–51]. It's worth noting that the observed association was exclusively found in carriers of the altered allele (G), suggesting that individuals with wild-type homozygotes, whose receptor activity is not impaired and who are known to be more efficient in mediating the action of vitamin D [52], did not show an association between low levels of vitamin D and disorder symptoms. However, in the presence of the altered allele (and, as a result, lower binding of vitamin D to its receptor), deficiency was linked to a higher prevalence of DS. Therefore, these findings imply that individuals with the presence of the altered allele should consider having higher levels of vitamin D due to its potential impact on DS.

Given the high prevalence of mental health disorders and vitamin D deficiency, their potential association represents a significant public health concern. As such, public health and mental health care policies should incorporate nutritional strategies as part of preventive or treatment interventions, particularly for depression. Maintaining adequate serum levels of vitamin D should therefore be a key focus. This can be achieved through sun exposure; however, the current literature lacks specific recommendations, or through the use of vitamin D supplements, which is an economical strategy and without significant adverse effects [53].

This study had some limitations. Among them, the cross-sectional design does not allow us to assess the direction of causality. Residual confounding by unmeasured factors cannot be completely excluded. In addition, gene-gene and gene-environment interactions should be the focus of further scientific interest when studying associations like the one proposed in our study.

In terms of strengths, we highlight that, to our knowledge, this is the first population-based study to evaluate the association of vitamin D deficiency and FokI polymorphism on symptoms of mental disorders in adults during the COVID-19 pandemic. In addition, the probabilistic sample selection and the calculation of the sample weight provided statistical power to the study, as well as internal and external validity; genetic marker evaluation in a large sample size; use of DAG to avoid unnecessary adjustments.

In conclusion, while vitamin D deficiency and the FokI polymorphism were not individually associated with AS and DS, there appears to be a synergistic effect between these two factors in relation to DS. Individuals who have both vitamin D deficiency and at least one altered allele are more likely to have a higher prevalence of DS.

Declaration of Interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Grants and funding

This study was supported by the “Conselho Nacional de Desenvolvimento Científico e Tecnológico” (CNPq, Distrito Federal, Brazil), "Coordenação de Aperfeiçoamento de Pessoal de Nível Superior" (CAPES) [nº 88881.504995/2020-01], “Fundação de Amparo à Pesquisa do Estado de Minas Gerais" (FAPEMIG) [nº nº001/2021; APQ-02445-21], and finance code 001 for Ph.D. student scholarship.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors acknowledge the Federal University of Ouro Preto (UFOP) and the “Grupo de Pesquisa e Ensino em Nutrição e Saúde Coletiva” (GPENSC) for their support. And we are grateful for the collaboration of the Municipal Health Secretariats of the Ouro Preto and Mariana.

Author's contributions

Thaís S. Sabião - data collection, conception and study design; analysis and interpretation of data; writing the manuscript, critical review and final approval.

Luiz Antônio Alves de Menezes-Júnior - data collection, assistance in laboratory analysis, critical review and final approval.

Aline Priscila Batista - data collection, assistance in laboratory analysis, critical review and final approval.

Samara Silva de Moura - data collection, assistance in laboratory analysis, critical review and final approval.

Mariana Carvalho de Menezes- project conception, management of financial resources, critical review and final approval.

Adriana L. Meireles - conception and coordination of data collection, management of financial resources, critical review and final approval.

George L. L. Machado-Coelho - conception and coordination of data collection, management of financial, critical review, supervision and final approval.

Júlia C. C. Carraro - conception and study design, analysis and interpretation of data; critical review, supervision and final approval.

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Table 1 – Socioeconomic, lifestyle and health conditions in adults according to vitamin D status during the COVID-19 pandemic, COVID-Inconfidentes Study (2020).

		Vitamin D Status
Characteristics	Total	Deficiency (%)	Sufficiency (%)				PR			95% CI		p- value *

