BDNF val66met genotype is not associated with psychological distress: A cross-sectional study in Indonesian young adults

BDNF val66met genotype is not associated with psychological distress: A cross-sectional study in Indonesian young adults | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research article BDNF val66met genotype is not associated with psychological distress: A cross-sectional study in Indonesian young adults Henry Ng, Sofa Dewi Alfian, Rizky Abdulah, Melisa Intan Barliana This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-32173/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The number of mental disorders has been increasing but has yet to receive sufficient attention. Healthcare students and professionals tend to have high stress burden. Finding the root cause of psychological distress is important to formulate a method for early detection. The association of BDNF val66met polymorphism to neuropsychiatric disorders has been widely studied. The aim of this study was to interplay between BDNF val66met polymorphism and sociodemographic factors in the pathogenesis of psychological distress among Indonesian students. Methods Level of psychological distress and sociodemographic profiling was assessed using the Kessler Psychological Distress Scale (K10) and sociodemographic questionnaires, respectively. Genotyping was performed using polymerase chain reaction-amplified refractory mutation system. Pearson’s chi square and binomial logistic tests were used to evaluate the correlation. Results This study recruited 148 participants. The psychological distress levels of the participants were well (27.03%), mild (37.16%), moderate (25.00%), and severe (10.81%). Genotypic distributions were AA (25.67%), GA (50.68%), and GG (23.65%). No statistical significance was found in the study ( p > 0.05). Conclusion Psychological distress is not affected by genotypic and environmental factors. Further confirmatory research with larger and broader populations is required. Medical Genetics psychological distress K10 amplified refractory mutation system val66met rs6265 Figures Figure 1 Background Steel et al. reported a lifetime prevalence (nearly 30%) of mental disorders (substance use, anxiety, and mood) among adults in 59 countries [ 1 ]. The severity of mental disorders has prompted public awareness regarding the importance of mental health; in fact, mental health is highlighted in Sustainable Development Goals. The distinct long-term manifestations of mental disorders are depression and anxiety. Therefore, finding an approach to measure mental health condition predictively is crucial [ 2 ]. Psychological distress is a common indicator of mental health in epidemiological and clinical studies [ 3 ]. Self-administered or clinician-administered standardized scales, such as the general health questionnaires (GHQ-12,-20,-28,-30), the Kessler scales (K-6,-10), and the symptom checklists (SCL-5,-25; BSI-18), are regularly used to assess psychological distress [ 4 – 7 ]. The various tools and scales of measurement render the prevalence of psychological distress hard to determine, with an approximate estimation of around 5–27%. Factors affecting psychological distress are categorized as inborn and external. Typical inborn psychological distress factors include age, gender, ethnicity, and other sociodemographic factors. External factors, such as experiences, social behavior, income, and occupations, are widely varied among individuals [ 3 ]. In particular, work-related burden or occupational stress is associated with mental and medical disorders [ 8 ]. Psychological distress affects the neuronal plasticity on brain regions, such as the prefrontal cortex, the hippocampus, and the amygdala, thus altering cognitive processes, such as mood, emotion, learning, and memory [ 9 , 10 ]. Brain-derived neurotrophic factor (BDNF) is an abundant growth factor in the central nervous system is. It is highly influential in mental disorders because of its critical roles in neuronal development and plasticity [ 11 ]. Reduced mRNA and protein expression levels of hippocampal BDNF have been found in depressive animal and human postmortem studies [ 12 ]. Genetic polymorphisms of BDNF (G196A, Val66Met, dbSNP: rs6265) result in the substitution of valine (val) to methionine (met), which modifies the secretion of BDNF and consequently affects mental health [ 13 , 14 ]. Despite its importance, the interaction between BDNF val66met polymorphism and sociodemographic profile in psychological distress has yet to be studied in developing countries, such as Indonesia. In the present study, we aim to (1) determine the allele and genotype distribution, (2) analyze the association between BDNF val66met polymorphism and psychological distress, and (3) analyze the correlation between sociodemographic factors and psychological distress to evaluate the psychological distress gene environment interaction in an Indonesian student population. Methods Study design and ethical considerations This cross-sectional study was approved by the Board of Ethics, Universitas Padjadjaran (727/UN6.C2.1.2/KE PK/PN.2014) and conducted in accordance with the Declaration of Helsinki. All participants were informed about the study and signed informed consent prior to their participation into the study. Participants Recruitment was done by using public notice boards in Universitas Padjadjaran, Sumedang, Indonesia. Healthy young adults aged 18–35 years were eligible to participate in this study. Subjects with a history of mental disorders were excluded. Phenotype Subjects were asked to fill in the Kessler Psychological Distress Scale (K10) and sociodemographic questionnaires. The K10 questionnaire was translated, validated, and categorized into well ( 29) stress. The sociodemographic questionnaire comprised of questions regarding gender, GPA, housing, and sources of funding for living and tuition fee. Genotype DNA was extracted from blood samples using the Purelink Genomic DNA mini kit (Invitrogen®). The quality of DNA was checked using WPA Lightwave II (Biochrom®). Polymorphism genotyping was performed through polymerase chain reaction-amplified refractory mutation system (PCR-ARMS) analysis as described by Sheikh et al. [ 15 ]. This genotyping method utilized tetra-primer (Sigma Aldrich, Singapore) consisting of two forward and two reverse primers (Table 1 ). PCR was conducted using PCR Supermix from Invitrogen® comprising 22 mM Tris-HCl (pH 8.4), 55 mM KCl, 1.65 mM Magnesium Chloride, 220 µM dGTP, 220 µM dATP, 220 µM dTTP, 220 µM dCTP, 22 U/mL recombinant Taq DNA Polymerase, and dan stabilizers. Amplifications were performed using thermocycler (Biometra®) under the following conditions: pre-incubation at 94 ℃ for 5 min, followed by 40 cycles of denaturation at 94 ℃ for 45 s, annealing at 59.8 ℃ for 1 min, extension at 72 ℃ for 1 min, and