Study Population and DNA Extraction
A case-control study included 205 patients with chronic insomnia and 154 age-matched healthy volunteers from the Department of Neurology at the Second Affiliated Hospital, University of South China (Hengyang, China) between Jul 2016 and Dec 2018. All subjects were unrelated Han Chinese from Hunan province. The diagnosis of chronic insomnia is based on the patient's subjective complaints about poor sleep quality, difficulty starting or maintaining sleep, or early to wake, along with reports of severe distress or daytime consequences, and duration of at least 3 or more nights per week for three months or longer, according to the diagnostic criteria from the International Classification of Sleep Disorder, 3rd (ICSD-3) (American Academy of Sleep Medicine 2014). It is well-established that chronic insomnia disorder in ICSD-3 can be combined with many other medical conditions, such as the dependence of these comorbidities on pain, mental disorders, life events, and pregnancy (Bollu and Kaur 2019; Fernandez-Mendoza and Vgontzas 2013; Nacar and Taşhan 2019). As these conditions were not appropriate for insomnia genetic studies. Therefore, subjects with these conditions should exclude from the study. Specifically, the exclusion criteria are: 1) patients with a standard total Self-rating Depression Scale (SDS) score of >62 points, or a standard total Self-rating Anxiety Scale (SAS) score of >59 points; 2) subjects with pregnancy, chronic pain, malignant tumor, dementia, stroke, moderate to severe obstructive sleep apnea hypopnea syndrome, chronic obstructive pulmonary disease, congestive heart failure, asthma, cirrhosis, renal impairment, and moderate to severe mental disorders; 3) subjects with a history of major emotional trauma six months before sampling, or a history of taking corticosteroids or psychotropic drugs.
All patients, whose chief complaint was poor sleeping quality, received the final diagnosis by the patient's clinical manifestations, clinical history, Pittsburgh Sleep Quality Index (PSQI), SAS, SDS and Polysomnography (PSG) results. The scoring used for PSQI, SDS, and SAS was conducted according to reference (Zung 1965; Zung 1971; Tsai et al. 2005). As described in the study (Tsai et al. 2005), a total PSQI score >7 points indicates sleep disturbance, and the higher scores indicate more serious the condition.
The study protocol was approved by the Human Ethics Committees Review Board at the University of South China (no. 201602001), and signed informed consent was obtained from all participants. Data from all participants were systematically collected, including gender, age, body weight index (BMI), glycated hemoglobin (HbA1c), and blood pressure. History of insomnia were collected from the patients.
Venous blood samples were collected from all participants. Every genomic DNA was extracted from the blood samples using TIANamp Genomic DNA Kit (TIANGEN BIOTECH, Beijing, China). The DNA concentration was determined with the NanoDrop 2000 (Thermo Fisher Scientific, MA, USA), and this was followed by dilution to a final concentration of 500ng/uL. Diluted extracts and extracted serum samples were stored at -20°C until further analysis.
Candidate SNPs Selection and Primer Designing
Candidate SNPs in the CACNA1C were selected from several large genome-wide association studies (GWAS) (Byrne et al. 2013; Parsons et al. 2013) and the NCBI database (http://www.ncbi.nlm.nih.gov/projects/SNP/), and each SNP must have a minimum allele frequency (MAF) of greater than 0.05 in the Chinese Han population. A total of 25 tagSNPs were initially selected, such as rs2051990, rs7301906, rs7304986, rs7316184, rs16929275, rs16929276 and rs16929278 in intron 3; rs2302729 in intron 9; rs215976, rs216008, rs1051375 and rs1544514 in exon; rs2041135, rs2470433, rs4765975, rs7302540, rs7316246, rs7957163, rs10466907, rs10713809, rs11062319, rs11353034, rs11429670, rs12809807 and rs35440646 located in 3'UTR. Because the regions of homologous or near-homologous sequence in the genome can compete with the target sequence of the genetic locus for primer hybridization that leads to PCR failure, rs16929278 in intron 3, and rs10713809, rs11429670 and rs35440646 in 3'UTR were not tested. Finally, twenty-one SNPs were chosen as candidates for the following experiments. Primers for detection potential polymorphisms were designed with MassARRAY Assay Designer v3.1 (Sequenom, CA, USA). Pairs of PCR primers and single base extension (SBE) primers were provided for each SNP, and listed in Tables 1 and 2.