		30.9	69.1
Age (years)	mean (CI 95%)	mean (CI 95%)			mean (CI 95%)
	42.9 (41.62-44.26)	51.0 (48.12-53.95)	39.8 (38.36-41.14)				1.03				1.02; 1.04	<0.001
Sex	% (CI 95%)	% (CI 95%)	% (CI 95%)
Female	51.3 (43.76-58.71)	54.9 (47.48-62.06)	49.6 (39.78-59.54)				1 (Ref.)
Male	48.7 (41.29-56.24)	45.1 (37.94-52.52)	50.4 (40.46-60.22)				0.86				0.62; 1.20	0.386
Family income”
≤ 2 MW^a	38.6 (33.37-44.15)	35.7 (26.11-46.60)		40.0(34.03-46.19)		1 (Ref.)
>2 to ≤ 4 MW	33.4 (27.86-39.50)	38.8 (29.97-48.39)		31.0 (24.09-38.84)					1.25		0.82; 1.93	0.296
>4 MW	28.0 (22.55-34.07)	25.5 (18.87-33.52)		29.0 (22.77-36.28)					0.99		0.68; 1.43	0.946
Skin color
White	26.4 (20.97-32.71)	30.4 (21.66-40.90)	24.6 (18.60-31.84)				1 (Ref.)
Black/brown	73.6 (67.29-79.03)	69.6 (59.10-78.34)	75.4 (68.16-81.40)				0.82				0.57; 1.18	0.285
Education level (years of schooling)
No schooling	1.6 (0.68-3.81)	4.4 (1.68-10.99)	3.8 (0.16-0.94)				1 (Ref.)
≤9	26.4 (21.63-31.81)	34.0 (27.47-41.12)	23.0 (16.71-30.85)				0.47				0.34; 0.66	<0.001
>9	72.0 (66.57-76.80)	61.6 (54.04-68.70)	76.6 (68.8-82.9)					0.32			0.24; 0.42	<0.001
Work status
Not work/housework	45.8 (41.28-50.34)	54.4(46.53-62.05)	41.9 (36.38-47.69)				1 (Ref.)
Currently employed	54.2 (49.66-58.72)	45.6 (37.95-53.47)	58.1 (52.31-63.62)				0.71				0.54; 0.92	0.011
Work routine during the pandemic
No work from home	32.8 (27.81-38.27)	28.3 (19.80-38.61)	34.9 (29.77-40.33)				1 (Ref.)
No work	21.4 (17.12-26.41)	17.3 (12.45-23.68)	23.2 (23.21-29.47)				0.94				0.61; 1.44	0.782
Work from home	45.8 (41.28-50.34)	54.4 (46.51-62.02)	41.9 (36.38-47.69)				1.38				0.97; 1.95	0.069
Social restriction
No	14.02 (10.19-18.97)	15.97 (8.32-28.47)	13.1 (9.69-17-57)				1 (Ref.)
Yes	85.98 (81.03-89.81	84.03 (71.53-91.68)	86.9 (82.43-90.31)				0.86				0.51; 1.43		0.551
Alcohol consumption
No	41.0 (34.80-47.47)	51.8 (42.99-60.49)	36.1 (29.10-43.82)				1 (Ref.)
Yes	59.0 (52.53-65.20)	48.2 (39.51-57.01)	63.9 (56.18-70.90)				0.65				0.47; 0.89	0.008
Smoking
No	83.9 (78.89-87.83)	80.5 (69.17-88.35)	85.4 (80.02-89.47)				1 (Ref.)
Yes	16.1 (12.17-21.11)	19.5 (11.65-30.83)	14.6 (10.53-19.98)				1.26				0.79; 2.00	0.325
Physical activity^b
Active	36.1 (28.48-44.52)	31.1 (22.25-41.68)	38.3 (28.24-49.50)				1 (Ref.)
Inactive	63.9 (55.48-71.52)	68.9 (58.32-77.75)	61.7 (50.50-71.76)				1.25				0.77; 2.02	0.357
Sun exposure^c
Sufficient	41.4 (34.04-49.09)	38.2 (28.38-49.09)	42.8 (33.17-52.96)				1 (Ref.)
Insufficient	58.8 (50.91-65.96)	61.8 (50.91-71.62)	57.2 (47.04-66.83)				1.14				0.73; 1.77	0.554
Vitamin D supplementation
No	93.3 (91.23-94.89)	95.1 (92.68-96.85)	92.4 (89.49-94.61)				1 (Ref.)
Yes	6.7 (5.11-8.77)	4.9 (3.15-7.32)	7.6 (5.39-10.51)				0.70				0.45; 1.09	0.115
Chronic disease^d
No	42.3 (35.22-49.75)	21.4 (15.59-28.58)	51.7 (42.75-60.50)				1 (Ref.)
Yes	57.7 (50.25-64.78)	78.6 (71.42-84.41)	48.3 (39.50-57.25)				2.70				1.76; 4.12	<0.001
Chronic pain^e
No	65.8 (61.23-70.13)	63.1 (56.90-68.97)	67.0 (60.66-72.80)				1 (Ref.)
Yes	34.2 (29.87-38.77)	36.9 (31.03-43.10)	33.0 (27.20-39.34)				1.12				0.87; 1.46	0.373
Self-rated health^f
Very good/good	79.3 (75.12-83.00)	66.7 (60.26-72.6)	85.0 (80.04-88.88)				1 (Ref.)
Fair/poor/very poor	20.7 (17.00-24.88)	33.3 (27.40-39.74)	15.01 (11.12-19.96)				1.92				1.47; 2.49	<0.001
Sleep quality^g
Good	46.2 (41.93-50.57)	42.1 (33.38-51.32)	48.1 (43.35-52.83)				1 (Ref.)
Poor	53.8 (49.43-58.07)	57.9 (48.68-66.62)	51.9 (47.17-56.65)				1.18				0.88; 1.58	0.257
COVID-19 Test
Soronegative	95.0 (93.22-96.26)	94.7 (91.22-96.86)	95.1 (92.56-96.75)				1 (Ref.)
Soropositive	5.0 (3.74-6.78)	5.3 (3.14-8.78)	4.9 (3.25-7.44)				1.05				0.62; 1.76	0.851
Genotype frequency (FokI)^h
AA	9.9 (5.53-16.77)	6.7 (4.47-9.82)	11.2 (5.54-21.34)				1 (Ref.)
AG	44.7 (40.59-48.96)	45.7 (37.11-54.62)	44.3 (40.09-48.58)				1.50				0.76; 2.97	0.237
GG	45.4 (39.41-51.65)	47.6 (39.47-55.87)	44.5 (36.70-52.59)				1.54				0.73; 3.25	0.253
Abbreviations: PR: Prevalence Ratio (crude). ^a MW: minimum wage. "Family income: minimum wage value (2020): BRL 1045.00 ≈ USD 194.25 (1 USD = 5.3797 BRL). ^bPhysical activity - active: ≥150 min of moderate physical activity or≥75 min of vigorous physical activity (WHO - World Health Organization, 2010). ^cSun exposure: insufficient sun exposure <30 min/day.^d Chronic disease: medical diagnosis of at least one chronic disease. ^e chronic physical pain, considering physical pain present for 3 months or more (yes, no). ^fSelf-rated health: fair/poor/very poor health or very good, good. ^gSleep quality: scores of 0–4 = good sleep quality; scores≥ 5 = poor sleep quality. ^hGenotype frequency (FokI): AA- homozygous wild, AG- heterozygous and GG- homozygous mutant. *p-value from univariate Poisson regression. Bold values indicate statistical significance of 5%.

