Haplotype function score improves biological interpretation and cross-ancestry polygenic prediction of human complex traits.

We propose a new framework for human genetic association studies: at each locus, a deep learning model (in this study, Sei) is used to calculate the functional genomic activity score for two haplotypes per individual. This score, defined as the Haplotype Function Score (HFS), replaces the original genotype in association studies. Applying the HFS framework to 14 complex traits in the UK Biobank, we identified 3619 independent HFS-trait associations with a significance of p < 5 × 10-8. Fine-mapping revealed 2699 causal associations, corresponding to a median increase of 63 causal findings per trait compared with single-nucleotide polymorphism (SNP)-based analysis. HFS-based enrichment analysis uncovered 727 pathway-trait associations and 153 tissue-trait associations with strong biological interpretability, including 'circadian pathway-chronotype' and 'arachidonic acid-intelligence'. Lastly, we applied least absolute shrinkage and selection operator (LASSO) regression to integrate HFS prediction score with SNP-based polygenic risk scores, which showed an improvement of 16.1-39.8% in cross-ancestry polygenic prediction. We concluded that HFS is a promising strategy for understanding the genetic basis of human complex traits.

Scattered throughout the human genome are variations in the genetic code that make individuals more or less likely to develop certain traits. To identify these variants, scientists carry out Genome-wide association studies (GWAS) which compare the DNA variants of large groups of people with and without the trait of interest. This method has been able to find the underlying genes for many human diseases, but it has limitations. For instance, some variations are linked together due to where they are positioned within DNA, which can result in GWAS falsely reporting associations between genetic variants and traits. This phenomenon, known as linkage equilibrium, can be avoided by analyzing functional genomics which looks at the multiple ways a gene's activity can be influenced by a variation. For instance, how the gene is copied and decoded in to proteins and RNA molecules, and the rate at which these products are generated. Researchers can now use an artificial intelligence technique called deep learning to generate functional genomic data from a particular DNA sequence. Here, Song et al. used one of these deep learning models to calculate the functional genomics of haplotypes, groups of genetic variants inherited from one parent. The approach was applied to DNA samples from over 350 thousand individuals included in the UK BioBank. An activity score, defined as the haplotype function score (or HFS for short), was calculated for at least two haplotypes per individual, and then compared to various complex traits like height or bone density. Song et al. found that the HFS framework was better at finding links between genes and specific traits than existing methods. It also provided more information on the biology that may be underpinning these outcomes. Although more work is needed to reduce the computer processing times required to calculate the HFS, Song et al. believe that their new method has the potential to improve the way researchers identify links between genes and human traits.

Comparative genomics of macaques and integrated insights into genetic variation and population history.

The crab-eating macaques ( Macaca fascicularis ) and rhesus macaques ( M. mulatta ) are widely studied nonhuman primates in biomedical and evolutionary research. Despite their significance, the current understanding of the complex genomic structure in macaques and the differences between species requires substantial improvement. Here, we present a complete genome assembly of a crab-eating macaque and 20 haplotype-resolved macaque assemblies to investigate the complex regions and major genomic differences between species. Segmental duplication in macaques is ∼42% lower, while centromeres are ∼3.7 times longer than those in humans. The characterization of ∼2 Mbp fixed genetic variants and ∼240 Mbp complex loci highlights potential associations with metabolic differences between the two macaque species (e.g., CYP2C76 and EHBP1L1 ). Additionally, hundreds of alternative splicing differences show post-transcriptional regulation divergence between these two species (e.g., PNPO ). We also characterize 91 large-scale genomic differences between macaques and humans at a single-base-pair resolution and highlight their impact on gene regulation in primate evolution (e.g., FOLH1 and PIEZO2 ). Finally, population genetics recapitulates macaque speciation and selective sweeps, highlighting potential genetic basis of reproduction and tail phenotype differences (e.g., STAB1 , SEMA3F , and HOXD13 ). In summary, the integrated analysis of genetic variation and population genetics in macaques greatly enhances our comprehension of lineage-specific phenotypes, adaptation, and primate evolution, thereby improving their biomedical applications in human diseases.

Structurally divergent and recurrently mutated regions of primate genomes.