a final extension at 72 ℃ for 5 min. The products were visualized using 2% agarose gel electrophoresis under 312 nm wavelength (Biometra®). The amplicons were 203 bp (A allele/Met), 253 bp (G allele/Val), and 401 bp (internal control). Table 1 Tetra primers in BDNF val66met polymorphism analysis Primers 5’ -> 3’ Sequence P1 (forward) CCTACAGTTCCACCAGGTGAGAAGAGTG P2 (reverse) TCATGGACATGTTTGCAGCATCTAGGTA P3 (forward - A allele specific) ATCATTGGCTGACACTTTCGAACCC A P4 (reverse - G allele specific) CTGGTC CTCATCCAACAGCTCTTCTATAA C Statistical analysis Psychological distress was divided into two categories, well and stress. The association between BDNF val66met genotype and psychological distress was analyzed using Pearson’s chi-square test, whereas the correlation between sociodemographic factors and psychological distress was evaluated using the generalized linear model with binomial logistic as the model. Deviation of allele frequencies was computed using Hardy–Weinberg equilibrium (HWE). All analyses were conducted using IBM-SPSS version 24.0 (IBM SPSS Statistics, USA, 2016). Statistical significance was set at p < 0.05. Results Variation of Kessler Psychological Distress Scale (K10) questionnaire result A total of 148 participants were recruited. The translated version of the K10 questionnaire was tested for its validity and reliability. Results indicated that the translated K10 questionnaire was valid (r > 0.338) and reliable (Cronbach’s alpha coefficient > 0.80). Forty participants (27.03%) were categorized as well, 55 participants (37.16%) as mild stress, 37 participants (25%) as moderate stress, and 16 participants (10.81%) as severe stress (Table 2 ). Genotyping of BDNF val66met and its correlation with the K10 questionnaire Tetra-primer ARMS genotyping generated three bands for the control amplicon (401 bp) and G and A allele-specific bands (253 and 201 bp, respectively) (Fig. 1 ). Homozygous samples showed only the control and the G or A allele-specific bands, whereas heterozygous samples showed all three bands. Thirty-eight participants (25.67%) were homozygous AA, 75 participants (50.68%) were heterozygous AG, and 35 participants (23.65%) were homozygous GG. The genotype frequencies were consistent with HWE as shown by p > 0.05 (Table 3 ). Table 2 Psychological distress and sociodemographic characteristics of participants Characteristics mean ± SEM Age 21 ± 0.046 n (%) Psychological distress level Well 40 (27.03) Mild 55 (37.16) Moderate 37 (25.00) Severe 16 (10.81) Gender Male 35 (23.6) Female 113 (76.4) Accommodation Boarding house 99 (66.9) Home with parents 44 (29.7) Both 5 (3.4) Source of living allowance Parents 114 (77.0) Scholarship 24 (16.2) Both 10 (6.8) Source of tuition fee Parents 130 (87.8) Scholarship 10 (6.8) Both 8 (5.4) GPA < 3.0 15 (10.1) 3 0 ≤ GPA < 3.5 106 (71.6) ≥ 3.5 27 (18.2) Table 3 Allele and genotype distribution of BDNF val66met polymorphism n (%) Allele A (met) 151 (51.01) G (val) 145 (48.99) Genotype AA (met/met) 38 (25.67) GA (val/met) 75 (50.68) GG (val/val) 35 (23.65) Hardy-Weinberg equilibrium fulfilled with p = 0.865 (inconsistent with HWE if p < 0.05) BDNF val66met genotype and environmental factor interaction in psychological distress No statistically significant association was found between BDNF val66met genotype and psychological distress. The correlation between sociodemographic factors was also not significant, except for the source of tuition fee in the female participants with p = 0.049 (Table 4 ). Table 4 Association between genotype, sociodemographic factors and psychological distress. p Genotype and psychological distress Pearson’s chi square test 0.076 Sociodemographic factors and psychological distress Male (n = 35) Female (n = 113) Accommodation 0.671 0.720 Source of living allowance 0.583 0.589 Source of tuition fee 1.000 0.049* GPA 0.794 0.098 Discussions The number of suicidal healthcare professionals, such as physicians, pharmacists, nurses, dentists, and veterinarians, is increasing [ 16 ]. Pharmacy ranked top three among other healthcare professional degree students in terms of psychological distress and depression as assessed by using GHQ-12 and Beck Depression Inventory-II [ 17 ]. The psychological distress level in our study supports pharmacy as one of the top stressful healthcare degrees and professions, with nearly 75% of the students found psychologically distressed. Current results also aligned with previous findings showing no significant correlation between psychological distress and sociodemographic factors, such as accommodation, GPA, source of living allowance, and tuition fee [ 18 ]. Our genotyping substantiated the variation of BDNF val66met genotype in different ethnicities, such as Asians and Caucasians [ 19 ]. Several neurodegenerative diseases studies also showed similar genotypic distribution of BDNF val66met polymorphism with Asian populations having higher heterogenous Val/Met genotype than homogenous genotypes [ 19 – 22 ]. Our finding suggests that BDNF val66met polymorphism and sociodemographic factors do not influence the pathogenesis of psychological distress. This insignificant correlation is possibly due to the limitations of our study. First, our study is limited by the number of participants (also imbalanced between gender) and the population of participants, which are primarily highly stress-burdened pharmacy students [ 16 , 17 ]. Second, the psychological distress questionnaire only focused on the short-term period (the last 4 weeks). Thus, it does not measure the psychological distress over time. Last, the students are subject to response bias, particularly the reluctance to express their true level of psychological distress due to negative image and public judgement toward mental disorders. This finding is supported by a study about depression in medical students where nearly 10% of the participants admitted giving false responses in the questionnaire due to the abovementioned reason [ 23 ]. Despite the non-associative findings, our study is the first gene-environment interaction (GxE) study in Indonesia that focused on psychological distress. GxE studies are useful in the development of personalized medicine in preventive (diagnostic) and therapeutic approaches [ 24 ]. Up till now, Indonesia is one of the developing countries that has yet to create its own genomic database. The BDNF val66met genotype profile we obtained contributes not only to the genomic database of the Indonesian population but also to that of the Asian ethnicity. According to Indonesia’s National Baseline Health Research report, in merely 5 years, the prevalence of emotional mental disorders increased nearly 4% from 6.0–9.8% among Indonesian citizens [ 25 , 26 ]. Our study also highlighted the importance of increasing public awareness and early screening of mental issues, specifically among healthcare