Table 2- Association between vitamin D deficiency and symptoms of anxiety and depression during the COVID-19 pandemic, and influence of polymorphism FokI (rs10735810) in the VDR gene in this association; COVID-Inconfidentes Study (2020).


	Symptoms of anxiety		p- value*	Symptoms of depression		p- value*
	PR	(95% CI)	p- value*	PR	(95% CI)

*Vitamin D*
Suficiency	1 (Ref)			1 (Ref)
Deficiency (Crude analysis)	0.97	(0.71 - 1.32)	0.842	1.47	(0.93 - 2.33)	0.101
Deficiency (Adjusted analysis)	1.02	(0.77 - 1.35)	0.882	1.31	(0.85 - 2.02)	0.225
*Polymorphism FokI*
AA	1 (Ref)			1 (Ref)
AG	0.98	(0.31 - 3.15)	0.980	0.76	(0.28 - 2.08)	0.588
GG	0.97	(0.38 - 2.48)	0.949	0.64	(0.24 - 1.74)	0.381
Adjustment^b
AA	1 (Ref)			1 (Ref)
AG	0.90	(0.33 - 2.43)	0.832	0.64	(0.30 - 1.35)	0.239
GG	0.89	(0.41 - 1.93)	0.770	0.54	(0.27 - 1.08)	0.080
*Crude interaction analysis*
Vitamin D sufficiency * AA	1 (Ref)			1 (Ref)
Vitamin D deficiency * AG	0.65	(0.12 - 3.49)	0.613	4.57	(1.01 - 20.73)	0.049
Vitamin D deficiency * GG	2.06	(0.52- 8.23)	0.301	5.39	(1.24 - 23.34)	0.025
*Adjusted Interaction analysis*ˠ
Vitamin D sufficiency * AA	1 (Ref)			1 (Ref)
Vitamin D deficiency * AG	0.65	(0.17 - 2.53)	0.531	2.84	(1.04 - 7.76)	0.042
Vitamin D deficiency * GG	2.32	(0.74- 7.33)	0.149	4.37	(1.62 - 11.83)	0.004

Abbreviations: PR: Prevalence ratio. The exposure variable was vitamin D deficiency (25(OH)D < 20 ng/mL in a healthy population or < 30 ng/mL for groups at risk). The outcome variables were symptoms of anxiety and symptoms of depression, evaluated by GAD-7 and PHQ-9, respectively. Polymorphisms were genotyped using Taqman probes in real time PCR, and were classified as homozygous wild (AA), heterozygous (AG), and homozygous mutant (GG). Directed acyclic graph (DAG) was used for the adjusted analysis in the association between vitamin D and symptoms of anxiety and depression. Adjusted for minimum and sufficient set of variables: sex, age, skin color, body mass index, physical activity, alcohol consumption, sun exposure, chronic disease, and social restriction. ˠAdjusted Interaction analysis: adjusted for minimum and sufficient set of variables. ^bAdjustment (exclusive for association between polymorphism and symptoms of anxiety and depression): sex and age. *p-value from Poisson regression. Bold values indicate statistical significance of 5%.

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Interaction between FokI polymorphism and vitamin D deficiency in the symptoms of mental disorders in adults: COVID-Inconfidentes, a population-based study in Brazil

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Exposure variable: Serum vitamin D levels

Interaction variable: Polymorphism FokI

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