We sequenced and assembled using multiple long-read sequencing technologies the genomes of chimpanzee, bonobo, gorilla, orangutan, gibbon, macaque, owl monkey, and marmoset. We identified 1,338,997 lineage-specific fixed structural variants (SVs) disrupting 1,561 protein-coding genes and 136,932 regulatory elements, including the most complete set of human-specific fixed differences. We estimate that 819.47 Mbp or ∼27% of the genome has been affected by SVs across primate evolution. We identify 1,607 structurally divergent regions wherein recurrent structural variation contributes to creating SV hotspots where genes are recurrently lost (e.g., CARD, C4, and OLAH gene families) and additional lineage-specific genes are generated (e.g., CKAP2, VPS36, ACBD7, and NEK5 paralogs), becoming targets of rapid chromosomal diversification and positive selection (e.g., RGPD gene family). High-fidelity long-read sequencing has made these dynamic regions of the genome accessible for sequence-level analyses within and between primate species.

Multiomics Analyses Reveal Microbiome-Gut-Brain Crosstalk Centered on Aberrant Gamma-Aminobutyric Acid and Tryptophan Metabolism in Drug-Naïve Patients with First-Episode Schizophrenia.

BACKGROUND AND HYPOTHESIS: Schizophrenia (SCZ) is associated with complex crosstalk between the gut microbiota and host metabolism, but the underlying mechanism remains elusive. Investigating the aberrant neurotransmitter processes reflected by alterations identified using multiomics analysis is valuable to fully explain the pathogenesis of SCZ. STUDY DESIGN: We conducted an integrative analysis of multiomics data, including the serum metabolome, fecal metagenome, single nucleotide polymorphism data, and neuroimaging data obtained from a cohort of 127 drug-naïve, first-episode SCZ patients and 92 healthy controls to characterize the microbiome-gut-brain axis in SCZ patients. We used pathway-based polygenic risk score (PRS) analyses to determine the biological pathways contributing to genetic risk and mediation effect analyses to determine the important neuroimaging features. Additionally, a random forest model was generated for effective SCZ diagnosis. STUDY RESULTS: We found that the altered metabolome and dysregulated microbiome were associated with neuroactive metabolites, including gamma-aminobutyric acid (GABA), tryptophan, and short-chain fatty acids. Further structural and functional magnetic resonance imaging analyses highlighted that gray matter volume and functional connectivity disturbances mediate the relationships between Ruminococcus_torgues and Collinsella_aerofaciens and symptom severity and the relationships between species Lactobacillus_ruminis and differential metabolites l-2,4-diaminobutyric acid and N-acetylserotonin and cognitive function. Moreover, analyses of the Polygenic Risk Score (PRS) support that alterations in GABA and tryptophan neurotransmitter pathways are associated with SCZ risk, and GABA might be a more dominant contributor. CONCLUSIONS: This study provides new insights into systematic relationships among genes, metabolism, and the gut microbiota that affect brain functional connectivity, thereby affecting SCZ pathogenesis.

Peripheral Nerve Block and Peri-operative Neurocognitive Disorders in Older Patients With Hip Fractures: A Systematic Review With Meta-analysis.

Background: Poor pain control and opioid use are risk factors for perioperative neurocognitive disorders (PND). The peripheral nerve block (PNB) can reduce pain and opioid consumption. This systematic review aimed to investigate the effects of PNB on PND in older patients with hip fractures. Methods: The PubMed, Cochrane Central Registers of Controlled Trial, Embase and ClinicalTrials.gov databases were searched from inception until November 19, 2021 for all randomized controlled trials (RCTs) comparing PNB with analgesics. The quality of the selected studies was assessed according to Version 2 of the Cochrane tool for assessing the risk of bias in RCTs. The primary outcome was the incidence of PND. Secondary outcomes included pain intensity and the incidence of postoperative nausea and vomiting. Subgroup analyses were based on population characteristics, type and infusion method of local anesthetics, and type of PNB. Results: Eight RCTs comprising 1015 older patients with hip fractures were included. Compared with analgesics, PNB did not reduce the incidence of PND in the elderly hip fracture population comprising patients with intact cognition and those with pre-existing dementia or cognitive impairment (risk ratio [RR] = .67; 95% confidence interval [CI] = .42 to 1.08; P = .10; I2 = 64%). However, PNB reduced the incidence of PND in older patients with intact cognition (RR = .61; 95% CI = .41 to .91; P = .02; I2 = 0%). Fascia iliaca compartment block, bupivacaine, and continuous infusion of local anesthetics were found to reduce the incidence of PND. Conclusions: PNB effectively reduced PND in older patients with hip fractures and intact cognition. When the study population included patients with intact cognition and those with pre-existing dementia or cognitive impairment, PNB showed no reduction in the incidence of PND. These conclusions should be confirmed with larger, higher-quality RCTs.