professions. We laid a basis for further research in GxE and provided suggestions that need to be considered in conducting mental health research. Conclusions In conclusion, we found no association between BDNF val66met polymorphism, sociodemographic factors, and psychological distress among Indonesian students. Further research with a larger gender-balanced and broader population of participants must be conducted to ascertain these findings. A tool to measure long-term psychological distress and the environmental factors affecting it must also be devised. The clinical significance of BDNF val66met polymorphism has been widely studied for more than a decade in neurodegenerative and neuropsychiatric disorders. To establish rs6265 as a marker for mental health and neuro-disorders, studies should consider BDNF protein level, brain MRI and fMRI on brain structures in association with the val66met polymorphism [ 27 , 28 ]. Abbreviations BDNF Brain-derived neurotrophic factor K10 Kessler Psychological Distress Scale PCR-ARMS Polymerase chain reaction-amplified refractory mutation system HWE Hardy–Weinberg equilibrium GPA Grade point average GxE Gene-environment interaction Val Valine Met Methionine Declarations Availability Of Data And Materials All data generated or analyzed during this study are included in this published article. Ethics approval and consent to participate This cross-sectional study was approved by the Board of Ethics, Universitas Padjadjaran (727/UN6.C2.1.2/KE PK/PN.2014) and conducted in accordance with the Declaration of Helsinki. All participants were informed about the study and signed informed consent prior to their participation into the study. Consent for publication Not Applicable Competing Interests The authors declare that they have no competing interests. Funding This research received no specific grant from any funding. Contributions HN performed investigation and writing original draft. SDA performed statistical analysis, RA performed supervision of writing original draft, MIB designed the methodology, performed supervision and reviewed the writing original draft. All authors read and approved the final manuscript. Acknowledgements We would like to thank our team: Shintya N. Amalya, Anzari Muhammad, Indah A. Sagita, Casuarina Rusmawati, and Carissa P. Purabaya for great team collaboration. References Steel Z, Marnane C, Iranpour C, Chey T, Jackson JW, Patel V, et al. The global prevalence of common mental disorders: A systematic review and meta-analysis 1980–2013. Int J Epidemiol. 2014;43:476–93. doi: 10.1093/ije/dyu038 . Mirowsky J, Ross CE. Measurement for a human science. J Health Soc Behav. 2002;43:152–70. doi: 10.2307/3090194 . 10.5772/30872 Drapeau A, Marchand A, Beaulieu-Prevost D. Epidemiology of Psychological Distress. In: Mental Illnesses - Understanding, Prediction and Control. InTech; 2012. doi: 10.5772/30872 . Goldberg D, Williams P. A user’s guide to the general health questionnaire. London: GL Assessments. Windsor, UK: NFER-Nelson Publishing Company;; 1988. 10.1002/mpr.310 Kessler RC, Green JG, Gruber MJ, Sampson NA, Bromet E, Cuitan M, et al. Screening for serious mental illness in the general population with the K6 screening scale: Results from the WHO World Mental Health (WMH) survey initiative. Int J Methods Psychiatr Res. 2010;19 SUPPL. 1:4–22. doi: 10.1002/mpr.310 . Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SLT, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med. 2002;32:959–76. doi: 10.1017/S0033291702006074 . Derogatis LR. Brief Symptom Inventory (BSI)-18: Administration, scoring and procedures manual. Minneapolis: NCS Pearson; 2001. Quick JC, Henderson DF. Occupational Stress: Preventing Suffering, Enhancing Wellbeing. Int J Environ Res Public Health. 2016;13. doi: 10.3390/ijerph13050459 . Kim JJ, Diamond DM. The stressed hippocampus, synaptic plasticity and lost memories. Nat Rev Neurosci. 2002;3:453–62. Roozendaal B, McEwen BS, Chattarji S. Stress, memory and the amygdala. Nat Rev Neurosci. 2009;10:423–33. Autry AE, Monteggia LM. Brain-derived neurotrophic factor and neuropsychiatric disorders. Pharmacol Rev. 2012;64:238–58. doi: 10.1124/pr.111.005108 . Calabrese F, Molteni R, Racagni G, Riva MA. Neuronal plasticity: A link between stress and mood disorders. Psychoneuroendocrinology. 2009;34:208–16. doi: 10.1016/j.psyneuen.2009.05.014 . Egan MF, Kojima M, Callicott JH, Goldberg TE, Kolachana BS, Bertolino A, et al. The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell. 2003;112:257–69. Yu H, Wang DD, Wang Y, Liu T, Lee FS, Chen ZY. Variant brain-derived neurotrophic factor Val66met polymorphism alters vulnerability to stress and response to antidepressants. J Neurosci. 2012;32:4092–101. Sheikh HI, Hayden EP, Kryski KR, Smith HJ, Singh SM. Genotyping the BDNF rs6265 (val66met) polymorphism by one-step amplified refractory mutation system PCR. Psychiatr Genet. 2010;20:109–12. Hawton K, Agerbo E, Simkin S, Platt B, Mellanby RJ. Risk of suicide in medical and related occupational groups: A national study based on Danish case population-based registers. J Affect Disord. 2011;134:320–6. doi: 10.1016/j.jad.2011.05.044 . Lewis EG, Cardwell JM. A comparative study of mental health and wellbeing among UK students on professional degree programmes. J Furth High Educ. 2018;43:1226–38. doi: 10.1080/0309877X.2018.1471125 . Sinuraya RK, Utami EP, Nasrullah D, Abdulah R. Pengukuran Tingkat Stres Mahasiswa di Fakultas Farmasi dengan Metode Kessler. In: The 1st Indonesian Conference on Clinical Pharmacy. Indonesia: Universitas Padjadjaran; 2013. Pivac N, Byungsu Kim G, Nedić YH, Joo, Dragica Kozarić-Kovačić, Jin Pyo Hong, et al. Ethnic differences in brainderived neurotrophic factor Val66Met polymorphism in croatian and Korean healthy participants. Croat Med J. 2009;50:43–8. Fukumoto N, Fujii T, Combarros O, Ilyas Kamboh M, Tsai S-J, Matsushita S, et al. Sexually Dimorphic Effect of the Val66Met Polymorphism of BDNF on Susceptibility to Alzheimer’s Disease: New Data and Meta-Analysis in Wiley InterScience. Neuropsychiatric Genetics. 2009. doi: 10.1002/ajmg.b.30986 . Bian J-T, Zhang J-W, Zhang Z-X, Zhao H-L. Association analysis of brain-derived neurotrophic factor (BDNF) gene 196 A/G polymorphism with Alzheimer’s disease (AD) in mainland Chinese. Neurosci Lett. 2005;387:11–6. doi: 10.1016/J.NEULET.2005.07.009 . Matsushita S, Arai H, Matsui T, Yuzuriha T, Urakami K, Masaki T, et al. Brain-derived neurotrophic factor gene polymorphisms and Alzheimer?s disease. J Neural Transm. 2005;112:703–71. doi: 10.1007/s00702-004-0210-3 . Levine RE, Breitkopf CR, Sierles FS, Camp G. Complications associated with surveying medical student depression: The importance of anonymity. Acad Psychiatry. 2003;27:12–8. doi: 10.1176/appi.ap.27.1.12 . Dempfle A, Scherag A, Hein R, Beckmann L, Chang-Claude J, Schäfer H. Gene–environment interactions for complex traits: definitions, methodological requirements and challenges. Eur J Hum Genet. 