Genotyping of each SNP locus was performed using a Sequenom MassARRAY system using matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) (Sequenom, CA, USA) at BGI (Beijing, China). All experimental operations were carried out in accordance with the manufacturers’ instructions. Each total 5µL PCR reaction contained 0.625µL 1.25×PCR Buffer, 1.000 µL (500nM each) PCR primer mix (synthesized by Thermo Fisher Scientific, MA, USA), 0.325µL 25mM MgCl2 , 0.1 µL 25 mM dNTP mix, 0.1000 µL HotStar Taq (5U/µL), and 1 µL of DNA sample (20ng), and 1.850 µL HPLC water. Primary PCR was performed on the GeneAMP PCR system 9700 (Thermo Fisher Scientific, MA, USA) with the following conditions: at 94°C for 5 min, 45 cycles of 94°C for 20 s, 56°C for 30 s, and 72°C for 60 s, and a final extension at 72°C for 3 min. Then, non-incorporated dNTPs in the PCR products were dephosphorylated by adding a cocktail of 1.53 µL HPLC water, 0.17 µL Shrimp Alkaline Phosphatase (SAP) Buffer and 0.3µL SAP enzyme (1U/µL) (Sequenom, CA, USA) incubated on the GeneAMP PCR system 9700 at 37°C for 20 min, and then followed by 85°C for 5 min. SBE reaction contained 7 µL of SAP-treated PCR products and 2µL iPLEX mix (Sequenom, CA, USA). The iPLEX mix contained 0.2000µL iPLEX buffer, 0.2000µL iPLEX Termination mix, 0.940µL extend primer mix(0.625µM:1.25µM), 0.041µL iPLEX enzyme and 0.619µL HPLC water. The SBE reaction was performed with the following conditions: 94 °C for 30 s, followed by 40 cycles of one step at 94°C for 5 s with five subcycles of 52 °C for 5 s and 80 °C for 5s, and followed by 72°C for 3 min. A total of 16 µL molecular HPLC water and each extension product were added to CLEAN Resin 384/6 MG Dimple plate (Sequenom, CA, USA) for further purification. Samples were rotated for 30 min on a tube rotator. After treatment, approximately 10 nL of products were spotted onto a 384-well SpectroCHIP bioarray (Sequenom, CA, USA), with the MassARRAY Nanodispenser RS1000 (Sequenom, CA, USA). The time of flight of these ionized products depends on the mass of each allele that will be measured by the mass spectrometer. The results were visualized on the MassArray Typer Analyzer v4.0 (Sequenom, CA, USA).
Clinical data and gene frequencies were analyzed using the t-test, Mann-Whitney U test and the χ2 test with SPSS 22.0 (IBM, NY, USA). Values were presented as mean ± SD, median (M) and range, or the number and percentage (%) based on the type of data. We calculated original genotype frequencies for each of the 21 polymorphisms in insomnia and control groups, and assessed Hardy-Weinberg equilibrium for each SNP locus among controls. Considering the imbalance of the possible clinical insomnia risk factors between the case group and the control group, and the errors in multiple comparisons, the SNPs which were significant differences in the distributions (P-value <0.05 in the initial results) of genotype frequencies between insomnia and control participants were selected for further analysis. To identify the effect of genetic models on insomnia, analyses were performed using dominant (wild-type homozygote versus heterozygote and mutant-homozygote), recessive (wild-type homozygote and heterozygote versus mutant-homozygote), and additive (wild-type homozygote versus mutant-homozygote) modes for each polymorphism (Zhu et al. 2019). We estimated the genetic odds ratio (OR) using logistic regression analyses to compute relative risks and 95% confidence intervals (CI). To address the use of a pooled control group, genetic analyses were adjusted for the matching factors of gender, age, BMI, hypertension, and HbA1c. We then perform false discovery rate (FDR) Benjamini and Hochberg procedure (BH) (Benjamini et al. 2001), a type of significance-level adjustment for controlling the error in multiple comparisons, to account for the increased probability of reporting false positive results through multiple tests. The procedure for controlling the FDR at level 0.05, and FDR (BH) thresholds for each of the 21 individual SNPs was calculated as described (Benjamini et al. 2001). Linkage disequilibrium (LD) and haplotype analysis were performed with Haploview v4.2 software, and a detailed description of the haplotype analysis is given elsewhere (Gabriel et al. 2002). A difference of P <0.05 (two-sided) indicates significant.