Involvement of iNOS-induced reactive enteric glia cells in gastrointestinal motility disorders of postoperative Ileus mice.

Postoperative ileus (POI) is the cessation or reduction of gastrointestinal (GI) motility after surgery. Reactive enteric glial cells (EGCs) are critical for maintaining bowel function. However, the triggering mechanisms and downstream effects of reactive EGCs in POI were poorly understood. The goal of this current study was to investigate whether the inducible nitric oxide synthase (iNOS)-driven reactive EGCs participated in GI motility disorders and mechanisms underlying altered GI motility in POI. Intestinal manipulation (IM)-induced POI mice and iNOS-/- mice were used in the study. Longitudinal muscle and myenteric plexuses (LMMPs) from the distal small intestine were stained by immunofluorescence. Our results found that the GI motility disorders occurred in the IM-induced POI mice, and reactive EGCs were observed in LMMPs. Glial metabolic inhibitor gliotoxin fluorocitrate (FC) treatment or iNOS gene knockout attenuated GI motility dysfunction. In addition, we also found that FC treatment or iNOS gene knockout significantly inhibited the fluorescence intensity macrophage colony-stimulating factor (M-CSF), which reduced M2 phenotype macrophages activation in LMMPs of IM-induced POI mice. Our findings demonstrated that iNOS-driven reactive EGCs played a key role and were tightly linked to the MMs homeostasis in the POI mice. EGCs are emerging as a new frontier in neurogastroenterology and a potential therapeutic target.

Chimeric vaccine design against the epidemic Langya Henipavirus using immunoinformatics and validation via immune simulation approaches.

In July 2022, a new virus called Langya virus (LayV) was discovered in China in patients who had a fever. This virus is a type of Henipavirus (HNV) and is considered a potential threat as it could spread from animals to humans. It causes respiratory disease with symptoms including fever, coughing, and fatigue and is closely linked to two other henipaviruses that are known to infect humans, namely Hendra and Nipah viruses. These viruses may cause fatal respiratory illnesses. Investigators believe that the LayV is spread by shrews, and may have infected humans directly or via an intermediary species. Thus, the use of vaccines or immunizations against LayV is an alternate strategy for disease prevention. In this study, we employed various immunoinformatics methods to predict B cell, HTL and T cell epitopes from the LayV proteome in order to find the most promising candidate for a LayV vaccine. The most potent epitopes that are immunogenic and non-allergenic were joined with each other through suitable linkers. Human ß-defensin 2 was employed as an adjuvant to increase the immunogenicity of the vaccine construct. The final sequence of a multi-epitope vaccine construct was modelled for docking with TLRs. Concisely, our results suggest that the docked complexes of vaccine-TLRs seemed to be stable. Additionally, in silico cloning was done using E. coli as the host in order to validate the expression of our designed vaccine construct. The GC content of 54.39% and CAI value of 0.94 revealed that the vaccine component expresses efficiently in the host. This study presents the novel vaccine construct for LayV which will be essential for further experimental validations to confirm the immunogenicity and safety of the proposed vaccine structure, and eventually to treat HNV-related diseases.

Population genetics of marmosets in Asian primate research centers and loci associated with epileptic risk revealed by whole-genome sequencing.

The common marmoset ( Callithrix jacchus) has emerged as a valuable nonhuman primate model in biomedical research with the recent release of high-quality reference genome assemblies. Epileptic marmosets have been independently reported in two Asian primate research centers. Nevertheless, the population genetics within these primate centers and the specific genetic variants associated with epilepsy in marmosets have not yet been elucidated. Here, we characterized the genetic relationships and risk variants for epilepsy in 41 samples from two epileptic marmoset pedigrees using whole-genome sequencing. We identified 14 558 184 single nucleotide polymorphisms (SNPs) from the 41 samples and found higher chimerism levels in blood samples than in fingernail samples. Genetic analysis showed fourth-degree of relatedness among marmosets at the primate centers. In addition, SNP and copy number variation (CNV) analyses suggested that the WW domain-containing oxidoreductase ( WWOX) and Tyrosine-protein phosphatase nonreceptor type 21 ( PTPN21) genes may be associated with epilepsy in marmosets. Notably, KCTD18-like gene deletion was more common in epileptic marmosets than control marmosets. This study provides valuable population genomic resources for marmosets in two Asian primate centers. Genetic analyses identified a reasonable breeding strategy for genetic diversity maintenance in the two centers, while the case-control study revealed potential risk genes/variants associated with epilepsy in marmosets.