2008;16:1164–72. doi: 10.1038/ejhg.2008.106 . Ministry of Health NI of HR and D. Riset Kesehatan Dasar. 2013 (National Baseline Health Research 2013). Jakarta: Badan Litbang Kesehatan; 2013. . Accessed 16 Nov 2019. Ministry of Health NI of HR and D. Laporan National Riset Kesehatan Dasar 2018 (National Report on Baseline Health Research 2018). Jakarta: Badan Litbang Kesehatan; 2018. http://labmandat.litbang.depkes.go.id/images/download/laporan/RKD/2018/Laporan_Nasional_RKD2018_FINAL.pdf . Accessed 16 Nov 2019. Shen T, You Y, Joseph C, Mirzaei M, Klistorner A, Graham SL, et al. BDNF polymorphism: A review of its diagnostic and clinical relevance in neurodegenerative disorders. Aging Dis. 2018;9:523–36. Tsai SJ. Critical issues in BDNF Val66met genetic studies of neuropsychiatric disorders. Front Mol Neurosci. 2018;11 May:1–15. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-32173","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":657886,"identity":"23385c8b-6a9d-4ea4-a78b-dc356d50576b","order_by":0,"name":"Henry Ng","email":"","orcid":"","institution":"Departement of of Biological Pharmacy, Biotechnology Laboratory, Faculty of Pharmacy, Universitas Padjadjaran","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Henry","middleName":"","lastName":"Ng","suffix":""},{"id":657887,"identity":"e6a2f1bd-3556-4b52-89aa-1e9b3c6a44a6","order_by":1,"name":"Sofa Dewi Alfian","email":"","orcid":"","institution":"Departement of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sofa","middleName":"Dewi","lastName":"Alfian","suffix":""},{"id":657888,"identity":"bf7f59c9-3d50-498e-851b-af2559183a1e","order_by":2,"name":"Rizky Abdulah","email":"","orcid":"","institution":"Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rizky","middleName":"","lastName":"Abdulah","suffix":""},{"id":657889,"identity":"77f9e13f-9a97-4062-85ec-eecbca792603","order_by":3,"name":"Melisa Intan Barliana","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0003-0015-9604","institution":"Faculty of Pharmacy, Universitas Padjadjaran","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Melisa","middleName":"Intan","lastName":"Barliana","suffix":""}],"badges":[],"createdAt":"2020-05-28 05:45:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-32173/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-32173/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":1311985,"identity":"5e685c88-fc0c-4a99-ab95-4f14e11578f9","added_by":"auto","created_at":"2020-06-11 23:36:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":92872,"visible":true,"origin":"","legend":"UV visualization of BDNF val66met polymorphism. The PCR-ARMS method resulted in three band namely the control (401 bp), G and A allele specific amplicons (253 and 201 bp).","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-32173/v1/fig1.png"},{"id":13540429,"identity":"1559e5bd-6ed3-41d2-8bcd-09b2d5cb16ca","added_by":"auto","created_at":"2021-09-17 01:47:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":434912,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-32173/v1/b4c4e2ad-c0b4-49e2-9edc-3bb6ea3deedb.pdf"}],"financialInterests":"","formattedTitle":"BDNF val66met genotype is not associated with psychological distress: A cross-sectional study in Indonesian young adults","fulltext":[{"header":"Background","content":" \u003cp\u003eSteel et al. reported a lifetime prevalence (nearly 30%) of mental disorders (substance use, anxiety, and mood) among adults in 59 countries [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The severity of mental disorders has prompted public awareness regarding the importance of mental health; in fact, mental health is highlighted in Sustainable Development Goals. The distinct long-term manifestations of mental disorders are depression and anxiety. Therefore, finding an approach to measure mental health condition predictively is crucial [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Psychological distress is a common indicator of mental health in epidemiological and clinical studies [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Self-administered or clinician-administered standardized scales, such as the general health questionnaires (GHQ-12,-20,-28,-30), the Kessler scales (K-6,-10), and the symptom checklists (SCL-5,-25; BSI-18), are regularly used to assess psychological distress [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The various tools and scales of measurement render the prevalence of psychological distress hard to determine, with an approximate estimation of around 5\u0026ndash;27%. Factors affecting psychological distress are categorized as inborn and external. Typical inborn psychological distress factors include age, gender, ethnicity, and other sociodemographic factors. External factors, such as experiences, social behavior, income, and occupations, are widely varied among individuals [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In particular, work-related burden or occupational stress is associated with mental and medical disorders [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePsychological distress affects the neuronal plasticity on brain regions, such as the prefrontal cortex, the hippocampus, and the amygdala, thus altering cognitive processes, such as mood, emotion, learning, and memory [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Brain-derived neurotrophic factor (BDNF) is an abundant growth factor in the central nervous system is. It is highly influential in mental disorders because of its critical roles in neuronal development and plasticity [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Reduced mRNA and protein expression levels of hippocampal BDNF have been found in depressive animal and human postmortem studies [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Genetic polymorphisms of BDNF (G196A, Val66Met, dbSNP: rs6265) result in the substitution of valine (val) to methionine (met), which modifies the secretion of BDNF and consequently affects mental health [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Despite its importance, the interaction between BDNF val66met polymorphism and sociodemographic profile in psychological distress has yet to be studied in developing countries, such as Indonesia. In the present study, we aim to (1) determine the allele and genotype distribution, (2) analyze the association between BDNF val66met polymorphism and psychological distress, and (3) analyze the correlation between sociodemographic factors and psychological distress to evaluate the psychological distress gene environment interaction in an Indonesian student population.\u003c/p\u003e "},{"header":"Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and ethical considerations\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was approved by the Board of Ethics, Universitas Padjadjaran (727/UN6.C2.1.2/KE PK/PN.2014) and conducted in accordance with the Declaration of Helsinki. All participants were informed about the study and signed informed consent prior to their participation into the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eRecruitment was done by using public notice boards in Universitas Padjadjaran, Sumedang, Indonesia. Healthy young adults aged 18\u0026ndash;35\u0026nbsp;years were eligible to participate in this study. Subjects with a history of mental disorders were excluded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePhenotype\u003c/h2\u003e \u003cp\u003eSubjects were asked to fill in the Kessler Psychological Distress Scale (K10) and sociodemographic questionnaires. The K10 questionnaire was translated, validated, and categorized into well (\u0026lt;\u0026thinsp;20), mild (20\u0026ndash;24), moderate (25\u0026ndash;29), and severe (\u0026gt;\u0026thinsp;29) stress. The sociodemographic questionnaire comprised of questions regarding gender, GPA, housing, and sources of funding for living and tuition fee.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eGenotype\u003c/h2\u003e \u003cp\u003eDNA was extracted from blood samples using the Purelink Genomic DNA mini kit (Invitrogen\u0026reg;). The quality of DNA was checked using WPA Lightwave II (Biochrom\u0026reg;). Polymorphism genotyping was performed through polymerase chain reaction-amplified refractory mutation system (PCR-ARMS) analysis as described by Sheikh et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This genotyping method utilized tetra-primer (Sigma Aldrich, Singapore) consisting of two forward and two reverse primers (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). PCR was conducted using PCR Supermix from Invitrogen\u0026reg; comprising 22\u0026nbsp;mM Tris-HCl (pH 8.4), 55\u0026nbsp;mM KCl, 1.65\u0026nbsp;mM Magnesium Chloride, 220\u0026nbsp;\u0026micro;M dGTP, 220\u0026nbsp;\u0026micro;M dATP, 220\u0026nbsp;\u0026micro;M dTTP, 220\u0026nbsp;\u0026micro;M dCTP, 22 U/mL recombinant Taq DNA Polymerase, and dan stabilizers. Amplifications were performed using thermocycler (Biometra\u0026reg;) under the following conditions: pre-incubation at 94 ℃ for 5\u0026nbsp;min, followed by 40 cycles of denaturation at 94 ℃ for 45\u0026nbsp;s, annealing at 59.8 ℃ for 1\u0026nbsp;min, extension at 72 ℃ for 1\u0026nbsp;min, and a final extension at 72 ℃ for 5\u0026nbsp;min. The products were visualized using 2% agarose gel electrophoresis under 312\u0026nbsp;nm wavelength (Biometra\u0026reg;). The amplicons were 203\u0026nbsp;bp (A allele/Met), 253\u0026nbsp;bp (G allele/Val), and 401\u0026nbsp;bp (internal control).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTetra primers in BDNF val66met polymorphism analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026rsquo; -\u0026gt; 3\u0026rsquo; Sequence\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1 (forward)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCTACAGTTCCACCAGGTGAGAAGAGTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2 (reverse)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCATGGACATGTTTGCAGCATCTAGGTA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP3 (forward - A allele specific)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCATTGGCTGACACTTTCGAACCC\u003cb\u003eA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP4 (reverse - G allele specific)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTGGTC CTCATCCAACAGCTCTTCTATAA\u003cb\u003eC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003ePsychological distress was divided into two categories, well and stress. The association between BDNF val66met genotype and psychological distress was analyzed using Pearson\u0026rsquo;s chi-square test, whereas the correlation between sociodemographic factors and psychological distress was evaluated using the generalized linear model with binomial logistic as the model. Deviation of allele frequencies was computed using Hardy\u0026ndash;Weinberg equilibrium (HWE). All analyses were conducted using IBM-SPSS version 24.0 (IBM SPSS Statistics, USA, 2016). Statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eVariation of Kessler Psychological Distress Scale (K10) questionnaire result\u003c/h2\u003e \u003cp\u003eA total of 148 participants were recruited. The translated version of the K10 questionnaire was tested for its validity and reliability. Results indicated that the translated K10 questionnaire was valid (r\u0026thinsp;\u0026gt;\u0026thinsp;0.338) and reliable (Cronbach\u0026rsquo;s alpha coefficient\u0026thinsp;\u0026gt;\u0026thinsp;0.80). Forty participants (27.03%) were categorized as well, 55 participants (37.16%) as mild stress, 37 participants (25%) as moderate stress, and 16 participants (10.81%) as severe stress (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eGenotyping of BDNF val66met and its correlation with the K10 questionnaire\u003c/h2\u003e \u003cp\u003eTetra-primer ARMS genotyping generated three bands for the control amplicon (401\u0026nbsp;bp) and G and A allele-specific bands (253 and 201\u0026nbsp;bp, respectively) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Homozygous samples showed only the control and the G or A allele-specific bands, whereas heterozygous samples showed all three bands. Thirty-eight participants (25.67%) were homozygous AA, 75 participants (50.68%) were heterozygous AG, and 35 participants (23.65%) were homozygous GG. The genotype frequencies were consistent with HWE as shown by \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePsychological distress and sociodemographic characteristics of participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychological distress level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (27.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (37.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (25.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (10.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (23.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113 (76.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccommodation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoarding house\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99 (66.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHome with parents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (29.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of living allowance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114 (77.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScholarship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (16.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (6.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of tuition fee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130 (87.