Effects of Propofol on Perioperative Sleep Quality in Patients Undergoing Gastrointestinal Endoscopy: A Prospective Cohort Study.

PURPOSE: Some patients experience sleep disturbances after endoscopy performed under sedation. This study aimed to evaluate the effects of propofol on sleep quality after gastrointestinal endoscopy (GE). DESIGN: This study was a prospective cohort study. METHODS: This study enrolled 880 patients who underwent GE. Patients who chose to undergo GE under sedation received intravenous propofol, whereas the control group did not. The Pittsburgh Sleep Quality Index (PSQI) was measured before GE (PSQI-1) and 3 weeks (PSQI-2) after GE. The Groningen Sleep Score Scale (GSQS) was used before GE (GSQS-1) and 1 (GSQS-2) and 7 days (GSQS-3) after GE. FINDINGS: There was a significant increase in GSQS scores from baseline to days 1 and 7 after GE (GSQS-2 vs GSQS-1, P < .001, GSQS-3 vs GSQS-1, P = .008). However, no significant changes were observed in the control group (GSQS-2 vs GSQS-1, P = .38, GSQS-3 vs GSQS-1, P = .66). On day 21, there were no significant changes in the baseline PSQI scores over time in either group (sedation group, P = .96; control group, P = .95). CONCLUSIONS: GE with propofol sedation negatively affected sleep quality for 7 days after GE but not 3 weeks after GE.

Identification of Distinct Genetic Profiles of Palindromic Rheumatism Using Whole-Exome Sequencing.

OBJECTIVE: Previous studies have underlined the genetic susceptibility in the pathogenesis of palindromic rheumatism (PR), but the known PR loci only partially explain the disease's genetic background. We aimed to genetically identify PR by whole-exome sequencing (WES). METHODS: This multicenter prospective study was conducted in 10 Chinese specialized rheumatology centers between September 2015 and January 2020. WES was performed in 185 patients with PR and in 272 healthy controls. PR patients were divided into PR subgroups who were negative for anti-citrullinated protein antibody (ACPA-) and positive for ACPA (ACPA+) according to ACPA titer (cutoff value 20 IU/liter). We conducted whole-exome association analysis for the WES data. We used HLA imputation to type HLA genes. In addition, we used the polygenic risk score to measure the genetic correlations between PR and rheumatoid arthritis (RA) and the genetic correlations between ACPA- PR and ACPA+ PR. RESULTS: Among 185 patients with PR enrolled in our study, 50 patients (27.02%) were ACPA+ and 135 PR patients (72.98%) were ACPA-. We identified 8 novel loci (in the ACPA- PR group: ZNF503, RPS6KL1, HOMER3, HLA-DRA; in the ACPA+ PR group: RPS6KL1, TNPO2, WASH2P, FANK1) and 3 HLA alleles (in the ACPA- PR group: HLA-DRB1*0803 and HLA-DQB1; in the ACPA+ PR group: HLA-DPA1*0401) that were associated with PR and that surpassed genome-wide significance (P < 5 × 10-8 ). Furthermore, polygenic risk score analysis showed that PR and RA were not similar (R2 < 0.025), whereas ACPA+ PR and ACPA- PR showed a moderate genetic correlation (0.38 < R2 < 0.8). CONCLUSION: This study demonstrated the distinct genetic background between ACPA- and ACPA+ PR patients. Additionally, our findings strengthened that PR and RA were not genetically similar.

Integrative Genomic Analysis of m6a-SNPs Identifies Potential Functional Variants Associated with Alzheimer's Disease.

Alzheimer's disease (AD) is a neurodegenerative disorder that affects 35 million people worldwide. However, no potential therapeutics currently are available for AD because of the multiple factors involved in it, such as regulatory factors with their candidate genes, factors associated with the expression levels of its corresponding genes, and many others. To date, 29 novel loci from GWAS have been reported for AD by the Psychiatric Genomics Consortium (PGC2). Nevertheless, the main challenge of the post-GWAS era, namely to detect significant variants of the target disease, has not been conducted for AD. N6-methyladenosine (m6a) is reported as the most prevalent mRNA modification that exists in eukaryotes and that influences mRNA nuclear export, translation, splicing, and the stability of mRNA. Furthermore, studies have also reported m6a's association with neurogenesis and brain development. We carried out an integrative genomic analysis of AD variants from GWAS and m6a-SNPs from m6AVAR to identify the effects of m6a-SNPs on AD and identified the significant variants using the statistically significance value (p-value <0.05). The cis-regularity variants with their corresponding genes and their influence on gene expression in the gene expression profiles of AD patients were determined, and showed 1458 potential m6a-SNPs (based on p-value <0.05) associated with AD. eQTL analysis showed that 258 m6a-SNPs had cis-eQTL signals that overlapped with six significant differentially expressed genes based on p-value <0.05 in two datasets of AD gene expression profiles. A follow-up study to elucidate the impact of our identified m6a-SNPs in the experimental study would validate our findings for AD, which would contribute to the etiology of AD.

Transversus Thoracis Muscle Plane Block in Paediatric Patients Who Underwent Minimally Invasive Closure of Transthoracic Ventricular Septal Defect: A Retrospective Study.

Objective: Minimally invasive closure of transthoracic ventricular septal defect (VSD) has been widely used in paediatric patients. This retrospective study aimed to explore the use of transversus thoracis muscle plane block (TTMPB) in the minimally invasive closure of transthoracic VSD in paediatric patients. Methods: From September 28, 2017, to July 25, 2022, a total of 119 paediatric patients scheduled for minimally invasive transthoracic VSD closure were considered for inclusion. Results: In total, 110 patients were included in the final analysis. Perioperative fentanyl consumption of the TTMPB group was not different from that of the non-TTMPB group (5.90 ± 1.32 µg/kg vs. 6.25 ± 1.74 µg/kg, p = 0.473). Both the time to extubation and postanesthesia care unit (PACU) stay were significantly shorter in the TTMPB group than in the non-TTMPB group (10.94 ± 10.31 min vs. 35.03 ± 23.52 min for extubation, and 42.55 ± 16.83 min vs. 59.98 ± 27.94 min for PACU stay, both p < 0.001). Furthermore, the postoperative paediatric intensive care unit (PICU) stay in the TTMPB group was significantly shorter than in the non-TTMPB group (1.04 ± 0.28 d vs. 1.34 ± 1.05 d, p = 0.005). Multivariate analysis demonstrated that TTMPB was significantly associated with shorter time to extubation (p < 0.001) and PACU stay (p = 0.001) but not postoperative PICU stay (p = 0.094). Discussion. This study showed that TTMPB was a beneficial and safe regional anaesthesia technique for paediatric patients who underwent minimally invasive closure of transthoracic VSD, although prospective randomized controlled trials are needed to confirm the results.

A regulatory variant at 19p13.3 is associated with primary biliary cholangitis risk and ARID3A expression.

Genome-wide association studies have identified 19p13.3 locus associated with primary biliary cholangitis (PBC). Here we aim to identify causative variant(s) and initiate efforts to define the mechanism by which the 19p13.3 locus variant(s) contributes to the pathogenesis of PBC. A genome-wide meta-analysis of 1931 PBC subjects and 7852 controls in two Han Chinese cohorts confirms the strong association between 19p13.3 locus and PBC. By integrating functional annotations, luciferase reporter assay and allele-specific chromatin immunoprecipitation, we prioritize rs2238574, an AT-Rich Interaction Domain 3A (ARID3A) intronic variant, as a potential causal variant at 19p13.3 locus. The risk allele of rs2238574 shows higher binding affinity of transcription factors, leading to an increased enhancer activity in myeloid cells. Genome-editing demonstrates the regulatory effect of rs2238574 on ARID3A expression through allele-specific enhancer activity. Furthermore, knock-down of ARID3A inhibits myeloid differentiation and activation pathway, and overexpression of the gene has the opposite effect. Finally, we find ARID3A expression and rs2238574 genotypes linked to disease severity in PBC. Our work provides several lines of evidence that a non-coding variant regulates ARID3A expression, presenting a mechanistic basis for association of 19p13.3 locus with the susceptibility to PBC.

Cancer Cells Enter an Adaptive Persistence to Survive Radiotherapy and Repopulate Tumor.