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScholarship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (6.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (5.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (10.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 0\u0026thinsp;\u0026le;\u0026thinsp;GPA\u0026thinsp;\u0026lt;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (71.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (18.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAllele and genotype distribution of BDNF val66met polymorphism\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAllele\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA (met)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e151 (51.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG (val)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145 (48.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGenotype\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAA (met/met)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (25.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGA (val/met)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (50.68)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG (val/val)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (23.65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHardy-Weinberg equilibrium fulfilled with \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.865 (inconsistent with HWE if \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBDNF val66met genotype and environmental factor interaction in psychological distress\u003c/h2\u003e \u003cp\u003eNo statistically significant association was found between BDNF val66met genotype and psychological distress. The correlation between sociodemographic factors was also not significant, except for the source of tuition fee in the female participants with \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between genotype, sociodemographic factors and psychological distress.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGenotype and psychological distress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePearson\u0026rsquo;s chi square test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSociodemographic factors and psychological distress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale (n\u0026thinsp;=\u0026thinsp;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale (n\u0026thinsp;=\u0026thinsp;113)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccommodation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.720\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of living allowance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of tuition fee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.049*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e "},{"header":"Discussions","content":" \u003cp\u003eThe number of suicidal healthcare professionals, such as physicians, pharmacists, nurses, dentists, and veterinarians, is increasing [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Pharmacy ranked top three among other healthcare professional degree students in terms of psychological distress and depression as assessed by using GHQ-12 and Beck Depression Inventory-II [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The psychological distress level in our study supports pharmacy as one of the top stressful healthcare degrees and professions, with nearly 75% of the students found psychologically distressed. Current results also aligned with previous findings showing no significant correlation between psychological distress and sociodemographic factors, such as accommodation, GPA, source of living allowance, and tuition fee [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur genotyping substantiated the variation of BDNF val66met genotype in different ethnicities, such as Asians and Caucasians [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Several neurodegenerative diseases studies also showed similar genotypic distribution of BDNF val66met polymorphism with Asian populations having higher heterogenous Val/Met genotype than homogenous genotypes [\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Our finding suggests that BDNF val66met polymorphism and sociodemographic factors do not influence the pathogenesis of psychological distress.\u003c/p\u003e \u003cp\u003eThis insignificant correlation is possibly due to the limitations of our study. First, our study is limited by the number of participants (also imbalanced between gender) and the population of participants, which are primarily highly stress-burdened pharmacy students [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Second, the psychological distress questionnaire only focused on the short-term period (the last 4 weeks). Thus, it does not measure the psychological distress over time. Last, the students are subject to response bias, particularly the reluctance to express their true level of psychological distress due to negative image and public judgement toward mental disorders. This finding is supported by a study about depression in medical students where nearly 10% of the participants admitted giving false responses in the questionnaire due to the abovementioned reason [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the non-associative findings, our study is the first gene-environment interaction (GxE) study in Indonesia that focused on psychological distress. GxE studies are useful in the development of personalized medicine in preventive (diagnostic) and therapeutic approaches [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Up till now, Indonesia is one of the developing countries that has yet to create its own genomic database. The BDNF val66met genotype profile we obtained contributes not only to the genomic database of the Indonesian population but also to that of the Asian ethnicity. According to Indonesia\u0026rsquo;s National Baseline Health Research report, in merely 5 years, the prevalence of emotional mental disorders increased nearly 4% from 6.0\u0026ndash;9.8% among Indonesian citizens [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Our study also highlighted the importance of increasing public awareness and early screening of mental issues, specifically among healthcare professions. We laid a basis for further research in GxE and provided suggestions that need to be considered in conducting mental health research.