Repopulation of residual tumor cells impedes curative radiotherapy, yet the mechanism is not fully understood. It is recently appreciated that cancer cells adopt a transient persistence to survive the stress of chemo- or targeted therapy and facilitate eventual relapse. Here, it is shown that cancer cells likewise enter a "radiation-tolerant persister" (RTP) state to evade radiation pressure in vitro and in vivo. RTP cells are characterized by enlarged cell size with complex karyotype, activated type I interferon pathway and two gene patterns represented by CST3 and SNCG. RTP cells have the potential to regenerate progenies via viral budding-like division, and type I interferon-mediated antiviral signaling impaired progeny production. Depleting CST3 or SNCG does not attenuate the formation of RTP cells, but can suppress RTP cells budding with impaired tumor repopulation. Interestingly, progeny cells produced by RTP cells actively lose their aberrant chromosomal fragments and gradually recover back to a chromosomal constitution similar to their unirradiated parental cells. Collectively, this study reveals a novel mechanism of tumor repopulation, i.e., cancer cell populations employ a reversible radiation-persistence by poly- and de-polyploidization to survive radiotherapy and repopulate the tumor, providing a new therapeutic concept to improve outcome of patients receiving radiotherapy.

DROEG: a method for cancer drug response prediction based on omics and essential genes integration.

Predicting therapeutic responses in cancer patients is a major challenge in the field of precision medicine due to high inter- and intra-tumor heterogeneity. Most drug response models need to be improved in terms of accuracy, and there is limited research to assess therapeutic responses of particular tumor types. Here, we developed a novel method DROEG (Drug Response based on Omics and Essential Genes) for prediction of drug response in tumor cell lines by integrating genomic, transcriptomic and methylomic data along with CRISPR essential genes, and revealed that the incorporation of tumor proliferation essential genes can improve drug sensitivity prediction. Concisely, DROEG integrates literature-based and statistics-based methods to select features and uses Support Vector Regression for model construction. We demonstrate that DROEG outperforms most state-of-the-art algorithms by both qualitative (prediction accuracy for drug-sensitive/resistant) and quantitative (Pearson correlation coefficient between the predicted and actual IC50) evaluation in Genomics of Drug Sensitivity in Cancer and Cancer Cell Line Encyclopedia datasets. In addition, DROEG is further applied to the pan-gastrointestinal tumor with high prevalence and mortality as a case study at both cell line and clinical levels to evaluate the model efficacy and discover potential prognostic biomarkers in Cisplatin and Epirubicin treatment. Interestingly, the CRISPR essential gene information is found to be the most important contributor to enhance the accuracy of the DROEG model. To our knowledge, this is the first study to integrate essential genes with multi-omics data to improve cancer drug response prediction and provide insights into personalized precision treatment.

Effects of Dexmedetomidine on Systemic Inflammation and Postoperative Complications in Laparoscopic Pancreaticoduodenectomy: A Double-blind Randomized Controlled Trial.

BACKGROUND: Laparoscopic pancreaticoduodenectomy (LPD) may induce intense inflammatory response which might be related to the patient's outcomes. Clinical dexmedetomidine (DEX) has been widely used for opioid-sparing anesthesia and satisfactory sedation. The objective of this study was to investigate the influence of DEX on inflammatory response and postoperative complications in LPD. METHODS: Ninety-nine patients undergoing LPD were randomly assigned to two groups: normal saline (NS) and DEX. The primary outcome was the neutrophil-to-lymphocyte ratio (NLR) differences postoperatively within 48 h. Secondary outcomes were postoperative complications, the length of postoperative hospital stay and the incidence of ICU admission. Other outcomes included anesthetics consumption and intraoperative vital signs. RESULTS: NLR at postoperative day 2 to baseline ratio decreased significantly in the DEX group (P = 0.032). Less major complications were observed in the DEX group such as pancreatic fistula, delayed gastric emptying and intra-abdominal infection (NS vs. DEX, 21.7% vs. 13.6%, P = 0.315; 10.9% vs. 2.3%, P = 0.226; 17.4% vs. 11.4%, P = 0.416, respectively) though there were no statistical differences. Three patients were transferred to the ICU after surgery in the NS group, while there was none in the DEX group (P = 0.242). The median postoperative hospital stay between groups were similar (P = 0.313). Both intraoperative propofol and opioids were less in the DEX group (P < 0.05). CONCLUSIONS: Intraoperative DEX reduced the early postoperative inflammatory response in LPD. It also reduced the use of narcotics that may related to reduced major complications, which need additional research further.