\u003c/p\u003e "},{"header":"Conclusions","content":" \u003cp\u003eIn conclusion, we found no association between BDNF val66met polymorphism, sociodemographic factors, and psychological distress among Indonesian students. Further research with a larger gender-balanced and broader population of participants must be conducted to ascertain these findings. A tool to measure long-term psychological distress and the environmental factors affecting it must also be devised. The clinical significance of BDNF val66met polymorphism has been widely studied for more than a decade in neurodegenerative and neuropsychiatric disorders. To establish rs6265 as a marker for mental health and neuro-disorders, studies should consider BDNF protein level, brain MRI and fMRI on brain structures in association with the val66met polymorphism [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e "},{"header":"Abbreviations","content":" \u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBDNF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBrain-derived neurotrophic factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eK10\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKessler Psychological Distress Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCR-ARMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePolymerase chain reaction-amplified refractory mutation system\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHWE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHardy\u0026ndash;Weinberg equilibrium\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGPA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGrade point average\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGxE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGene-environment interaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVal\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eValine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMet\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMethionine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003ch2\u003eAvailability Of Data And Materials\u003c/h2\u003e \n \u003cp\u003eAll data generated or analyzed during this study are included in this published article.\u003c/p\u003e \n\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was approved by the Board of Ethics, Universitas Padjadjaran (727/UN6.C2.1.2/KE PK/PN.2014) and conducted in accordance with the Declaration of Helsinki. All participants were informed about the study and signed informed consent prior to their participation into the study.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot Applicable\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting Interests\u003c/strong\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e \u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no specific grant from any funding.\u003c/p\u003e \u003ch2\u003eContributions\u003c/h2\u003e \u003cp\u003eHN performed investigation and writing original draft. SDA performed statistical analysis, RA performed supervision of writing original draft, MIB designed the methodology, performed supervision and reviewed the writing original draft. All authors read and approved the final manuscript.\u003c/p\u003e \u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe would like to thank our team: Shintya N. Amalya, Anzari Muhammad, Indah A. Sagita, Casuarina Rusmawati, and Carissa P. Purabaya for great team collaboration.\u003c/p\u003e "},{"header":"References","content":"\u003col\u003e\u003cli\u003e \u003cspan\u003eSteel Z, Marnane C, Iranpour C, Chey T, Jackson JW, Patel V, et al. The global prevalence of common mental disorders: A systematic review and meta-analysis 1980\u0026ndash;2013. Int J Epidemiol. 2014;43:476\u0026ndash;93. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ije/dyu038\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eMirowsky J, Ross CE. Measurement for a human science. J Health Soc Behav. 2002;43:152\u0026ndash;70. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2307/3090194\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cdiv class=\"BibBookDOI\"\u003e10.5772/30872\u003c/div\u003e \u003cspan\u003eDrapeau A, Marchand A, Beaulieu-Prevost D. Epidemiology of Psychological Distress. In: Mental Illnesses - Understanding, Prediction and Control. InTech; 2012. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5772/30872\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eGoldberg D, Williams P. A user\u0026rsquo;s guide to the general health questionnaire. London: GL Assessments. Windsor, UK: NFER-Nelson Publishing Company;; 1988.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cdiv class=\"BibBookDOI\"\u003e10.1002/mpr.310\u003c/div\u003e \u003cspan\u003eKessler RC, Green JG, Gruber MJ, Sampson NA, Bromet E, Cuitan M, et al. Screening for serious mental illness in the general population with the K6 screening scale: Results from the WHO World Mental Health (WMH) survey initiative. Int J Methods Psychiatr Res. 2010;19 SUPPL. 1:4\u0026ndash;22. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/mpr.310\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eKessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SLT, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med. 2002;32:959\u0026ndash;76. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0033291702006074\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eDerogatis LR. Brief Symptom Inventory (BSI)-18: Administration, scoring and procedures manual. Minneapolis: NCS Pearson; 2001.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eQuick JC, Henderson DF. Occupational Stress: Preventing Suffering, Enhancing Wellbeing. Int J Environ Res Public Health. 2016;13. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph13050459\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eKim JJ, Diamond DM. The stressed hippocampus, synaptic plasticity and lost memories. Nat Rev Neurosci. 2002;3:453\u0026ndash;62.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eRoozendaal B, McEwen BS, Chattarji S. Stress, memory and the amygdala. Nat Rev Neurosci. 2009;10:423\u0026ndash;33.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAutry AE, Monteggia LM. Brain-derived neurotrophic factor and neuropsychiatric disorders. Pharmacol Rev. 2012;64:238\u0026ndash;58. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1124/pr.111.005108\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eCalabrese F, Molteni R, Racagni G, Riva MA. Neuronal plasticity: A link between stress and mood disorders. Psychoneuroendocrinology. 2009;34:208\u0026ndash;16. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.psyneuen.2009.05.014\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eEgan MF, Kojima M, Callicott JH, Goldberg TE, Kolachana BS, Bertolino A, et al. The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell. 2003;112:257\u0026ndash;69.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eYu H, Wang DD, Wang Y, Liu T, Lee FS, Chen ZY. Variant brain-derived neurotrophic factor Val66met polymorphism alters vulnerability to stress and response to antidepressants. J Neurosci. 2012;32:4092\u0026ndash;101.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eSheikh HI, Hayden EP, Kryski KR, Smith HJ, Singh SM. Genotyping the BDNF rs6265 (val66met) polymorphism by one-step amplified refractory mutation system PCR. Psychiatr Genet. 2010;20:109\u0026ndash;12.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eHawton K, Agerbo E, Simkin S, Platt B, Mellanby RJ. Risk of suicide in medical and related occupational groups: A national study based on Danish case population-based registers. J Affect Disord. 2011;134:320\u0026ndash;6. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2011.05.044\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLewis EG, Cardwell JM. A comparative study of mental health and wellbeing among UK students on professional degree programmes. J Furth High Educ. 2018;43:1226\u0026ndash;38. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/0309877X.2018.1471125\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eSinuraya RK, Utami EP, Nasrullah D, Abdulah R. Pengukuran Tingkat Stres Mahasiswa di Fakultas Farmasi dengan Metode Kessler. In: The 1st Indonesian Conference on Clinical Pharmacy. Indonesia: Universitas Padjadjaran; 2013.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003ePivac N, Byungsu Kim G, Nedić YH, Joo, Dragica Kozarić-Kovačić, Jin Pyo Hong, et al. Ethnic differences in brainderived neurotrophic factor Val66Met polymorphism in croatian and Korean healthy participants. Croat Med J. 2009;50:43\u0026ndash;8.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eFukumoto N, Fujii T, Combarros O, Ilyas Kamboh M, Tsai S-J, Matsushita S, et al. Sexually Dimorphic Effect of the Val66Met Polymorphism of BDNF on Susceptibility to Alzheimer\u0026rsquo;s Disease: New Data and Meta-Analysis in Wiley InterScience. Neuropsychiatric Genetics. 2009. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/ajmg.b.30986\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eBian J-T, Zhang J-W, Zhang Z-X, Zhao H-L. Association analysis of brain-derived neurotrophic factor (BDNF) gene 196 A/G polymorphism with Alzheimer\u0026rsquo;s disease (AD) in mainland Chinese. Neurosci Lett. 2005;387:11\u0026ndash;6. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/J.NEULET.2005.07.009\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eMatsushita S, Arai H, Matsui T, Yuzuriha T, Urakami K, Masaki T, et al. Brain-derived neurotrophic factor gene polymorphisms and Alzheimer?s disease. J Neural Transm. 2005;112:703\u0026ndash;71. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00702-004-0210-3\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLevine RE, Breitkopf CR, Sierles FS, Camp G. Complications associated with surveying medical student depression: The importance of anonymity. Acad Psychiatry. 2003;27:12\u0026ndash;8. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1176/appi.ap.27.1.12\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eDempfle A, Scherag A, Hein R, Beckmann L, Chang-Claude J, Sch\u0026auml;fer H. Gene\u0026ndash;environment interactions for complex traits: definitions, methodological requirements and challenges. Eur J Hum Genet. 2008;16:1164\u0026ndash;72. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/ejhg.2008.106\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eMinistry of Health NI of HR and D. Riset Kesehatan Dasar. 2013 (National Baseline Health Research 2013). Jakarta: Badan Litbang Kesehatan; 2013. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 16 Nov 2019.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eMinistry of Health NI of HR and D. Laporan National Riset Kesehatan Dasar 2018 (National Report on Baseline Health Research 2018). Jakarta: Badan Litbang Kesehatan; 2018. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://labmandat.litbang.depkes.go.id/images/download/laporan/RKD/2018/Laporan_Nasional_RKD2018_FINAL.pdf\u003c/span\u003e\u003c/span\u003e. Accessed 16 Nov 2019.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eShen T, You Y, Joseph C, Mirzaei M, Klistorner A, Graham SL, et al. BDNF polymorphism: A review of its diagnostic and clinical relevance in neurodegenerative disorders. Aging Dis. 2018;9:523\u0026ndash;36.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eTsai SJ. Critical issues in BDNF Val66met genetic studies of neuropsychiatric disorders. Front Mol Neurosci. 2018;11 May:1\u0026ndash;15.\u003c/span\u003e \u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"psychological distress, K10, amplified refractory mutation system, val66met, rs6265","lastPublishedDoi":"10.21203/rs.3.rs-32173/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-32173/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe number of mental disorders has been increasing but has yet to receive sufficient attention. Healthcare students and professionals tend to have high stress burden. Finding the root cause of psychological distress is important to formulate a method for early detection. The association of BDNF val66met polymorphism to neuropsychiatric disorders has been widely studied. The aim of this study was to interplay between BDNF val66met polymorphism and sociodemographic factors in the pathogenesis of psychological distress among Indonesian students.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eLevel of psychological distress and sociodemographic profiling was assessed using the Kessler Psychological Distress Scale (K10) and sociodemographic questionnaires, respectively. Genotyping was performed using polymerase chain reaction-amplified refractory mutation system. Pearson\u0026rsquo;s chi square and binomial logistic tests were used to evaluate the correlation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThis study recruited 148 participants. The psychological distress levels of the participants were well (27.03%), mild (37.16%), moderate (25.00%), and severe (10.81%). Genotypic distributions were AA (25.67%), GA (50.68%), and GG (23.65%). No statistical significance was found in the study (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePsychological distress is not affected by genotypic and environmental factors. Further confirmatory research with larger and broader populations is required.\u003c/p\u003e","manuscriptTitle":"BDNF val66met genotype is not associated with psychological distress: A cross-sectional study in Indonesian young adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-06-11 23:36:54","doi":"10.21203/rs.3.rs-32173/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"35b2c4f8-1c0d-4436-b9e6-fbbd122e6b61","owner":[],"postedDate":"June 11th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":118478,"name":"Medical Genetics"}],"tags":[],"updatedAt":"2020-08-12T11:44:22+00:00","versionOfRecord":[],"versionCreatedAt":"2020-06-11 23:36:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-32173","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-32173","identity":"rs-32173","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}